Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-5749-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5749-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
09 Nov 2021
Review article |
| 09 Nov 2021
| 09 Nov 2021
The International Soil Moisture Network: serving Earth system science for over a decade
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Irene Himmelbauer
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Daniel Aberer
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Lukas Schremmer
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Ivana Petrakovic
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Luca Zappa
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Wolfgang Preimesberger
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Angelika Xaver
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Frank Annor
Trans-African Hydro-Meteorological Observatory, TU Delft, Delft, the Netherlands
Water Management Department, TU Delft, Delft, the Netherlands
Jonas Ardö
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Dennis Baldocchi
Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA
Marco Bitelli
Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
Günter Blöschl
Institute of Hydraulic Engineering and Water Resources Management, TU Wien, Vienna, Austria
Heye Bogena
Institute of Bio- and Geosciences Agrosphere (IBG-3), Forschungszentrum Juelich GmbH, Juelich, Germany
Luca Brocca
Research Institute for Geo-Hydrological Protection, National Research Council of Italy, Perugia, Italy
Jean-Christophe Calvet
CNRM, Université de Toulouse, Météo-France, CNRS – Centre national de la recherche scientifique, Toulouse, France
J. Julio Camarero
Instituto Pirenaico de Ecología, IPE-CSIC, Zaragoza, Spain
Giorgio Capello
Institute of Sciences and Technologies for Sustainable Energy and Mobility, National Research Council of Italy, Torino, Italy
Minha Choi
Environment and Remote Sensing Laboratory, School of Civil, Architectural and Environmental Engineering, College of Engineering, Sungkyunkwan University, Jangan-gu, Suwon, Gyeonggi-do, Republic of Korea
Michael C. Cosh
Hydrology and Remote Sensing Laboratory, USDA–Agricultural Research Service (USDA-ARS), Beltsville, MD, USA
Nick van de Giesen
Water Management Department, TU Delft, Delft, the Netherlands
Istvan Hajdu
PlantTech Research Institute, Tauranga, New Zealand
Jaakko Ikonen
Space and Earth Observation Centre, Finnish Meteorological Institute, Helsinki, Finland
Karsten H. Jensen
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Kasturi Devi Kanniah
Centre for Environmental Sustainability and Water Security (IPASA), Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
Ileen de Kat
VanderSat B. V., Haarlem, the Netherlands
Gottfried Kirchengast
Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
Pankaj Kumar Rai
Department of Biotechnology, Invertis University, Bareilly, India
Jenni Kyrouac
Environmental Science Division, Argonne National Laboratory, Lemont, IL, USA
Kristine Larson
Department of Aerospace Engineering Sciences, University of Colorado, Boulder, CO, USA
Suxia Liu
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese
Academy of Sciences, Beijing, China
Sino-Danish Center, University of Chinese Academy of Sciences, Beijing, China
Alexander Loew
Department of Geography, Ludwig-Maximilian-Universität, Munich, Germany
deceased, 2 July 2017
Mahta Moghaddam
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
José Martínez Fernández
Instituto Hispano Luso de Investigaciones Agrarias, CIALE, Universidad de Salamanca, Villamayor, Spain
Cristian Mattar Bader
Laboratory for Analysis of the Biosphere, University of Chile, Santiago, Chile
Renato Morbidelli
Department of Civil and Environmental Engineering, University of Perugia, Perugia, Italy
Jan P. Musial
Institute of Geodesy and Cartography (IGiK), Remote Sensing Centre, Warsaw, Poland
Elise Osenga
Aspen Global Change Institute (AGCI), Basalt, CO, USA
Michael A. Palecki
NOAA National Centers for Environmental Information, Asheville, NC, USA
Thierry Pellarin
CNRS – Centre national de la recherche scientifique, LTHE, University of Grenoble Alpes, France
George P. Petropoulos
Department of Geography, Harokopio University of Athens, Athens, Greece
Isabella Pfeil
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Jarrett Powers
Science and Technology Branch, Agriculture and Agri-Food Canada, Winnipeg, MB, Canada
Alan Robock
Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA
Christoph Rüdiger
Department of Civil Engineering, Monash University, Clayton, Australia
Udo Rummel
Meteorologisches Observatorium Lindenberg – Richard-Aßmann-Observatorium, DWD, Lindenberg, Germany
Michael Strobel
USDA-NRCS National Water and Climate Center, Portland, OR, USA
Zhongbo Su
Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, the Netherlands
Ryan Sullivan
Environmental Science Division, Argonne National Laboratory, Lemont, IL, USA
Torbern Tagesson
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Andrej Varlagin
A. N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, Russia
Mariette Vreugdenhil
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Jeffrey Walker
Department of Civil Engineering, Monash University, Clayton, Australia
Jun Wen
College of Atmospheric Sciences, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu, China
Fred Wenger
Norwegian Water Resources and Energy Directorate, Oslo, Norway
Jean Pierre Wigneron
MOST, ISPA, INRAE Bordeaux Aquitaine, Bordeaux, France
Mel Woods
Social Digital, Duncan of Jordanstone College of Art and Design, University of Dundee, Dundee, UK
Kun Yang
Department of Earth System Science, Tsinghua University, Beijing, China
Yijian Zeng
Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, the Netherlands
Xiang Zhang
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China
Marek Zreda
Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
Stephan Dietrich
International Centre for Water Resources and Global Change ICWRGC (UNESCO), Federal Institute of Hydrology, Koblenz, Germany
Alexander Gruber
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Peter van Oevelen
International GEWEX Project Office, Washington, DC, USA
Wolfgang Wagner
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Klaus Scipal
ESRIN, European Space Agency, Frascati, Italy
Matthias Drusch
ESTEC, European Space Agency, Noordwijk, the Netherlands
Roberto Sabia
ESRIN, European Space Agency, Frascati, Italy
Related authors
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo
Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
Short summary
Short summary
VODCA v2 is a dataset providing vegetation indicators for long-term ecosystem monitoring. VODCA v2 comprises two products: VODCA CXKu, spanning 34 years of observations (1987–2021), suitable for monitoring upper canopy dynamics, and VODCA L (2010–2021), for above-ground biomass monitoring. VODCA v2 has lower noise levels than the previous product version and provides valuable insights into plant water dynamics and biomass changes, even in areas where optical data are limited.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, Luke Smallmann, Susan Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zähle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek El-Madany, Mirco Migliavacca, Marika Honkanen, Yann Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaetan Pique, Amanda Ojasalo, Shaun Quegan, Peter Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
EGUsphere, https://doi.org/10.5194/egusphere-2024-1534, https://doi.org/10.5194/egusphere-2024-1534, 2024
Short summary
Short summary
When it comes to climate change, the land surfaces are where the vast majority of impacts happen. The task of monitoring those across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us see what changes on our lands.
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
Short summary
Short summary
We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
Martin Hirschi, Bas Crezee, Pietro Stradiotti, Wouter Dorigo, and Sonia I. Seneviratne
EGUsphere, https://doi.org/10.5194/egusphere-2023-2499, https://doi.org/10.5194/egusphere-2023-2499, 2023
Short summary
Short summary
Based on surface and root-zone soil moisture, we compare the ability of selected long-term reanalysis and merged remote-sensing products to represent major agroecological drought events. While all products capture the investigated droughts, they particularly show differences in the drought magnitudes. Globally, the diverse and regionally contradicting dry-season soil moisture trends of the products is an important factor governing their drought representation and monitoring capability.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
Short summary
Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Remi Madelon, Nemesio J. Rodríguez-Fernández, Hassan Bazzi, Nicolas Baghdadi, Clement Albergel, Wouter Dorigo, and Mehrez Zribi
Hydrol. Earth Syst. Sci., 27, 1221–1242, https://doi.org/10.5194/hess-27-1221-2023, https://doi.org/10.5194/hess-27-1221-2023, 2023
Short summary
Short summary
We present an approach to estimate soil moisture (SM) at 1 km resolution using Sentinel-1 and Sentinel-3 satellites. The estimates were compared to other high-resolution (HR) datasets over Europe, northern Africa, Australia, and North America, showing good agreement. However, the discrepancies between the different HR datasets and their lower performances compared with in situ measurements and coarse-resolution datasets show the remaining challenges for large-scale HR SM mapping.
Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
Short summary
Short summary
Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
Short summary
Short summary
Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023, https://doi.org/10.5194/hess-27-39-2023, 2023
Short summary
Short summary
The live fuel moisture content (LFMC) of vegetation canopies is a driver of wildfires. We investigate the relation between LFMC and passive microwave satellite observations of vegetation optical depth (VOD) and develop a method to estimate LFMC from VOD globally. Our global VOD-based estimates of LFMC can be used to investigate drought effects on vegetation and fire risks.
Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo
Biogeosciences, 19, 5107–5123, https://doi.org/10.5194/bg-19-5107-2022, https://doi.org/10.5194/bg-19-5107-2022, 2022
Short summary
Short summary
The standardized vegetation optical depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage, spans the past 3 decades and is derived from multiple spaceborne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data even if the data are not gap-free.
Robin van der Schalie, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu
Hydrol. Earth Syst. Sci., 26, 3611–3627, https://doi.org/10.5194/hess-26-3611-2022, https://doi.org/10.5194/hess-26-3611-2022, 2022
Short summary
Short summary
Climate data records of surface soil moisture, vegetation optical depth, and land surface temperature can be derived from passive microwave observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here, we present a case study over the Okavango Delta, where we focus on inter-annual variability.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
Short summary
Short summary
Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
Short summary
Short summary
Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
Short summary
Short summary
Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
Short summary
Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
Short summary
Short summary
We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
Angelika Xaver, Luca Zappa, Gerhard Rab, Isabella Pfeil, Mariette Vreugdenhil, Drew Hemment, and Wouter Arnoud Dorigo
Geosci. Instrum. Method. Data Syst., 9, 117–139, https://doi.org/10.5194/gi-9-117-2020, https://doi.org/10.5194/gi-9-117-2020, 2020
Short summary
Short summary
Soil moisture plays a key role in the hydrological cycle and the climate system. Although soil moisture can be observed by the means of satellites, ground observations are still crucial for evaluating and improving these satellite products. In this study, we investigate the performance of a consumer low-cost soil moisture sensor in the lab and in the field. We demonstrate that this sensor can be used for scientific applications, for example to create a dataset valuable for satellite validation.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
Short summary
Short summary
The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
Short summary
Short summary
Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
Alexander Gruber, Tracy Scanlon, Robin van der Schalie, Wolfgang Wagner, and Wouter Dorigo
Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, https://doi.org/10.5194/essd-11-717-2019, 2019
Short summary
Short summary
Soil moisture is a key variable in our Earth system. Knowledge of soil moisture and its dynamics across scales is vital for many applications such as the prediction of agricultural yields or irrigation demands, flood and drought monitoring, weather forecasting and climate modelling. To date, the ESA CCI SM products are the only consistent long-term multi-satellite soil moisture data sets available. This paper reviews the evolution of these products and their underlying merging methodology.
Felix Zaussinger, Wouter Dorigo, Alexander Gruber, Angelica Tarpanelli, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019, https://doi.org/10.5194/hess-23-897-2019, 2019
Short summary
Short summary
About 70 % of global freshwater is consumed by irrigation. Yet, policy-relevant estimates of irrigation water use (IWU) are virtually lacking at regional to global scales. To bridge this gap, we develop a method for quantifying IWU from a combination of state-of-the-art remotely sensed and modeled soil moisture products and apply it over the United States for the period 2013–2016. Overall, our estimates agree well with reference data on irrigated area and irrigation water withdrawals.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
Short summary
Short summary
This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
Short summary
Short summary
Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Luca Ciabatta, Christian Massari, Luca Brocca, Alexander Gruber, Christoph Reimer, Sebastian Hahn, Christoph Paulik, Wouter Dorigo, Richard Kidd, and Wolfgang Wagner
Earth Syst. Sci. Data, 10, 267–280, https://doi.org/10.5194/essd-10-267-2018, https://doi.org/10.5194/essd-10-267-2018, 2018
Short summary
Short summary
In this study, rainfall is estimated starting from satellite soil moisture observation on a global scale, using the ESA CCI soil moisture datasets. The new obtained rainfall product has proven to correctly identify rainfall events, showing performance sometimes higher than those obtained by using classical rainfall estimation approaches.
Matthias Forkel, Wouter Dorigo, Gitta Lasslop, Irene Teubner, Emilio Chuvieco, and Kirsten Thonicke
Geosci. Model Dev., 10, 4443–4476, https://doi.org/10.5194/gmd-10-4443-2017, https://doi.org/10.5194/gmd-10-4443-2017, 2017
Short summary
Short summary
Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
Short summary
Short summary
LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
Short summary
Short summary
This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
Short summary
Short summary
The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
Short summary
Short summary
Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman
Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, https://doi.org/10.5194/gmd-10-1945-2017, 2017
Short summary
Short summary
Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.
Markus Enenkel, Christoph Reimer, Wouter Dorigo, Wolfgang Wagner, Isabella Pfeil, Robert Parinussa, and Richard De Jeu
Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, https://doi.org/10.5194/hess-20-4191-2016, 2016
Short summary
Short summary
Soil moisture is a crucial variable for a variety of applications, ranging from weather forecasting and agricultural production to the monitoring of floods and droughts. Satellite observations are particularly important in regions where no in situ measurements are available. Our study presents a method to integrate global near-real-time satellite observations from different sensors into one harmonized, daily data set. A first validation shows good results on a global scale.
C. Szczypta, J.-C. Calvet, F. Maignan, W. Dorigo, F. Baret, and P. Ciais
Geosci. Model Dev., 7, 931–946, https://doi.org/10.5194/gmd-7-931-2014, https://doi.org/10.5194/gmd-7-931-2014, 2014
A. Loew, T. Stacke, W. Dorigo, R. de Jeu, and S. Hagemann
Hydrol. Earth Syst. Sci., 17, 3523–3542, https://doi.org/10.5194/hess-17-3523-2013, https://doi.org/10.5194/hess-17-3523-2013, 2013
Ling Zhang, Yanhua Xie, Xiufang Zhu, Qimin Ma, and Luca Brocca
Earth Syst. Sci. Data, 16, 5207–5226, https://doi.org/10.5194/essd-16-5207-2024, https://doi.org/10.5194/essd-16-5207-2024, 2024
Short summary
Short summary
This study presented new annual maps of irrigated cropland in China from 2000 to 2020 (CIrrMap250). These maps were developed by integrating remote sensing data, irrigation statistics and surveys, and an irrigation suitability map. CIrrMap250 achieved high accuracy and outperformed currently available products. The new irrigation maps revealed a clear expansion of China’s irrigation area, with the majority (61%) occurring in the water-unsustainable regions facing severe to extreme water stress.
Yanyi He, Kaicun Wang, Kun Yang, Chunlüe Zhou, Changkun Shao, and Changjian Yin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-493, https://doi.org/10.5194/essd-2024-493, 2024
Preprint under review for ESSD
Short summary
Short summary
To address key gaps in data availability and homogeneity of sunshine duration, we compiled raw data and made a homogenization protocol to produce a homogenized daily observational dataset of sunshine duration from 1961 to 2022 in China. The dataset avoids a sharp drop in zero-value frequency after 2019, caused by the instrument upgrade, but also is more continuous for various periods. This dataset is crucial for accurately assessing the dimming and brightening, and supporting other applications.
Zengjing Song, Yijian Zeng, Yunfei Wang, Enting Tang, Danyang Yu, Fakhereh Alidoost, Mingguo Ma, Xujun Han, Xuguang Tang, Zhongjing Zhu, Yao Xiao, Debing Kong, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2024-2940, https://doi.org/10.5194/egusphere-2024-2940, 2024
Short summary
Short summary
The exchange of water and carbon between the plant and the atmosphere is affected under water stress conditions. In this study, a leaf-water-potential-based water stress factor is considered in the STEMMUS-SCOPE (hereafter STEMMUS-SCOPE-PHS), to replace the conventional soil-moisture-based water stress factor. The results show that leaf water potential reflects the plant water stress well, and the STEMMUS-SCOPE-PHS outperforms STEMMUS-SCOPE in the dynamics of the water, energy and carbon fluxes.
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo
Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
Short summary
Short summary
VODCA v2 is a dataset providing vegetation indicators for long-term ecosystem monitoring. VODCA v2 comprises two products: VODCA CXKu, spanning 34 years of observations (1987–2021), suitable for monitoring upper canopy dynamics, and VODCA L (2010–2021), for above-ground biomass monitoring. VODCA v2 has lower noise levels than the previous product version and provides valuable insights into plant water dynamics and biomass changes, even in areas where optical data are limited.
Ivana Petrakovic, Andrea Binn, and Georg Gartner
Abstr. Int. Cartogr. Assoc., 7, 124, https://doi.org/10.5194/ica-abs-7-124-2024, https://doi.org/10.5194/ica-abs-7-124-2024, 2024
Julia Danzer, Magdalena Pieler, and Gottfried Kirchengast
Atmos. Meas. Tech., 17, 4979–4995, https://doi.org/10.5194/amt-17-4979-2024, https://doi.org/10.5194/amt-17-4979-2024, 2024
Short summary
Short summary
We investigated the potential of radio occultation (RO) data for climate-oriented wind field monitoring, focusing on the equatorial band within ±5° latitude. In this region, the geostrophic balance breaks down, and the equatorial balance approximation takes over. The study encourages the use of RO wind fields for mesoscale climate monitoring for the equatorial region, showing a small improvement in the troposphere when including the meridional wind in the zonal-mean total wind speed.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
Short summary
The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
Short summary
Short summary
Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, Luke Smallmann, Susan Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zähle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek El-Madany, Mirco Migliavacca, Marika Honkanen, Yann Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaetan Pique, Amanda Ojasalo, Shaun Quegan, Peter Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
EGUsphere, https://doi.org/10.5194/egusphere-2024-1534, https://doi.org/10.5194/egusphere-2024-1534, 2024
Short summary
Short summary
When it comes to climate change, the land surfaces are where the vast majority of impacts happen. The task of monitoring those across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us see what changes on our lands.
Francisco Rodrigues do Amaral, Benoît Camenen, Tin Nguyen Trung, Tran Anh Tu, Thierry Pellarin, and Nicolas Gratiot
EGUsphere, https://doi.org/10.5194/egusphere-2024-1563, https://doi.org/10.5194/egusphere-2024-1563, 2024
Short summary
Short summary
This study explores how to improve models predicting water flow in South Vietnam's Saigon and Dongnai rivers, where data is scarce. By testing three different methods to adjust the river model using river water level and river discharge measurements, we found ways to better predict river behavior. These findings can help manage water resources more effectively and aid decision-making for flood protection and environmental conservation.
Jaime Gaona, Davide Bavera, Guido Fioravanti, Sebastian Hahn, Pietro Stradiotti, Paolo Filippucci, Stefania Camici, Luca Ciabatta, Hamidreza Mossaffa, Silvia Puca, Nicoletta Roberto, and Luca Brocca
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-182, https://doi.org/10.5194/hess-2024-182, 2024
Preprint under review for HESS
Short summary
Short summary
Soil moisture is crucial for the water cycle since it is the frontline of drought. Satellite, model, and in-situ data help identify soil moisture stress but challenged by data uncertainties. This study evaluates trends and data coherence of common active/passive microwave sensors and model-based soil moisture data against in-situ stations across Europe from 2007 to 2022. Data reliability is increasing but combining data types improves soil moisture monitoring capabilities.
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024, https://doi.org/10.5194/nhess-24-2071-2024, 2024
Short summary
Short summary
A methodology of regional flood hazard mapping is proposed, based on data in Austria, which combines automatic methods with manual interventions to maximise efficiency and to obtain estimation accuracy similar to that of local studies. Flood discharge records from 781 stations are used to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. The hazard maps are used for civil protection, risk awareness and insurance purposes.
Jacopo Dari, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 28, 2651–2659, https://doi.org/10.5194/hess-28-2651-2024, https://doi.org/10.5194/hess-28-2651-2024, 2024
Short summary
Short summary
We have developed the first operational system (10 d latency) for estimating irrigation water use from accessible satellite and reanalysis data. As a proof of concept, the method has been implemented over an irrigated area fed by the Kakhovka Reservoir, in Ukraine, which collapsed on June 6, 2023. Estimates for the period 2015–2023 reveal that, as expected, the irrigation season of 2023 was characterized by the lowest amounts of irrigation.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
Short summary
Short summary
Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
EGUsphere, https://doi.org/10.5194/egusphere-2024-1678, https://doi.org/10.5194/egusphere-2024-1678, 2024
Short summary
Short summary
The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two end members of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented super-sites.
En Liu, Yonghua Zhu, Jean-Christophe Calvet, Haishen Lü, Bertrand Bonan, Jingyao Zheng, Qiqi Gou, Xiaoyi Wang, Zhenzhou Ding, Haiting Xu, Ying Pan, and Tingxing Chen
Hydrol. Earth Syst. Sci., 28, 2375–2400, https://doi.org/10.5194/hess-28-2375-2024, https://doi.org/10.5194/hess-28-2375-2024, 2024
Short summary
Short summary
Overestimated root zone soil moisture (RZSM) based on land surface models (LSMs) is attributed to overestimated precipitation and an underestimated ratio of transpiration to total evapotranspiration and performs better in the wet season. Underestimated SMOS L3 surface SM triggers the underestimated SMOS L4 RZSM, which performs better in the dry season due to the attenuated radiation in the wet season. LSMs should reduce and increase the frequency of wet and dry soil moisture, respectively.
Charles E. Miller, Peter C. Griffith, Elizabeth Hoy, Naiara S. Pinto, Yunling Lou, Scott Hensley, Bruce D. Chapman, Jennifer Baltzer, Kazem Bakian-Dogaheh, W. Robert Bolton, Laura Bourgeau-Chavez, Richard H. Chen, Byung-Hun Choe, Leah K. Clayton, Thomas A. Douglas, Nancy French, Jean E. Holloway, Gang Hong, Lingcao Huang, Go Iwahana, Liza Jenkins, John S. Kimball, Tatiana Loboda, Michelle Mack, Philip Marsh, Roger J. Michaelides, Mahta Moghaddam, Andrew Parsekian, Kevin Schaefer, Paul R. Siqueira, Debjani Singh, Alireza Tabatabaeenejad, Merritt Turetsky, Ridha Touzi, Elizabeth Wig, Cathy J. Wilson, Paul Wilson, Stan D. Wullschleger, Yonghong Yi, Howard A. Zebker, Yu Zhang, Yuhuan Zhao, and Scott J. Goetz
Earth Syst. Sci. Data, 16, 2605–2624, https://doi.org/10.5194/essd-16-2605-2024, https://doi.org/10.5194/essd-16-2605-2024, 2024
Short summary
Short summary
NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) conducted airborne synthetic aperture radar (SAR) surveys of over 120 000 km2 in Alaska and northwestern Canada during 2017, 2018, 2019, and 2022. This paper summarizes those results and provides links to details on ~ 80 individual flight lines. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band SAR data.
Yunfei Wang, Yijian Zeng, Zengjing Song, Danyang Yu, Qianqian Han, Enting Tang, Henk de Bruin, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2024-1321, https://doi.org/10.5194/egusphere-2024-1321, 2024
Preprint archived
Short summary
Short summary
Various methods were proposed to estimate irrigation water requirements (IWR). However, the simulated IWR exhibits large differences. This study evaluates six potential evapotranspiration (PET) methods and proposes a practical approach to estimate IWR. The radiation-based methods show promise in approximating daily PET accurately, and the STEMMUS-SCOPE model can reliably estimate IWR. This research enhances our understanding of different PET methods and their implications for water management.
Sophie Barthelemy, Bertrand Bonan, Miquel Tomas-Burguera, Gilles Grandjean, Séverine Bernardie, Jean-Philippe Naulin, Patrick Le Moigne, Aaron Boone, and Jean-Christophe Calvet
EGUsphere, https://doi.org/10.5194/egusphere-2024-1079, https://doi.org/10.5194/egusphere-2024-1079, 2024
Short summary
Short summary
A drought index is developed that quantifies drought on an annual scale for deciduous broadleaf vegetation, making it applicable to monitoring clay shrinkage damage to buildings, agriculture or forestry. It is found that significant soil moisture drought events occurred in France in 2003, 2018, 2019, 2020 and 2022. Particularly high index values are observed throughout the country in 2022. It is also found that droughts will become more severe in the future.
Wendy Sharples, Katayoon Bahramian, Kesav Unnithan, Christoph Rüdiger, Jiawei Hou, Christopher Pickett-Heaps, and Elisabetta Carrara
Proc. IAHS, 386, 237–249, https://doi.org/10.5194/piahs-386-237-2024, https://doi.org/10.5194/piahs-386-237-2024, 2024
Short summary
Short summary
Two flood events occurred in the Hawkesbury-Nepean valley in 2020 and 2021, however, the impact of each of those events was different in terms of lives lost (2 fatalities compared to none) and economic losses (more than 2 billion compared to less than 1 billion AUD). Reasons for the variation in impacts are explored by determining the inundation extents, and examining antecedent and climatic conditions. We found that antecedent conditions exerted a major control on the size of the impact.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Short summary
This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Irena Nimac, Julia Danzer, and Gottfried Kirchengast
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-59, https://doi.org/10.5194/amt-2024-59, 2024
Revised manuscript under review for AMT
Short summary
Short summary
Due to shortcomings of available observations, having accurate global 3D wind fields remains a challenge. Promising option is the use of radio occultation (RO) satellite data, which enable to derive winds based on the wind approximations. We test how well RO winds describe the ERA5 reanalysis winds. We separate the total wind difference into the approximation bias and the systematic difference between the two datasets. The results show the utility of RO winds for climate monitoring and analyses.
Bruno Merz, Günter Blöschl, Robert Jüpner, Heidi Kreibich, Kai Schröter, and Sergiy Vorogushyn
EGUsphere, https://doi.org/10.5194/egusphere-2024-856, https://doi.org/10.5194/egusphere-2024-856, 2024
Short summary
Short summary
We discuss the validation of flood hazard and risk assessments (FHRAs) to ensure they are useful for decision-making. We propose a new validation framework that considers not only technical aspects but also the real-world context in which decisions are made. By applying this framework to flood emergency planning, we demonstrate its practicality.
Sophie Barthelemy, Bertrand Bonan, Jean-Christophe Calvet, Gilles Grandjean, David Moncoulon, Dorothée Kapsambelis, and Séverine Bernardie
Nat. Hazards Earth Syst. Sci., 24, 999–1016, https://doi.org/10.5194/nhess-24-999-2024, https://doi.org/10.5194/nhess-24-999-2024, 2024
Short summary
Short summary
This work presents a drought index specifically adapted to subsidence, a seasonal phenomenon of soil shrinkage that occurs frequently in France and damages buildings. The index is computed from land surface model simulations and evaluated by a rank correlation test with insurance data. With its optimal configuration, the index is able to identify years of both zero and significant loss.
Lukas Strebel, Heye Bogena, Harry Vereecken, Mie Andreasen, Sergio Aranda-Barranco, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 28, 1001–1026, https://doi.org/10.5194/hess-28-1001-2024, https://doi.org/10.5194/hess-28-1001-2024, 2024
Short summary
Short summary
We present results from using soil water content measurements from 13 European forest sites in a state-of-the-art land surface model. We use data assimilation to perform a combination of observed and modeled soil water content and show the improvements in the representation of soil water content. However, we also look at the impact on evapotranspiration and see no corresponding improvements.
Min Huang, Gregory R. Carmichael, James H. Crawford, Kevin W. Bowman, Isabelle De Smedt, Andreas Colliander, Michael H. Cosh, Sujay V. Kumar, Alex B. Guenther, Scott J. Janz, Ryan M. Stauffer, Anne M. Thompson, Niko M. Fedkin, Robert J. Swap, John D. Bolten, and Alicia T. Joseph
EGUsphere, https://doi.org/10.5194/egusphere-2024-484, https://doi.org/10.5194/egusphere-2024-484, 2024
Short summary
Short summary
This study uses model simulations along with multiplatform, multidisciplinary observations and a range of analysis methods to estimate and understand the distributions, temporal changes, and impacts of reactive nitrogen and ozone over the most populous US region that has undergone significant environmental changes. Deposition, biogenic emissions, and extra-regional sources have been playing increasingly important roles in controlling pollutants’ budgets in this area as local emissions go down.
Enting Tang, Yijian Zeng, Yunfei Wang, Zengjing Song, Danyang Yu, Hongyue Wu, Chenglong Qiao, Christiaan van der Tol, Lingtong Du, and Zhongbo Su
Biogeosciences, 21, 893–909, https://doi.org/10.5194/bg-21-893-2024, https://doi.org/10.5194/bg-21-893-2024, 2024
Short summary
Short summary
Our study shows that planting shrubs in a semiarid grassland reduced the soil moisture and increased plant water uptake and transpiration. Notably, the water used by the ecosystem exceeded the rainfall received during the growing seasons, indicating an imbalance in the water cycle. The findings demonstrate the effectiveness of the STEMMUS–SCOPE model as a tool to represent ecohydrological processes and highlight the need to consider energy and water budgets for future revegetation projects.
Trine Enemark, Rasmus Bødker Madsen, Torben O. Sonnenborg, Lærke Therese Andersen, Peter B. E. Sandersen, Jacob Kidmose, Ingelise Møller, Thomas Mejer Hansen, Karsten Høgh Jensen, and Anne-Sophie Høyer
Hydrol. Earth Syst. Sci., 28, 505–523, https://doi.org/10.5194/hess-28-505-2024, https://doi.org/10.5194/hess-28-505-2024, 2024
Short summary
Short summary
In this study, we demonstrate an approach to evaluate the interpretation uncertainty within a manually interpreted geological model in a groundwater model. Using qualitative estimates of uncertainties, several geological realizations are developed and implemented in groundwater models. We confirm existing evidence that if the conceptual model is well defined, interpretation uncertainties within the conceptual model have limited impact on groundwater model predictions.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billdesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Gharun Mana, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2024-165, https://doi.org/10.5194/egusphere-2024-165, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the earth surface to the atmosphere, or flux, is an important process to understand that impacts all of our lives. Here we outline a method to estimate global water and CO2 fluxes based on direct measurements from site around the world called FLUXCOM-X. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Søren Julsgaard Kragh, Jacopo Dari, Sara Modanesi, Christian Massari, Luca Brocca, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 28, 441–457, https://doi.org/10.5194/hess-28-441-2024, https://doi.org/10.5194/hess-28-441-2024, 2024
Short summary
Short summary
This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin De Kauwe, Sam Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2023-3084, https://doi.org/10.5194/egusphere-2023-3084, 2024
Short summary
Short summary
This paper evaluates land models – computer based models that simulate ecosystem dynamics, the land carbon, water and energy cycles and the role of land in the climate system. It uses machine learning / AI approaches to show that despite the complexity of land models, they do not perform nearly as well as they could, given the amount of information they are provided with about the prediction problem.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
J. Zhao, F. Roth, B. Bauer-Marschallinger, W. Wagner, M. Chini, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 911–918, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023, 2023
Chenwei Xiao, Sönke Zaehle, Hui Yang, Jean-Pierre Wigneron, Christiane Schmullius, and Ana Bastos
Earth Syst. Dynam., 14, 1211–1237, https://doi.org/10.5194/esd-14-1211-2023, https://doi.org/10.5194/esd-14-1211-2023, 2023
Short summary
Short summary
Ecosystem resistance reflects their susceptibility during adverse conditions and can be changed by land management. We estimate ecosystem resistance to drought and temperature globally. We find a higher resistance to drought in forests compared to croplands and an evident loss of resistance to drought when primary forests are converted to secondary forests or they are harvested. Old-growth trees tend to be more resistant in some forests and crops benefit from irrigation during drought periods.
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
Short summary
Short summary
We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
Josef Innerkofler, Gottfried Kirchengast, Marc Schwärz, Christian Marquardt, and Yago Andres
Atmos. Meas. Tech., 16, 5217–5247, https://doi.org/10.5194/amt-16-5217-2023, https://doi.org/10.5194/amt-16-5217-2023, 2023
Short summary
Short summary
Atmosphere remote sensing using GNSS radio occultation provides a highly valuable basis for atmospheric and climate science. For the highest-quality demands, the Wegener Center set up a rigorous system for processing low-level measurement data. This excess-phase processing setup includes integrated quality control and uncertainty estimation. It was successfully evaluated and inter-compared, ensuring the capability of producing reliable long-term data records for climate applications.
Francisco Rodrigues do Amaral, Nicolas Gratiot, Thierry Pellarin, and Tran Anh Tu
Nat. Hazards Earth Syst. Sci., 23, 3379–3405, https://doi.org/10.5194/nhess-23-3379-2023, https://doi.org/10.5194/nhess-23-3379-2023, 2023
Short summary
Short summary
We propose an in-depth analysis of typhoon-induced compound flood drivers in the megacity of Ho Chi Minh, Vietnam. We use in situ and satellite measurements throughout the event to form a holistic overview of its impact. No evidence of storm surge was found, and peak precipitation presents a 16 h time lag to peak river discharge, which evacuates only 1.5 % of available water. The astronomical tide controls the river level even during the extreme event, and it is the main urban flood driver.
Martin Schwartz, Philippe Ciais, Aurélien De Truchis, Jérôme Chave, Catherine Ottlé, Cedric Vega, Jean-Pierre Wigneron, Manuel Nicolas, Sami Jouaber, Siyu Liu, Martin Brandt, and Ibrahim Fayad
Earth Syst. Sci. Data, 15, 4927–4945, https://doi.org/10.5194/essd-15-4927-2023, https://doi.org/10.5194/essd-15-4927-2023, 2023
Short summary
Short summary
As forests play a key role in climate-related issues, their accurate monitoring is critical to reduce global carbon emissions effectively. Based on open-access remote-sensing sensors, and artificial intelligence methods, we created high-resolution tree height, wood volume, and biomass maps of metropolitan France that outperform previous products. This study, based on freely available data, provides essential information to support climate-efficient forest management policies at a low cost.
Martin Hirschi, Bas Crezee, Pietro Stradiotti, Wouter Dorigo, and Sonia I. Seneviratne
EGUsphere, https://doi.org/10.5194/egusphere-2023-2499, https://doi.org/10.5194/egusphere-2023-2499, 2023
Short summary
Short summary
Based on surface and root-zone soil moisture, we compare the ability of selected long-term reanalysis and merged remote-sensing products to represent major agroecological drought events. While all products capture the investigated droughts, they particularly show differences in the drought magnitudes. Globally, the diverse and regionally contradicting dry-season soil moisture trends of the products is an important factor governing their drought representation and monitoring capability.
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023, https://doi.org/10.5194/nhess-23-3305-2023, 2023
Short summary
Short summary
In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
Qianqian Han, Yijian Zeng, Lijie Zhang, Calimanut-Ionut Cira, Egor Prikaziuk, Ting Duan, Chao Wang, Brigitta Szabó, Salvatore Manfreda, Ruodan Zhuang, and Bob Su
Geosci. Model Dev., 16, 5825–5845, https://doi.org/10.5194/gmd-16-5825-2023, https://doi.org/10.5194/gmd-16-5825-2023, 2023
Short summary
Short summary
Using machine learning, we estimated global surface soil moisture (SSM) to aid in understanding water, energy, and carbon exchange. Ensemble models outperformed individual algorithms in predicting SSM under different climates. The best-performing ensemble included K-neighbours Regressor, Random Forest Regressor, and Extreme Gradient Boosting. This is important for hydrological and climatological applications such as water cycle monitoring, irrigation management, and crop yield prediction.
Jessica A. Eisma, Gerrit Schoups, Jeffrey C. Davids, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 27, 3565–3579, https://doi.org/10.5194/hess-27-3565-2023, https://doi.org/10.5194/hess-27-3565-2023, 2023
Short summary
Short summary
Citizen scientists often submit high-quality data, but a robust method for assessing data quality is needed. This study develops a semi-automated program that characterizes the mistakes made by citizen scientists by grouping them into communities of citizen scientists with similar mistake tendencies and flags potentially erroneous data for further review. This work may help citizen science programs assess the quality of their data and can inform training practices.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
Short summary
Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
Short summary
Short summary
In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Andrew O. Hoffman, Michelle Maclennan, Jan Lenaerts, Kristine M. Larson, and Knut Chrsitianson
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-114, https://doi.org/10.5194/tc-2023-114, 2023
Preprint under review for TC
Short summary
Short summary
Traditionally, glaciologists have used GNSS to measure the surface elevation, and velocity of glaciers to understand processes associated with ice flow. Using the interference of GNSS signals that bounce off of the ice sheet surface, we measure the surface height change of several receivers in the Amundsen Sea Embayment. From surface height change, we infer accumulation records and use these records to understand the drivers of extreme precipitation on Thwaites Glacier.
Tanja Denager, Torben O. Sonnenborg, Majken C. Looms, Heye Bogena, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 27, 2827–2845, https://doi.org/10.5194/hess-27-2827-2023, https://doi.org/10.5194/hess-27-2827-2023, 2023
Short summary
Short summary
This study contributes to improvements in the model characterization of water and energy fluxes. The results show that multi-objective autocalibration in combination with mathematical regularization is a powerful tool to improve land surface models. Using the direct measurement of turbulent fluxes as the target variable, parameter optimization matches simulations and observations of latent heat, whereas sensible heat is clearly biased.
Kai-Gao Ouyang, Xiao-Wei Jiang, Gang Mei, Hong-Bin Yan, Ran Niu, Li Wan, and Yijian Zeng
Hydrol. Earth Syst. Sci., 27, 2579–2590, https://doi.org/10.5194/hess-27-2579-2023, https://doi.org/10.5194/hess-27-2579-2023, 2023
Short summary
Short summary
Our knowledge on sources and dynamics of rock moisture is limited. By using frequency domain reflectometry (FDR), we monitored rock moisture in a cave. The results of an explainable deep learning model reveal that the direct source of rock moisture responsible for weathering in the studied cave is vapour, not infiltrating precipitation. A physics-informed deep learning model, which uses variables controlling vapor condensation as model inputs, leads to accurate rock water content predictions.
Haibo Du, Michael C. Stambaugh, Jesús Julio Camarero, Mai-He Li, Dapao Yu, Shengwei Zong, Hong S. He, and Zhengfang Wu
Clim. Past, 19, 1295–1304, https://doi.org/10.5194/cp-19-1295-2023, https://doi.org/10.5194/cp-19-1295-2023, 2023
Short summary
Short summary
We reconstruct, for the first time, high-resolution temperatures prior to the Millennium Eruption (946 CE) using a unique tree-ring proxy dataset in Changbai Mountain and compare them with modern temperatures. The temperatures during the last 1.5 centuries have stronger fluctuations, more frequent abruption, and a weaker periodicity of temperature variance compared to the pre-millennium temperatures. These recent changes correspond to long-term anthropogenic influences on regional climate.
Lena Katharina Jänicke, Rene Preusker, Marco Celesti, Marin Tudoroiu, Jürgen Fischer, Dirk Schüttemeyer, and Matthias Drusch
Atmos. Meas. Tech., 16, 3101–3121, https://doi.org/10.5194/amt-16-3101-2023, https://doi.org/10.5194/amt-16-3101-2023, 2023
Short summary
Short summary
To compare two top-of-atmosphere radiances measured by instruments with different spectral characteristics, a transfer function has been developed. It is applied to a tandem data set of Sentinel-3A and B, for which OLCI-B mimicked the ESA’s eighth Earth Explorer FLEX. We found that OLCI-A measured radiances about 2 % brighter than OLCI-FLEX. Only at larger wavelengths were OLCI-A measurements about 5 % darker. The method is thus successful, being sensitive to calibration and processing issues.
Alan Robock, Lili Xia, Cheryl S. Harrison, Joshua Coupe, Owen B. Toon, and Charles G. Bardeen
Atmos. Chem. Phys., 23, 6691–6701, https://doi.org/10.5194/acp-23-6691-2023, https://doi.org/10.5194/acp-23-6691-2023, 2023
Short summary
Short summary
A nuclear war could produce a nuclear winter, with catastrophic consequences for global food supplies. Nuclear winter theory helped to end the nuclear arms race in the 1980s, but more than 10 000 nuclear weapons still exist. This means they can be used, by unstable leaders, accidently from technical malfunctions or human error, or by terrorists. Therefore, it is urgent for scientists to study these issues, broadly communicate their results, and work for the elimination of nuclear weapons.
Irena Nimac, Julia Danzer, and Gottfried Kirchengast
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-100, https://doi.org/10.5194/amt-2023-100, 2023
Revised manuscript not accepted
Short summary
Short summary
As global wind measurements are limited by low spatial coverage or lack of vertical profile information, radio occultation (RO) satellite data might be of help. Wind fields are indirectly retrieved using the geostrophic approximation. We first test how well the method performs, finding agreement better than 2 m/s in wind speed. In a second step, we investigate how good RO and reanalysis data compare. The results suggest that RO-derived wind fields provide added value for climate monitoring.
Jerom P.M. Aerts, Jannis M. Hoch, Gemma Coxon, Nick C. van de Giesen, and Rolf W. Hut
EGUsphere, https://doi.org/10.5194/egusphere-2023-1156, https://doi.org/10.5194/egusphere-2023-1156, 2023
Short summary
Short summary
Hydrological model performance involves comparing simulated states and fluxes with observed counterparts. Often, it is overlooked that there is inherent uncertainty surrounding the observations. This can significantly impact the results. In this publication, we emphasize the significance of accounting for observation uncertainty in model comparison. We propose a practical method that is applicable for any observational time series with available uncertainty estimations.
Daniele Visioni, Ben Kravitz, Alan Robock, Simone Tilmes, Jim Haywood, Olivier Boucher, Mark Lawrence, Peter Irvine, Ulrike Niemeier, Lili Xia, Gabriel Chiodo, Chris Lennard, Shingo Watanabe, John C. Moore, and Helene Muri
Atmos. Chem. Phys., 23, 5149–5176, https://doi.org/10.5194/acp-23-5149-2023, https://doi.org/10.5194/acp-23-5149-2023, 2023
Short summary
Short summary
Geoengineering indicates methods aiming to reduce the temperature of the planet by means of reflecting back a part of the incoming radiation before it reaches the surface or allowing more of the planetary radiation to escape into space. It aims to produce modelling experiments that are easy to reproduce and compare with different climate models, in order to understand the potential impacts of these techniques. Here we assess its past successes and failures and talk about its future.
Lianyu Yu, Yijian Zeng, Huanjie Cai, Mengna Li, Yuanyuan Zha, Jicai Zeng, Hui Qian, and Zhongbo Su
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-221, https://doi.org/10.5194/gmd-2022-221, 2023
Revised manuscript not accepted
Short summary
Short summary
We developed a coupled soil water-groundwater (SW-GW) model, which is verified as physically accurate and applicable in large-scale groundwater problems. The role of vadose zone processes, coupling approach, and spatiotemporal heterogeneity of SW-GW interactions were highlighted as essential to represent the SW-GW system. Given the relevant dataset, the developed SW-GW modeling framework has the potential to portray the processes "from bedrock to atmosphere" in a physically consistent manner.
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Bart Schilperoort, Nick van de Giesen, Imasiku Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 1695–1722, https://doi.org/10.5194/hess-27-1695-2023, https://doi.org/10.5194/hess-27-1695-2023, 2023
Short summary
Short summary
Miombo woodland plants continue to lose water even during the driest part of the year. This appears to be facilitated by the adapted features such as deep rooting (beyond 5 m) with access to deep soil moisture, potentially even ground water. It appears the trend and amount of water that the plants lose is correlated more to the available energy. This loss of water in the dry season by miombo woodland plants appears to be incorrectly captured by satellite-based evaporation estimates.
Ane LaBianca, Mette H. Mortensen, Peter Sandersen, Torben O. Sonnenborg, Karsten H. Jensen, and Jacob Kidmose
Hydrol. Earth Syst. Sci., 27, 1645–1666, https://doi.org/10.5194/hess-27-1645-2023, https://doi.org/10.5194/hess-27-1645-2023, 2023
Short summary
Short summary
The study explores the effect of Anthropocene geology and the computational grid size on the simulation of shallow urban groundwater. Many cities are facing challenges with high groundwater levels close to the surface, yet urban planning and development seldom consider its impact on the groundwater resource. This study illustrates that the urban subsurface infrastructure significantly affects the groundwater flow paths and the residence time of shallow urban groundwater.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
Short summary
Short summary
Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Shengli Tao, Zurui Ao, Jean-Pierre Wigneron, Sassan Saatchi, Philippe Ciais, Jérôme Chave, Thuy Le Toan, Pierre-Louis Frison, Xiaomei Hu, Chi Chen, Lei Fan, Mengjia Wang, Jiangling Zhu, Xia Zhao, Xiaojun Li, Xiangzhuo Liu, Yanjun Su, Tianyu Hu, Qinghua Guo, Zhiheng Wang, Zhiyao Tang, Yi Y. Liu, and Jingyun Fang
Earth Syst. Sci. Data, 15, 1577–1596, https://doi.org/10.5194/essd-15-1577-2023, https://doi.org/10.5194/essd-15-1577-2023, 2023
Short summary
Short summary
We provide the first long-term (since 1992), high-resolution (8.9 km) satellite radar backscatter data set (LHScat) with a C-band (5.3 GHz) signal dynamic for global lands. LHScat was created by fusing signals from ERS (1992–2001; C-band), QSCAT (1999–2009; Ku-band), and ASCAT (since 2007; C-band). LHScat has been validated against independent ERS-2 signals. It could be used in a variety of studies, such as vegetation monitoring and hydrological modelling.
Jacopo Dari, Luca Brocca, Sara Modanesi, Christian Massari, Angelica Tarpanelli, Silvia Barbetta, Raphael Quast, Mariette Vreugdenhil, Vahid Freeman, Anaïs Barella-Ortiz, Pere Quintana-Seguí, David Bretreger, and Espen Volden
Earth Syst. Sci. Data, 15, 1555–1575, https://doi.org/10.5194/essd-15-1555-2023, https://doi.org/10.5194/essd-15-1555-2023, 2023
Short summary
Short summary
Irrigation is the main source of global freshwater consumption. Despite this, a detailed knowledge of irrigation dynamics (i.e., timing, extent of irrigated areas, and amounts of water used) are generally lacking worldwide. Satellites represent a useful tool to fill this knowledge gap and monitor irrigation water from space. In this study, three regional-scale and high-resolution (1 and 6 km) products of irrigation amounts estimated by inverting the satellite soil moisture signals are presented.
Remi Madelon, Nemesio J. Rodríguez-Fernández, Hassan Bazzi, Nicolas Baghdadi, Clement Albergel, Wouter Dorigo, and Mehrez Zribi
Hydrol. Earth Syst. Sci., 27, 1221–1242, https://doi.org/10.5194/hess-27-1221-2023, https://doi.org/10.5194/hess-27-1221-2023, 2023
Short summary
Short summary
We present an approach to estimate soil moisture (SM) at 1 km resolution using Sentinel-1 and Sentinel-3 satellites. The estimates were compared to other high-resolution (HR) datasets over Europe, northern Africa, Australia, and North America, showing good agreement. However, the discrepancies between the different HR datasets and their lower performances compared with in situ measurements and coarse-resolution datasets show the remaining challenges for large-scale HR SM mapping.
Mohammad Ghoreishi, Amin Elshorbagy, Saman Razavi, Günter Blöschl, Murugesu Sivapalan, and Ahmed Abdelkader
Hydrol. Earth Syst. Sci., 27, 1201–1219, https://doi.org/10.5194/hess-27-1201-2023, https://doi.org/10.5194/hess-27-1201-2023, 2023
Short summary
Short summary
The study proposes a quantitative model of the willingness to cooperate in the Eastern Nile River basin. Our results suggest that the 2008 food crisis may account for Sudan recovering its willingness to cooperate with Ethiopia. Long-term lack of trust among the riparian countries may have reduced basin-wide cooperation. The model can be used to explore the effects of changes in future dam operations and other management decisions on the emergence of basin cooperation.
Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
Short summary
Short summary
Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Ranndal, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 27, 1011–1032, https://doi.org/10.5194/hess-27-1011-2023, https://doi.org/10.5194/hess-27-1011-2023, 2023
Short summary
Short summary
This paper uses remote sensing data from ICESat-2 to calibrate a 1D hydraulic model. With the model, we can make estimations of discharge and water surface elevation, which are important indicators in flooding risk assessment. ICESat-2 data give an added value, thanks to the 0.7 m resolution, which allows the measurement of narrow river streams. In addition, ICESat-2 provides measurements on the river dry portion geometry that can be included in the model.
En Liu, Yonghua Zhu, Jean-christophe Calvet, Haishen Lü, Bertrand Bonan, Jingyao Zheng, Qiqi Gou, Xiaoyi Wang, Zhenzhou Ding, Haiting Xu, Ying Pan, and Tingxing Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-33, https://doi.org/10.5194/hess-2023-33, 2023
Manuscript not accepted for further review
Short summary
Short summary
Among the 8 considered products, GLDAS_CLSM product performs best. All RZSM products overestimate the in situ measurements which attributes to a wet bias of air temperature, precipitation amount and frequency except the underestimation of SMOS L4 RZSM related to the underestimation of SMOS L3 SSM. The higher R between SMPA L4 and MERRA-2 was attributed to they both use CLSM and meteorological forcing from GEOS-5 where precipitation was corrected with CPCU precipitation product.
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
Short summary
Short summary
Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Ying Li, Gottfried Kirchengast, Marc Schwaerz, and Yunbin Yuan
Atmos. Chem. Phys., 23, 1259–1284, https://doi.org/10.5194/acp-23-1259-2023, https://doi.org/10.5194/acp-23-1259-2023, 2023
Short summary
Short summary
We develop a new approach to monitor sudden stratospheric warming (SSW) events since 1980 and develop a 42-year SSW event climatology. Detection and evaluation results suggest that the new method is robust for SSW monitoring. We also found an increase in the duration of SSW main-phase warmings of about 5(±2) d over the three decades from the 1980s to the 2010s, raising the average duration from about 10 to 15 d, and the warming strength is also found increased.
Kunlong He, Wei Zhao, Luca Brocca, and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023, https://doi.org/10.5194/hess-27-169-2023, 2023
Short summary
Short summary
In this study, we developed a soil moisture-based precipitation downscaling (SMPD) method for spatially downscaling the GPM daily precipitation product by exploiting the connection between surface soil moisture and precipitation according to the soil water balance equation. Based on this physical method, the spatial resolution of the daily precipitation product was downscaled to 1 km and the SMPD method shows good potential for the development of the high-resolution precipitation product.
Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023, https://doi.org/10.5194/hess-27-39-2023, 2023
Short summary
Short summary
The live fuel moisture content (LFMC) of vegetation canopies is a driver of wildfires. We investigate the relation between LFMC and passive microwave satellite observations of vegetation optical depth (VOD) and develop a method to estimate LFMC from VOD globally. Our global VOD-based estimates of LFMC can be used to investigate drought effects on vegetation and fire risks.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yaoming Ma, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 14, 5513–5542, https://doi.org/10.5194/essd-14-5513-2022, https://doi.org/10.5194/essd-14-5513-2022, 2022
Short summary
Short summary
Soil moisture and soil temperature (SMST) are important state variables for quantifying the heat–water exchange between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements at multiple depths are scarce on the Tibetan Plateau (TP). The presented dataset would be valuable for the evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
Short summary
Short summary
Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Bimal K. Bhattacharya, Kaniska Mallick, Devansh Desai, Ganapati S. Bhat, Ross Morrison, Jamie R. Clevery, William Woodgate, Jason Beringer, Kerry Cawse-Nicholson, Siyan Ma, Joseph Verfaillie, and Dennis Baldocchi
Biogeosciences, 19, 5521–5551, https://doi.org/10.5194/bg-19-5521-2022, https://doi.org/10.5194/bg-19-5521-2022, 2022
Short summary
Short summary
Evaporation retrieval in heterogeneous ecosystems is challenging due to empirical estimation of ground heat flux and complex parameterizations of conductances. We developed a parameter-sparse coupled ground heat flux-evaporation model and tested it across different limits of water stress and vegetation fraction in the Northern/Southern Hemisphere. The model performed particularly well in the savannas and showed good potential for evaporative stress monitoring from thermal infrared satellites.
Enrico Bonanno, Günter Blöschl, and Julian Klaus
Hydrol. Earth Syst. Sci., 26, 6003–6028, https://doi.org/10.5194/hess-26-6003-2022, https://doi.org/10.5194/hess-26-6003-2022, 2022
Short summary
Short summary
There is an unclear understanding of which processes regulate the transport of water, solutes, and pollutants in streams. This is crucial since these processes control water quality in river networks. Compared to other approaches, we obtained clearer insights into the processes controlling solute transport in the investigated reach. This work highlights the risks of using uncertain results for interpreting the processes controlling water movement in streams.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022, https://doi.org/10.5194/hess-26-5955-2022, 2022
Short summary
Short summary
We proposed a practical method that predicts the evaporation rates on land surfaces (ET) where only atmospheric data are available. Using a traditional equation that describes partitioning of precipitation into ET and streamflow, we could approximately identify the key parameter of the predicting formulation based on land–atmosphere interactions. The simple method conditioned by local climates outperformed sophisticated models in reproducing water-balance estimates across Australia.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
Short summary
Short summary
Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo
Biogeosciences, 19, 5107–5123, https://doi.org/10.5194/bg-19-5107-2022, https://doi.org/10.5194/bg-19-5107-2022, 2022
Short summary
Short summary
The standardized vegetation optical depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage, spans the past 3 decades and is derived from multiple spaceborne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data even if the data are not gap-free.
Hong Zhao, Yijian Zeng, Jan G. Hofste, Ting Duan, Jun Wen, and Zhongbo Su
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-333, https://doi.org/10.5194/hess-2022-333, 2022
Revised manuscript not accepted
Short summary
Short summary
This paper demonstrated the capability of our developed platform for simulating microwave emission and backscatter signals at multi-frequency. The results of associated investigations on impacts of vegetation water (VW) and temperature (T) imply the need to first disentangle the impact of T for the use of high-frequency signals as its variation is more due to dynamic T. Estimated vegetation optical depth is frequency-dependent, while its diurnal variation depends on that of VW despite frequency.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 5015–5033, https://doi.org/10.5194/hess-26-5015-2022, https://doi.org/10.5194/hess-26-5015-2022, 2022
Short summary
Short summary
There is serious concern that river floods are increasing. Starting from explanations discussed in public, the article addresses three hypotheses: land-use change, hydraulic structures, and climate change increase floods. This review finds that all three changes have the potential to not only increase floods, but also to reduce them. It is crucial to consider all three factors of change in flood risk management and communicate them to the general public in a nuanced way.
Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
Short summary
Short summary
Given the crucial impact of irrigation practices on the water cycle, this study aims at estimating irrigation through the development of an innovative data assimilation system able to ingest high-resolution Sentinel-1 radar observations into the Noah-MP land surface model. The developed methodology has important implications for global water resource management and the comprehension of human impacts on the water cycle and identifies main challenges and outlooks for future research.
Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
Short summary
Short summary
This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Jerom P. M. Aerts, Rolf W. Hut, Nick C. van de Giesen, Niels Drost, Willem J. van Verseveld, Albrecht H. Weerts, and Pieter Hazenberg
Hydrol. Earth Syst. Sci., 26, 4407–4430, https://doi.org/10.5194/hess-26-4407-2022, https://doi.org/10.5194/hess-26-4407-2022, 2022
Short summary
Short summary
In recent years gridded hydrological modelling moved into the realm of hyper-resolution modelling (<10 km). In this study, we investigate the effect of varying grid-cell sizes for the wflow_sbm hydrological model. We used a large sample of basins from the CAMELS data set to test the effect that varying grid-cell sizes has on the simulation of streamflow at the basin outlet. Results show that there is no single best grid-cell size for modelling streamflow throughout the domain.
M. Tupas, C. Navacchi, F. Roth, B. Bauer-Marschallinger, F. Reuß, and W. Wagner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 495–502, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-495-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-495-2022, 2022
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
Short summary
Short summary
This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Rolf Hut, Niels Drost, Nick van de Giesen, Ben van Werkhoven, Banafsheh Abdollahi, Jerom Aerts, Thomas Albers, Fakhereh Alidoost, Bouwe Andela, Jaro Camphuijsen, Yifat Dzigan, Ronald van Haren, Eric Hutton, Peter Kalverla, Maarten van Meersbergen, Gijs van den Oord, Inti Pelupessy, Stef Smeets, Stefan Verhoeven, Martine de Vos, and Berend Weel
Geosci. Model Dev., 15, 5371–5390, https://doi.org/10.5194/gmd-15-5371-2022, https://doi.org/10.5194/gmd-15-5371-2022, 2022
Short summary
Short summary
With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.
Robin van der Schalie, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu
Hydrol. Earth Syst. Sci., 26, 3611–3627, https://doi.org/10.5194/hess-26-3611-2022, https://doi.org/10.5194/hess-26-3611-2022, 2022
Short summary
Short summary
Climate data records of surface soil moisture, vegetation optical depth, and land surface temperature can be derived from passive microwave observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here, we present a case study over the Okavango Delta, where we focus on inter-annual variability.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
Short summary
Short summary
Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Rena Meyer, Wenmin Zhang, Søren Julsgaard Kragh, Mie Andreasen, Karsten Høgh Jensen, Rasmus Fensholt, Simon Stisen, and Majken C. Looms
Hydrol. Earth Syst. Sci., 26, 3337–3357, https://doi.org/10.5194/hess-26-3337-2022, https://doi.org/10.5194/hess-26-3337-2022, 2022
Short summary
Short summary
The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of great relevance for agriculture and water management. Here, we investigate whether the established downscaling algorithm combining different satellite products to estimate medium-scale soil moisture is applicable to higher resolutions and whether results can be improved by accounting for land cover types. Original satellite data and downscaled soil moisture are compared with ground observations.
Shengping Wang, Borbala Szeles, Carmen Krammer, Elmar Schmaltz, Kepeng Song, Yifan Li, Zhiqiang Zhang, Günter Blöschl, and Peter Strauss
Hydrol. Earth Syst. Sci., 26, 3021–3036, https://doi.org/10.5194/hess-26-3021-2022, https://doi.org/10.5194/hess-26-3021-2022, 2022
Short summary
Short summary
This study explored the quantitative contribution of agricultural intensification and climate change to the sediment load of a small agricultural watershed. Rather than a change in climatic conditions, changes in the land structure notably altered sediment concentrations under high-flow conditions, thereby contributing most to the increase in annual sediment loads. More consideration of land structure improvement is required when combating the transfer of soil from land to water.
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022, https://doi.org/10.5194/hess-26-2997-2022, 2022
Short summary
Short summary
This study investigates spatial and temporal patterns in the incidence angle dependence of backscatter from the ASCAT C-band scatterometer and relates those to precipitation, humidity, and radiation data and GRACE equivalent water thickness in ecoregions in the Amazon. The results show that the ASCAT data record offers a unique perspective on vegetation water dynamics exhibiting sensitivity to moisture availability and demand and phenological change at interannual, seasonal, and diurnal scales.
Maik Heistermann, Heye Bogena, Till Francke, Andreas Güntner, Jannis Jakobi, Daniel Rasche, Martin Schrön, Veronika Döpper, Benjamin Fersch, Jannis Groh, Amol Patil, Thomas Pütz, Marvin Reich, Steffen Zacharias, Carmen Zengerle, and Sascha Oswald
Earth Syst. Sci. Data, 14, 2501–2519, https://doi.org/10.5194/essd-14-2501-2022, https://doi.org/10.5194/essd-14-2501-2022, 2022
Short summary
Short summary
This paper presents a dense network of cosmic-ray neutron sensing (CRNS) to measure spatio-temporal soil moisture patterns during a 2-month campaign in the Wüstebach headwater catchment in Germany. Stationary, mobile, and airborne CRNS technology monitored the root-zone water dynamics as well as spatial heterogeneity in the 0.4 km2 area. The 15 CRNS stations were supported by a hydrogravimeter, biomass sampling, and a wireless soil sensor network to facilitate holistic hydrological analysis.
Wei Qu, Heye Bogena, Christoph Schüth, Harry Vereecken, Zongmei Li, and Stephan Schulz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-131, https://doi.org/10.5194/gmd-2022-131, 2022
Publication in GMD not foreseen
Short summary
Short summary
We applied the global sensitivity analysis LH-OAT to the integrated hydrology model ParFlow-CLM to investigate the sensitivity of the 12 parameters for different scenarios. And we found that the general patterns of the parameter sensitivities were consistent, however, for some parameters a significantly larger span of the sensitivities was observed, especially for the higher slope and in subarctic climatic scenarios.
Anthony Mucia, Bertrand Bonan, Clément Albergel, Yongjun Zheng, and Jean-Christophe Calvet
Biogeosciences, 19, 2557–2581, https://doi.org/10.5194/bg-19-2557-2022, https://doi.org/10.5194/bg-19-2557-2022, 2022
Short summary
Short summary
For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
Verónica González-Gambau, Estrella Olmedo, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Justino Martínez, Pekka Alenius, Laura Tuomi, Rafael Catany, Manuel Arias, Carolina Gabarró, Nina Hoareau, Marta Umbert, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 2343–2368, https://doi.org/10.5194/essd-14-2343-2022, https://doi.org/10.5194/essd-14-2343-2022, 2022
Short summary
Short summary
We present the first Soil Moisture and Ocean Salinity Sea Surface Salinity (SSS) dedicated products over the Baltic Sea (ESA Baltic+ Salinity Dynamics). The Baltic+ L3 product covers 9 days in a 0.25° grid. The Baltic+ L4 is derived by merging L3 SSS with sea surface temperature information, giving a daily product in a 0.05° grid. The accuracy of L3 is 0.7–0.8 and 0.4 psu for the L4. Baltic+ products have shown to be useful, covering spatiotemporal data gaps and for validating numerical models.
Paolo Filippucci, Luca Brocca, Raphael Quast, Luca Ciabatta, Carla Saltalippi, Wolfgang Wagner, and Angelica Tarpanelli
Hydrol. Earth Syst. Sci., 26, 2481–2497, https://doi.org/10.5194/hess-26-2481-2022, https://doi.org/10.5194/hess-26-2481-2022, 2022
Short summary
Short summary
A high-resolution (1 km) rainfall product with 10–30 d temporal resolution was obtained starting from SM data from Sentinel-1. Good performances are achieved using observed data (gauge and radar) over the Po River Valley, Italy, as a benchmark. The comparison with a product characterized by lower spatial resolution (25 km) highlights areas where the high spatial resolution of Sentinel-1 has great benefits. Possible applications include water management, agriculture and index-based insurances.
Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 2469–2480, https://doi.org/10.5194/hess-26-2469-2022, https://doi.org/10.5194/hess-26-2469-2022, 2022
Short summary
Short summary
Sound understanding of how floods come about allows for the development of more reliable flood management tools that assist in mitigating their negative impacts. This article reviews river flood generation processes and flow paths across space scales, starting from water movement in the soil pores and moving up to hillslopes, catchments, regions and entire continents. To assist model development, there is a need to learn from observed patterns of flood generation processes at all spatial scales.
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Petra Hulsman, Nick van de Giesen, Imasiku Nyambe, and Hubert Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-114, https://doi.org/10.5194/hess-2022-114, 2022
Manuscript not accepted for further review
Short summary
Short summary
We compare performance of evaporation models in the Luangwa Basin located in a semi-arid and complex Miombo ecosystem in Africa. Miombo plants changes colour, drop off leaves and acquire new leaves during the dry season. In addition, the plant roots go deep in the soil and appear to access groundwater. Results show that evaporation models with structure and process that do not capture this unique plant structure and behaviour appears to have difficulties to correctly estimating evaporation.
Rui Tong, Juraj Parajka, Borbála Széles, Isabella Greimeister-Pfeil, Mariette Vreugdenhil, Jürgen Komma, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 1779–1799, https://doi.org/10.5194/hess-26-1779-2022, https://doi.org/10.5194/hess-26-1779-2022, 2022
Short summary
Short summary
The role and impact of using additional data (other than runoff) for the prediction of daily hydrographs in ungauged basins are not well understood. In this study, we assessed the model performance in terms of runoff, soil moisture, and snow cover predictions with the existing regionalization approaches. Results show that the best transfer methods are the similarity and the kriging approaches. The performance of the transfer methods differs between lowland and alpine catchments.
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
Short summary
Short summary
This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
Short summary
Short summary
Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
Short summary
Short summary
Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Paul C. Vermunt, Susan C. Steele-Dunne, Saeed Khabbazan, Jasmeet Judge, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022, https://doi.org/10.5194/hess-26-1223-2022, 2022
Short summary
Short summary
This study investigates the use of hydrometeorological sensors to reconstruct variations in internal vegetation water content of corn and relates these variations to the sub-daily behaviour of polarimetric L-band backscatter. The results show significant sensitivity of backscatter to the daily cycles of vegetation water content and dew, particularly on dry days and for vertical and cross-polarizations, which demonstrates the potential for using radar for studies on vegetation water dynamics.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
Short summary
Short summary
Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
Justino Martínez, Carolina Gabarró, Antonio Turiel, Verónica González-Gambau, Marta Umbert, Nina Hoareau, Cristina González-Haro, Estrella Olmedo, Manuel Arias, Rafael Catany, Laurent Bertino, Roshin P. Raj, Jiping Xie, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 307–323, https://doi.org/10.5194/essd-14-307-2022, https://doi.org/10.5194/essd-14-307-2022, 2022
Short summary
Short summary
Measuring salinity from space is challenging since the sensitivity of the brightness temperature to sea surface salinity is low, but the retrieval of SSS in cold waters is even more challenging. In 2019, the ESA launched a specific initiative called Arctic+Salinity to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
Short summary
Short summary
The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
Lukas Strebel, Heye R. Bogena, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 15, 395–411, https://doi.org/10.5194/gmd-15-395-2022, https://doi.org/10.5194/gmd-15-395-2022, 2022
Short summary
Short summary
We present the technical coupling between a land surface model (CLM5) and the Parallel Data Assimilation Framework (PDAF). This coupling enables measurement data to update simulated model states and parameters in a statistically optimal way. We demonstrate the viability of the model framework using an application in a forested catchment where the inclusion of soil water measurements significantly improved the simulation quality.
Shaoning Lv, Clemens Simmer, Yijian Zeng, Jun Wen, Yuanyuan Guo, and Zhongbo Su
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-369, https://doi.org/10.5194/tc-2021-369, 2022
Preprint withdrawn
Short summary
Short summary
The freeze-thaw of the ground is an interesting topic to climatology, hydrology, and other earth sciences. The global freeze-thaw distribution is available by passive microwave remote sensing technique. However, the remote sensing technique indirectly detects freeze-thaw states by measuring the brightness temperature difference between frozen and unfrozen soil. Thus, we present different interprets of the brightness signals to the FT-state by using its sub-daily character.
Chang-Hwan Park, Aaron Berg, Michael H. Cosh, Andreas Colliander, Andreas Behrendt, Hida Manns, Jinkyu Hong, Johan Lee, Runze Zhang, and Volker Wulfmeyer
Hydrol. Earth Syst. Sci., 25, 6407–6420, https://doi.org/10.5194/hess-25-6407-2021, https://doi.org/10.5194/hess-25-6407-2021, 2021
Short summary
Short summary
In this study, we proposed an inversion of the dielectric mixing model for a 50 Hz soil sensor for agricultural organic soil. This model can reflect the variability of soil organic matter (SOM) in wilting point and porosity, which play a critical role in improving the accuracy of SM estimation, using a dielectric-based soil sensor. The results of statistical analyses demonstrated a higher performance of the new model than the factory setting probe algorithm.
Sara Modanesi, Christian Massari, Alexander Gruber, Hans Lievens, Angelica Tarpanelli, Renato Morbidelli, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 6283–6307, https://doi.org/10.5194/hess-25-6283-2021, https://doi.org/10.5194/hess-25-6283-2021, 2021
Short summary
Short summary
Worldwide, the amount of water used for agricultural purposes is rising and the quantification of irrigation is becoming a crucial topic. Land surface models are not able to correctly simulate irrigation. Remote sensing observations offer an opportunity to fill this gap as they are directly affected by irrigation. We equipped a land surface model with an observation operator able to transform Sentinel-1 backscatter observations into realistic vegetation and soil states via data assimilation.
Lianyu Yu, Yijian Zeng, and Zhongbo Su
Geosci. Model Dev., 14, 7345–7376, https://doi.org/10.5194/gmd-14-7345-2021, https://doi.org/10.5194/gmd-14-7345-2021, 2021
Short summary
Short summary
We developed an integrated soil–snow–atmosphere model (STEMMUS-UEB) dedicated to the physical description of snow and soil processes with various complexities. With STEMMUS-UEB, we demonstrated that the snowpack affects not only the soil surface moisture conditions (in the liquid and ice phase) and energy-related states (albedo, LE) but also the subsurface soil water and vapor transfer, which contributes to a better understanding of the hydrothermal implications of the snowpack in cold regions.
Gil Mahé, Gamal Abdo, Ernest Amoussou, Telesphore Brou, Stephan Dietrich, Ahmed El Tayeb, Henny van Lanen, Mohamed Meddi, Anil Mishra, Didier Orange, Thi Phuong Quynh Le, Raphael Tshimanga, Patrick Valimba, Santiago Yepez, Andrew Ogilvie, and Oula Amrouni
Proc. IAHS, 384, 5–18, https://doi.org/10.5194/piahs-384-5-2021, https://doi.org/10.5194/piahs-384-5-2021, 2021
Short summary
Short summary
The FRIEND-Water program (FWP) is the oldest and the most transverse program within the UNESCO IHP. It allows large communities of hydrologists to collaborate across borders on common shared data and scientific topics, addressed through 8 large world regions. Research priorities evolve according to the projections given by the member States during the IHP councils. FWP further activities follow the IHP IX program with the support of the Montpellier UNESCO Category II Center ICIREWAD.
Ernest Amoussou, Gil Mahe, Oula Amrouni, Ansoumana Bodian, Christophe Cudennec, Stephan Dietrich, Domiho Japhet Kodja, and Expédit Wilfrid Vissin
Proc. IAHS, 384, 1–4, https://doi.org/10.5194/piahs-384-1-2021, https://doi.org/10.5194/piahs-384-1-2021, 2021
Short summary
Short summary
This short paper is the preface of the PIAHS volume of the IAHS/UNESCO FRIEND-Water conference of Cotonou in November 2021.
Daniele Masseroni, Stefania Camici, Alessio Cislaghi, Giorgio Vacchiano, Christian Massari, and Luca Brocca
Hydrol. Earth Syst. Sci., 25, 5589–5601, https://doi.org/10.5194/hess-25-5589-2021, https://doi.org/10.5194/hess-25-5589-2021, 2021
Short summary
Short summary
We evaluate 63 years of changes in annual streamflow volume across Europe, using a data set of more than 3000 stations, with a special focus on the Mediterranean basin. The results show decreasing (increasing) volumes in the southern (northern) regions. These trends are strongly consistent with the changes in temperature and precipitation.
David Lun, Alberto Viglione, Miriam Bertola, Jürgen Komma, Juraj Parajka, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 5535–5560, https://doi.org/10.5194/hess-25-5535-2021, https://doi.org/10.5194/hess-25-5535-2021, 2021
Short summary
Short summary
We investigate statistical properties of observed flood series on a European scale. There are pronounced regional patterns, for instance: regions with strong Atlantic influence show less year-to-year variability in the magnitude of observed floods when compared with more arid regions of Europe. The hydrological controls on the patterns are quantified and discussed. On the European scale, climate seems to be the dominant driver for the observed patterns.
Mengna Li, Yijian Zeng, Maciek W. Lubczynski, Jean Roy, Lianyu Yu, Hui Qian, Zhenyu Li, Jie Chen, Lei Han, Han Zheng, Tom Veldkamp, Jeroen M. Schoorl, Harrie-Jan Hendricks Franssen, Kai Hou, Qiying Zhang, Panpan Xu, Fan Li, Kai Lu, Yulin Li, and Zhongbo Su
Earth Syst. Sci. Data, 13, 4727–4757, https://doi.org/10.5194/essd-13-4727-2021, https://doi.org/10.5194/essd-13-4727-2021, 2021
Short summary
Short summary
The Tibetan Plateau is the source of most of Asia's major rivers and has been called the Asian Water Tower. Due to its remoteness and the harsh environment, there is a lack of field survey data to investigate its hydrogeology. Borehole core lithology analysis, an altitude survey, soil thickness measurement, hydrogeological surveys, and hydrogeophysical surveys were conducted in the Maqu catchment within the Yellow River source region to improve a full–picture understanding of the water cycle.
Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp
Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, https://doi.org/10.5194/hess-25-4887-2021, 2021
Short summary
Short summary
Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.
Didier de Villiers, Marc Schleiss, Marie-Claire ten Veldhuis, Rolf Hut, and Nick van de Giesen
Atmos. Meas. Tech., 14, 5607–5623, https://doi.org/10.5194/amt-14-5607-2021, https://doi.org/10.5194/amt-14-5607-2021, 2021
Short summary
Short summary
Ground-based rainfall observations across the African continent are sparse. We present a new and inexpensive rainfall measuring instrument (the intervalometer) and use it to derive reasonably accurate rainfall rates. These are dependent on a fundamental assumption that is widely used in parameterisations of the rain drop size distribution. This assumption is tested and found to not apply for most raindrops but is still useful in deriving rainfall rates. The intervalometer shows good potential.
Hong-Yu Xie, Xiao-Wei Jiang, Shu-Cong Tan, Li Wan, Xu-Sheng Wang, Si-Hai Liang, and Yijian Zeng
Hydrol. Earth Syst. Sci., 25, 4243–4257, https://doi.org/10.5194/hess-25-4243-2021, https://doi.org/10.5194/hess-25-4243-2021, 2021
Short summary
Short summary
Freezing-induced groundwater migration and water table decline are widely observed, but quantitative understanding of these processes is lacking. By considering wintertime atmospheric conditions and occurrence of lateral groundwater inflow, a model coupling soil water and groundwater reproduced field observations of soil temperature, soil water content, and groundwater level well. The model results led to a clear understanding of the balance of the water budget during the freezing–thawing cycle.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
Short summary
Short summary
Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, and Peng Gong
Geosci. Model Dev., 14, 4573–4592, https://doi.org/10.5194/gmd-14-4573-2021, https://doi.org/10.5194/gmd-14-4573-2021, 2021
Short summary
Short summary
In this study, we implemented the specific morphology, phenology and harvest process of oil palm in the global land surface model ORCHIDEE-MICT. The improved model generally reproduces the same leaf area index, biomass density and life cycle fruit yield as observations. This explicit representation of oil palm in a global land surface model offers a useful tool for understanding the ecological processes of oil palm growth and assessing the environmental impacts of oil palm plantations.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
Short summary
Short summary
The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Cunbo Han, Yaoming Ma, Binbin Wang, Lei Zhong, Weiqiang Ma, Xuelong Chen, and Zhongbo Su
Earth Syst. Sci. Data, 13, 3513–3524, https://doi.org/10.5194/essd-13-3513-2021, https://doi.org/10.5194/essd-13-3513-2021, 2021
Short summary
Short summary
Actual terrestrial evapotranspiration (ETa) is a key parameter controlling the land–atmosphere interaction processes and water cycle. However, the spatial distribution and temporal changes in ETa over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001–2018) monthly ETa and its spatial distribution on the TP by a combination of meteorological data and satellite products. Results have been validated at six eddy-covariance monitoring sites and show high accuracy.
Concetta Di Mauro, Renaud Hostache, Patrick Matgen, Ramona Pelich, Marco Chini, Peter Jan van Leeuwen, Nancy K. Nichols, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 4081–4097, https://doi.org/10.5194/hess-25-4081-2021, https://doi.org/10.5194/hess-25-4081-2021, 2021
Short summary
Short summary
This study evaluates how the sequential assimilation of flood extent derived from synthetic aperture radar data can help improve flood forecasting. In particular, we carried out twin experiments based on a synthetically generated dataset with controlled uncertainty. Our empirical results demonstrate the efficiency of the proposed data assimilation framework, as forecasting errors are substantially reduced as a result of the assimilation.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 13, 3075–3102, https://doi.org/10.5194/essd-13-3075-2021, https://doi.org/10.5194/essd-13-3075-2021, 2021
Short summary
Short summary
This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface soil moisture (SM) dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs. This surface SM dataset includes the original 15 min in situ measurements collected by multiple SM monitoring sites of three networks (i.e. the Maqu, Naqu, and Ngari networks) and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks.
A. Iglseder, M. Bruggisser, A. Dostálová, N. Pfeifer, S. Schlaffer, W. Wagner, and M. Hollaus
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 567–574, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-567-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-567-2021, 2021
K. D. Kanniah, N. A. F. Kamarul Zaman, and K. Perumal
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 399–403, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-399-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-399-2021, 2021
Jaber Rahimi, Expedit Evariste Ago, Augustine Ayantunde, Sina Berger, Jan Bogaert, Klaus Butterbach-Bahl, Bernard Cappelaere, Jean-Martial Cohard, Jérôme Demarty, Abdoul Aziz Diouf, Ulrike Falk, Edwin Haas, Pierre Hiernaux, David Kraus, Olivier Roupsard, Clemens Scheer, Amit Kumar Srivastava, Torbern Tagesson, and Rüdiger Grote
Geosci. Model Dev., 14, 3789–3812, https://doi.org/10.5194/gmd-14-3789-2021, https://doi.org/10.5194/gmd-14-3789-2021, 2021
Short summary
Short summary
West African Sahelian and Sudanian ecosystems are important regions for global carbon exchange, and they provide valuable food and fodder resources. Therefore, we simulated net ecosystem exchange and aboveground biomass of typical ecosystems in this region with an improved process-based biogeochemical model, LandscapeDNDC. Carbon stocks and exchange rates were particularly correlated with the abundance of trees. Grass and crop yields increased under humid climatic conditions.
Jan G. Hofste, Rogier van der Velde, Jun Wen, Xin Wang, Zuoliang Wang, Donghai Zheng, Christiaan van der Tol, and Zhongbo Su
Earth Syst. Sci. Data, 13, 2819–2856, https://doi.org/10.5194/essd-13-2819-2021, https://doi.org/10.5194/essd-13-2819-2021, 2021
Short summary
Short summary
The dataset reported in this paper concerns the measurement of microwave reflections from an alpine meadow over the Tibetan Plateau. These microwave reflections were measured continuously over 1 year. With it, variations in soil water content due to evaporation, precipitation, drainage, and soil freezing/thawing can be seen. A better understanding of the effects aforementioned processes have on microwave reflections may improve methods for estimating soil water content used by satellites.
Maria Teresa Brunetti, Massimo Melillo, Stefano Luigi Gariano, Luca Ciabatta, Luca Brocca, Giriraj Amarnath, and Silvia Peruccacci
Hydrol. Earth Syst. Sci., 25, 3267–3279, https://doi.org/10.5194/hess-25-3267-2021, https://doi.org/10.5194/hess-25-3267-2021, 2021
Short summary
Short summary
Satellite and rain gauge data are tested to predict landslides in India, where the annual toll of human lives and loss of property urgently demands the implementation of strategies to prevent geo-hydrological instability. For this purpose, we calculated empirical rainfall thresholds for landslide initiation. The validation of thresholds showed that satellite-based rainfall data perform better than ground-based data, and the best performance is obtained with an hourly temporal resolution.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
Short summary
Short summary
Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Yanbin Lei, Tandong Yao, Kun Yang, Lazhu, Yaoming Ma, and Broxton W. Bird
Hydrol. Earth Syst. Sci., 25, 3163–3177, https://doi.org/10.5194/hess-25-3163-2021, https://doi.org/10.5194/hess-25-3163-2021, 2021
Short summary
Short summary
Lake evaporation from Paiku Co on the TP is low in spring and summer and high in autumn and early winter. There is a ~ 5-month lag between net radiation and evaporation due to large lake heat storage. High evaporation and low inflow cause significant lake-level decrease in autumn and early winter, while low evaporation and high inflow cause considerable lake-level increase in summer. This study implies that evaporation can affect the different amplitudes of lake-level variations on the TP.
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
Short summary
Short summary
Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
Short summary
Short summary
We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Anteneh Getachew Mengistu, Gizaw Mengistu Tsidu, Gerbrand Koren, Maurits L. Kooreman, K. Folkert Boersma, Torbern Tagesson, Jonas Ardö, Yann Nouvellon, and Wouter Peters
Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, https://doi.org/10.5194/bg-18-2843-2021, 2021
Short summary
Short summary
In this study, we assess the usefulness of Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval (SIFTER) data from the GOME-2A instrument and near-infrared reflectance of vegetation (NIRv) from MODIS to capture the seasonality and magnitudes of gross primary production (GPP) derived from six eddy-covariance flux towers in Africa in the overlap years between 2007–2014. We also test the robustness of sun-induced fluoresence and NIRv to compare the seasonality of GPP for the major biomes.
Antara Banerjee, Amy H. Butler, Lorenzo M. Polvani, Alan Robock, Isla R. Simpson, and Lantao Sun
Atmos. Chem. Phys., 21, 6985–6997, https://doi.org/10.5194/acp-21-6985-2021, https://doi.org/10.5194/acp-21-6985-2021, 2021
Short summary
Short summary
We find that simulated stratospheric sulfate geoengineering could lead to warmer Eurasian winters alongside a drier Mediterranean and wetting to the north. These effects occur due to the strengthening of the Northern Hemisphere stratospheric polar vortex, which shifts the North Atlantic Oscillation to a more positive phase. We find the effects in our simulations to be much more significant than the wintertime effects of large tropical volcanic eruptions which inject much less sulfate aerosol.
Lovrenc Pavlin, Borbála Széles, Peter Strauss, Alfred Paul Blaschke, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 2327–2352, https://doi.org/10.5194/hess-25-2327-2021, https://doi.org/10.5194/hess-25-2327-2021, 2021
Short summary
Short summary
We compared the dynamics of streamflow, groundwater and soil moisture to investigate how different parts of an agricultural catchment in Lower Austria are connected. Groundwater is best connected around the stream and worse uphill, where groundwater is deeper. Soil moisture connectivity increases with increasing catchment wetness but is not influenced by spatial position in the catchment. Groundwater is more connected to the stream on the seasonal scale compared to the event scale.
Hiroki Mizuochi, Agnès Ducharne, Frédérique Cheruy, Josefine Ghattas, Amen Al-Yaari, Jean-Pierre Wigneron, Vladislav Bastrikov, Philippe Peylin, Fabienne Maignan, and Nicolas Vuichard
Hydrol. Earth Syst. Sci., 25, 2199–2221, https://doi.org/10.5194/hess-25-2199-2021, https://doi.org/10.5194/hess-25-2199-2021, 2021
Ying Li, Gottfried Kirchengast, Marc Schwärz, Florian Ladstädter, and Yunbin Yuan
Atmos. Meas. Tech., 14, 2327–2343, https://doi.org/10.5194/amt-14-2327-2021, https://doi.org/10.5194/amt-14-2327-2021, 2021
Short summary
Short summary
We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known Jan.–Feb. 2009 event. We found that RO data are capable of SSW monitoring. Based on our method, a SSW event can be detected and tracked, and the duration and the strength of the event can be recorded. The results are consistent with other research on the 2009 event.
Jürgen Fuchsberger, Gottfried Kirchengast, and Thomas Kabas
Earth Syst. Sci. Data, 13, 1307–1334, https://doi.org/10.5194/essd-13-1307-2021, https://doi.org/10.5194/essd-13-1307-2021, 2021
Short summary
Short summary
The paper describes the most recent weather and climate data from the WegenerNet station networks, providing hydrometeorological measurements since 2007 at very high spatial and temporal resolution for long-term observation in two regions in southeastern Austria: the WegenerNet Feldbach Region, in the Alpine forelands, comprising 155 stations with 1 station about every 2 km2, and the WegenerNet Johnsbachtal, in a mountainous region, with 14 stations at altitudes from about 600 m to 2200 m.
Rui Tong, Juraj Parajka, Andreas Salentinig, Isabella Pfeil, Jürgen Komma, Borbála Széles, Martin Kubáň, Peter Valent, Mariette Vreugdenhil, Wolfgang Wagner, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1389–1410, https://doi.org/10.5194/hess-25-1389-2021, https://doi.org/10.5194/hess-25-1389-2021, 2021
Short summary
Short summary
We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index data set and Moderate Resolution Imaging Spectroradiometer (MODIS) C6 snow cover products for multiple objective calibrations of the TUWmodel in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.
Ben Kravitz, Douglas G. MacMartin, Daniele Visioni, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Andy Jones, Thibaut Lurton, Pierre Nabat, Ulrike Niemeier, Alan Robock, Roland Séférian, and Simone Tilmes
Atmos. Chem. Phys., 21, 4231–4247, https://doi.org/10.5194/acp-21-4231-2021, https://doi.org/10.5194/acp-21-4231-2021, 2021
Short summary
Short summary
This study investigates multi-model response to idealized geoengineering (high CO2 with solar reduction) across two different generations of climate models. We find that, with the exception of a few cases, the results are unchanged between the different generations. This gives us confidence that broad conclusions about the response to idealized geoengineering are robust.
Miriam Bertola, Alberto Viglione, Sergiy Vorogushyn, David Lun, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1347–1364, https://doi.org/10.5194/hess-25-1347-2021, https://doi.org/10.5194/hess-25-1347-2021, 2021
Short summary
Short summary
We estimate the contribution of extreme precipitation, antecedent soil moisture and snowmelt to changes in small and large floods across Europe.
In northwestern and eastern Europe, changes in small and large floods are driven mainly by one single driver (i.e. extreme precipitation and snowmelt, respectively). In southern Europe both antecedent soil moisture and extreme precipitation significantly contribute to flood changes, and their relative importance depends on flood magnitude.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-126, https://doi.org/10.5194/hess-2021-126, 2021
Revised manuscript not accepted
Short summary
Short summary
This work evaluate a convenient operational method to simulate evaporation over dry land surfaces across Australia. While this chosen method based on the responsive behavior of atmospheric water demand outperformed commonly-used sophisticated models in predicting evaporation in the United States and China, it showed some poor performance in wet river basins Australia. Yet, its performance was still good under (semi-)arid climates.
Yunfei Wang, Yijian Zeng, Lianyu Yu, Peiqi Yang, Christiaan Van der Tol, Qiang Yu, Xiaoliang Lü, Huanjie Cai, and Zhongbo Su
Geosci. Model Dev., 14, 1379–1407, https://doi.org/10.5194/gmd-14-1379-2021, https://doi.org/10.5194/gmd-14-1379-2021, 2021
Short summary
Short summary
This study integrates photosynthesis and transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum system, via a simplified 1D root growth model. The results indicated that the simulation of land surface fluxes was significantly improved by considering the root water uptake, especially when vegetation was experiencing severe water stress. This finding highlights the importance of enhanced soil heat and moisture transfer in simulating ecosystem functioning.
Margot Clyne, Jean-Francois Lamarque, Michael J. Mills, Myriam Khodri, William Ball, Slimane Bekki, Sandip S. Dhomse, Nicolas Lebas, Graham Mann, Lauren Marshall, Ulrike Niemeier, Virginie Poulain, Alan Robock, Eugene Rozanov, Anja Schmidt, Andrea Stenke, Timofei Sukhodolov, Claudia Timmreck, Matthew Toohey, Fiona Tummon, Davide Zanchettin, Yunqian Zhu, and Owen B. Toon
Atmos. Chem. Phys., 21, 3317–3343, https://doi.org/10.5194/acp-21-3317-2021, https://doi.org/10.5194/acp-21-3317-2021, 2021
Short summary
Short summary
This study finds how and why five state-of-the-art global climate models with interactive stratospheric aerosols differ when simulating the aftermath of large volcanic injections as part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP). We identify and explain the consequences of significant disparities in the underlying physics and chemistry currently in some of the models, which are problems likely not unique to the models participating in this study.
María P. González-Dugo, Xuelong Chen, Ana Andreu, Elisabet Carpintero, Pedro J. Gómez-Giraldez, Arnaud Carrara, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 755–768, https://doi.org/10.5194/hess-25-755-2021, https://doi.org/10.5194/hess-25-755-2021, 2021
Short summary
Short summary
Drought is a devastating natural hazard and difficult to define, detect and quantify. Global meteorological data and remote-sensing products present new opportunities to characterize drought in an objective way. In this paper, we applied the surface energy balance model SEBS to estimate monthly evapotranspiration (ET) from 2001 to 2018 over the dehesa area of the Iberian Peninsula. ET anomalies were used to identify the main drought events and analyze their impacts on dehesa vegetation.
Louise Mimeau, Yves Tramblay, Luca Brocca, Christian Massari, Stefania Camici, and Pascal Finaud-Guyot
Hydrol. Earth Syst. Sci., 25, 653–669, https://doi.org/10.5194/hess-25-653-2021, https://doi.org/10.5194/hess-25-653-2021, 2021
Short summary
Short summary
Soil moisture is a key variable related to droughts and flood genesis, but little is known about the evolution of soil moisture under climate change. Here, using a simulation approach, we show that changes in soil moisture are driven by changes in precipitation intermittence rather than changes in precipitation intensity or in temperature.
Michael Gorbunov, Gottfried Kirchengast, and Kent B. Lauritsen
Atmos. Meas. Tech., 14, 853–867, https://doi.org/10.5194/amt-14-853-2021, https://doi.org/10.5194/amt-14-853-2021, 2021
Short summary
Short summary
Currently, the canonical transform (CT) approach to the processing of radio occultation observations is widely used. For the spherically symmetric atmosphere, the applicability of this method can be strictly proven. However, in the presence of horizontal gradients, this approach may not work. Here we introduce a generalization of the CT method in order to reduce the errors due to horizontal gradients.
Nataniel M. Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, and Alexandra G. Konings
Biogeosciences, 18, 739–753, https://doi.org/10.5194/bg-18-739-2021, https://doi.org/10.5194/bg-18-739-2021, 2021
Short summary
Short summary
Microwave radiation coming from Earth's land surface is affected by both soil moisture and the water in plants that cover the soil. We measured such radiation with a sensor elevated above a forest canopy while repeatedly measuring the amount of water stored in trees at the same location. Changes in the microwave signal over time were closely related to tree water storage changes. Satellites with similar sensors could thus be used to monitor how trees in an entire region respond to drought.
Rogier van der Velde, Andreas Colliander, Michiel Pezij, Harm-Jan F. Benninga, Rajat Bindlish, Steven K. Chan, Thomas J. Jackson, Dimmie M. D. Hendriks, Denie C. M. Augustijn, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 473–495, https://doi.org/10.5194/hess-25-473-2021, https://doi.org/10.5194/hess-25-473-2021, 2021
Short summary
Short summary
NASA’s SMAP satellite provides estimates of the amount of water in the soil. With measurements from a network of 20 monitoring stations, the accuracy of these estimates has been studied for a 4-year period. We found an agreement between satellite and in situ estimates in line with the mission requirements once the large mismatches associated with rapidly changing water contents, e.g. soil freezing and rainfall, are excluded.
Andy Jones, Jim M. Haywood, Anthony C. Jones, Simone Tilmes, Ben Kravitz, and Alan Robock
Atmos. Chem. Phys., 21, 1287–1304, https://doi.org/10.5194/acp-21-1287-2021, https://doi.org/10.5194/acp-21-1287-2021, 2021
Short summary
Short summary
Two different methods of simulating a geoengineering scenario are compared using data from two different Earth system models. One method is very idealised while the other includes details of a plausible mechanism. The results from both models agree that the idealised approach does not capture an impact found when detailed modelling is included, namely that geoengineering induces a positive phase of the North Atlantic Oscillation which leads to warmer, wetter winters in northern Europe.
Theresa Boas, Heye Bogena, Thomas Grünwald, Bernard Heinesch, Dongryeol Ryu, Marius Schmidt, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, https://doi.org/10.5194/gmd-14-573-2021, 2021
Short summary
Short summary
In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
Wim Verbruggen, Guy Schurgers, Stéphanie Horion, Jonas Ardö, Paulo N. Bernardino, Bernard Cappelaere, Jérôme Demarty, Rasmus Fensholt, Laurent Kergoat, Thomas Sibret, Torbern Tagesson, and Hans Verbeeck
Biogeosciences, 18, 77–93, https://doi.org/10.5194/bg-18-77-2021, https://doi.org/10.5194/bg-18-77-2021, 2021
Short summary
Short summary
A large part of Earth's land surface is covered by dryland ecosystems, which are subject to climate extremes that are projected to increase under future climate scenarios. By using a mathematical vegetation model, we studied the impact of single years of extreme rainfall on the vegetation in the Sahel. We found a contrasting response of grasses and trees to these extremes, strongly dependent on the way precipitation is spread over the rainy season, as well as a long-term impact on CO2 uptake.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
Short summary
Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Lianyu Yu, Simone Fatichi, Yijian Zeng, and Zhongbo Su
The Cryosphere, 14, 4653–4673, https://doi.org/10.5194/tc-14-4653-2020, https://doi.org/10.5194/tc-14-4653-2020, 2020
Short summary
Short summary
The role of soil water and heat transfer physics in portraying the function of a cold region ecosystem was investigated. We found that explicitly considering the frozen soil physics and coupled water and heat transfer is important in mimicking soil hydrothermal dynamics. The presence of soil ice can alter the vegetation leaf onset date and deep leakage. Different complexity in representing vadose zone physics does not considerably affect interannual energy, water, and carbon fluxes.
Jędrzej S. Bojanowski and Jan P. Musiał
Atmos. Meas. Tech., 13, 6771–6788, https://doi.org/10.5194/amt-13-6771-2020, https://doi.org/10.5194/amt-13-6771-2020, 2020
Short summary
Short summary
Satellites such as NOAA's Advanced Very High Resolution Radiometer can uniquely observe changes in cloud cover but are affected by orbital drift that results in shifted image acquisition times, which in turn lead to spurious trends in cloud cover detected during climatological analyses. Providing a detailed quantification of these trends, we show that climate data records must be analysed with caution, as for some periods and regions they do not comply with the requirements for climate data.
Pierre-Yves Tournigand, Valeria Cigala, Elzbieta Lasota, Mohammed Hammouti, Lieven Clarisse, Hugues Brenot, Fred Prata, Gottfried Kirchengast, Andrea K. Steiner, and Riccardo Biondi
Earth Syst. Sci. Data, 12, 3139–3159, https://doi.org/10.5194/essd-12-3139-2020, https://doi.org/10.5194/essd-12-3139-2020, 2020
Short summary
Short summary
The detection and monitoring of volcanic clouds are important for aviation management, climate and weather forecasts. We present in this paper the first comprehensive archive collecting spatial and temporal information about volcanic clouds generated by the 11 largest eruptions of this century. We provide a complete set of state-of-the-art data allowing the development and testing of new algorithms contributing to improve the accuracy of the estimation of fundamental volcanic cloud parameters.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406, https://doi.org/10.5194/hess-24-5379-2020, https://doi.org/10.5194/hess-24-5379-2020, 2020
Short summary
Short summary
This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
Elżbieta Lasota, Andrea K. Steiner, Gottfried Kirchengast, and Riccardo Biondi
Earth Syst. Sci. Data, 12, 2679–2693, https://doi.org/10.5194/essd-12-2679-2020, https://doi.org/10.5194/essd-12-2679-2020, 2020
Short summary
Short summary
In this work, we provide a comprehensive archive of tropical cyclone vertical structure for the period 2001–2018. The tropical cyclone best tracks are co-located in time and space with high-vertical-resolution atmospheric profiles (temperature, pressure, humidity and refractivity) from radio occultations and with climatological profiles. This dataset can be used to analyze the inner vertical thermodynamic structure of tropical cyclones and the pre-cyclone environment.
Xu Yuan, Xiaolong Yu, and Zhongbo Su
Ocean Sci., 16, 1285–1296, https://doi.org/10.5194/os-16-1285-2020, https://doi.org/10.5194/os-16-1285-2020, 2020
Short summary
Short summary
This work investigates the variabilities of the barrier layer thickness (BLT) in the tropical Indian Ocean with the Simple Ocean Data Assimilation version 3 ocean reanalysis data. Our results show that the seasonal variation of the BLT is in relation to the changes of thermocline and sea surface salinity. In terms of the interannual timescale, BLT presents a clear seasonal phase locking dominated by different drivers during the Indian Dipole and El Niño–Southern Oscillation events.
M. M. Salvia, N. Sánchez, M. Piles, A. Gonzalez-Zamora, and J. Martínez-Fernández
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3-W2-2020, 53–58, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-53-2020, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-53-2020, 2020
Justus G. V. van Ramshorst, Miriam Coenders-Gerrits, Bart Schilperoort, Bas J. H. van de Wiel, Jonathan G. Izett, John S. Selker, Chad W. Higgins, Hubert H. G. Savenije, and Nick C. van de Giesen
Atmos. Meas. Tech., 13, 5423–5439, https://doi.org/10.5194/amt-13-5423-2020, https://doi.org/10.5194/amt-13-5423-2020, 2020
Short summary
Short summary
In this work we present experimental results of a novel actively heated fiber-optic (AHFO) observational wind-probing technique. We utilized a controlled wind-tunnel setup to assess both the accuracy and precision of AHFO under a range of operational conditions (wind speed, angles of attack and temperature differences). AHFO has the potential to provide high-resolution distributed observations of wind speeds, allowing for better spatial characterization of fine-scale processes.
Stefania Camici, Christian Massari, Luca Ciabatta, Ivan Marchesini, and Luca Brocca
Hydrol. Earth Syst. Sci., 24, 4869–4885, https://doi.org/10.5194/hess-24-4869-2020, https://doi.org/10.5194/hess-24-4869-2020, 2020
Short summary
Short summary
The paper performs the most comprehensive European-scale evaluation to date of satellite rainfall products for river flow prediction. In doing so, how errors transfer from satellite-based rainfall products into flood simulation is investigated in depth and, for the first time, quantitative guidelines on the use of these products for hydrological applications are provided. This result can represent a keystone in the use of satellite rainfall products, especially in data-scarce regions.
Lianyu Yu, Yijian Zeng, and Zhongbo Su
Hydrol. Earth Syst. Sci., 24, 4813–4830, https://doi.org/10.5194/hess-24-4813-2020, https://doi.org/10.5194/hess-24-4813-2020, 2020
Short summary
Short summary
Soil mass and heat transfer processes were represented in three levels of model complexities to understand soil freeze–thaw mechanisms. Results indicate that coupled mass and heat transfer models considerably improved simulations of the soil hydrothermal regime. Vapor flow and thermal effects on water flow are the main mechanisms for the improvements. Given the explicit consideration of airflow, vapor flow and its effects on heat transfer were enhanced during the freeze–thaw transition period.
El Mahdi El Khalki, Yves Tramblay, Christian Massari, Luca Brocca, Vincent Simonneaux, Simon Gascoin, and Mohamed El Mehdi Saidi
Nat. Hazards Earth Syst. Sci., 20, 2591–2607, https://doi.org/10.5194/nhess-20-2591-2020, https://doi.org/10.5194/nhess-20-2591-2020, 2020
Short summary
Short summary
In North Africa, the vulnerability to floods is high, and there is a need to improve the flood-forecasting systems. Remote-sensing and reanalysis data can palliate the lack of in situ measurements, in particular for soil moisture, which is a crucial parameter to consider when modeling floods. In this study we provide an evaluation of recent globally available soil moisture products for flood modeling in Morocco.
Clara Hohmann, Gottfried Kirchengast, Sungmin O, Wolfgang Rieger, and Ulrich Foelsche
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-453, https://doi.org/10.5194/hess-2020-453, 2020
Manuscript not accepted for further review
Short summary
Short summary
Heavy precipitation events are still feeding with a large uncertainty into hydrological models. Based on the highly dense station network WegenerNet (one station per 2 km2) we analyzed the sensitivity of runoff simulations to different rain network densities and interpolation methods in small catchments. We find, and quantify relevant characteristics, that runoff curves especially from
short-duration convective rainfall events are strongly influenced by gauge station density and distribution.
Jie Tian, Zhibo Han, Heye Reemt Bogena, Johan Alexander Huisman, Carsten Montzka, Baoqing Zhang, and Chansheng He
Hydrol. Earth Syst. Sci., 24, 4659–4674, https://doi.org/10.5194/hess-24-4659-2020, https://doi.org/10.5194/hess-24-4659-2020, 2020
Short summary
Short summary
Large-scale profile soil moisture (SM) is important for water resource management, but its estimation is a challenge. Thus, based on in situ SM observations in a cold mountain, a strong relationship between the surface SM and subsurface SM is found. Both the subsurface SM of 10–30 cm and the profile SM of 0–70 cm can be estimated from the surface SM of 0–10 cm accurately. By combing with the satellite product, we improve the large-scale profile SM estimation in the cold mountains finally.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
Short summary
Short summary
Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, https://doi.org/10.5194/hess-24-4291-2020, 2020
Short summary
Short summary
LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
Yongjun Zheng, Clément Albergel, Simon Munier, Bertrand Bonan, and Jean-Christophe Calvet
Geosci. Model Dev., 13, 3607–3625, https://doi.org/10.5194/gmd-13-3607-2020, https://doi.org/10.5194/gmd-13-3607-2020, 2020
Short summary
Short summary
This study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framework for high-dimensional ensemble Kalman filters. The offline and online modes of ensemble Kalman filters are built to comprehensively assess their time to solution efficiencies. The offline mode is substantially faster than the online mode in terms of time to solution, especially for large-scale assimilation problems.
J. Zhao, M. Chini, R. Pelich, P. Matgen, R. Hostache, S. Cao, and W. Wagner
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 395–400, https://doi.org/10.5194/isprs-annals-V-1-2020-395-2020, https://doi.org/10.5194/isprs-annals-V-1-2020-395-2020, 2020
W. Wagner, V. Freeman, S. Cao, P. Matgen, M. Chini, P. Salamon, N. McCormick, S. Martinis, B. Bauer-Marschallinger, C. Navacchi, M. Schramm, C. Reimer, and C. Briese
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 641–648, https://doi.org/10.5194/isprs-annals-V-3-2020-641-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-641-2020, 2020
D. Chen, X. Zhang, N. Chen, J. Yang, and J. Gong
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2020, 115–121, https://doi.org/10.5194/isprs-annals-V-4-2020-115-2020, https://doi.org/10.5194/isprs-annals-V-4-2020-115-2020, 2020
Simone Tilmes, Douglas G. MacMartin, Jan T. M. Lenaerts, Leo van Kampenhout, Laura Muntjewerf, Lili Xia, Cheryl S. Harrison, Kristen M. Krumhardt, Michael J. Mills, Ben Kravitz, and Alan Robock
Earth Syst. Dynam., 11, 579–601, https://doi.org/10.5194/esd-11-579-2020, https://doi.org/10.5194/esd-11-579-2020, 2020
Short summary
Short summary
This paper introduces new geoengineering model experiments as part of a larger model intercomparison effort, using reflective particles to block some of the incoming solar radiation to reach surface temperature targets. Outcomes of these applications are contrasted based on a high greenhouse gas emission pathway and a pathway with strong mitigation and negative emissions after 2040. We compare quantities that matter for societal and ecosystem impacts between the different scenarios.
Doris Duethmann, Günter Blöschl, and Juraj Parajka
Hydrol. Earth Syst. Sci., 24, 3493–3511, https://doi.org/10.5194/hess-24-3493-2020, https://doi.org/10.5194/hess-24-3493-2020, 2020
Short summary
Short summary
We investigate why a conceptual hydrological model failed to correctly predict observed discharge changes in response to increasing precipitation and air temperature in 156 Austrian catchments. Simulations indicate that poor model performance is related to two problems, namely a model structure that neglects changes in vegetation dynamics and inhomogeneities in precipitation data caused by changes in stations density with time. Other hypotheses did not improve simulated discharge changes.
Francesca Gallo, Janek Uin, Stephen Springston, Jian Wang, Guangjie Zheng, Chongai Kuang, Robert Wood, Eduardo B. Azevedo, Allison McComiskey, Fan Mei, Adam Theisen, Jenni Kyrouac, and Allison C. Aiken
Atmos. Chem. Phys., 20, 7553–7573, https://doi.org/10.5194/acp-20-7553-2020, https://doi.org/10.5194/acp-20-7553-2020, 2020
Short summary
Short summary
Continuous high-time-resolution ambient data can include periods when aerosol properties do not represent regional aerosol processes due to high-concentration local events. We develop a novel aerosol mask at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) facility in the eastern North Atlantic (ENA). We use two ground sites to validate the mask, include a comparison with aircraft overflights, and provide guidance to increase data quality at ENA and other locations.
Kristine M. Larson, Michael MacFerrin, and Thomas Nylen
The Cryosphere, 14, 1985–1988, https://doi.org/10.5194/tc-14-1985-2020, https://doi.org/10.5194/tc-14-1985-2020, 2020
Short summary
Short summary
Reflected GPS signals can be used to measure snow accumulation. The GPS method is accurate and has a footprint that is larger than that of many other methods. This short note makes available 9 years of daily snow accumulation measurements from Greenland that were derived from reflected GPS signals. It also provides information about open-source software that the cryosphere community can use to analyze other datasets.
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020, https://doi.org/10.5194/hess-24-2687-2020, 2020
Short summary
Short summary
Rain gauges are unevenly spaced around the world with extremely low gauge density over places like Africa and South America. Here, water-related problems like floods, drought and famine are particularly severe and able to cause fatalities, migration and diseases. We have developed a rainfall dataset that exploits the synergies between rainfall and soil moisture to provide accurate rainfall observations which can be used to face these problems.
Andrea K. Steiner, Florian Ladstädter, Chi O. Ao, Hans Gleisner, Shu-Peng Ho, Doug Hunt, Torsten Schmidt, Ulrich Foelsche, Gottfried Kirchengast, Ying-Hwa Kuo, Kent B. Lauritsen, Anthony J. Mannucci, Johannes K. Nielsen, William Schreiner, Marc Schwärz, Sergey Sokolovskiy, Stig Syndergaard, and Jens Wickert
Atmos. Meas. Tech., 13, 2547–2575, https://doi.org/10.5194/amt-13-2547-2020, https://doi.org/10.5194/amt-13-2547-2020, 2020
Short summary
Short summary
High-quality observations are critically important for monitoring the Earth’s changing climate. We provide information on the consistency and long-term stability of observations from GPS radio occultation (RO). We assess, for the first time, RO records from multiple RO missions and all major RO data providers. Our results quantify where RO can be used for reliable trend assessment and confirm its climate quality.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
Short summary
Short summary
We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
Miriam Bertola, Alberto Viglione, David Lun, Julia Hall, and Günter Blöschl
Hydrol. Earth Syst. Sci., 24, 1805–1822, https://doi.org/10.5194/hess-24-1805-2020, https://doi.org/10.5194/hess-24-1805-2020, 2020
Short summary
Short summary
We investigate changes that occurred in small vs. big flood events and in small vs. large catchments across Europe over 5 decades. Annual maximum discharge series between 1960 and 2010 from 2370 gauges in Europe are analysed. Distinctive patterns of flood regime change are identified for large regions across Europe, which depend on flood magnitude and catchment size.
Angelika Xaver, Luca Zappa, Gerhard Rab, Isabella Pfeil, Mariette Vreugdenhil, Drew Hemment, and Wouter Arnoud Dorigo
Geosci. Instrum. Method. Data Syst., 9, 117–139, https://doi.org/10.5194/gi-9-117-2020, https://doi.org/10.5194/gi-9-117-2020, 2020
Short summary
Short summary
Soil moisture plays a key role in the hydrological cycle and the climate system. Although soil moisture can be observed by the means of satellites, ground observations are still crucial for evaluating and improving these satellite products. In this study, we investigate the performance of a consumer low-cost soil moisture sensor in the lab and in the field. We demonstrate that this sensor can be used for scientific applications, for example to create a dataset valuable for satellite validation.
Chris R. Flechard, Andreas Ibrom, Ute M. Skiba, Wim de Vries, Marcel van Oijen, David R. Cameron, Nancy B. Dise, Janne F. J. Korhonen, Nina Buchmann, Arnaud Legout, David Simpson, Maria J. Sanz, Marc Aubinet, Denis Loustau, Leonardo Montagnani, Johan Neirynck, Ivan A. Janssens, Mari Pihlatie, Ralf Kiese, Jan Siemens, André-Jean Francez, Jürgen Augustin, Andrej Varlagin, Janusz Olejnik, Radosław Juszczak, Mika Aurela, Daniel Berveiller, Bogdan H. Chojnicki, Ulrich Dämmgen, Nicolas Delpierre, Vesna Djuricic, Julia Drewer, Eric Dufrêne, Werner Eugster, Yannick Fauvel, David Fowler, Arnoud Frumau, André Granier, Patrick Gross, Yannick Hamon, Carole Helfter, Arjan Hensen, László Horváth, Barbara Kitzler, Bart Kruijt, Werner L. Kutsch, Raquel Lobo-do-Vale, Annalea Lohila, Bernard Longdoz, Michal V. Marek, Giorgio Matteucci, Marta Mitosinkova, Virginie Moreaux, Albrecht Neftel, Jean-Marc Ourcival, Kim Pilegaard, Gabriel Pita, Francisco Sanz, Jan K. Schjoerring, Maria-Teresa Sebastià, Y. Sim Tang, Hilde Uggerud, Marek Urbaniak, Netty van Dijk, Timo Vesala, Sonja Vidic, Caroline Vincke, Tamás Weidinger, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Eiko Nemitz, and Mark A. Sutton
Biogeosciences, 17, 1583–1620, https://doi.org/10.5194/bg-17-1583-2020, https://doi.org/10.5194/bg-17-1583-2020, 2020
Short summary
Short summary
Experimental evidence from a network of 40 monitoring sites in Europe suggests that atmospheric nitrogen deposition to forests and other semi-natural vegetation impacts the carbon sequestration rates in ecosystems, as well as the net greenhouse gas balance including other greenhouse gases such as nitrous oxide and methane. Excess nitrogen deposition in polluted areas also leads to other environmental impacts such as nitrogen leaching to groundwater and other pollutant gaseous emissions.
Chris R. Flechard, Marcel van Oijen, David R. Cameron, Wim de Vries, Andreas Ibrom, Nina Buchmann, Nancy B. Dise, Ivan A. Janssens, Johan Neirynck, Leonardo Montagnani, Andrej Varlagin, Denis Loustau, Arnaud Legout, Klaudia Ziemblińska, Marc Aubinet, Mika Aurela, Bogdan H. Chojnicki, Julia Drewer, Werner Eugster, André-Jean Francez, Radosław Juszczak, Barbara Kitzler, Werner L. Kutsch, Annalea Lohila, Bernard Longdoz, Giorgio Matteucci, Virginie Moreaux, Albrecht Neftel, Janusz Olejnik, Maria J. Sanz, Jan Siemens, Timo Vesala, Caroline Vincke, Eiko Nemitz, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Ute M. Skiba, and Mark A. Sutton
Biogeosciences, 17, 1621–1654, https://doi.org/10.5194/bg-17-1621-2020, https://doi.org/10.5194/bg-17-1621-2020, 2020
Short summary
Short summary
Nitrogen deposition from the atmosphere to unfertilized terrestrial vegetation such as forests can increase carbon dioxide uptake and favour carbon sequestration by ecosystems. However the data from observational networks are difficult to interpret in terms of a carbon-to-nitrogen response, because there are a number of other confounding factors, such as climate, soil physical properties and fertility, and forest age. We propose a model-based method to untangle the different influences.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
Short summary
Short summary
The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
Short summary
Short summary
Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
Bertrand Bonan, Clément Albergel, Yongjun Zheng, Alina Lavinia Barbu, David Fairbairn, Simon Munier, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 325–347, https://doi.org/10.5194/hess-24-325-2020, https://doi.org/10.5194/hess-24-325-2020, 2020
Short summary
Short summary
This paper introduces an ensemble square root filter (EnSRF), a deterministic ensemble Kalman filter, for jointly assimilating observations of the surface soil moisture and leaf area index in the Land Data Assimilation System LDAS-Monde. LDAS-Monde constrains the Interaction between Soil, Biosphere and Atmosphere (ISBA) land surface model to improve the reanalysis of land surface variables. EnSRF is compared with the simplified extended Kalman filter over the European Mediterranean region.
Michael Paul Stockinger, Heye Reemt Bogena, Andreas Lücke, Christine Stumpp, and Harry Vereecken
Hydrol. Earth Syst. Sci., 23, 4333–4347, https://doi.org/10.5194/hess-23-4333-2019, https://doi.org/10.5194/hess-23-4333-2019, 2019
Short summary
Short summary
Precipitation moves through the soil to become stream water. The fraction of precipitation that becomes stream water after 3 months (Fyw) can be calculated with the stable isotopes of water. Previously, this was done for all the isotope data available, e.g., for several years. We used 1 year of data to calculate Fyw and moved this calculation time window over the time series. Results highlight that Fyw varies in time. Comparison studies of different regions should take this into account.
Luca Brocca, Paolo Filippucci, Sebastian Hahn, Luca Ciabatta, Christian Massari, Stefania Camici, Lothar Schüller, Bojan Bojkov, and Wolfgang Wagner
Earth Syst. Sci. Data, 11, 1583–1601, https://doi.org/10.5194/essd-11-1583-2019, https://doi.org/10.5194/essd-11-1583-2019, 2019
Short summary
Short summary
SM2RAIN–ASCAT is a new 12-year (2007–2018) global-scale rainfall dataset obtained by applying the SM2RAIN algorithm to ASCAT soil moisture data. The dataset has a spatiotemporal sampling resolution of 12.5 km and 1 d. Results show that the new dataset performs particularly well in Africa and South America, i.e. in the continents in which ground observations are scarce and the need for satellite rainfall data is high. SM2RAIN–ASCAT is available at http://doi.org/10.5281/zenodo.340556.
Jing Tao, Randal D. Koster, Rolf H. Reichle, Barton A. Forman, Yuan Xue, Richard H. Chen, and Mahta Moghaddam
The Cryosphere, 13, 2087–2110, https://doi.org/10.5194/tc-13-2087-2019, https://doi.org/10.5194/tc-13-2087-2019, 2019
Short summary
Short summary
The active layer thickness (ALT) in middle-to-high northern latitudes from 1980 to 2017 was produced at 81 km2 resolution by a global land surface model (NASA's CLSM) with forcing fields from a reanalysis data set, MERRA-2. The simulated permafrost distribution and ALTs agree reasonably well with an observation-based map and in situ measurements, respectively. The accumulated above-freezing air temperature and maximum snow water equivalent explain most of the year-to-year variability of ALT.
Britta Schmalz, Stephan Dietrich, and João L. M. P. de Lima
Adv. Geosci., 48, 49–51, https://doi.org/10.5194/adgeo-48-49-2019, https://doi.org/10.5194/adgeo-48-49-2019, 2019
Christoph Schlager, Gottfried Kirchengast, Juergen Fuchsberger, Alexander Kann, and Heimo Truhetz
Geosci. Model Dev., 12, 2855–2873, https://doi.org/10.5194/gmd-12-2855-2019, https://doi.org/10.5194/gmd-12-2855-2019, 2019
Short summary
Short summary
Empirical high-resolution surface wind fields from two study areas, automatically generated by a weather diagnostic application, were intercompared with wind fields of different modeling approaches. The focus is on evaluating spatial differences and displacements between the different datasets. In general, the spatial verification indicates a better statistical agreement for the first study area (hilly WegenerNet Feldbach Region), than for the second one (mountainous WegenerNet Johnsbachtal).
X. Chen, Z. Su, and Y. Ma
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1729–1733, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1729-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1729-2019, 2019
Alexander Gruber, Tracy Scanlon, Robin van der Schalie, Wolfgang Wagner, and Wouter Dorigo
Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, https://doi.org/10.5194/essd-11-717-2019, 2019
Short summary
Short summary
Soil moisture is a key variable in our Earth system. Knowledge of soil moisture and its dynamics across scales is vital for many applications such as the prediction of agricultural yields or irrigation demands, flood and drought monitoring, weather forecasting and climate modelling. To date, the ESA CCI SM products are the only consistent long-term multi-satellite soil moisture data sets available. This paper reviews the evolution of these products and their underlying merging methodology.
Claire Delon, Corinne Galy-Lacaux, Dominique Serça, Erwan Personne, Eric Mougin, Marcellin Adon, Valérie Le Dantec, Benjamin Loubet, Rasmus Fensholt, and Torbern Tagesson
Biogeosciences, 16, 2049–2077, https://doi.org/10.5194/bg-16-2049-2019, https://doi.org/10.5194/bg-16-2049-2019, 2019
Short summary
Short summary
In the Sahel region during the wet season, CO2 and NO are released to the atmosphere, and NH3 is deposited on the soil. During the dry season, processes are strongly reduced. This paper shows the temporal variation in these soil–atmosphere exchanges of trace gases for 2 years, their sharp increase when the first rains fall onto dry soils, and how microbial processes are involved. We use a modelling approach, which is necessary when continuous measurements are not possible in remote regions.
Sibo Zhang, Catherine Meurey, and Jean-Christophe Calvet
Atmos. Chem. Phys., 19, 5005–5020, https://doi.org/10.5194/acp-19-5005-2019, https://doi.org/10.5194/acp-19-5005-2019, 2019
Short summary
Short summary
In situ rain temperature measurements are rare. Soil moisture and soil temperature observations in southern France are used to assess the cooling effects on soils of rainfall events. The rainwater temperature is estimated using observed changes of topsoil volumetric soil moisture and soil temperature in response to the rainfall event. The obtained rain temperature estimates are generally lower than the ambient air temperatures, wet-bulb temperatures, and topsoil temperatures.
Jeffrey C. Davids, Martine M. Rutten, Anusha Pandey, Nischal Devkota, Wessel David van Oyen, Rajaram Prajapati, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 23, 1045–1065, https://doi.org/10.5194/hess-23-1045-2019, https://doi.org/10.5194/hess-23-1045-2019, 2019
Short summary
Short summary
Wise management of water resources requires data. Nevertheless, the amount of water data being collected continues to decline. We evaluated potential citizen science approaches for measuring flows of headwater streams and springs. After selecting salt dilution as the preferred approach, we partnered with Nepali students to cost-effectively measure flows and water quality with smartphones at 264 springs and streams which provide crucial water supplies to the rapidly expanding Kathmandu Valley.
Felix Zaussinger, Wouter Dorigo, Alexander Gruber, Angelica Tarpanelli, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019, https://doi.org/10.5194/hess-23-897-2019, 2019
Short summary
Short summary
About 70 % of global freshwater is consumed by irrigation. Yet, policy-relevant estimates of irrigation water use (IWU) are virtually lacking at regional to global scales. To bridge this gap, we develop a method for quantifying IWU from a combination of state-of-the-art remotely sensed and modeled soil moisture products and apply it over the United States for the period 2013–2016. Overall, our estimates agree well with reference data on irrigated area and irrigation water withdrawals.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
Short summary
Short summary
This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Yonghong Yi, John S. Kimball, Richard H. Chen, Mahta Moghaddam, and Charles E. Miller
The Cryosphere, 13, 197–218, https://doi.org/10.5194/tc-13-197-2019, https://doi.org/10.5194/tc-13-197-2019, 2019
Short summary
Short summary
To better understand active-layer freezing process and its climate sensitivity, we developed a new 1 km snow data set for permafrost modeling and used the model simulations with multiple new in situ and P-band radar data sets to characterize the soil freeze onset and duration of zero curtain in Arctic Alaska. Results show that zero curtains of upper soils are primarily affected by early snow cover accumulation, while zero curtains of deeper soils are more closely related to maximum thaw depth.
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
Short summary
Short summary
Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Diana Lucatero, Henrik Madsen, Jens C. Refsgaard, Jacob Kidmose, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 22, 6591–6609, https://doi.org/10.5194/hess-22-6591-2018, https://doi.org/10.5194/hess-22-6591-2018, 2018
Short summary
Short summary
The present study evaluates the skill of a seasonal forecasting system for hydrological relevant variables in Denmark. Linear scaling and quantile mapping were used to correct the forecasts. Uncorrected forecasts tend to be more skillful than climatology, in general, for the first month lead time only. Corrected forecasts show a reduced bias in the mean; are more consistent; and show a level of accuracy that is closer to, although no higher than, that of ensemble climatology, in general.
Miriam Pablos, Ángel González-Zamora, Nilda Sánchez, and José Martínez-Fernández
Proc. IAHS, 380, 55–66, https://doi.org/10.5194/piahs-380-55-2018, https://doi.org/10.5194/piahs-380-55-2018, 2018
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Proc. IAHS, 380, 3–8, https://doi.org/10.5194/piahs-380-3-2018, https://doi.org/10.5194/piahs-380-3-2018, 2018
Christian Reszler, Jürgen Komma, Hermann Stadler, Elmar Strobl, and Günter Blöschl
Hydrol. Earth Syst. Sci., 22, 6147–6161, https://doi.org/10.5194/hess-22-6147-2018, https://doi.org/10.5194/hess-22-6147-2018, 2018
Short summary
Short summary
Karst aquifers are vulnerable to pollution due to the typically short particle travel times. As the rainwater runs off on the surface it may collect contamination before infiltrating. This paper proposes a new field-mapping method for the ability of the landscape to produce and convey surface runoff. The method is based on local data collection in the field, and a visual assessment of surface runoff traces from a distance, which makes it suitable for larger areas than traditional field mapping.
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Hydrol. Earth Syst. Sci., 22, 5735–5739, https://doi.org/10.5194/hess-22-5735-2018, https://doi.org/10.5194/hess-22-5735-2018, 2018
Tim van Emmerik, Susan Steele-Dunne, Pierre Gentine, Rafael S. Oliveira, Paulo Bittencourt, Fernanda Barros, and Nick van de Giesen
Biogeosciences, 15, 6439–6449, https://doi.org/10.5194/bg-15-6439-2018, https://doi.org/10.5194/bg-15-6439-2018, 2018
Short summary
Short summary
Trees are very important for the water and carbon cycles. Climate and weather models often assume constant vegetation parameters because good measurements are missing. We used affordable accelerometers to measure tree sway of 19 trees in the Amazon rainforest. We show that trees respond very differently to the same weather conditions, which means that vegetation parameters are dynamic. With our measurements trees can be accounted for more realistically, improving climate and weather models.
Yueqiang Sun, Weihua Bai, Congliang Liu, Yan Liu, Qifei Du, Xianyi Wang, Guanglin Yang, Mi Liao, Zhongdong Yang, Xiaoxin Zhang, Xiangguang Meng, Danyang Zhao, Junming Xia, Yuerong Cai, and Gottfried Kirchengast
Atmos. Meas. Tech., 11, 5797–5811, https://doi.org/10.5194/amt-11-5797-2018, https://doi.org/10.5194/amt-11-5797-2018, 2018
Short summary
Short summary
The GNSS Occultation Sounder (GNOS) is one of the new-generation payloads on board the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth’s neutral atmosphere and ionosphere. FY-3C GNOS, on board the FY-3 series C satellite launched in September 2013, was designed to acquire setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BDS and the US GPS. This paper reviews the FY-3C GNOS mission.
Christoph Schlager, Gottfried Kirchengast, and Juergen Fuchsberger
Atmos. Meas. Tech., 11, 5607–5627, https://doi.org/10.5194/amt-11-5607-2018, https://doi.org/10.5194/amt-11-5607-2018, 2018
Short summary
Short summary
In this work we further developed and evaluated an operational weather diagnostic application, the WegenerNet Wind Product Generator (WPG), and applied it to the WegenerNet Johnsbachtal (JBT), a dense meteorological station network located in a mountainous Alpine region. The WPG automatically generates gridded high-resolution wind fields in near-real time with a temporal resolution of 30 min and a spatial resolution of 100 m x 100 m.
Doris Duethmann and Günter Blöschl
Hydrol. Earth Syst. Sci., 22, 5143–5158, https://doi.org/10.5194/hess-22-5143-2018, https://doi.org/10.5194/hess-22-5143-2018, 2018
Short summary
Short summary
We analyze changes in catchment evaporation estimated from the water balances of 156 catchments in Austria over 1977–2014, as well as the possible causes of these changes. Our results show that catchment evaporation increased on average by 29 ± 14 mm yr−1 decade−1. We attribute this increase to changes in atmospheric demand (based on reference and pan evaporation), changes in vegetation (quantified by a satellite-based vegetation index), and changes in precipitation.
Ben Kravitz, Philip J. Rasch, Hailong Wang, Alan Robock, Corey Gabriel, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Duoying Ji, Andy Jones, Andrew Lenton, John C. Moore, Helene Muri, Ulrike Niemeier, Steven Phipps, Hauke Schmidt, Shingo Watanabe, Shuting Yang, and Jin-Ho Yoon
Atmos. Chem. Phys., 18, 13097–13113, https://doi.org/10.5194/acp-18-13097-2018, https://doi.org/10.5194/acp-18-13097-2018, 2018
Short summary
Short summary
Marine cloud brightening has been proposed as a means of geoengineering/climate intervention, or deliberately altering the climate system to offset anthropogenic climate change. In idealized simulations that highlight contrasts between land and ocean, we find that the globe warms, including the ocean due to transport of heat from land. This study reinforces that no net energy input into the Earth system does not mean that temperature will necessarily remain unchanged.
Alessio Pugliese, Simone Persiano, Stefano Bagli, Paolo Mazzoli, Juraj Parajka, Berit Arheimer, René Capell, Alberto Montanari, Günter Blöschl, and Attilio Castellarin
Hydrol. Earth Syst. Sci., 22, 4633–4648, https://doi.org/10.5194/hess-22-4633-2018, https://doi.org/10.5194/hess-22-4633-2018, 2018
Short summary
Short summary
This research work focuses on the development of an innovative method for enhancing the predictive capability of macro-scale rainfall–runoff models by means of a geostatistical apporach. In our method, one can get enhanced streamflow simulations without any further model calibration. Indeed, this method is neither computational nor data-intensive and is implemented only using observed streamflow data and a GIS vector layer with catchment boundaries. Assessments are performed in the Tyrol region.
Simon Zwieback, Andreas Colliander, Michael H. Cosh, José Martínez-Fernández, Heather McNairn, Patrick J. Starks, Marc Thibeault, and Aaron Berg
Hydrol. Earth Syst. Sci., 22, 4473–4489, https://doi.org/10.5194/hess-22-4473-2018, https://doi.org/10.5194/hess-22-4473-2018, 2018
Short summary
Short summary
Satellite soil moisture products can provide critical information on incipient droughts and the interplay between vegetation and water availability. However, time-variant systematic errors in the soil moisture products may impede their usefulness. Using a novel statistical approach, we detect such errors (associated with changing vegetation) in the SMAP soil moisture product. The vegetation-associated biases impede drought detection and the quantification of vegetation–water interactions.
Daniel D. Richter, Sharon A. Billings, Peter M. Groffman, Eugene F. Kelly, Kathleen A. Lohse, William H. McDowell, Timothy S. White, Suzanne Anderson, Dennis D. Baldocchi, Steve Banwart, Susan Brantley, Jean J. Braun, Zachary S. Brecheisen, Charles W. Cook, Hilairy E. Hartnett, Sarah E. Hobbie, Jerome Gaillardet, Esteban Jobbagy, Hermann F. Jungkunst, Clare E. Kazanski, Jagdish Krishnaswamy, Daniel Markewitz, Katherine O'Neill, Clifford S. Riebe, Paul Schroeder, Christina Siebe, Whendee L. Silver, Aaron Thompson, Anne Verhoef, and Ganlin Zhang
Biogeosciences, 15, 4815–4832, https://doi.org/10.5194/bg-15-4815-2018, https://doi.org/10.5194/bg-15-4815-2018, 2018
Short summary
Short summary
As knowledge in biology and geology explodes, science becomes increasingly specialized. Given the overlap of the environmental sciences, however, the explosion in knowledge inevitably creates opportunities for interconnecting the biogeosciences. Here, 30 scientists emphasize the opportunities for biogeoscience collaborations across the world’s remarkable long-term environmental research networks that can advance science and engage larger scientific and public audiences.
Nemesio J. Rodríguez-Fernández, Arnaud Mialon, Stephane Mermoz, Alexandre Bouvet, Philippe Richaume, Ahmad Al Bitar, Amen Al-Yaari, Martin Brandt, Thomas Kaminski, Thuy Le Toan, Yann H. Kerr, and Jean-Pierre Wigneron
Biogeosciences, 15, 4627–4645, https://doi.org/10.5194/bg-15-4627-2018, https://doi.org/10.5194/bg-15-4627-2018, 2018
Short summary
Short summary
Existing global scale above-ground biomass (AGB) maps are made at very high spatial resolution collecting data during several years. In this paper we discuss the use of a new data set from the SMOS satellite: the vegetation optical depth estimated from low microwave frequencies. It is shown that this new data set is highly sensitive to AGB. The spacial resolution of SMOS is coarse (40 km) but the new data set can be used to monitor AGB variations with time due to its high revisit frequency.
Julia Hall and Günter Blöschl
Hydrol. Earth Syst. Sci., 22, 3883–3901, https://doi.org/10.5194/hess-22-3883-2018, https://doi.org/10.5194/hess-22-3883-2018, 2018
Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Béatrice Béchet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G. Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido-Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan-Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken
Earth Syst. Sci. Data, 10, 1237–1263, https://doi.org/10.5194/essd-10-1237-2018, https://doi.org/10.5194/essd-10-1237-2018, 2018
Short summary
Short summary
This paper presents and analyzes a global database of soil infiltration data, the SWIG database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists or they were digitized from published articles. We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models.
Diana Lucatero, Henrik Madsen, Jens C. Refsgaard, Jacob Kidmose, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 22, 3601–3617, https://doi.org/10.5194/hess-22-3601-2018, https://doi.org/10.5194/hess-22-3601-2018, 2018
Short summary
Short summary
The skill of an experimental streamflow forecast system in the Ahlergaarde catchment, Denmark, is analyzed. Inputs to generate the forecasts are taken from the ECMWF System 4 seasonal forecasting system and an ensemble of observations (ESP). Reduction of biases is achieved by processing the meteorological and/or streamflow forecasts. In general, this is not sufficient to ensure a higher level of accuracy than the ESP, indicating a modest added value of a seasonal meteorological system.
Clement Albergel, Emanuel Dutra, Simon Munier, Jean-Christophe Calvet, Joaquin Munoz-Sabater, Patricia de Rosnay, and Gianpaolo Balsamo
Hydrol. Earth Syst. Sci., 22, 3515–3532, https://doi.org/10.5194/hess-22-3515-2018, https://doi.org/10.5194/hess-22-3515-2018, 2018
Short summary
Short summary
ECMWF recently released the first 7-year segment of its latest atmospheric reanalysis: ERA-5 (2010–2016). ERA-5 has important changes relative to ERA-Interim including higher spatial and temporal resolutions as well as a more recent model and data assimilation system. ERA-5 is foreseen to replace ERA-Interim reanalysis. One of the main goals of this study is to assess whether ERA-5 can enhance the simulation performances with respect to ERA-Interim when it is used to force a land surface model.
Hong Zhao, Yijian Zeng, Shaoning Lv, and Zhongbo Su
Earth Syst. Sci. Data, 10, 1031–1061, https://doi.org/10.5194/essd-10-1031-2018, https://doi.org/10.5194/essd-10-1031-2018, 2018
Short summary
Short summary
The Tibet-Obs soil properties dataset was compiled based on in situ and laboratory measurements of soil profiles across three climate zones on the Tibetan Plateau. The appropriate parameterization schemes of soil hydraulic and thermal properties were discussed for their applicability in land surface modeling. The uncertainties of existing soil datasets were evaluated. This paper contributes to land surface modeling and hydro-climatology communities for their studies of the third pole region.
Marlies Holkje Barendrecht, Alberto Viglione, Heidi Kreibich, Sergiy Vorogushyn, Bruno Merz, and Günter Blöschl
Proc. IAHS, 379, 193–198, https://doi.org/10.5194/piahs-379-193-2018, https://doi.org/10.5194/piahs-379-193-2018, 2018
Short summary
Short summary
The aim of this paper is to assess whether a Socio-Hydrological model can be calibrated to data artificially generated from it. This is not trivial because the model is highly nonlinear and it is not clear what amount of data would be needed for calibration. We demonstrate that, using Bayesian inference, the parameters of the model can be estimated quite accurately from relatively few data, which could be available in real case studies.
Congliang Liu, Gottfried Kirchengast, Yueqiang Sun, Kefei Zhang, Robert Norman, Marc Schwaerz, Weihua Bai, Qifei Du, and Ying Li
Atmos. Meas. Tech., 11, 2427–2440, https://doi.org/10.5194/amt-11-2427-2018, https://doi.org/10.5194/amt-11-2427-2018, 2018
Short summary
Short summary
In this study, we focused on investigating the causes of the higher-order residual ionospheric error (RIE) in the GNSS RO events, by employing detailed along-ray-path analyses of atmospheric and ionospheric refractivities, impact parameter changes, and bending angles and RIEs under asymmetric and symmetric ionospheric structures. We found that the main causes of the high RIEs are a combination of physics-based effects, where asymmetric ionospheric conditions play the primary role.
Elena Cristiano, Marie-Claire ten Veldhuis, Santiago Gaitan, Susana Ochoa Rodriguez, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 22, 2425–2447, https://doi.org/10.5194/hess-22-2425-2018, https://doi.org/10.5194/hess-22-2425-2018, 2018
Short summary
Short summary
In this work we investigate the influence rainfall and catchment scales have on hydrological response. This problem is quite relevant in urban areas, where the response is fast due to the high degree of imperviousness. We presented a new approach to classify rainfall variability in space and time and use this classification to investigate rainfall aggregation effects on urban hydrological response. This classification allows the spatial extension of the main core of the storm to be identified.
Emiliano Gelati, Bertrand Decharme, Jean-Christophe Calvet, Marie Minvielle, Jan Polcher, David Fairbairn, and Graham P. Weedon
Hydrol. Earth Syst. Sci., 22, 2091–2115, https://doi.org/10.5194/hess-22-2091-2018, https://doi.org/10.5194/hess-22-2091-2018, 2018
Short summary
Short summary
We compared land surface model simulations forced by several meteorological datasets with observations over the Euro-Mediterranean area, for the 1979–2012 period. Precipitation was the most uncertain forcing variable. The impacts of forcing uncertainty were larger on the mean and standard deviation rather than the timing, shape and inter-annual variability of simulated discharge. Simulated leaf area index and surface soil moisture were relatively insensitive to these uncertainties.
Sibo Zhang, Jean-Christophe Calvet, José Darrozes, Nicolas Roussel, Frédéric Frappart, and Gilles Bouhours
Hydrol. Earth Syst. Sci., 22, 1931–1946, https://doi.org/10.5194/hess-22-1931-2018, https://doi.org/10.5194/hess-22-1931-2018, 2018
Short summary
Short summary
Surface soil moisture was retrieved from a grassland site in southwestern France using the GNSS-IR technique. In order to efficiently limit the impact of perturbing vegetation effects, the grass growth period and the senescence period are treated separately. While the vegetation biomass effect can be corrected for, the litter water interception influences the observations and cannot be easily accounted for.
Jannis von Buttlar, Jakob Zscheischler, Anja Rammig, Sebastian Sippel, Markus Reichstein, Alexander Knohl, Martin Jung, Olaf Menzer, M. Altaf Arain, Nina Buchmann, Alessandro Cescatti, Damiano Gianelle, Gerard Kiely, Beverly E. Law, Vincenzo Magliulo, Hank Margolis, Harry McCaughey, Lutz Merbold, Mirco Migliavacca, Leonardo Montagnani, Walter Oechel, Marian Pavelka, Matthias Peichl, Serge Rambal, Antonio Raschi, Russell L. Scott, Francesco P. Vaccari, Eva van Gorsel, Andrej Varlagin, Georg Wohlfahrt, and Miguel D. Mahecha
Biogeosciences, 15, 1293–1318, https://doi.org/10.5194/bg-15-1293-2018, https://doi.org/10.5194/bg-15-1293-2018, 2018
Short summary
Short summary
Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity (GPP) and ecosystem respiration globally across a wide range of ecosystems. We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Lauren Marshall, Anja Schmidt, Matthew Toohey, Ken S. Carslaw, Graham W. Mann, Michael Sigl, Myriam Khodri, Claudia Timmreck, Davide Zanchettin, William T. Ball, Slimane Bekki, James S. A. Brooke, Sandip Dhomse, Colin Johnson, Jean-Francois Lamarque, Allegra N. LeGrande, Michael J. Mills, Ulrike Niemeier, James O. Pope, Virginie Poulain, Alan Robock, Eugene Rozanov, Andrea Stenke, Timofei Sukhodolov, Simone Tilmes, Kostas Tsigaridis, and Fiona Tummon
Atmos. Chem. Phys., 18, 2307–2328, https://doi.org/10.5194/acp-18-2307-2018, https://doi.org/10.5194/acp-18-2307-2018, 2018
Short summary
Short summary
We use four global aerosol models to compare the simulated sulfate deposition from the 1815 Mt. Tambora eruption to ice core records. Inter-model volcanic sulfate deposition differs considerably. Volcanic sulfate deposited on polar ice sheets is used to estimate the atmospheric sulfate burden and subsequently radiative forcing of historic eruptions. Our results suggest that deriving such relationships from model simulations may be associated with greater uncertainties than previously thought.
Weihua Bai, Congliang Liu, Xiangguang Meng, Yueqiang Sun, Gottfried Kirchengast, Qifei Du, Xianyi Wang, Guanglin Yang, Mi Liao, Zhongdong Yang, Danyang Zhao, Junming Xia, Yuerong Cai, Lijun Liu, and Dongwei Wang
Atmos. Meas. Tech., 11, 819–833, https://doi.org/10.5194/amt-11-819-2018, https://doi.org/10.5194/amt-11-819-2018, 2018
Short summary
Short summary
In this study we focus on evaluating zero-difference processing of BDS RO data vs. single-difference processing. From the statistics, average bias (and standard deviation) of the bending angle and refractivity profiles were found to be as small as about 0.05–0.2 % (and 0.7–1.6 %) over the upper troposphere and lower stratosphere, including for the GEO, IGSO, and MEO subsets. Zero differencing was found to perform slightly better, as may be expected from its lower vulnerability to noise.
Luca Ciabatta, Christian Massari, Luca Brocca, Alexander Gruber, Christoph Reimer, Sebastian Hahn, Christoph Paulik, Wouter Dorigo, Richard Kidd, and Wolfgang Wagner
Earth Syst. Sci. Data, 10, 267–280, https://doi.org/10.5194/essd-10-267-2018, https://doi.org/10.5194/essd-10-267-2018, 2018
Short summary
Short summary
In this study, rainfall is estimated starting from satellite soil moisture observation on a global scale, using the ESA CCI soil moisture datasets. The new obtained rainfall product has proven to correctly identify rainfall events, showing performance sometimes higher than those obtained by using classical rainfall estimation approaches.
Lin Liu and Kristine M. Larson
The Cryosphere, 12, 477–489, https://doi.org/10.5194/tc-12-477-2018, https://doi.org/10.5194/tc-12-477-2018, 2018
Short summary
Short summary
We demonstrate the use of reflected GPS signals to measure elevation changes over a permafrost area in northern Alaska. For the first time, we construct a daily-sampled time series of elevation changes over 12 summers. Our results show regular thaw subsidence within each summer and a secular subsidence trend of 0.3 cm per year. This method promises a new way to utilize GPS data in cold regions for studying frozen ground consistently and sustainably over a long time.
Koen Hilgersom, Marcel Zijlema, and Nick van de Giesen
Geosci. Model Dev., 11, 521–540, https://doi.org/10.5194/gmd-11-521-2018, https://doi.org/10.5194/gmd-11-521-2018, 2018
Short summary
Short summary
This study models the local inflow of groundwater at the bottom of a stream with large density gradients between the groundwater and surface water. Modelling salt and heat transport in a water body is very challenging, as it requires large computation times. Due to the circular local groundwater inflow and a negligible stream discharge, we assume axisymmetry around the inflow, which is easily implemented in an existing model, largely reduces the computation times, and still performs accurately.
Hubertus M. Coerver, Martine M. Rutten, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 22, 831–851, https://doi.org/10.5194/hess-22-831-2018, https://doi.org/10.5194/hess-22-831-2018, 2018
Short summary
Short summary
Global hydrological models aim to model hydrological processes, like flows in a river, on a global scale, as opposed to traditional models which are regional. A big challenge in creating these models is the inclusion of impacts on the hydrological cycle caused by humans, for example by the operation of large (hydropower) dams. The presented study investigates a new way to include these impacts by dams into global hydrological models.
Yonghong Yi, John S. Kimball, Richard H. Chen, Mahta Moghaddam, Rolf H. Reichle, Umakant Mishra, Donatella Zona, and Walter C. Oechel
The Cryosphere, 12, 145–161, https://doi.org/10.5194/tc-12-145-2018, https://doi.org/10.5194/tc-12-145-2018, 2018
Short summary
Short summary
An important feature of the Arctic is large spatial heterogeneity in active layer conditions. We developed a modeling framework integrating airborne longwave radar and satellite data to investigate active layer thickness (ALT) sensitivity to landscape heterogeneity in Alaska. We find uncertainty in spatial and vertical distribution of soil organic carbon is the largest factor affecting ALT accuracy. Advances in remote sensing of soil conditions will enable more accurate ALT predictions.
Michael E. Gorbunov and Gottfried Kirchengast
Atmos. Meas. Tech., 11, 111–125, https://doi.org/10.5194/amt-11-111-2018, https://doi.org/10.5194/amt-11-111-2018, 2018
Short summary
Short summary
We study the systematic discreapancies between atmospheric refractivity derived from radio occulation (RO) sounding of the Earth's atmosphere and the reanalyses of the European Centre for Medium-Range Weather Forecasts. We construct a regression-based bias model. The model can be used for the RO data propagation in the new reference occultation processing system (rOPS) including the uncertainty propagation through the retrieval chain.
Sungmin O, Ulrich Foelsche, Gottfried Kirchengast, Juergen Fuchsberger, Jackson Tan, and Walter A. Petersen
Hydrol. Earth Syst. Sci., 21, 6559–6572, https://doi.org/10.5194/hess-21-6559-2017, https://doi.org/10.5194/hess-21-6559-2017, 2017
Short summary
Short summary
We evaluate gridded satellite rainfall estimates, from GPM IMERG, through a direct grid-to-grid comparison with gauge data from the WegenerNet Feldbach (WEGN) network in southeastern Austria. As the WEGN data are independent of the IMERG gauge adjustment process, we could analyze the IMERG estimates across its three different runs. Our results show the effects of additional retrieval processes on the final rainfall estimates, and consequently provide IMERG accuracy information for data users.
Florian Sallaba, Stefan Olin, Kerstin Engström, Abdulhakim M. Abdi, Niklas Boke-Olén, Veiko Lehsten, Jonas Ardö, and Jonathan W. Seaquist
Earth Syst. Dynam., 8, 1191–1221, https://doi.org/10.5194/esd-8-1191-2017, https://doi.org/10.5194/esd-8-1191-2017, 2017
Short summary
Short summary
The UN sustainable development goals for eradicating hunger are at high risk for failure in the Sahel. We show that the demand for food and feed biomass will begin to outstrip its supply in the 2040s if current trends continue. Though supply continues to increase it is outpaced by a greater increase in demand due to a combination of population growth and a shift to diets rich in animal proteins. This underscores the importance of policy interventions that would act to mitigate such developments.
Barbara Angerer, Florian Ladstädter, Barbara Scherllin-Pirscher, Marc Schwärz, Andrea K. Steiner, Ulrich Foelsche, and Gottfried Kirchengast
Atmos. Meas. Tech., 10, 4845–4863, https://doi.org/10.5194/amt-10-4845-2017, https://doi.org/10.5194/amt-10-4845-2017, 2017
Short summary
Short summary
We present a detailed analysis of the latest Wegener Center GPS radio occultation reprocessing (OPSv5.6) output. Knowledge of differences in data quality, as well as of data consistency, is essential when combining data from different missions to a long-term climate record. We compare quality aspects of the various processed satellite missions and present satellite-dependent variations. Temperature data from various satellites are found to be highly consistent within 8 to 25 km.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
Short summary
Short summary
This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Matthias Forkel, Wouter Dorigo, Gitta Lasslop, Irene Teubner, Emilio Chuvieco, and Kirsten Thonicke
Geosci. Model Dev., 10, 4443–4476, https://doi.org/10.5194/gmd-10-4443-2017, https://doi.org/10.5194/gmd-10-4443-2017, 2017
Short summary
Short summary
Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
David E. Shean, Knut Christianson, Kristine M. Larson, Stefan R. M. Ligtenberg, Ian R. Joughin, Ben E. Smith, C. Max Stevens, Mitchell Bushuk, and David M. Holland
The Cryosphere, 11, 2655–2674, https://doi.org/10.5194/tc-11-2655-2017, https://doi.org/10.5194/tc-11-2655-2017, 2017
Short summary
Short summary
We used long-term GPS data and interferometric reflectometry (GPS-IR) to measure velocity, strain rate and surface elevation for the PIG ice shelf – a site of significant mass loss in recent decades. We combined these observations with high-res DEMs and firn model output to constrain surface mass balance and basal melt rates. We document notable spatial variability in basal melt rates but limited temporal variability from 2012 to 2014 despite significant changes in sub-shelf ocean heat content.
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
Short summary
Short summary
LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
Lili Xia, Peer J. Nowack, Simone Tilmes, and Alan Robock
Atmos. Chem. Phys., 17, 11913–11928, https://doi.org/10.5194/acp-17-11913-2017, https://doi.org/10.5194/acp-17-11913-2017, 2017
Short summary
Short summary
Ozone is a key air pollutant. We model two geoengineering schemes, stratospheric sulfur injection and solar irradiance reduction, to compare their impacts on atmospheric ozone concentrations. With the nearly identical global mean surface temperature reduction, solar dimming increases global average surface ozone concentration, while sulfate injection decreases it. This difference is due to different stratosphere–troposphere exchange of ozone and tropospheric ozone chemistry in the two scenarios.
Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, https://doi.org/10.5194/hess-21-5009-2017, 2017
Short summary
Short summary
A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.
Hélène Dewaele, Simon Munier, Clément Albergel, Carole Planque, Nabil Laanaia, Dominique Carrer, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4861–4878, https://doi.org/10.5194/hess-21-4861-2017, https://doi.org/10.5194/hess-21-4861-2017, 2017
Short summary
Short summary
Soil maximum available water content (MaxAWC) is a key parameter in land surface models. Being difficult to measure, this parameter is usually unavailable. A 15-year time series of satellite-derived observations of leaf area index (LAI) is used to retrieve MaxAWC for rainfed straw cereals over France. Disaggregated LAI is sequentially assimilated into the ISBA LSM. MaxAWC is estimated minimising LAI analyses increments. Annual maximum LAI observations correlate with the MaxAWC estimates.
Sibo Zhang, Nicolas Roussel, Karen Boniface, Minh Cuong Ha, Frédéric Frappart, José Darrozes, Frédéric Baup, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4767–4784, https://doi.org/10.5194/hess-21-4767-2017, https://doi.org/10.5194/hess-21-4767-2017, 2017
Short summary
Short summary
GNSS SNR data were obtained from an intensively cultivated wheat field in southwestern France. The data were used to retrieve soil moisture and vegetation characteristics during the growing period of wheat. Vegetation growth broke up the constant height assumption used in soil moisture retrieval algorithms. Soil moisture could not be retrieved after wheat tillering. A new algorithm based on a wavelet analysis was implemented and used to retrieve vegetation height.
Christian Massari, Wade Crow, and Luca Brocca
Hydrol. Earth Syst. Sci., 21, 4347–4361, https://doi.org/10.5194/hess-21-4347-2017, https://doi.org/10.5194/hess-21-4347-2017, 2017
Short summary
Short summary
The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Natalie C. Ceperley, Theophile Mande, Nick van de Giesen, Scott Tyler, Hamma Yacouba, and Marc B. Parlange
Hydrol. Earth Syst. Sci., 21, 4149–4167, https://doi.org/10.5194/hess-21-4149-2017, https://doi.org/10.5194/hess-21-4149-2017, 2017
Short summary
Short summary
We relate land cover (savanna forest and agriculture) to evaporation in Burkina Faso, west Africa. We observe more evaporation and temperature movement over the savanna forest in the headwater area relative to the agricultural section of the watershed. We find that the fraction of available energy converted to evaporation relates to vegetation cover and soil moisture. From the results, evaporation can be calculated where ground-based measurements are lacking, frequently the case across Africa.
Elena Cristiano, Marie-Claire ten Veldhuis, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 21, 3859–3878, https://doi.org/10.5194/hess-21-3859-2017, https://doi.org/10.5194/hess-21-3859-2017, 2017
Short summary
Short summary
In the last decades, new instruments were developed to measure rainfall and hydrological processes at high resolution. Weather radars are used, for example, to measure how rainfall varies in space and time. At the same time, new models were proposed to reproduce and predict hydrological response, in order to prevent flooding in urban areas. This paper presents a review of our current knowledge of rainfall and hydrological processes in urban areas, focusing on their variability in time and space.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
Short summary
Short summary
We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
Short summary
Short summary
Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
Short summary
Short summary
This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
Xiaodong Gao, Xining Zhao, Luca Brocca, Gaopeng Huo, Ting Lv, and Pute Wu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-292, https://doi.org/10.5194/hess-2017-292, 2017
Preprint retracted
Short summary
Short summary
Profile soil moisture is key state variable in the Critical Zone ecology and hydrology. This paper sucessfully used a simple statistical method, the cumulative distribution frequency (CDF) matching method for the first time, to predict profile soil moisture (0–100 cm) from surface measurement (5 cm). The findings here can provide insights into profile soil moisture estimation from remote sensing moisture products.
Waqas Ahmad, Minha Choi, Soohyun Kim, and Dongkyun Kim
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-234, https://doi.org/10.5194/nhess-2017-234, 2017
Revised manuscript not accepted
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
Short summary
Short summary
The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Wuletawu Abera, Giuseppe Formetta, Luca Brocca, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 21, 3145–3165, https://doi.org/10.5194/hess-21-3145-2017, https://doi.org/10.5194/hess-21-3145-2017, 2017
Short summary
Short summary
This study documents a state-of-the-art estimation of the water budget (rainfall, evapotranspiration, discharge, and soil and groundwater storage) components for the Upper Blue Nile river. The budget uses various JGrass-NewAGE components, satellite data and all ground measurements available. The analysis shows that precipitation of the basin is 1360 ± 230 mm per year. Evapotranspiration accounts for 56 %, runoff is 33 %, and storage varies from minus 10 % to plus 17 % of the annual water budget.
Sebastian F. Zastruzny, Bo Elberling, Lars Nielsen, and Karsten H. Jensen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-97, https://doi.org/10.5194/tc-2017-97, 2017
Revised manuscript has not been submitted
Short summary
Short summary
The hydrological regime in the arctic will change as the climate conditions change and the release and associated transport of nutrients will also be affected. In this study we analyze water flow and tracer transport along a sloping transect in Disko Island in Greenland. The results suggest that the movement of dissolved nitrogen compounds such as nitrate, being released along the slope in consequence of permafrost thawing, can quickly influence nitrogen cycling at the end of the slope.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
Short summary
Short summary
Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman
Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, https://doi.org/10.5194/gmd-10-1945-2017, 2017
Short summary
Short summary
Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.
Roland Baatz, Harrie-Jan Hendricks Franssen, Xujun Han, Tim Hoar, Heye Reemt Bogena, and Harry Vereecken
Hydrol. Earth Syst. Sci., 21, 2509–2530, https://doi.org/10.5194/hess-21-2509-2017, https://doi.org/10.5194/hess-21-2509-2017, 2017
Short summary
Short summary
Soil moisture is a major variable that affects regional climate, weather and hydrologic processes on the Earth's surface. In this study, real-world data of a network of cosmic-ray sensors were assimilated into a regional land surface model to improve model states and soil hydraulic parameters. The results show the potential of these networks for improving model states and parameters. It is suggested to widen the number of observed variables and to increase the number of estimated parameters.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, https://doi.org/10.5194/hess-21-2015-2017, 2017
Short summary
Short summary
This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Mie Andreasen, Karsten H. Jensen, Darin Desilets, Marek Zreda, Heye R. Bogena, and Majken C. Looms
Hydrol. Earth Syst. Sci., 21, 1875–1894, https://doi.org/10.5194/hess-21-1875-2017, https://doi.org/10.5194/hess-21-1875-2017, 2017
Short summary
Short summary
The cosmic-ray method holds a potential for quantifying canopy interception and biomass. We use measurements and modeling of thermal and epithermal neutron intensity in a forest to examine this potential. Canopy interception is a variable important to forest hydrology, yet difficult to monitor remotely. Forest growth impacts the carbon-cycle and can be used to mitigate climate changes by carbon sequestration in biomass. An efficient method to monitor tree growth is therefore of high relevance.
Torbern Tagesson, Jonas Ardö, Bernard Cappelaere, Laurent Kergoat, Abdulhakim Abdi, Stéphanie Horion, and Rasmus Fensholt
Biogeosciences, 14, 1333–1348, https://doi.org/10.5194/bg-14-1333-2017, https://doi.org/10.5194/bg-14-1333-2017, 2017
Short summary
Short summary
Vegetation growth in semi-arid regions is an important sink for human-induced fossil fuel emissions of CO2 and this study addresses the strong need for improved understanding and spatially explicit estimates of CO2 uptake by semi-arid ecosystems. We show that a model incorporating photosynthetic parameters upscaled using satellite-based earth observation simulates CO2 uptake well for the Sahel, one of the largest semi-arid regions in the world.
Fakhereh Alidoost, Alfred Stein, Zhongbo Su, and Ali Sharifi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-93, https://doi.org/10.5194/hess-2017-93, 2017
Manuscript not accepted for further review
Short summary
Short summary
Weather stations are often sparse and systematic under/overestimation of a global weather forecast system leads to bias. Most of the available bias correction methods do not consider higher order moments of a probability distribution and they use same distributions families to estimate both marginal and multivariate distributions. We propose three new copula-based bias correction methods, which describe the dependence structure between air temperature and covariates.
Xingguo Mo, Xuejuan Chen, Shi Hu, Suxia Liu, and Jun Xia
Hydrol. Earth Syst. Sci., 21, 295–310, https://doi.org/10.5194/hess-21-295-2017, https://doi.org/10.5194/hess-21-295-2017, 2017
Short summary
Short summary
Attributing changes in ET and GPP is crucial to impact and adaptation assessment of climate change over the NCP. Simulations with the VIP ecohydrological model illustrated relative contributions of climatic change, CO2 fertilization, and management to ET and GPP. Global radiation was the cause of GPP decline in summer, while air warming intensified the water cycle and advanced plant productivity in spring. Agronomical improvement was the main driver of crop productivity enhancement.
Corey J. Gabriel, Alan Robock, Lili Xia, Brian Zambri, and Ben Kravitz
Atmos. Chem. Phys., 17, 595–613, https://doi.org/10.5194/acp-17-595-2017, https://doi.org/10.5194/acp-17-595-2017, 2017
Short summary
Short summary
The National Center for Atmospheric Research CESM-CAM4-CHEM global climate model was modified to simulate a scheme in which the albedo of the ocean surface is raised over the subtropical ocean gyres in the Southern Hemisphere. Global mean surface temperature in G4Foam is 0.6K lower than RCP6.0, with statistically significant cooling relative to RCP6.0 south of 30° N and an increase in rainfall over land, most pronouncedly during the JJA season, relative to both G4SSA and RCP6.0.
Jean-Christophe Calvet, Noureddine Fritz, Christine Berne, Bruno Piguet, William Maurel, and Catherine Meurey
SOIL, 2, 615–629, https://doi.org/10.5194/soil-2-615-2016, https://doi.org/10.5194/soil-2-615-2016, 2016
Short summary
Short summary
Soil thermal conductivity in wet conditions can be retrieved together with the soil quartz content using a reverse modelling technique based on sub-hourly soil temperature observations at three depths below the soil surface.
A pedotransfer function is proposed for quartz, for the considered region in France.
Gravels have a major impact on soil thermal conductivity, and omitting the soil organic matter information tends to enhance this impact.
Xiaodong Gao, Xining Zhao, Luca Brocca, Ting Lv, Gaopeng Huo, and Pute Wu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-617, https://doi.org/10.5194/hess-2016-617, 2016
Preprint retracted
Short summary
Short summary
We built observation operators by the CDF matching method. Two-year duration was identified as the optimal data length in prediction accuracy. Application in different climates in USA showed these operators are a robust statistical tool for upscaling soil moisture from surface to profile by using exponential filter as a reference method. The findings here may be applied in the prediction of profile soil moisture from surface measurements via remote sensing techniques.
Wei Qu, Heye R. Bogena, Johan A. Huisman, Marius Schmidt, Ralf Kunkel, Ansgar Weuthen, Henning Schiedung, Bernd Schilling, Jürgen Sorg, and Harry Vereecken
Earth Syst. Sci. Data, 8, 517–529, https://doi.org/10.5194/essd-8-517-2016, https://doi.org/10.5194/essd-8-517-2016, 2016
Short summary
Short summary
The Rollesbroich catchment is a hydrological observatory of the TERENO (Terrestrial Environmental Observatories) initiative. Hydrometeorological data and spatiotemporal variations in soil water content are measured at high temporal resolution and can be used for many purposes, e.g. validation of remote sensing retrievals, improving hydrological understanding, optimizing data assimilation and inverse modelling techniques. The data set is freely available online (http://www.tereno.net).
Rolf Hut, Niels Drost, Maarten van Meersbergen, Edwin Sutanudjaja, Marc Bierkens, and Nick van de Giesen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-225, https://doi.org/10.5194/gmd-2016-225, 2016
Revised manuscript not accepted
Short summary
Short summary
A system that predicts the amount of water flowing in each river on earth, 9 days ahead, is build using existing parts of open source computer code build by different researchers in other projects.
The glue between all pre-existing parts are all open interfaces which means that the pieces system click together like a house of LEGOs. It is easy to remove a piece (a brick) and replace it with another, improved, piece.
The resulting predictions are available online at forecast.ewatercycle.org
Markus Enenkel, Christoph Reimer, Wouter Dorigo, Wolfgang Wagner, Isabella Pfeil, Robert Parinussa, and Richard De Jeu
Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, https://doi.org/10.5194/hess-20-4191-2016, 2016
Short summary
Short summary
Soil moisture is a crucial variable for a variety of applications, ranging from weather forecasting and agricultural production to the monitoring of floods and droughts. Satellite observations are particularly important in regions where no in situ measurements are available. Our study presents a method to integrate global near-real-time satellite observations from different sensors into one harmonized, daily data set. A first validation shows good results on a global scale.
Gregor Laaha, Juraj Parajka, Alberto Viglione, Daniel Koffler, Klaus Haslinger, Wolfgang Schöner, Judith Zehetgruber, and Günter Blöschl
Hydrol. Earth Syst. Sci., 20, 3967–3985, https://doi.org/10.5194/hess-20-3967-2016, https://doi.org/10.5194/hess-20-3967-2016, 2016
Short summary
Short summary
We present a framework for assessing climate impacts on future low flows that combines different sources of information termed pillars. To illustrate the framework, three pillars are chosen: low-flow observation, climate observations and climate projections. By combining different sources of information we aim at more robust projections than obtained from each pillar alone. The viability of the framework is illustrated for four example catchments from Austria.
Davide Zanchettin, Myriam Khodri, Claudia Timmreck, Matthew Toohey, Anja Schmidt, Edwin P. Gerber, Gabriele Hegerl, Alan Robock, Francesco S. R. Pausata, William T. Ball, Susanne E. Bauer, Slimane Bekki, Sandip S. Dhomse, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Michael Mills, Marion Marchand, Ulrike Niemeier, Virginie Poulain, Eugene Rozanov, Angelo Rubino, Andrea Stenke, Kostas Tsigaridis, and Fiona Tummon
Geosci. Model Dev., 9, 2701–2719, https://doi.org/10.5194/gmd-9-2701-2016, https://doi.org/10.5194/gmd-9-2701-2016, 2016
Short summary
Short summary
Simulating volcanically-forced climate variability is a challenging task for climate models. The Model Intercomparison Project on the climatic response to volcanic forcing (VolMIP) – an endorsed contribution to CMIP6 – defines a protocol for idealized volcanic-perturbation experiments to improve comparability of results across different climate models. This paper illustrates the design of VolMIP's experiments and describes the aerosol forcing input datasets to be used.
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182, https://doi.org/10.5194/hess-20-3167-2016, https://doi.org/10.5194/hess-20-3167-2016, 2016
Short summary
Short summary
The Tibetan Plateau plays a major role in regional and global climate. The knowledge of latent heat flux can help to better describe the complex interactions between land and atmosphere. The purpose of this paper is to provide a detailed cross-comparison of existing latent heat flux products over the TP. The results highlight the recently developed latent heat product – High Resolution Land Surface Parameters from Space (HOLAPS).
N. Sánchez, J. Martínez-Fernández, and A. González-Zamora
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 393–398, https://doi.org/10.5194/isprs-archives-XLI-B8-393-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-393-2016, 2016
Juraj Parajka, Alfred Paul Blaschke, Günter Blöschl, Klaus Haslinger, Gerold Hepp, Gregor Laaha, Wolfgang Schöner, Helene Trautvetter, Alberto Viglione, and Matthias Zessner
Hydrol. Earth Syst. Sci., 20, 2085–2101, https://doi.org/10.5194/hess-20-2085-2016, https://doi.org/10.5194/hess-20-2085-2016, 2016
Short summary
Short summary
Streamflow estimation during low-flow conditions is important for estimation of environmental flows, effluent water quality, hydropower operations, etc. However, it is not clear how the uncertainties in assumptions used in the projections translate into uncertainty of estimated future low flows. The objective of the study is to explore the relative role of hydrologic model calibration and climate scenarios in the uncertainty of low-flow projections in Austria.
Koen Hilgersom, Tim van Emmerik, Anna Solcerova, Wouter Berghuijs, John Selker, and Nick van de Giesen
Geosci. Instrum. Method. Data Syst., 5, 151–162, https://doi.org/10.5194/gi-5-151-2016, https://doi.org/10.5194/gi-5-151-2016, 2016
Short summary
Short summary
Fibre optic distributed temperature sensing allows one to measure temperature patterns along a fibre optic cable with resolutions down to 25 cm. In geosciences, we sometimes wrap the cable to a coil to measure temperature at even smaller scales. We show that coils with narrow bends affect the measured temperatures. This also holds for the object to which the coil is attached, when heated by solar radiation. We therefore recommend the necessity to carefully design such distributed temperature probes.
Günter Blöschl
Proc. IAHS, 373, 57–60, https://doi.org/10.5194/piahs-373-57-2016, https://doi.org/10.5194/piahs-373-57-2016, 2016
Short summary
Short summary
The spatial dimensions of water management heavily rely on accurate hydrological estimates in the landscape. This has been the focus of the Predictions in Ungauged Basins (PUB) initiative of the IAHS. The initiative has significantly advanced the science by furthering process understanding and estimation methods, and by synthesising the knowledge across processes, places and scales. Ongoing research on PUB is increasingly accounts for the feedbacks between humans and water in the landscape.
Ján Szolgay, Ladislav Gaál, Tomáš Bacigál, Silvia Kohnová, Kamila Hlavčová, Roman Výleta, and Günter Blöschl
Proc. IAHS, 373, 61–67, https://doi.org/10.5194/piahs-373-61-2016, https://doi.org/10.5194/piahs-373-61-2016, 2016
Short summary
Short summary
The design of hydraulic structures where storage is involved, requires estimates of joint probability distribution of flood volumes and flood peaks. The problem of choosing a joint distribution was so far approached more from a statistical point of view. In the paper the suitability of various copula models of this relationships was analysed with a particular focus on the type and seasonality of flood generation processes in a regional context.
Serena Ceola, Alberto Montanari, Juraj Parajka, Alberto Viglione, Günter Blöschl, and Francesco Laio
Proc. IAHS, 373, 131–136, https://doi.org/10.5194/piahs-373-131-2016, https://doi.org/10.5194/piahs-373-131-2016, 2016
Short summary
Short summary
This paper analyses the evolution in space and time of human presence in terms of settlements and associated economic activities along the Eastern Alpine river network in Austria and Italy by using high-resolution satellite images. To this aim, nocturnal artificial luminosity images and the geographical location of streams and rivers are employed. Our results reveal a significant increase of nighttime lights, and thus of human presence.
Jaakko Ikonen, Juho Vehviläinen, Kimmo Rautiainen, Tuomo Smolander, Juha Lemmetyinen, Simone Bircher, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 95–108, https://doi.org/10.5194/gi-5-95-2016, https://doi.org/10.5194/gi-5-95-2016, 2016
Short summary
Short summary
A comprehensive, distributed network of in situ measurement stations gathering information on soil moisture has been set up in recent years at the Finnish Meteorological Institute's (FMI) Sodankylä Arctic research station. The network is used as a tool to evaluate the validity of satellite retrievals of soil properties. We present the soil moisture observation network and the results of comparisons of top layer soil moisture between 2012 and 2014 against ESA CCI product soil moisture retrievals.
Roland Séférian, Christine Delire, Bertrand Decharme, Aurore Voldoire, David Salas y Melia, Matthieu Chevallier, David Saint-Martin, Olivier Aumont, Jean-Christophe Calvet, Dominique Carrer, Hervé Douville, Laurent Franchistéguy, Emilie Joetzjer, and Séphane Sénési
Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, https://doi.org/10.5194/gmd-9-1423-2016, 2016
Short summary
Short summary
This paper presents the first IPCC-class Earth system model developed at Centre National de Recherches Météorologiques (CNRM-ESM1). We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers, comparing model results to the most up-to-date climate and carbon cycle dataset over the latest decades.
Demetris Koutsoyiannis, Günter Blöschl, András Bárdossy, Christophe Cudennec, Denis Hughes, Alberto Montanari, Insa Neuweiler, and Hubert Savenije
Hydrol. Earth Syst. Sci., 20, 1081–1084, https://doi.org/10.5194/hess-20-1081-2016, https://doi.org/10.5194/hess-20-1081-2016, 2016
Lianyu Yu, Yijian Zeng, Zhongbo Su, Huanjie Cai, and Zhen Zheng
Hydrol. Earth Syst. Sci., 20, 975–990, https://doi.org/10.5194/hess-20-975-2016, https://doi.org/10.5194/hess-20-975-2016, 2016
Short summary
Short summary
The coupled water vapor and heat transport model using two different ET (ETdir, ETind) methods varied concerning the simulation of soil moisture and ET components, while agreed well for the simulation of soil temperature. Considering aerodynamic and surface resistance terms improved the ETdir method regarding simulating soil evaporation, especially after irrigation. The interactive effect of crop growth parameters with changing environment played an important role in estimating ET components.
Zhuo-Yi Zhu, Ying Wu, Su-Mei Liu, Fred Wenger, Jun Hu, Jing Zhang, and Rui-Feng Zhang
Biogeosciences, 13, 975–987, https://doi.org/10.5194/bg-13-975-2016, https://doi.org/10.5194/bg-13-975-2016, 2016
Short summary
Short summary
Svalbard archipelago has lots of valley glaciers, and its position in organic carbon flux to ocean remains unclear. In this work, we found that these valley glaciers have a much higher area-weighted and discharge-weighted organic carbon flux, relative to Greenland Ice Sheet, and are comparable to other valley glaciers like those in the Alaska region. Hence Svalbard glaciers are an important source for terrestrial carbon.
Claus Davidsen, Suxia Liu, Xingguo Mo, Dan Rosbjerg, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 20, 771–785, https://doi.org/10.5194/hess-20-771-2016, https://doi.org/10.5194/hess-20-771-2016, 2016
Short summary
Short summary
In northern China, rivers run dry and groundwater tables drop, causing economic losses for all water use sectors. We present a groundwater-surface water allocation decision support tool for cost-effective long-term recovery of an overpumped aquifer. The tool is demonstrated for a part of the North China Plain and can support the implementation of the recent China No. 1 Document in a rational and economically efficient way.
L. Xia, A. Robock, S. Tilmes, and R. R. Neely III
Atmos. Chem. Phys., 16, 1479–1489, https://doi.org/10.5194/acp-16-1479-2016, https://doi.org/10.5194/acp-16-1479-2016, 2016
Short summary
Short summary
Climate model simulations show that stratospheric sulfate geoengineering could impact the terrestrial carbon cycle by enhancing the carbon sink. Enhanced downward diffuse radiation, combined with cooling, could stimulate plants to grow more and absorb more carbon dioxide. This beneficial impact of stratospheric sulfate geoengineering would need to be balanced by a large number of potential risks in any future decisions about implementation of geoengineering.
M. K. van der Molen, R. A. M. de Jeu, W. Wagner, I. R. van der Velde, P. Kolari, J. Kurbatova, A. Varlagin, T. C. Maximov, A. V. Kononov, T. Ohta, A. Kotani, M. C. Krol, and W. Peters
Hydrol. Earth Syst. Sci., 20, 605–624, https://doi.org/10.5194/hess-20-605-2016, https://doi.org/10.5194/hess-20-605-2016, 2016
Short summary
Short summary
Boreal Eurasia contains extensive forests, which play an important role in the terrestrial carbon cycle. Droughts can modify this cycle considerably, although very few ground-based observations are available in the region. We test whether satellite-observed soil moisture may be used to improve carbon cycle models in this region. This paper explains when and where this works best. The interpretation of satellite soil moisture is best in summer conditions, and is hampered by snow, ice and ponding.
Riccardo Biondi, Andrea Steiner, Gottfried Kirchengast, Hugues Brenot, and Therese Rieckh
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2015-974, https://doi.org/10.5194/acp-2015-974, 2016
Revised manuscript not accepted
Short summary
Short summary
Cloud structure and cloud top height are key parameters for the monitoring of volcanic cloud movement and for characterizing eruptive processes and understanding the impact on short-term climate variability.
We have studied the eruption of Nabro volcano, which has been recognized as the largest stratospheric sulfur injection since Pinatubo (1991) and we have found a clear warming signature after the eruption of Nabro persisting for a few months.
G. Blöschl, A. P. Blaschke, M. Broer, C. Bucher, G. Carr, X. Chen, A. Eder, M. Exner-Kittridge, A. Farnleitner, A. Flores-Orozco, P. Haas, P. Hogan, A. Kazemi Amiri, M. Oismüller, J. Parajka, R. Silasari, P. Stadler, P. Strauss, M. Vreugdenhil, W. Wagner, and M. Zessner
Hydrol. Earth Syst. Sci., 20, 227–255, https://doi.org/10.5194/hess-20-227-2016, https://doi.org/10.5194/hess-20-227-2016, 2016
Short summary
Short summary
This paper illustrates the experimental and monitoring set-up of the 66 ha Hydrological Open Air Laboratory (HOAL) in Petzenkirchen, Lower Austria, which allows meaningful hypothesis testing. The HOAL catchment features a range of different runoff generation processes (surface runoff, springs, tile drains, wetlands), and is convenient from a logistic point of view as all instruments can be connected to the power grid and a high-speed glassfibre local area network.
D. Fairbairn, A. L. Barbu, J.-F. Mahfouf, J.-C. Calvet, and E. Gelati
Hydrol. Earth Syst. Sci., 19, 4811–4830, https://doi.org/10.5194/hess-19-4811-2015, https://doi.org/10.5194/hess-19-4811-2015, 2015
Short summary
Short summary
The ensemble Kalman filter (EnKF) and simplified extended Kalman filter (SEKF) root-zone soil moisture analyses are compared when assimilating in situ surface observations. In the synthetic experiments, the EnKF performs best because it can stochastically capture the errors in the precipitation. The two methods perform similarly in the real experiments. During the summer period, both methods perform poorly as a result of nonlinearities in the land surface model.
C. J. Gabriel and A. Robock
Atmos. Chem. Phys., 15, 11949–11966, https://doi.org/10.5194/acp-15-11949-2015, https://doi.org/10.5194/acp-15-11949-2015, 2015
Short summary
Short summary
This is a first look at how the El Niño/Southern Oscillation (ENSO) might change under a regime of stratospheric geoengineering (GE). We find neither ENSO event frequency nor ENSO event amplitude will be different under various GE experiments than they would under unabated global warming. We additionally find substantial disagreement between models in depicting ENSO amplitude and frequency. Additionally, output from several GCMs is excluded from comparison due to unrealistic ENSO variability.
B. Kravitz, A. Robock, S. Tilmes, O. Boucher, J. M. English, P. J. Irvine, A. Jones, M. G. Lawrence, M. MacCracken, H. Muri, J. C. Moore, U. Niemeier, S. J. Phipps, J. Sillmann, T. Storelvmo, H. Wang, and S. Watanabe
Geosci. Model Dev., 8, 3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, https://doi.org/10.5194/gmd-8-3379-2015, 2015
G. P. Petropoulos, M. R. North, G. Ireland, P. K. Srivastava, and D. V. Rendall
Geosci. Model Dev., 8, 3257–3284, https://doi.org/10.5194/gmd-8-3257-2015, https://doi.org/10.5194/gmd-8-3257-2015, 2015
Short summary
Short summary
The performance of the SimSphere SVAT model was comprehensively validated against in situ measurements from selected US and Australian sites of the FLUXNET monitoring network for 2011. The results obtained confirmed the correspondence of the model structure to the real conditions for which it was parameterised, evidencing its ability to reproduce outputs akin to the in situ reference data.To our knowledge this is the first comprehensive validation of SimSphere for Australia and the USA.
Y. Yi, J. S. Kimball, M. A. Rawlins, M. Moghaddam, and E. S. Euskirchen
Biogeosciences, 12, 5811–5829, https://doi.org/10.5194/bg-12-5811-2015, https://doi.org/10.5194/bg-12-5811-2015, 2015
Short summary
Short summary
We found that regional warming promotes widespread deepening of soil thaw in the pan-Arctic area; continued warming will most likely promote permafrost degradation in the warm permafrost areas. We also found that deeper snowpack enhances soil respiration from deeper soil carbon pool more than temperature does, particularly in the cold permafrost areas, where a large amount of soil carbon is stored in deep perennial frozen soils but is potentially vulnerable to mobilization from climate change.
S. Garrigues, A. Olioso, D. Carrer, B. Decharme, J.-C. Calvet, E. Martin, S. Moulin, and O. Marloie
Geosci. Model Dev., 8, 3033–3053, https://doi.org/10.5194/gmd-8-3033-2015, https://doi.org/10.5194/gmd-8-3033-2015, 2015
Short summary
Short summary
This paper investigates the impacts of uncertainties in the climate, the vegetation dynamic, the soil properties and the cropland management on the simulation of evapotranspiration from the ISBA-A-gs land surface model over a 12-year Mediterranean crop succession. It mainly shows that errors in the soil parameters and the lack of irrigation in the simulation have the largest influence on evapotranspiration compared to the uncertainties in the climate and the vegetation dynamic.
K. E. R. Pramana, M. W. Ertsen, and N. C. van de Giesen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-9489-2015, https://doi.org/10.5194/hessd-12-9489-2015, 2015
Revised manuscript not accepted
F. Todisco, L. Brocca, L. F. Termite, and W. Wagner
Hydrol. Earth Syst. Sci., 19, 3845–3856, https://doi.org/10.5194/hess-19-3845-2015, https://doi.org/10.5194/hess-19-3845-2015, 2015
Short summary
Short summary
We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.
J. Hoogeveen, J.-M. Faurès, L. Peiser, J. Burke, and N. van de Giesen
Hydrol. Earth Syst. Sci., 19, 3829–3844, https://doi.org/10.5194/hess-19-3829-2015, https://doi.org/10.5194/hess-19-3829-2015, 2015
Short summary
Short summary
GlobWat is a freely distributed, global soil water balance model that is used by FAO to assess water use in irrigated agriculture, the main factor behind scarcity of freshwater in an increasing number of regions. The model is based on spatially distributed high-resolution data sets that are consistent at global level and is calibrated and validated against information published in global databases. The paper describes methodology, input and output data, calibration and validation of the model.
Y. Li, G. Kirchengast, B. Scherllin-Pirscher, R. Norman, Y. B. Yuan, J. Fritzer, M. Schwaerz, and K. Zhang
Atmos. Meas. Tech., 8, 3447–3465, https://doi.org/10.5194/amt-8-3447-2015, https://doi.org/10.5194/amt-8-3447-2015, 2015
Short summary
Short summary
We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System-based radio occultation measurements. The new algorithm is evaluated against the OPSv5.6 algorithm developed by the Wegener Center using both simulated and real observed data. It is found that the algorithm can significantly reduce the random errors of optimized bending angles. The retrieved refractivity and temperature profiles are also benefited.
V. Proschek, G. Kirchengast, S. Schweitzer, J. S. A. Brooke, P. F. Bernath, C. B. Thomas, J.-G. Wang, K. A. Tereszchuk, G. González Abad, R. J. Hargreaves, C. A. Beale, J. J. Harrison, P. A. Martin, V. L. Kasyutich, C. Gerbig, O. Kolle, and A. Loescher
Atmos. Meas. Tech., 8, 3315–3336, https://doi.org/10.5194/amt-8-3315-2015, https://doi.org/10.5194/amt-8-3315-2015, 2015
T. Tagesson, R. Fensholt, S. Huber, S. Horion, I. Guiro, A. Ehammer, and J. Ardö
Biogeosciences, 12, 4621–4635, https://doi.org/10.5194/bg-12-4621-2015, https://doi.org/10.5194/bg-12-4621-2015, 2015
Short summary
Short summary
Relationships between ecosystem properties of semi-arid savanna and reflected solar radiance between 35 and 1800nm were investigated. Normalised combinations of reflectance for the near infrared, shortwave infrared, and 600 to 700nm were strongly affected by solar and viewing angle effects. Ecosystem properties of savannas were strongly correlated with reflectance at 350-1800nm, and normalised combinations of reflectance were strong predictors of the savanna ecosystem properties.
J. H. Matthes, S. H. Knox, C. Sturtevant, O. Sonnentag, J. Verfaillie, and D. Baldocchi
Biogeosciences, 12, 4577–4594, https://doi.org/10.5194/bg-12-4577-2015, https://doi.org/10.5194/bg-12-4577-2015, 2015
Short summary
Short summary
This research used a long-term data set of near-surface canopy hyperspectral reflectance collected over 5 years to test the ability of these measurements to predict ecosystem carbon flux at a pasture and rice paddy in the California Delta, USA. We determined that each reflectance sampling event best captured the integrated prior week of carbon dioxide uptake, providing an important benchmark for understanding the lagged correlation between ecosystem carbon uptake and biochemical reflectance.
C. L. Liu, G. Kirchengast, K. Zhang, R. Norman, Y. Li, S. C. Zhang, J. Fritzer, M. Schwaerz, S. Q. Wu, and Z. X. Tan
Atmos. Meas. Tech., 8, 2999–3019, https://doi.org/10.5194/amt-8-2999-2015, https://doi.org/10.5194/amt-8-2999-2015, 2015
J. Iwema, R. Rosolem, R. Baatz, T. Wagener, and H. R. Bogena
Hydrol. Earth Syst. Sci., 19, 3203–3216, https://doi.org/10.5194/hess-19-3203-2015, https://doi.org/10.5194/hess-19-3203-2015, 2015
Short summary
Short summary
The cosmic-ray neutron sensor can provide soil moisture content averages over areas of roughly half a kilometre by half a kilometre. Although this sensor is usually calibrated using soil samples taken on a single day, we found that multiple sampling days are needed. The calibration results were also affected by the soil wetness conditions of the sampling days. The outcome of this study will help researchers to calibrate/validate new cosmic-ray neutron sensor sites more accurately.
S. Garrigues, A. Olioso, J. C. Calvet, E. Martin, S. Lafont, S. Moulin, A. Chanzy, O. Marloie, S. Buis, V. Desfonds, N. Bertrand, and D. Renard
Hydrol. Earth Syst. Sci., 19, 3109–3131, https://doi.org/10.5194/hess-19-3109-2015, https://doi.org/10.5194/hess-19-3109-2015, 2015
Short summary
Short summary
Land surface model simulations of evapotranspiration are assessed over a 12-year Mediterranean crop succession. Evapotranspiration mainly results from soil evaporation when it is simulated over a Mediterranean crop succession. This leads to a high sensitivity to the soil parameters. Errors on soil hydraulic properties can lead to a large bias in cumulative evapotranspiration over a long period of time. Accounting for uncertainties in soil properties is essential for land surface modelling.
A. Plach, V. Proschek, and G. Kirchengast
Atmos. Meas. Tech., 8, 2813–2825, https://doi.org/10.5194/amt-8-2813-2015, https://doi.org/10.5194/amt-8-2813-2015, 2015
Short summary
Short summary
This paper discusses simulation results of a newly developed line-of-sight wind retrieval algorithm expanding an existing simulation framework that includes the retrieval of thermodynamic variables and greenhouse gases in the upper troposphere/lower stratosphere region. The underlying mission concept further develops the radio occultation technique (i.e. satellite remote sensing technique scanning the atmosphere with high vertical resolution) employing microwave and infrared-laser signals.
S. Liu, L. Tan, X. Mo, and S. Zhang
Proc. IAHS, 371, 167–172, https://doi.org/10.5194/piahs-371-167-2015, https://doi.org/10.5194/piahs-371-167-2015, 2015
Short summary
Short summary
By taking an example of Allen’s formula as a hydrological model based on long-term data at a Chinese site, the relationships between driving forces and responses for average, minimum and maximum values at daily, monthly and annual scale are revealed. It indicates due to the relationships’ nonlinearity a routine model may not be able to catch hydrological responses extreme from extreme driving events and it is even more so for future. Finding a primary driver is one of the ways for improvements.
R. A. P. Perdigão and G. Blöschl
Proc. IAHS, 370, 125–130, https://doi.org/10.5194/piahs-370-125-2015, https://doi.org/10.5194/piahs-370-125-2015, 2015
Short summary
Short summary
Flood regimes are behavioural patterns in floods across a wide variety of events under diverse circumstances. Our goal is to provide a unifying framework to address those regimes, how and why they change in space and time. For that purpose, we introduce a general model of flood regime dynamics under interacting natural factors and validate it with observations spanning a great diversity of hydrological settings. The model ultimately brings better flood understanding and forecasting abilities.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 2015
J. Szolgay, L. Gaál, S. Kohnová, K. Hlavčová, R. Výleta, T. Bacigál, and G. Blöschl
Proc. IAHS, 370, 183–188, https://doi.org/10.5194/piahs-370-183-2015, https://doi.org/10.5194/piahs-370-183-2015, 2015
Short summary
Short summary
The design of hydraulic structures where storage is involved, requires estimates of flood volumes related to flood peaks. The problem was so far approached more from a statistical point of view. In the paper it was attempted to better understand the hydrological factors controlling this relationship. The suitability of various copula models of the relationships between flood peaks and flood volumes was analysed with a particular focus on the type and seasonality of flood generation processes.
J. Grames, A. Prskawetz, D. Grass, and G. Blöschl
Proc. IAHS, 369, 3–6, https://doi.org/10.5194/piahs-369-3-2015, https://doi.org/10.5194/piahs-369-3-2015, 2015
Short summary
Short summary
Communities live close to rivers and therefore are confronted with the risk of flooding. It is important to understand the drivers and mechanisms of the consumption and investment behavior of these societies in order to identify an optimal investment strategy into flood defense capital. To solve such an economic optimization model we develop a periodic water function to approximate the former discrete stochastic time series of rainfall events and apply it to an existing socio-hydrology model.
M. Bordoni, C. Meisina, R. Valentino, M. Bittelli, and S. Chersich
Nat. Hazards Earth Syst. Sci., 15, 1025–1050, https://doi.org/10.5194/nhess-15-1025-2015, https://doi.org/10.5194/nhess-15-1025-2015, 2015
Short summary
Short summary
This manuscript defines a reliable methodology for shallow landslides triggering zones assessment at site-specific or local scales by using a well-established physically based model (TRIGRS-unsaturated) based on the calibration of the model at slope scale using soil hydrological behavior analyzed through a continuous field monitoring. Moreover, the paper analyzes the effects on triggering zones assessment of taking into account for different unit mapping of the slope soils of a studied area.
R. Biondi, A. K. Steiner, G. Kirchengast, and T. Rieckh
Atmos. Chem. Phys., 15, 5181–5193, https://doi.org/10.5194/acp-15-5181-2015, https://doi.org/10.5194/acp-15-5181-2015, 2015
S. Ceola, B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione, and T. Wagener
Hydrol. Earth Syst. Sci., 19, 2101–2117, https://doi.org/10.5194/hess-19-2101-2015, https://doi.org/10.5194/hess-19-2101-2015, 2015
Short summary
Short summary
We present the outcomes of a collaborative hydrological experiment undertaken by five different international research groups in a virtual laboratory. Moving from the definition of accurate protocols, a rainfall-runoff model was independently applied by the research groups, which then engaged in a comparative discussion. The results revealed that sharing protocols and running the experiment within a controlled environment is fundamental for ensuring experiment repeatability and reproducibility.
F. Ladstädter, A. K. Steiner, M. Schwärz, and G. Kirchengast
Atmos. Meas. Tech., 8, 1819–1834, https://doi.org/10.5194/amt-8-1819-2015, https://doi.org/10.5194/amt-8-1819-2015, 2015
B. A. Drewniak, U. Mishra, J. Song, J. Prell, and V. R. Kotamarthi
Biogeosciences, 12, 2119–2129, https://doi.org/10.5194/bg-12-2119-2015, https://doi.org/10.5194/bg-12-2119-2015, 2015
A. Kann, I. Meirold-Mautner, F. Schmid, G. Kirchengast, J. Fuchsberger, V. Meyer, L. Tüchler, and B. Bica
Hydrol. Earth Syst. Sci., 19, 1547–1559, https://doi.org/10.5194/hess-19-1547-2015, https://doi.org/10.5194/hess-19-1547-2015, 2015
Short summary
Short summary
The paper introduces a high resolution precipitation analysis system which operates on 1 km x 1 km resolution with high frequency updates of 5 minutes. The ability of such a system to adequately assess the convective precipitation distribution is evaluated by means of an independant, high resolution station network. This dense station network allows for a thorough evaluation of the analyses under different convective situations and of the representativeness error of raingaue measurements.
M. R. North, G. P. Petropoulos, G. Ireland, and J. P. McCalmont
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-6-217-2015, https://doi.org/10.5194/esdd-6-217-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
This study evaluated the ability of the SimSphere SVAT model in estimating key parameters characterising land surface interactions. Results confirmed the correspondence of the model structure to real conditions for which it had been parameterised, evidencing its ability to reproduce outputs akin to the in situ data. To our knowledge this is the first comprehensive validation of the model. Findings are very important since use of the model is growing globally as educational and research tool.
G. Bruni, R. Reinoso, N. C. van de Giesen, F. H. L. R. Clemens, and J. A. E. ten Veldhuis
Hydrol. Earth Syst. Sci., 19, 691–709, https://doi.org/10.5194/hess-19-691-2015, https://doi.org/10.5194/hess-19-691-2015, 2015
M. P. Jensen, T. Toto, D. Troyan, P. E. Ciesielski, D. Holdridge, J. Kyrouac, J. Schatz, Y. Zhang, and S. Xie
Atmos. Meas. Tech., 8, 421–434, https://doi.org/10.5194/amt-8-421-2015, https://doi.org/10.5194/amt-8-421-2015, 2015
Short summary
Short summary
A major component of the 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state. This manuscript describes the details of the MC3E radiosonde operations including the instrumentation, data processing and analysis of the impacts of bias correction and algorithm assumptions on the determination of forcing data sets.
S. A. P. de Jong, J. D. Slingerland, and N. C. van de Giesen
Atmos. Meas. Tech., 8, 335–339, https://doi.org/10.5194/amt-8-335-2015, https://doi.org/10.5194/amt-8-335-2015, 2015
Short summary
Short summary
By using two cylindrical thermometers with different diameters, one can determine what temperature a zero diameter thermometer would have. Such a virtual thermometer would not be affected by solar heating and would take on the temperature of the surrounding air. We applied this principle to atmospheric temperature measurements with fiber optic cables using distributed temperature sensing (DTS). With two unshielded cable pairs, one black pair and one white pair, good results were obtained.
S. Tilmes, M. J. Mills, U. Niemeier, H. Schmidt, A. Robock, B. Kravitz, J.-F. Lamarque, G. Pitari, and J. M. English
Geosci. Model Dev., 8, 43–49, https://doi.org/10.5194/gmd-8-43-2015, https://doi.org/10.5194/gmd-8-43-2015, 2015
Short summary
Short summary
A new Geoengineering Model Intercomparison Project (GeoMIP) experiment “G4 specified stratospheric aerosols” (G4SSA) is proposed to investigate the impact of stratospheric aerosol geoengineering on atmosphere, chemistry, dynamics, climate, and the environment. In contrast to the earlier G4 GeoMIP experiment, which requires an emission of sulfur dioxide (SO2) into the model, a prescribed aerosol forcing file is provided to the community, to be consistently applied to future model experiments.
X. Chen, Z. Su, Y. Ma, S. Liu, Q. Yu, and Z. Xu
Atmos. Chem. Phys., 14, 13097–13117, https://doi.org/10.5194/acp-14-13097-2014, https://doi.org/10.5194/acp-14-13097-2014, 2014
N. Canal, J.-C. Calvet, B. Decharme, D. Carrer, S. Lafont, and G. Pigeon
Hydrol. Earth Syst. Sci., 18, 4979–4999, https://doi.org/10.5194/hess-18-4979-2014, https://doi.org/10.5194/hess-18-4979-2014, 2014
Short summary
Short summary
Regional French agricultural yield statistics are used to benchmark root water uptake representations in the ISBA-A-gs model. Key model parameters governing the inter-annual variability of the simulated biomass are retrieved. A complex multi-layer soil hydrology model does not outperform a simple bulk root-zone reservoir approach. This could be explained by missing processes/information in the model such as hydraulic redistribution and detailed soil properties.
E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, R. Fisher, B. Christoffersen, J. C. Calvet, A. C. L. da Costa, L. V. Ferreira, and P. Meir
Geosci. Model Dev., 7, 2933–2950, https://doi.org/10.5194/gmd-7-2933-2014, https://doi.org/10.5194/gmd-7-2933-2014, 2014
Z. H. He, J. Parajka, F. Q. Tian, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 4773–4789, https://doi.org/10.5194/hess-18-4773-2014, https://doi.org/10.5194/hess-18-4773-2014, 2014
Short summary
Short summary
In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDFS) directly from MODIS snow covered area (SCA) and ground-based snow depth data without calibration. Snow density is estimated as the ratio between observed precipitation and changes in the snow volume for days with snow accumulation. DDFS values are estimated as the ratio between changes in the snow water equivalent and difference between the daily temperature and a threshold value for days with snowmelt.
G. P. Petropoulos, H. M. Griffiths, T. N. Carlson, P. Ioannou-Katidis, and T. Holt
Geosci. Model Dev., 7, 1873–1887, https://doi.org/10.5194/gmd-7-1873-2014, https://doi.org/10.5194/gmd-7-1873-2014, 2014
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
B. Merz, J. Aerts, K. Arnbjerg-Nielsen, M. Baldi, A. Becker, A. Bichet, G. Blöschl, L. M. Bouwer, A. Brauer, F. Cioffi, J. M. Delgado, M. Gocht, F. Guzzetti, S. Harrigan, K. Hirschboeck, C. Kilsby, W. Kron, H.-H. Kwon, U. Lall, R. Merz, K. Nissen, P. Salvatti, T. Swierczynski, U. Ulbrich, A. Viglione, P. J. Ward, M. Weiler, B. Wilhelm, and M. Nied
Nat. Hazards Earth Syst. Sci., 14, 1921–1942, https://doi.org/10.5194/nhess-14-1921-2014, https://doi.org/10.5194/nhess-14-1921-2014, 2014
G. Blöschl, A. Bárdossy, D. Koutsoyiannis, Z. W. Kundzewicz, I. Littlewood, A. Montanari, and H. Savenije
Hydrol. Earth Syst. Sci., 18, 2433–2435, https://doi.org/10.5194/hess-18-2433-2014, https://doi.org/10.5194/hess-18-2433-2014, 2014
H. M. Holländer, H. Bormann, T. Blume, W. Buytaert, G. B. Chirico, J.-F. Exbrayat, D. Gustafsson, H. Hölzel, T. Krauße, P. Kraft, S. Stoll, G. Blöschl, and H. Flühler
Hydrol. Earth Syst. Sci., 18, 2065–2085, https://doi.org/10.5194/hess-18-2065-2014, https://doi.org/10.5194/hess-18-2065-2014, 2014
X. Tian-Kunze, L. Kaleschke, N. Maaß, M. Mäkynen, N. Serra, M. Drusch, and T. Krumpen
The Cryosphere, 8, 997–1018, https://doi.org/10.5194/tc-8-997-2014, https://doi.org/10.5194/tc-8-997-2014, 2014
M. Balzarolo, S. Boussetta, G. Balsamo, A. Beljaars, F. Maignan, J.-C. Calvet, S. Lafont, A. Barbu, B. Poulter, F. Chevallier, C. Szczypta, and D. Papale
Biogeosciences, 11, 2661–2678, https://doi.org/10.5194/bg-11-2661-2014, https://doi.org/10.5194/bg-11-2661-2014, 2014
C. Szczypta, J.-C. Calvet, F. Maignan, W. Dorigo, F. Baret, and P. Ciais
Geosci. Model Dev., 7, 931–946, https://doi.org/10.5194/gmd-7-931-2014, https://doi.org/10.5194/gmd-7-931-2014, 2014
M. Verma, M. A. Friedl, A. D. Richardson, G. Kiely, A. Cescatti, B. E. Law, G. Wohlfahrt, B. Gielen, O. Roupsard, E. J. Moors, P. Toscano, F. P. Vaccari, D. Gianelle, G. Bohrer, A. Varlagin, N. Buchmann, E. van Gorsel, L. Montagnani, and P. Propastin
Biogeosciences, 11, 2185–2200, https://doi.org/10.5194/bg-11-2185-2014, https://doi.org/10.5194/bg-11-2185-2014, 2014
R. van der Velde, M. S. Salama, T. Pellarin, M. Ofwono, Y. Ma, and Z. Su
Hydrol. Earth Syst. Sci., 18, 1323–1337, https://doi.org/10.5194/hess-18-1323-2014, https://doi.org/10.5194/hess-18-1323-2014, 2014
S. Manfreda, L. Brocca, T. Moramarco, F. Melone, and J. Sheffield
Hydrol. Earth Syst. Sci., 18, 1199–1212, https://doi.org/10.5194/hess-18-1199-2014, https://doi.org/10.5194/hess-18-1199-2014, 2014
M. Huntemann, G. Heygster, L. Kaleschke, T. Krumpen, M. Mäkynen, and M. Drusch
The Cryosphere, 8, 439–451, https://doi.org/10.5194/tc-8-439-2014, https://doi.org/10.5194/tc-8-439-2014, 2014
A. Eder, M. Exner-Kittridge, P. Strauss, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 1043–1052, https://doi.org/10.5194/hess-18-1043-2014, https://doi.org/10.5194/hess-18-1043-2014, 2014
C. Massari, L. Brocca, S. Barbetta, C. Papathanasiou, M. Mimikou, and T. Moramarco
Hydrol. Earth Syst. Sci., 18, 839–853, https://doi.org/10.5194/hess-18-839-2014, https://doi.org/10.5194/hess-18-839-2014, 2014
U. Ehret, H. V. Gupta, M. Sivapalan, S. V. Weijs, S. J. Schymanski, G. Blöschl, A. N. Gelfan, C. Harman, A. Kleidon, T. A. Bogaard, D. Wang, T. Wagener, U. Scherer, E. Zehe, M. F. P. Bierkens, G. Di Baldassarre, J. Parajka, L. P. H. van Beek, A. van Griensven, M. C. Westhoff, and H. C. Winsemius
Hydrol. Earth Syst. Sci., 18, 649–671, https://doi.org/10.5194/hess-18-649-2014, https://doi.org/10.5194/hess-18-649-2014, 2014
M. Parrens, J.-F. Mahfouf, A. L. Barbu, and J.-C. Calvet
Hydrol. Earth Syst. Sci., 18, 673–689, https://doi.org/10.5194/hess-18-673-2014, https://doi.org/10.5194/hess-18-673-2014, 2014
H. V. Gupta, C. Perrin, G. Blöschl, A. Montanari, R. Kumar, M. Clark, and V. Andréassian
Hydrol. Earth Syst. Sci., 18, 463–477, https://doi.org/10.5194/hess-18-463-2014, https://doi.org/10.5194/hess-18-463-2014, 2014
A. L. Barbu, J.-C. Calvet, J.-F. Mahfouf, and S. Lafont
Hydrol. Earth Syst. Sci., 18, 173–192, https://doi.org/10.5194/hess-18-173-2014, https://doi.org/10.5194/hess-18-173-2014, 2014
G. Blöschl, T. Nester, J. Komma, J. Parajka, and R. A. P. Perdigão
Hydrol. Earth Syst. Sci., 17, 5197–5212, https://doi.org/10.5194/hess-17-5197-2013, https://doi.org/10.5194/hess-17-5197-2013, 2013
B. Chrisman and M. Zreda
Hydrol. Earth Syst. Sci., 17, 5097–5108, https://doi.org/10.5194/hess-17-5097-2013, https://doi.org/10.5194/hess-17-5097-2013, 2013
S. E. Thompson, M. Sivapalan, C. J. Harman, V. Srinivasan, M. R. Hipsey, P. Reed, A. Montanari, and G. Blöschl
Hydrol. Earth Syst. Sci., 17, 5013–5039, https://doi.org/10.5194/hess-17-5013-2013, https://doi.org/10.5194/hess-17-5013-2013, 2013
W. Yuan, S. Liu, W. Cai, W. Dong, J. Chen, A. Arain, P. D. Blanken, A. Cescatti, G. Wohlfahrt, T. Georgiadis, L. Genesio, D. Gianelle, A. Grelle, G. Kiely, A. Knohl, D. Liu, M. Marek, L. Merbold, L. Montagnani, O. Panferov, M. Peltoniemi, S. Rambal, A. Raschi, A. Varlagin, and J. Xia
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-5475-2013, https://doi.org/10.5194/gmdd-6-5475-2013, 2013
Revised manuscript not accepted
A. Loew, T. Stacke, W. Dorigo, R. de Jeu, and S. Hagemann
Hydrol. Earth Syst. Sci., 17, 3523–3542, https://doi.org/10.5194/hess-17-3523-2013, https://doi.org/10.5194/hess-17-3523-2013, 2013
G. Di Baldassarre, A. Viglione, G. Carr, L. Kuil, J. L. Salinas, and G. Blöschl
Hydrol. Earth Syst. Sci., 17, 3295–3303, https://doi.org/10.5194/hess-17-3295-2013, https://doi.org/10.5194/hess-17-3295-2013, 2013
J. Shuttleworth, R. Rosolem, M. Zreda, and T. Franz
Hydrol. Earth Syst. Sci., 17, 3205–3217, https://doi.org/10.5194/hess-17-3205-2013, https://doi.org/10.5194/hess-17-3205-2013, 2013
L. Brocca, S. Liersch, F. Melone, T. Moramarco, and M. Volk
Hydrol. Earth Syst. Sci., 17, 3159–3169, https://doi.org/10.5194/hess-17-3159-2013, https://doi.org/10.5194/hess-17-3159-2013, 2013
S. V. Weijs, N. van de Giesen, and M. B. Parlange
Hydrol. Earth Syst. Sci., 17, 3171–3187, https://doi.org/10.5194/hess-17-3171-2013, https://doi.org/10.5194/hess-17-3171-2013, 2013
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
J. L. Salinas, G. Laaha, M. Rogger, J. Parajka, A. Viglione, M. Sivapalan, and G. Blöschl
Hydrol. Earth Syst. Sci., 17, 2637–2652, https://doi.org/10.5194/hess-17-2637-2013, https://doi.org/10.5194/hess-17-2637-2013, 2013
R. Amri, M. Zribi, Z. Lili-Chabaane, C. Szczypta, J. C. Calvet, and G. Boulet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-8117-2013, https://doi.org/10.5194/hessd-10-8117-2013, 2013
Revised manuscript not accepted
A. Viglione, J. Parajka, M. Rogger, J. L. Salinas, G. Laaha, M. Sivapalan, and G. Blöschl
Hydrol. Earth Syst. Sci., 17, 2263–2279, https://doi.org/10.5194/hess-17-2263-2013, https://doi.org/10.5194/hess-17-2263-2013, 2013
D. P. Kalivas, G. P. Petropoulos, I. M. Athanasiou, and V. J. Kollias
Nonlin. Processes Geophys., 20, 397–409, https://doi.org/10.5194/npg-20-397-2013, https://doi.org/10.5194/npg-20-397-2013, 2013
J. Parajka, A. Viglione, M. Rogger, J. L. Salinas, M. Sivapalan, and G. Blöschl
Hydrol. Earth Syst. Sci., 17, 1783–1795, https://doi.org/10.5194/hess-17-1783-2013, https://doi.org/10.5194/hess-17-1783-2013, 2013
B. Drewniak, J. Song, J. Prell, V. R. Kotamarthi, and R. Jacob
Geosci. Model Dev., 6, 495–515, https://doi.org/10.5194/gmd-6-495-2013, https://doi.org/10.5194/gmd-6-495-2013, 2013
O. A. C. Hoes, R. W. Hut, N. C. van de Giesen, and M. Boomgaard
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-1-417-2013, https://doi.org/10.5194/nhessd-1-417-2013, 2013
Revised manuscript has not been submitted
A. K. Steiner, D. Hunt, S.-P. Ho, G. Kirchengast, A. J. Mannucci, B. Scherllin-Pirscher, H. Gleisner, A. von Engeln, T. Schmidt, C. Ao, S. S. Leroy, E. R. Kursinski, U. Foelsche, M. Gorbunov, S. Heise, Y.-H. Kuo, K. B. Lauritsen, C. Marquardt, C. Rocken, W. Schreiner, S. Sokolovskiy, S. Syndergaard, and J. Wickert
Atmos. Chem. Phys., 13, 1469–1484, https://doi.org/10.5194/acp-13-1469-2013, https://doi.org/10.5194/acp-13-1469-2013, 2013
T. E. Franz, M. Zreda, R. Rosolem, and T. P. A. Ferre
Hydrol. Earth Syst. Sci., 17, 453–460, https://doi.org/10.5194/hess-17-453-2013, https://doi.org/10.5194/hess-17-453-2013, 2013
S. Dietrich, M. Werner, T. Spangehl, and G. Lohmann
Clim. Past, 9, 13–26, https://doi.org/10.5194/cp-9-13-2013, https://doi.org/10.5194/cp-9-13-2013, 2013
Related subject area
Subject: Vadose Zone Hydrology | Techniques and Approaches: Instruments and observation techniques
High-resolution operational soil moisture monitoring for forests in central Germany
Technical Note: Revisiting the general calibration of cosmic-ray neutron sensors to estimate soil water content
Effects of changes in climatic conditions on soil water storage patterns
Coupled hydrogeophysical inversion of an artificial infiltration experiment monitored with ground-penetrating radar: synthetic demonstration
Technical note: Discrete in situ vapor sampling for subsequent lab-based water stable isotope analysis
A change in perspective: downhole cosmic-ray neutron sensing for the estimation of soil moisture
Impacts of soil management and climate on saturated and near-saturated hydraulic conductivity: analyses of the Open Tension-disk Infiltrometer Meta-database (OTIM)
Physics-informed machine learning for understanding rock moisture dynamics in a sandstone cave
Relationship of seasonal variations in drip water δ13CDIC, δ18O, and trace elements with surface and physical cave conditions of La Vallina cave, NW Spain
In situ estimation of soil hydraulic and hydrodispersive properties by inversion of electromagnetic induction measurements and soil hydrological modeling
Towards disentangling heterogeneous soil moisture patterns in cosmic-ray neutron sensor footprints
Technical note: Evaporating water is different from bulk soil water in δ2H and δ18O and has implications for evaporation calculation
Technical note: Unresolved aspects of the direct vapor equilibration method for stable isotope analysis (δ18O, δ2H) of matrix-bound water: unifying protocols through empirical and mathematical scrutiny
Spatio-temporal soil moisture retrieval at the catchment scale using a dense network of cosmic-ray neutron sensors
Deep desiccation of soils observed by long-term high-resolution measurements on a large inclined lysimeter
A novel analytical approach for the simultaneous measurement of nitrate and dissolved organic carbon in soil water
Exploring the regolith with electrical resistivity tomography in large-scale surveys: electrode spacing-related issues and possibility
Soil dielectric characterization during freeze–thaw transitions using L-band coaxial and soil moisture probes
Hydrological signals in tilt and gravity residuals at Conrad Observatory (Austria)
New measures of deep soil water recharge during the vegetation restoration process in semi-arid regions of northern China
Estimation of subsurface soil moisture from surface soil moisture in cold mountainous areas
Investigating unproductive water losses from irrigated agricultural crops in the humid tropics through analyses of stable isotopes of water
Pacific climate reflected in Waipuna Cave drip water hydrochemistry
Field observations of soil hydrological flow path evolution over 10 millennia
A proposed method for estimating interception from near-surface soil moisture response
Controls of fluorescent tracer retention by soils and sediments
Reflection tomography of time-lapse GPR data for studying dynamic unsaturated flow phenomena
Effects of preferential flow on snowmelt partitioning and groundwater recharge in frozen soils
Spatio-temporal relevance and controls of preferential flow at the landscape scale
Real-time monitoring of nitrate in soils as a key for optimization of agricultural productivity and prevention of groundwater pollution
A soil non-aqueous phase liquid (NAPL) flushing laboratory experiment based on measuring the dielectric properties of soil–organic mixtures via time domain reflectometry (TDR)
The value of satellite remote sensing soil moisture data and the DISPATCH algorithm in irrigation fields
Estimating epikarst water storage by time-lapse surface-to-depth gravity measurements
Inter-laboratory comparison of cryogenic water extraction systems for stable isotope analysis of soil water
Preferential flow systems amended with biogeochemical components: imaging of a two-dimensional study
Imaging groundwater infiltration dynamics in the karst vadose zone with long-term ERT monitoring
Calibrating electromagnetic induction conductivities with time-domain reflectometry measurements
Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors
Field-scale water balance closure in seasonally frozen conditions
Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity
Is annual recharge coefficient a valid concept in arid and semi-arid regions?
Transport and degradation of perchlorate in deep vadose zone: implications from direct observations during bioremediation treatment
Monitoring soil moisture from middle to high elevation in Switzerland: set-up and first results from the SOMOMOUNT network
Experimental study on retardation of a heavy NAPL vapor in partially saturated porous media
Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network
ENSO–cave drip water hydrochemical relationship: a 7-year dataset from south-eastern Australia
Incorporation of globally available datasets into the roving cosmic-ray neutron probe method for estimating field-scale soil water content
Real-time monitoring of nitrate transport in the deep vadose zone under a crop field – implications for groundwater protection
Technical note: Improving the AWAT filter with interpolation schemes for advanced processing of high resolution data
Estimating field-scale root zone soil moisture using the cosmic-ray neutron probe
Ivan Vorobevskii, Thi Thanh Luong, Rico Kronenberg, and Rainer Petzold
Hydrol. Earth Syst. Sci., 28, 3567–3595, https://doi.org/10.5194/hess-28-3567-2024, https://doi.org/10.5194/hess-28-3567-2024, 2024
Short summary
Short summary
An introduced high-resolution soil moisture monitoring framework combines a 1D water balance model, real-time meteorological data, and a national soil database to present point-based operational data with a user-friendly web platform. Its significance lies in the improvement of forest management by making informed, local-scale decisions crucial for mitigating climate change impacts. In the paper, we present a technical description and validation of the framework and showcase its features.
Maik Heistermann, Till Francke, Martin Schrön, and Sascha E. Oswald
Hydrol. Earth Syst. Sci., 28, 989–1000, https://doi.org/10.5194/hess-28-989-2024, https://doi.org/10.5194/hess-28-989-2024, 2024
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) is a non-invasive technique used to obtain estimates of soil water content (SWC) at a horizontal footprint of around 150 m and a vertical penetration depth of up to 30 cm. However, typical CRNS applications require the local calibration of a function which converts neutron counts to SWC. As an alternative, we propose a generalized function as a way to avoid the use of local reference measurements of SWC and hence a major source of uncertainty.
Annelie Ehrhardt, Jannis S. Groh, and Horst H. Gerke
EGUsphere, https://doi.org/10.5194/egusphere-2024-118, https://doi.org/10.5194/egusphere-2024-118, 2024
Short summary
Short summary
Soil water storage (SWS) describes the amount of water in the root zone of plants accessible for crop growth. SWS underlies annual cycles with maximum values in winter and minimum values in summer. For a soil that was transferred from a drier to a more humid climate we found that the maximum peak of SWS occurs earlier every year. This can be explained by an earlier start of the vegetation period. It is a first indication that the ability of soils to store water is affected by climate change.
Rohianuu Moua, Nolwenn Lesparre, Jean-François Girard, Benjamin Belfort, François Lehmann, and Anis Younes
Hydrol. Earth Syst. Sci., 27, 4317–4334, https://doi.org/10.5194/hess-27-4317-2023, https://doi.org/10.5194/hess-27-4317-2023, 2023
Short summary
Short summary
Hydraulic properties of soil include the ability of water to move through the soil and the amount of water that is held in the soil in dry or wet conditions. In this work, we further investigate a protocol used to evaluate such hydraulic properties. We propose a modified version of the protocol, with which we show (i) how the data obtained with this protocol are influenced by the soil hydraulic properties and (ii) how one can use it to estimate these properties.
Barbara Herbstritt, Benjamin Gralher, Stefan Seeger, Michael Rinderer, and Markus Weiler
Hydrol. Earth Syst. Sci., 27, 3701–3718, https://doi.org/10.5194/hess-27-3701-2023, https://doi.org/10.5194/hess-27-3701-2023, 2023
Short summary
Short summary
We present a method to collect water vapor samples into bags in the field without an in-field analyser, followed by isotope analysis in the lab. This new method resolves even fine-scaled natural isotope variations. It combines low-cost and lightweight components for maximum spatial and temporal flexibility regarding environmental setups. Hence, it allows for sampling even in terrains that are rather difficult to access, enabling future extended isotope datasets in soil sciences and ecohydrology.
Daniel Rasche, Jannis Weimar, Martin Schrön, Markus Köhli, Markus Morgner, Andreas Güntner, and Theresa Blume
Hydrol. Earth Syst. Sci., 27, 3059–3082, https://doi.org/10.5194/hess-27-3059-2023, https://doi.org/10.5194/hess-27-3059-2023, 2023
Short summary
Short summary
We introduce passive downhole cosmic-ray neutron sensing (d-CRNS) as an approach for the non-invasive estimation of soil moisture in deeper layers of the unsaturated zone which exceed the observational window of above-ground CRNS applications. Neutron transport simulations are used to derive mathematical descriptions and transfer functions, while experimental measurements in an existing groundwater observation well illustrate the feasibility and applicability of the approach.
Guillaume Blanchy, Lukas Albrecht, Gilberto Bragato, Sarah Garré, Nicholas Jarvis, and John Koestel
Hydrol. Earth Syst. Sci., 27, 2703–2724, https://doi.org/10.5194/hess-27-2703-2023, https://doi.org/10.5194/hess-27-2703-2023, 2023
Short summary
Short summary
We collated the Open Tension-disk Infiltrometer Meta-database (OTIM). We analysed topsoil hydraulic conductivities at supply tensions between 0 and 100 mm of 466 data entries. We found indications of different flow mechanisms at saturation and at tensions >20 mm. Climate factors were better correlated with near-saturated hydraulic conductivities than soil properties. Land use, tillage system, soil compaction and experimenter bias significantly influenced K to a similar degree to soil properties.
Kai-Gao Ouyang, Xiao-Wei Jiang, Gang Mei, Hong-Bin Yan, Ran Niu, Li Wan, and Yijian Zeng
Hydrol. Earth Syst. Sci., 27, 2579–2590, https://doi.org/10.5194/hess-27-2579-2023, https://doi.org/10.5194/hess-27-2579-2023, 2023
Short summary
Short summary
Our knowledge on sources and dynamics of rock moisture is limited. By using frequency domain reflectometry (FDR), we monitored rock moisture in a cave. The results of an explainable deep learning model reveal that the direct source of rock moisture responsible for weathering in the studied cave is vapour, not infiltrating precipitation. A physics-informed deep learning model, which uses variables controlling vapor condensation as model inputs, leads to accurate rock water content predictions.
Oliver Kost, Saúl González-Lemos, Laura Rodríguez-Rodríguez, Jakub Sliwinski, Laura Endres, Negar Haghipour, and Heather Stoll
Hydrol. Earth Syst. Sci., 27, 2227–2255, https://doi.org/10.5194/hess-27-2227-2023, https://doi.org/10.5194/hess-27-2227-2023, 2023
Short summary
Short summary
Cave monitoring studies including cave drip water are unique opportunities to sample water which has percolated through the soil and rock. The change in drip water chemistry is resolved over the course of 16 months, inferring seasonal and hydrological variations in soil and karst processes at the water–air and water–rock interface. Such data sets improve the understanding of hydrological and hydrochemical processes and ultimately advance the interpretation of geochemical stalagmite records.
Giovanna Dragonetti, Mohammad Farzamian, Angelo Basile, Fernando Monteiro Santos, and Antonio Coppola
Hydrol. Earth Syst. Sci., 26, 5119–5136, https://doi.org/10.5194/hess-26-5119-2022, https://doi.org/10.5194/hess-26-5119-2022, 2022
Short summary
Short summary
Soil hydraulic and hydrodispersive properties are necessary for modeling water and solute fluxes in agricultural and environmental systems. Despite the major efforts in developing methods (e.g., lab-based, pedotransfer functions), their characterization at applicative scales remains an imperative requirement. Thus, this paper proposes a noninvasive in situ method integrating electromagnetic induction and hydrological modeling to estimate soil hydraulic and transport properties at the plot scale.
Daniel Rasche, Markus Köhli, Martin Schrön, Theresa Blume, and Andreas Güntner
Hydrol. Earth Syst. Sci., 25, 6547–6566, https://doi.org/10.5194/hess-25-6547-2021, https://doi.org/10.5194/hess-25-6547-2021, 2021
Short summary
Short summary
Cosmic-ray neutron sensing provides areal average soil moisture measurements. We investigated how distinct differences in spatial soil moisture patterns influence the soil moisture estimates and present two approaches to improve the estimate of soil moisture close to the instrument by reducing the influence of soil moisture further afield. Additionally, we show that the heterogeneity of soil moisture can be assessed based on the relationship of different neutron energies.
Hongxiu Wang, Jingjing Jin, Buli Cui, Bingcheng Si, Xiaojun Ma, and Mingyi Wen
Hydrol. Earth Syst. Sci., 25, 5399–5413, https://doi.org/10.5194/hess-25-5399-2021, https://doi.org/10.5194/hess-25-5399-2021, 2021
Short summary
Short summary
Evaporation led to progressively more heavy-isotope-enriched bulk soil water (BW) following the precipitation/irrigation of heavy-isotope-depleted new water but causes progressively more heavy-isotope-depleted BW following irrigation of heavy-isotope-enriched new water. The results indicated that δ2H and δ18O in evaporating water (EW) were similar to new water and differed from BW. However, the evaporative water loss calculated from BW did not differ significantly from that of EW.
Benjamin Gralher, Barbara Herbstritt, and Markus Weiler
Hydrol. Earth Syst. Sci., 25, 5219–5235, https://doi.org/10.5194/hess-25-5219-2021, https://doi.org/10.5194/hess-25-5219-2021, 2021
Short summary
Short summary
We scrutinized the quickest currently available method for stable isotope analysis of matrix-bound water. Simulating common procedures, we demonstrated the limits of certain materials currently used and identified a reliable and cost-efficient alternative. Further, we calculated the optimum proportions of important protocol aspects critical for precise and accurate analyses. Our unifying protocol suggestions increase data quality and comparability as well as the method's general applicability.
Maik Heistermann, Till Francke, Martin Schrön, and Sascha E. Oswald
Hydrol. Earth Syst. Sci., 25, 4807–4824, https://doi.org/10.5194/hess-25-4807-2021, https://doi.org/10.5194/hess-25-4807-2021, 2021
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) is a powerful technique for retrieving representative estimates of soil moisture in footprints extending over hectometres in the horizontal and decimetres in the vertical. This study, however, demonstrates the potential of CRNS to obtain spatio-temporal patterns of soil moisture beyond isolated footprints. To that end, we analyse data from a unique observational campaign that featured a dense network of more than 20 neutron detectors in an area of just 1 km2.
Markus Merk, Nadine Goeppert, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 25, 3519–3538, https://doi.org/10.5194/hess-25-3519-2021, https://doi.org/10.5194/hess-25-3519-2021, 2021
Short summary
Short summary
Soil moisture levels have decreased significantly over the past 2 decades. This decrease is not uniformly distributed over the observation period. The largest changes occur at tipping points during years of extreme drought, after which soil moisture levels reach significantly different alternate stable states. Not only the overall trend in soil moisture is affected, but also the seasonal dynamics.
Elad Yeshno, Ofer Dahan, Shoshana Bernstain, and Shlomi Arnon
Hydrol. Earth Syst. Sci., 25, 2159–2168, https://doi.org/10.5194/hess-25-2159-2021, https://doi.org/10.5194/hess-25-2159-2021, 2021
Short summary
Short summary
In this research, we present a novel approach, enabling the measurement of nitrate concentrations in natural soil porewater containing natural soil dissolved organic carbon. This method can be used as the basis onto which an affordable and miniaturized nitrate monitoring sensor for soils can be developed. This sensor can play a significant role in reducing nitrate pollution in water resources, optimizing fertilizers application during agricultural activity and decreasing food production costs.
Laurent Gourdol, Rémi Clément, Jérôme Juilleret, Laurent Pfister, and Christophe Hissler
Hydrol. Earth Syst. Sci., 25, 1785–1812, https://doi.org/10.5194/hess-25-1785-2021, https://doi.org/10.5194/hess-25-1785-2021, 2021
Short summary
Short summary
Electrical resistivity tomography (ERT) is a remarkable tool for characterizing the regolith, but its use over large areas remains cumbersome due to the requirement of small electrode spacing (ES). In this study we document the issues of using oversized ESs and propose a new approach to overcome this limitation. We demonstrate that our protocol significantly improves the accuracy of ERT profiles using large ES and offers a cost-effective means for carrying out large-scale surveys.
Alex Mavrovic, Renato Pardo Lara, Aaron Berg, François Demontoux, Alain Royer, and Alexandre Roy
Hydrol. Earth Syst. Sci., 25, 1117–1131, https://doi.org/10.5194/hess-25-1117-2021, https://doi.org/10.5194/hess-25-1117-2021, 2021
Short summary
Short summary
This paper presents a new probe that measures soil microwave permittivity in the frequency range of satellite L-band sensors. The probe capacities will allow for validation and calibration of the models used to estimate landscape physical properties from raw microwave satellite datasets. Our results show important discrepancies between model estimates and instrument measurements that will need to be addressed.
Bruno Meurers, Gábor Papp, Hannu Ruotsalainen, Judit Benedek, and Roman Leonhardt
Hydrol. Earth Syst. Sci., 25, 217–236, https://doi.org/10.5194/hess-25-217-2021, https://doi.org/10.5194/hess-25-217-2021, 2021
Short summary
Short summary
Gravity and tilt time series acquired at Conrad Observatory (Austria) reflect gravity and deformation associated with short- and long-term environmental processes, revealing a complex water transport process after heavy rain and rapid snowmelt. Gravity residuals are sensitive to the Newtonian effect of water mass transport. Tilt residual anomalies capture strain–tilt coupling effects due to surface or subsurface deformation from precipitation or pressure changes in the adjacent fracture system.
Yiben Cheng, Xinle Li, Yunqi Wang, Hongbin Zhan, Wenbin Yang, and Qunou Jiang
Hydrol. Earth Syst. Sci., 24, 5875–5890, https://doi.org/10.5194/hess-24-5875-2020, https://doi.org/10.5194/hess-24-5875-2020, 2020
Short summary
Short summary
The Three North Forest Program has produced a vast area of lined forest in semi-arid regions, which consumes a large amount of water resources. This study uses a newly designed lysimeter to measure water distribution without destroying the in situ vegetation soil structure. It addresses the shortcomings of a traditional lysimeter, in terms of changing the in situ soil structure and destroying the vegetation root system, and the shortcomings of high costs and inconvenient installation.
Jie Tian, Zhibo Han, Heye Reemt Bogena, Johan Alexander Huisman, Carsten Montzka, Baoqing Zhang, and Chansheng He
Hydrol. Earth Syst. Sci., 24, 4659–4674, https://doi.org/10.5194/hess-24-4659-2020, https://doi.org/10.5194/hess-24-4659-2020, 2020
Short summary
Short summary
Large-scale profile soil moisture (SM) is important for water resource management, but its estimation is a challenge. Thus, based on in situ SM observations in a cold mountain, a strong relationship between the surface SM and subsurface SM is found. Both the subsurface SM of 10–30 cm and the profile SM of 0–70 cm can be estimated from the surface SM of 0–10 cm accurately. By combing with the satellite product, we improve the large-scale profile SM estimation in the cold mountains finally.
Amani Mahindawansha, Christoph Külls, Philipp Kraft, and Lutz Breuer
Hydrol. Earth Syst. Sci., 24, 3627–3642, https://doi.org/10.5194/hess-24-3627-2020, https://doi.org/10.5194/hess-24-3627-2020, 2020
Short summary
Short summary
Stable isotopes of soil water are an effective tool to reveal soil hydrological processes in irrigated agricultural fields. Flow mechanisms and isotopic patterns of soil water in the soil matrix differ, depending on the crop and irrigation practices. Isotope data supported the fact that unproductive water losses via evaporation can be reduced by introducing dry seasonal crops to the crop rotation system.
Cinthya Nava-Fernandez, Adam Hartland, Fernando Gázquez, Ola Kwiecien, Norbert Marwan, Bethany Fox, John Hellstrom, Andrew Pearson, Brittany Ward, Amanda French, David A. Hodell, Adrian Immenhauser, and Sebastian F. M. Breitenbach
Hydrol. Earth Syst. Sci., 24, 3361–3380, https://doi.org/10.5194/hess-24-3361-2020, https://doi.org/10.5194/hess-24-3361-2020, 2020
Short summary
Short summary
Speleothems are powerful archives of past climate for understanding modern local hydrology and its relation to regional circulation patterns. We use a 3-year monitoring dataset to test the sensitivity of Waipuna Cave to seasonal changes and El Niño–Southern Oscillation (ENSO) dynamics. Drip water data suggest a fast response to rainfall events; its elemental composition reflects a seasonal cycle and ENSO variability. Waipuna Cave speleothems have a high potential for past ENSO reconstructions.
Anne Hartmann, Ekaterina Semenova, Markus Weiler, and Theresa Blume
Hydrol. Earth Syst. Sci., 24, 3271–3288, https://doi.org/10.5194/hess-24-3271-2020, https://doi.org/10.5194/hess-24-3271-2020, 2020
Short summary
Short summary
Our field observation-based examination of flow path evolution, soil formation, and vegetation succession across 10 millennia shows how water flow paths and subsurface water storage are linked to the organization of evolving landscapes.
The increase found in water storage and preferential flow paths with increasing soil age shows the effect of the complex interaction of vegetation and soil development on flow paths, water balance, and runoff formation during landscape evolution.
Subodh Acharya, Daniel McLaughlin, David Kaplan, and Matthew J. Cohen
Hydrol. Earth Syst. Sci., 24, 1859–1870, https://doi.org/10.5194/hess-24-1859-2020, https://doi.org/10.5194/hess-24-1859-2020, 2020
Short summary
Short summary
Interception is the storage and subsequent evaporation of rain by vegetation and surface litter. Quantifying interception is critical for understanding the water balance, but it can be difficult and costly to measure. We developed an approach to estimate interception using automated soil moisture measurements during rainfall events. Results suggest that interception can be estimated using soil moisture data, leading to potential cost savings and logistical advantages over conventional methods.
Marcus Bork, Jens Lange, Markus Graf-Rosenfellner, and Friederike Lang
Hydrol. Earth Syst. Sci., 24, 977–989, https://doi.org/10.5194/hess-24-977-2020, https://doi.org/10.5194/hess-24-977-2020, 2020
Short summary
Short summary
Fluorescent tracers such as uranine and sulforhodamine B are useful tools to gain knowledge about water and solute fluxes in aquatic and terrestrial ecosystems. In this study we systematically investigated the influence of important soil properties (pH, organic carbon content and texture) on tracer adsorption in soils and sediments. These properties also determine whether the tracers in the respective soil behave conservatively or non-conservatively.
Adam R. Mangel, Stephen M. J. Moysey, and John Bradford
Hydrol. Earth Syst. Sci., 24, 159–167, https://doi.org/10.5194/hess-24-159-2020, https://doi.org/10.5194/hess-24-159-2020, 2020
Short summary
Short summary
Water flows through soils in an incredibly complex network of pathways. Understanding these pathways is critical to sustainable use of water resources. Ground-penetrating radar (GPR) can image water in near-surface soils the same way an X-ray is used to image the human body. Utilizing innovative ways of collecting and processing the GPR data, we can image complex water flow in space and through time, which allows for the continued development of our ideas and models of subsurface water flow.
Aaron A. Mohammed, Igor Pavlovskii, Edwin E. Cey, and Masaki Hayashi
Hydrol. Earth Syst. Sci., 23, 5017–5031, https://doi.org/10.5194/hess-23-5017-2019, https://doi.org/10.5194/hess-23-5017-2019, 2019
Short summary
Short summary
In cold regions, the permeability of the frozen ground is an important factor influencing a watershed's response to snowmelt. This study highlights the effects of preferential flow in frozen soils on snowmelt redistribution and groundwater recharge in seasonally frozen landscapes.
Dominic Demand, Theresa Blume, and Markus Weiler
Hydrol. Earth Syst. Sci., 23, 4869–4889, https://doi.org/10.5194/hess-23-4869-2019, https://doi.org/10.5194/hess-23-4869-2019, 2019
Short summary
Short summary
This study presents an analysis of 135 soil moisture profiles for identification of the spatial and temporal preferential flow occurrence in a complex landscape. Especially dry conditions and high rainfall intensities were found to increase preferential flow occurrence in soils. This results in a seasonal pattern of preferential flow with a higher occurrence in summer. During this time grasslands showed increased flow velocities, whereas forest sites exhibited a higher amount of bypass flow.
Elad Yeshno, Shlomi Arnon, and Ofer Dahan
Hydrol. Earth Syst. Sci., 23, 3997–4010, https://doi.org/10.5194/hess-23-3997-2019, https://doi.org/10.5194/hess-23-3997-2019, 2019
Short summary
Short summary
Lack of adequate instrumentation for monitoring nutrient availability in agricultural soils leads in most cases to over-application of fertilizers, often resulting in groundwater pollution. This research presents a novel approach for real-time, in situ monitoring of nitrate in soils using absorption spectroscopy techniques while preventing interference from dissolved organic carbon. Column experiments with this system resulted in accurate nitrate measurements in three different soil types.
Alessandro Comegna, Antonio Coppola, Giovanna Dragonetti, and Angelo Sommella
Hydrol. Earth Syst. Sci., 23, 3593–3602, https://doi.org/10.5194/hess-23-3593-2019, https://doi.org/10.5194/hess-23-3593-2019, 2019
Short summary
Short summary
We carried out a series of laboratory-controlled experiments in order to simulate different scenarios of practical interest aiming to analyze, from a dielectric point of view, the influence of different washing solutions on non-aqueous phase liquid (NAPL) removal. Furthermore, on the basis of the results obtained, we validated a dielectric mixing model for predicting the volumetric amounts of NAPL (θNAPL) within the contaminated soil as the decontamination process progressed.
Mireia Fontanet, Daniel Fernàndez-Garcia, and Francesc Ferrer
Hydrol. Earth Syst. Sci., 22, 5889–5900, https://doi.org/10.5194/hess-22-5889-2018, https://doi.org/10.5194/hess-22-5889-2018, 2018
Short summary
Short summary
One of the main objectives of remote sensing methodology is to downscale soil moisture to improve irrigation management. The DISPATCH algorithm is able to measure soil moisture at 1 km resolution using SMOS and MODIS data. In this work DISPATCH has been evaluated with soil moisture sensors, under heterogeneous conditions where local irrigation is applied. Results show that DISPATCH is not sensitive when local irrigation is applied even at low resolution.
Cédric Champollion, Sabrina Deville, Jean Chéry, Erik Doerflinger, Nicolas Le Moigne, Roger Bayer, Philippe Vernant, and Naomi Mazzilli
Hydrol. Earth Syst. Sci., 22, 3825–3839, https://doi.org/10.5194/hess-22-3825-2018, https://doi.org/10.5194/hess-22-3825-2018, 2018
Short summary
Short summary
Gravity monitoring at the surface and in situ (in caves) has been conducted in a karst hydro-system in the south of France (Larzac plateau). Subsurface water storage is evidenced with a spatial variability probably associated with lithology differences and confirmed by MRS measurements. Gravity allows transient water storage to be estimated on the seasonal scale.
Natalie Orlowski, Lutz Breuer, Nicolas Angeli, Pascal Boeckx, Christophe Brumbt, Craig S. Cook, Maren Dubbert, Jens Dyckmans, Barbora Gallagher, Benjamin Gralher, Barbara Herbstritt, Pedro Hervé-Fernández, Christophe Hissler, Paul Koeniger, Arnaud Legout, Chandelle Joan Macdonald, Carlos Oyarzún, Regine Redelstein, Christof Seidler, Rolf Siegwolf, Christine Stumpp, Simon Thomsen, Markus Weiler, Christiane Werner, and Jeffrey J. McDonnell
Hydrol. Earth Syst. Sci., 22, 3619–3637, https://doi.org/10.5194/hess-22-3619-2018, https://doi.org/10.5194/hess-22-3619-2018, 2018
Short summary
Short summary
To extract water from soils for isotopic analysis, cryogenic water extraction is the most widely used removal technique. This work presents results from a worldwide laboratory intercomparison test of cryogenic extraction systems. Our results showed large differences in retrieved isotopic signatures among participating laboratories linked to interactions between soil type and properties, system setup, extraction efficiency, extraction system leaks, and each lab’s internal accuracy.
Ashley R. Pales, Biting Li, Heather M. Clifford, Shyla Kupis, Nimisha Edayilam, Dawn Montgomery, Wei-zhen Liang, Mine Dogan, Nishanth Tharayil, Nicole Martinez, Stephen Moysey, Brian Powell, and Christophe J. G. Darnault
Hydrol. Earth Syst. Sci., 22, 2487–2509, https://doi.org/10.5194/hess-22-2487-2018, https://doi.org/10.5194/hess-22-2487-2018, 2018
Arnaud Watlet, Olivier Kaufmann, Antoine Triantafyllou, Amaël Poulain, Jonathan E. Chambers, Philip I. Meldrum, Paul B. Wilkinson, Vincent Hallet, Yves Quinif, Michel Van Ruymbeke, and Michel Van Camp
Hydrol. Earth Syst. Sci., 22, 1563–1592, https://doi.org/10.5194/hess-22-1563-2018, https://doi.org/10.5194/hess-22-1563-2018, 2018
Short summary
Short summary
Understanding water infiltration in karst regions is crucial as the aquifers they host provide drinkable water for a quarter of the world's population. We present a non-invasive tool to image hydrological processes in karst systems. At our field site, the injection of electrical current in the ground, repeated daily over a 3-year period, allowed imaging changes in the groundwater content. We show that specific geological layers control seasonal to rainfall-triggered water infiltration dynamics.
Giovanna Dragonetti, Alessandro Comegna, Ali Ajeel, Gian Piero Deidda, Nicola Lamaddalena, Giuseppe Rodriguez, Giulio Vignoli, and Antonio Coppola
Hydrol. Earth Syst. Sci., 22, 1509–1523, https://doi.org/10.5194/hess-22-1509-2018, https://doi.org/10.5194/hess-22-1509-2018, 2018
Short summary
Short summary
The paper aims to infer the bulk electrical conductivity distribution in the root zone from EMI readings. TDR measurements were used as ground-truth data to evaluate the goodness of the estimations by EMI inversion. The approach is based on the mean and standard deviation of the EMI and TDR series. It looks for the physical reasons for the differences between EMI- and TDR-based electrical conductivity and provides a correction of the bias based on the statistical sources of the discrepancies.
David McJannet, Aaron Hawdon, Brett Baker, Luigi Renzullo, and Ross Searle
Hydrol. Earth Syst. Sci., 21, 6049–6067, https://doi.org/10.5194/hess-21-6049-2017, https://doi.org/10.5194/hess-21-6049-2017, 2017
Short summary
Short summary
Satellite and broad-scale model estimates of soil moisture have improved in resolution. However, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. We use a mobile soil moisture monitoring platform, known as the
rover, to derive soil moisture at 9 km and 1 km resolution. We describe methods to calculate soil moisture and present results from multiple surveys. The products produced are well suited to validation studies.
Xicai Pan, Warren Helgason, Andrew Ireson, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 5401–5413, https://doi.org/10.5194/hess-21-5401-2017, https://doi.org/10.5194/hess-21-5401-2017, 2017
Short summary
Short summary
In this paper we present a case study from a heterogeneous pasture site in the Canadian prairies, where we have quantified the various components of the water balance on the field scale, and critically examine some of the simplifying assumptions which are often invoked when applying water budget approaches in applied hydrology. We highlight challenges caused by lateral fluxes of blowing snow and ambiguous partitioning of snow melt water into runoff and infiltration.
Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, https://doi.org/10.5194/hess-21-5009-2017, 2017
Short summary
Short summary
A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.
Yiben Cheng, Hongbin Zhan, Wenbin Yang, Hongzhong Dang, and Wei Li
Hydrol. Earth Syst. Sci., 21, 5031–5042, https://doi.org/10.5194/hess-21-5031-2017, https://doi.org/10.5194/hess-21-5031-2017, 2017
Short summary
Short summary
This study uses a newly designed lysimeter to study three consecutive years (2013–2015) of deep soil recharge (DSR) underneath bare sand land on the eastern margin of Mu Us Sandy Land in the Ordos Basin of China. The objective is to identify the characteristics of the DSR distribution and the factors affecting the DSR distribution. Specifically, we would like to examine if the commonly used recharge coefficient concept can be applied for arid and semi-arid regions.
Ofer Dahan, Idan Katz, Lior Avishai, and Zeev Ronen
Hydrol. Earth Syst. Sci., 21, 4011–4020, https://doi.org/10.5194/hess-21-4011-2017, https://doi.org/10.5194/hess-21-4011-2017, 2017
Short summary
Short summary
In situ bioremediation of a perchlorate-contaminated vadose zone was conducted through infiltration of electron-donor-enriched water. A vadose zone monitoring system (VMS) provided real-time tracking of the hydraulic and chemical conditions across the unsaturated zone. Variations in concentration profiles of perchlorate, chloride, DOC and bromide in the vadose zone pore water showed limited migration capacity of biologically consumable carbon and significant mobilization of perchlorate.
Cécile Pellet and Christian Hauck
Hydrol. Earth Syst. Sci., 21, 3199–3220, https://doi.org/10.5194/hess-21-3199-2017, https://doi.org/10.5194/hess-21-3199-2017, 2017
Short summary
Short summary
This paper presents a detailed description of the new Swiss soil moisture monitoring network SOMOMOUNT, which comprises six stations distributed along an elevation gradient ranging from 1205 to 3410 m. The liquid soil moisture (LSM) data collected during the first 3 years are discussed with regard to their soil type and climate dependency as well as their altitudinal distribution. The elevation dependency of the LSM was found to be non-linear with distinct dynamics at high and low elevation.
Simon Matthias Kleinknecht, Holger Class, and Jürgen Braun
Hydrol. Earth Syst. Sci., 21, 1381–1396, https://doi.org/10.5194/hess-21-1381-2017, https://doi.org/10.5194/hess-21-1381-2017, 2017
Short summary
Short summary
Retardation of migrating contaminant vapors in the subsurface may mitigate groundwater contamination or vapor intrusion into buildings. An experimental investigation was conducted to quantify the retardation of carbon disulfide (CS2) vapor in moist porous media based on the analysis of concentration breakthrough curves. Findings linked retardation to types of porous media and water saturation. Moreover, the first evidence of biodegradation of the CS2 vapor was found in the column experiments.
Edoardo Martini, Ulrike Werban, Steffen Zacharias, Marco Pohle, Peter Dietrich, and Ute Wollschläger
Hydrol. Earth Syst. Sci., 21, 495–513, https://doi.org/10.5194/hess-21-495-2017, https://doi.org/10.5194/hess-21-495-2017, 2017
Short summary
Short summary
With a process-based interpretation of electromagnetic induction measurements, we discussed the potential and limitations of such a method for soil moisture mapping. Results will help clarify the complex and time-varying effect of stable soil properties and dynamic state variables on the physical parameters measured, with implications for future studies. We highlighted the importance of time-series data and the need for a multidisciplinary approach for proper interpretation.
Carol V. Tadros, Pauline C. Treble, Andy Baker, Ian Fairchild, Stuart Hankin, Regina Roach, Monika Markowska, and Janece McDonald
Hydrol. Earth Syst. Sci., 20, 4625–4640, https://doi.org/10.5194/hess-20-4625-2016, https://doi.org/10.5194/hess-20-4625-2016, 2016
Short summary
Short summary
We investigated the potential use of trace element and stable oxygen-isotope variations in cave drip water as palaeorainfall proxies in an Australian alpine karst site. Using 7 years of cave monitoring data, we constrained the hydrological processes impacting the drip-water composition and identified a robust ENSO–drip water hydrochemical relationship. These findings are fundamental for reconstructing past ENSO variability from speleothems (cave deposits) regionally and globally.
William Alexander Avery, Catherine Finkenbiner, Trenton E. Franz, Tiejun Wang, Anthony L. Nguy-Robertson, Andrew Suyker, Timothy Arkebauer, and Francisco Muñoz-Arriola
Hydrol. Earth Syst. Sci., 20, 3859–3872, https://doi.org/10.5194/hess-20-3859-2016, https://doi.org/10.5194/hess-20-3859-2016, 2016
Short summary
Short summary
Here we present a strategy to use globally available datasets in the calibration function used to convert observed moderated neutron counts into volumetric soil water content. While local sampling protocols are well documented for fixed probes, the use of roving probes presents new calibration challenges. With over 200 fixed probes and 10 roving probes in use globally, we anticipate this paper will serve as a keystone for the growing cosmic-ray neutron probe and hydrologic community.
Tuvia Turkeltaub, Daniel Kurtzman, and Ofer Dahan
Hydrol. Earth Syst. Sci., 20, 3099–3108, https://doi.org/10.5194/hess-20-3099-2016, https://doi.org/10.5194/hess-20-3099-2016, 2016
Short summary
Short summary
Efficient groundwater protection from pollution originating in agriculture requires effective monitoring means capable of tacking pollution processes in the vadose zone, long before groundwater pollution turns into an unavoidable fact. In this study, a vadose zone monitoring system that was installed under a crop field fertilized by dairy slurry enabled real-time tracking of nitrate plum migration down the vadose zone from the land surface to the water table at 18m depth.
Andre Peters, Thomas Nehls, and Gerd Wessolek
Hydrol. Earth Syst. Sci., 20, 2309–2315, https://doi.org/10.5194/hess-20-2309-2016, https://doi.org/10.5194/hess-20-2309-2016, 2016
Short summary
Short summary
The AWAT (Adaptive Window and Adaptive Threshold) filter routine for high-resolution lysimeter data is improved. The threshold scheme with original step interpolation yields unrealistic fluxes for high temporal resolution. Improvement applies linear and spline interpolation schemes so that fluxes in high temporal resolution are automatically calculated. The spline scheme allows continuous differentiability of filtered data so that any output resolution for the fluxes is sound.
Amber M. Peterson, Warren D. Helgason, and Andrew M. Ireson
Hydrol. Earth Syst. Sci., 20, 1373–1385, https://doi.org/10.5194/hess-20-1373-2016, https://doi.org/10.5194/hess-20-1373-2016, 2016
Short summary
Short summary
Remote sensing techniques can provide useful large-scale estimates of soil moisture. However, these methods often only sense near-surface soil moisture, whereas many applications require estimates of the entire root zone. In this study we propose and test methods to "depth-scale" the shallow soil moisture measurements obtained using the cosmic-ray neutron probe to represent the entire root zone, thereby improving the applicability of this measurement approach.
Cited articles
Abbaszadeh, P., Moradkhani, H., and Zhan, X.: Downscaling SMAP Radiometer Soil Moisture Over the CONUS Using an Ensemble Learning Method, Water Resour.
Res., 55, 324–344, https://doi.org/10.1029/2018WR023354, 2019. a
Aberer, D.: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global – without anomalies and without ISMN flags, Zenodo [data set], https://doi.org/10.5281/zenodo.4288919, 2020a. a
Aberer, D.: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global – without Anomalies and ISMN flagged, Zenodo [data set], https://doi.org/10.5281/zenodo.4288921, 2020b. a
Aberer, D.: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global – Anomalies and no ISMN flags, Zenodo [data set], https://doi.org/10.5281/zenodo.4288915, 2020c. a
Aberer, D.: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global – Anomalies and ISMN flagged, Zenodo [data set], https://doi.org/10.5281/zenodo.4288913, 2020d. a
Aberer, D., Xaver, A., and Preimesberger, W.: TUW-GEO/flagit, GitHub [code], https://github.com/TUW-GEO/flagit, last access: 8 November 2021. a
Adla, S., Rai, N. K., Karumanchi, S. H., Tripathi, S., Disse, M., and Pande,
S.: Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive
and Very Low-Cost Resistive Soil Moisture Sensors, Sensors, 20, 363,
https://doi.org/10.3390/s20020363, 2020. a
Albergel, C., Calvet, J.-C., de Rosnay, P., Balsamo, G., Wagner, W., Hasenauer, S., Naeimi, V., Martin, E., Bazile, E., Bouyssel, F., and Mahfouf, J.-F.: Cross-evaluation of modelled and remotely sensed surface soil moisture with in situ data in southwestern France, Hydrol. Earth Syst. Sci., 14, 2177–2191, https://doi.org/10.5194/hess-14-2177-2010, 2010. a, b
Albergel, C., Balsamo, G., de Rosnay, P., Muñoz Sabater, J., and Boussetta, S.: A bare ground evaporation revision in the ECMWF land-surface scheme: evaluation of its impact using ground soil moisture and satellite microwave data, Hydrol. Earth Syst. Sci., 16, 3607–3620,
https://doi.org/10.5194/hess-16-3607-2012, 2012a. a, b
Albergel, C., de Rosnay, P., Balsamo, G., Isaksen, L., and Muñoz-Sabater,
J.: Soil Moisture Analyses at ECMWF: Evaluation Using Global Ground-Based In
Situ Observations, J. Hydrometeorol., 13, 1442–1460, https://doi.org/10.1175/JHM-D-11-0107.1, 2012b. a
Albergel, C., de Rosnay, P., Gruhier, C., Muñoz-Sabater, J., Hasenauer,
S., Isaksen, L., Kerr, Y., and Wagner, W.: Evaluation of remotely sensed and
modelled soil moisture products using global ground-based in situ observations, Remote Sens. Environ., 118, 215–226, https://doi.org/10.1016/j.rse.2011.11.017, 2012c. a, b, c
Albergel, C., Dorigo, W., Balsamo, G., Muñoz-Sabater, J., de Rosnay,
P., Isaksen, L., Brocca, L., de Jeu, R., and Wagner, W.: Monitoring multi-decadal satellite earth observation of soil moisture products through
land surface reanalyses, Remote Sens. Environ., 138, 77–89,
https://doi.org/10.1016/j.rse.2013.07.009, 2013a. a
Albergel, C., Dorigo, W., Reichle, R. H., Balsamo, G., de Rosnay, P.,
Muñoz-Sabater, J., Isaksen, L., de Jeu, R., and Wagner, W.: Skill and
Global Trend Analysis of Soil Moisture from Reanalyses and Microwave Remote
Sensing, J. Hydrometeorol., 14, 1259–1277, https://doi.org/10.1175/JHM-D-12-0161.1, 2013b. a, b, c, d, e, f, g
Albergel, C., Dutra, E., Muñoz-Sabater, J., Haiden, T., Balsamo, G.,
Beljaars, A., Isaksen, L., de Rosnay, P., Sandu, I., and Wedi, N.: Soil
temperature at ECMWF: An assessment using ground-based observations, J. Geophys. Res.-Atmos., 120, 1361–1373, https://doi.org/10.1002/2014JD022505, 2015. a, b, c, d
Albergel, C., Munier, S., Bocher, A., Bonan, B., Zheng, Y., Draper, C., Leroux, D., and Calvet, J.-C.: LDAS-Monde Sequential Assimilation of Satellite Derived Observations Applied to the Contiguous US: An ERA-5 Driven Reanalysis of the Land Surface Variables, Remote Sens., 10, 1627,
https://doi.org/10.3390/rs10101627, 2018. a
Albergel, C., Zheng, Y., Bonan, B., Dutra, E., Rodríguez-Fernández, N., Munier, S., Draper, C., de Rosnay, P., Muñoz Sabater, J., Balsamo, G., Fairbairn, D., Meurey, C., and Calvet, J.-C.: Data assimilation for
continuous global assessment of severe conditions over terrestrial surfaces,
Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, 2020. a, b
Alday, J. G., Camarero, J. J., Revilla, J., and Dios, V. R.: Similar diurnal,
seasonal and annual rhythms in radial root expansion across two coexisting
Mediterranean oak species, Tree Physiol., 40, 956–968, 2020. a
Alemohammad, S. H., Kolassa, J., Prigent, C., Aires, F., and Gentine, P.:
Global downscaling of remotely sensed soil moisture using neural networks,
Hydrol. Earth Syst. Sci., 22, 5341–5356, https://doi.org/10.5194/hess-22-5341-2018, 2018. a, b
Almendra-Martín, L., Martínez-Fernández, J., Piles, M., and
González-Zamora, Á.: Comparison of gap-filling techniques applied
to the CCI soil moisture database in Southern Europe, Remote Sens. Environ., 258, 112377, https://doi.org/10.1016/j.rse.2021.112377, 2021. a
Al-Yaari, A., Wigneron, J., Kerr, Y., de Jeu, R., Rodriguez-Fernandez, N.,
van der Schalie, R., Al Bitar, A., Mialon, A., Richaume, P., Dolman, A.,
and Ducharne, A.: Testing regression equations to derive long-term global
soil moisture datasets from passive microwave observations, Remote Sens.
Environ., 180, 453–464, https://doi.org/10.1016/j.rse.2015.11.022, 2016. a
Al-Yaari, A., Wigneron, J.-P., Kerr, Y., Rodriguez-Fernandez, N., O'Neill, P., Jackson, T., De Lannoy, G., Al Bitar, A., Mialon, A., Richaume, P.,
Walker, J., Mahmoodi, A., and Yueh, S.: Evaluating soil moisture retrievals
from ESA's SMOS and NASA's SMAP brightness temperature datasets, Remote
Sens. Environ., 193, 257–273, https://doi.org/10.1016/j.rse.2017.03.010, 2017. a, b
Al-Yaari, A., Dayau, S., Chipeaux, C., Aluome, C., Kruszewski, A., Loustau, D., and Wigneron, J.-P.: The AQUI Soil Moisture Network for Satellite Microwave Remote Sensing Validation in South-Western France, Remote Sens., 10, 1105, https://doi.org/10.3390/rs10111839, 2018a. a
Al-Yaari, A., Dayau, S., Chipeaux, C., Aluome, C., Kruszewski, A., Loustau, D., and Wigneron, J.-P.: The AQUI Soil Moisture Network for Satellite Microwave Remote Sensing Validation in South-Western France, Remote Sens., 10, 1839, https://doi.org/10.3390/rs10111839, 2018b. a, b, c
Al-Yaari, A., Ducharne, A., Cheruy, F., Crow, W. T., and Wigneron, J.-P.:
Satellite-based soil moisture provides missing link between summertime
precipitation and surface temperature biases in CMIP5 simulations over
conterminous United States, Scient. Rep., 9, 1657, https://doi.org/10.1038/s41598-018-38309-5, 2019a. a, b
Al-Yaari, A., Wigneron, J.-P., Dorigo, W., Colliander, A., Pellarin, T., Hahn, S., Mialon, A., Richaume, P., Fernandez-Moran, R., Fan, L., Kerr, Y., and Lannoy, G. D.: Assessment and inter-comparison of recently
developed/reprocessed microwave satellite soil moisture products using ISMN
ground-based measurements, Remote Sens. Environ., 224, 289–303,
https://doi.org/10.1016/j.rse.2019.02.008, 2019b. a, b, c, d, e
An, R., Zhang, L., Wang, Z., Quaye-Ballard, J. A., You, J., Shen, X., Gao, W., Huang, L., Zhao, Y., and Ke, Z.: Validation of the ESA CCI soil moisture
product in China, Int. J. Appl. Earth Obs. Geoinf., 48, 28–36, https://doi.org/10.1016/j.jag.2015.09.009, 2016. a
Ángel González-Zamora, Sánchez, N., Martínez-Fernández, J., and Wagner, W.: Root-zone plant available water estimation using the SMOS-derived soil water index, Adv. Water Resour., 96, 339–353, https://doi.org/10.1016/j.advwatres.2016.08.001, 2016. a
Angevine, W. M., Bazile, E., Legain, D., and Pino, D.: Land surface spinup for episodic modeling, Atmos. Chem. Phys., 14, 8165–8172,
https://doi.org/10.5194/acp-14-8165-2014, 2014. a, b, c, d
Anoop, S., Maurya, D. K., Rao, P. V. N., and Sekhar, M.: Validation and
Comparison of LPRM Retrieved Soil Moisture Using AMSR2 Brightness Temperature
at Two Spatial Resolutions in the Indian Region, IEEE Geosci. Remote Sens. Lett., 14, 1561–1564, https://doi.org/10.1109/LGRS.2017.2722542, 2017. a, b
Ardö, J.: A 10-Year Dataset of Basic Meteorology and Soil Properties in
Central Sudan, Dataset Papers in Geosciences [data set], https://doi.org/10.7167/2013/297973/dataset, 2013. a
Bai, L., Lv, X., and Li, X.: Evaluation of Two SMAP Soil Moisture Retrievals
Using Modeled- and Ground-Based Measurements, Remote Sens., 11, 2891,
https://doi.org/10.3390/rs11242891, 2019. a
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S.,
Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein, A.,
Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, J., Oechel, W.,
and Richardson, F.: FLUXNET: A New Tool to Study the Temporal and Spatial
Variability of Ecosystem–Scale Carbon Dioxide, Water Vapor, and Energy Flux
Densities, B. Am. Meteorol. Soc., 82, 2415–2434, https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2, 2001. a
Balenzano, A., Mattia, F., Satalino, G., Lovergine, F. P., Palmisano, D., Peng, J., Marzahn, P., Wegmüller, U., Cartus, O., Da̧browska-Zielińska, K., Musial, J. P., Davidson, M. W., Pauwels, V. R., Cosh, M. H., McNairn, H., Johnson, J. T., Walker, J. P., Yueh, S. H., Entekhabi, D., Kerr, Y. H., and Jackson, T. J.: Sentinel-1 soil moisture at 1 km resolution: a validation study, Remote Sens. Environ., 263, 112554,
https://doi.org/10.1016/j.rse.2021.112554, 2021. a
Balsamo, G., Albergel, C., Beljaars, A., Boussetta, S., Brun, E., Cloke, H.,
Dee, D., Dutra, E., Muñoz Sabater, J., Pappenberger, F., de Rosnay, P.,
Stockdale, T., and Vitart, F.: ERA-Interim/Land: a global land surface
reanalysis data set, Hydrol. Earth Syst. Sci., 19, 389–407,
https://doi.org/10.5194/hess-19-389-2015, 2015. a, b
Bao, Y., Lin, L., Wu, S., Deng, K. A. K., and Petropoulos, G. P.: Surface soil moisture retrievals over partially vegetated areas from the synergy of
Sentinel-1 and Landsat 8 data using a modified water-cloud model, Int. J. Appl. Earth Obs. Geoinf., 72, 76–85, https://doi.org/10.1016/j.jag.2018.05.026, 2018. a, b
Barbu, A. L., Calvet, J.-C., Mahfouf, J.-F., and Lafont, S.: Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France, Hydrol. Earth Syst. Sci., 18, 173–192, https://doi.org/10.5194/hess-18-173-2014, 2014. a
Bauer-Marschallinger, B., Paulik, C., Hochstöger, S., Mistelbauer, T.,
Modanesi, S., Ciabatta, L., Massari, C., Brocca, L., and Wagner, W.: Soil
Moisture from Fusion of Scatterometer and SAR: Closing the Scale Gap with
Temporal Filtering, Remote Sens., 10, 1030, https://doi.org/10.3390/rs10071030, 2018. a, b, c, d
Bauer-Marschallinger, B., Freeman, V., Cao, S., Paulik, C., Schaufler, S.,
Stachl, T., Modanesi, S., Massari, C., Ciabatta, L., Brocca, L., and Wagner,
W.: Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing Assets
and Overcoming Obstacles, IEEE T. Geosci. Remote, 57, 520–539, https://doi.org/10.1109/TGRS.2018.2858004, 2019. a, b
Bayat, B., Camacho, F., Nickeson, J., Cosh, M., Bolten, J., Vereecken, H., and Montzka, C.: Toward operational validation systems for global satellite-based terrestrial essential climate variables, Int. J. Appl. Earth Obs. Geoinf., 95, 102240, https://doi.org/10.1016/j.jag.2020.102240, 2021. a, b
Beck, H. E., Pan, M., Miralles, D. G., Reichle, R. H., Dorigo, W. A., Hahn, S., Sheffield, J., Karthikeyan, L., Balsamo, G., Parinussa, R. M., van Dijk, A. I. J. M., Du, J., Kimball, J. S., Vergopolan, N., and Wood, E. F.: Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors, Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, 2021. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Bell, J., Palecki, M., Baker, B., Collins, W., Lawrimore, J., Leeper, R., Hall, M., Kochendorfer, J., Meyers, T., Wilson, T., and Diamond, H.: U.S. Climate Reference Network Soil Moisture and Temperature Observations, J.
Hydrometeorol., 14, 977–988, https://doi.org/10.1175/JHM-D-12-0146.1, 2013. a
Beyrich, F. and Adam, W.: Site and Data Report for the Lindenberg Reference
Site in CEOP – Phase 1, 230, Berichte des Deutschen Wetterdienstes, Offenbach am Main, 2007. a
Bi, H., Ma, J., Zheng, W., and Zeng, J.: Comparison of soil moisture in GLDAS
model simulations and in situ observations over the Tibetan Plateau, J. Geophys. Res.-Atmos., 121, 2658–2678, https://doi.org/10.1002/2015JD024131, 2016. a, b, c, d
Biddoccu, M., Ferraris, S., Opsi, F., and Cavallo, E.: Long-term monitoring of soil management effects on runoff and soil erosion in sloping vineyards in
Alto Monferrato (North West Italy), Soil Till. Res., 155, 176–189,
https://doi.org/10.1016/j.still.2015.07.005, 2016. a
Bircher, S., Skou, N., Jensen, K. H., Walker, J. P., and Rasmussen, L.: A soil moisture and temperature network for SMOS validation in Western Denmark, Hydrol. Earth Syst. Sci., 16, 1445–1463, https://doi.org/10.5194/hess-16-1445-2012, 2012. a, b
Blöschl, G., Blaschke, A. P., Broer, M., Bucher, C., Carr, G., Chen, X.,
Eder, A., Exner-Kittridge, M., Farnleitner, A., Flores-Orozco, A., Haas, P.,
Hogan, P., Kazemi Amiri, A., Oismüller, M., Parajka, J., Silasari, R.,
Stadler, P., Strauss, P., Vreugdenhil, M., Wagner, W., and Zessner, M.: The
Hydrological Open Air Laboratory (HOAL) in Petzenkirchen: a hypothesis-driven
observatory, Hydrol. Earth Syst. Sci., 20, 227–255, https://doi.org/10.5194/hess-20-227-2016, 2016. a
Blyverket, J., Hamer, P., Bertino, L., Albergel, C., Fairbairn, D., and Lahoz, W.: An Evaluation of the EnKF vs. EnOI and the Assimilation of SMAP, SMOS and ESA CCI Soil Moisture Data over the Contiguous US, Remote Sens., 11, 478, https://doi.org/10.3390/rs11050478, 2019a. a, b, c, d
Blyverket, J., Hamer, P., Bertino, L., Albergel, C., Fairbairn, D., and Lahoz, W.: An Evaluation of the EnKF vs. EnOI and the Assimilation of SMAP, SMOS and ESA CCI Soil Moisture Data over the Contiguous US, Remote Sens., 11,
012046, https://doi.org/10.3390/rs11050478, 2019b. a, b, c
Bogena, H., Huisman, J., Oberdörster, C., and Vereecken, H.: Evaluation
of a low-cost soil water content sensor for wireless network applications, J. Hydrol., 344, 32–42, https://doi.org/10.1016/j.jhydrol.2007.06.032, 2007. a
Bogena, H., Kunkel, R., Pütz, T., Vereecken, H., Kruger, E., Zacharias, S., Dietrich, P., Wollschläger, U., Kunstmann, H., Papen, H., Schmid, H., Munch, J., Priesack, E., Schwank, M., Bens, O., Brauer, A., Borg, E., and Hajnsek, I.: TERENO – Long-term monitoring network for terrestrial environmental research, Hydrol. Wasserbewirt., 56, 138–143, 2012. a
Bogena, H. R.: TERENO: German network of terrestrial environmental observatories, J. Large-scale Res. Facil., 2, A52, https://doi.org/10.17815/jlsrf-2-98, 2016. a
Bogena, H. R., Huisman, J. A., Güntner, A., Hübner, C., Kusche, J.,
Jonard, F., Vey, S., and Vereecken, H.: Emerging methods for noninvasive
sensing of soil moisture dynamics from field to catchment scale: a review:
Emerging methods for noninvasive sensing of soil moisture dynamics, Wiley
Interdisciplin. Rev.: Water, 2, 635–647, https://doi.org/10.1002/wat2.1097, 2015. a
Bonney, R., Cooper, C. B., Dickinson, J., Kelling, S., Phillips, T., Rosenberg, K. V., and Shirk, J.: Citizen Science: A Developing Tool for Expanding Science Knowledge and Scientific Literacy, BioScience, 59, 977–984, https://doi.org/10.1525/bio.2009.59.11.9, 2009. a
Boussetta, S., Balsamo, G., Dutra, E., Beljaars, A., and Albergel, C.: Assimilation of surface albedo and vegetation states from satellite observations and their impact on numerical weather prediction, Remote Sens.
Environ., 163, 111–126, https://doi.org/10.1016/j.rse.2015.03.009, 2015. a, b
Brocca, L., Morbidelli, R., Melone, F., and Moramarco, T.: Soil moisture spatial variability in experimental areas of central Italy, J. Hydrol., 333, 356–373, https://doi.org/10.1016/j.jhydrol.2006.09.004, 2007. a
Brocca, L., Melone, F., and Moramarco, T.: On the estimation of antecedent
wetness condition in rainfall-runoff modeling, Hydrol. Process., 22, 629–642, https://doi.org/10.1002/hyp.6629, 2008. a
Brocca, L., Melone, F., Moramarco, T., and Morbidelli, R.: Antecedent wetness
conditions based on ERS scatterometer data, J. Hydrol., 364, 73–87, 2009. a
Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W.
A. D., Matgen, P., Martínez-Fernández, J., Llorens, P., Latron, J., Martin, C., and Bittelli, M.: Soil moisture estimation through ASCAT and
AMSR-E sensors: An intercomparison and validation study across Europe, Remote
Sens. Environ., 115, 3390–3408, https://doi.org/10.1016/j.rse.2011.08.003, 2011. a, b, c, d, e
Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., and Levizzani, V.: Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data, J. Geophys. Res.-Atmos., 119, 5128–5141, https://doi.org/10.1002/2014jd021489, 2014a. a
Brocca, L., Zucco, G., Mittelbach, H., Moramarco, T., and Seneviratne, S. I.:
Absolute versus temporal anomaly and percent of saturation soil moisture
spatial variability for six networks worldwide, Water Resour. Res., 50, 5560–5576, https://doi.org/10.1002/2014WR015684, 2014b. a
Brocca, L., Massari, C., Ciabatta, L., Moramarco, T., Penna, D., Zuecco, G.,
Pianezzola, L., Borga, M., Matgen, P., and Martínez-Fernández, J.:
Rainfall estimation from in situ soil moisture observations at several sites
in Europe: an evaluation of the SM2RAIN algorithm, J. Hydrol. Hydromech., 63, 201–209, https://doi.org/10.1515/johh-2015-0016, 2015. a
Brocca, L., Ciabatta, L., Massari, C., Camici, S., and Tarpanelli, A.: Soil
Moisture for Hydrological Applications: Open Questions and New Opportunities,
Water, 9, 140, https://doi.org/10.3390/w9020140, 2017. a
Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., and Piguet,
B.: In situ soil moisture observations for the CAL/VAL of SMOS: the SMOSMANIA
network, in: 2007 IEEE International Geoscience and Remote Sensing Symposium, 1196–1199, https://doi.org/10.1109/IGARSS.2007.4423019, 2007. a
Calvet, J.-C., Fritz, N., Berne, C., Piguet, B., Maurel, W., and Meurey, C.:
Deriving pedotransfer functions for soil quartz fraction in southern France
from reverse modeling, SOIL, 2, 615–629, https://doi.org/10.5194/soil-2-615-2016,
2016. a, b
Campo, L., Castelli, F., Caparrini, F., and Entekhabi, D.: Production of a
5-years Dataset of Soil Moisture Maps on Italian Territory with an Operational Algorithm, Eur. Water, 35, 45–56, 2011. a
Canisius, F.: Calibration of Casselman, Ontario Soil Moisture Monitoring
Network, Agriculture and Agri-Food, Ottawa, ON, Canada, 37 pp., 2011. a
Capello, G., Biddoccu, M., Ferraris, S., and Cavallo, E.: Effects of Tractor
Passes on Hydrological and Soil Erosion Processes in Tilled and Grassed
Vineyards, Water, 11, 2118, https://doi.org/10.3390/w11102118, 2019. a
Castell, N., Dauge, F. R., Schneider, P., Vogt, M., Lerner, U., Fishbain, B.,
Broday, D., and Bartonova, A.: Can commercial low-cost sensor platforms
contribute to air quality monitoring and exposure estimates?, Environ. Int., 99, 293–302, https://doi.org/10.1016/j.envint.2016.12.007, 2017. a
Chawla, S., Bachhtey, S., Gupta, V., Sharma, S., Seth, S., Gandhi, T.,
Varshney, S., Mehta, S., and Jha, R.: Low Cost Soil Moisture Sensors and
their Application in Automatic Irrigation System, p. 4, available at: https://www.researchgate.net/publication/308742451_Low_Cost_Soil_Moisture_Sensors_and_their_Application_in_Automatic_Irrigation_System (last access: 28 October 2021), 2019. a
Chen, F., Crow, W. T., Colliander, A., Cosh, M. H., Jackson, T. J., Bindlish,
R., Reichle, R. H., Chan, S. K., Bosch, D. D., Starks, P. J., Goodrich, D. C., and Seyfried, M. S.: Application of Triple Collocation in Ground-Based
Validation of Soil Moisture Active/Passive (SMAP) Level 2 Data Products, IEEE
J. Select. Top. Appl. Earth Obs. Remote Sens., 10, 489–502, https://doi.org/10.1109/JSTARS.2016.2569998, 2017. a
Chen, N., Xiang, Z., and Wang, C.: Integrated open geospatial web service
enabled cyber-physical information infrastructure for precision agriculture
monitoring, Comput. Electron. Agricult., 111, 78–91, https://doi.org/10.1016/j.compag.2014.12.009, 2015a. a
Chen, N., Xiao, C., Pu, F., Wang, X., Wang, C., Wang, Z., and Gong, J.:
Cyber-Physical Geographical Information Service-Enabled Control of Diverse
In-Situ Sensors, Sensors (Basel, Switzerland), 15, 2565–2592, https://doi.org/10.3390/s150202565, 2015b. a
Chen, X., Su, Y., Liao, J., Shang, J., Dong, T., Wang, C., Liu, W., Zhou, G.,
and Liu, L.: Detecting significant decreasing trends of land surface soil
moisture in eastern China during the past three decades (1979–2010), J.
Geophys. Res.-Atmos., 121, 5177–5192, https://doi.org/10.1002/2015JD024676, 2016. a
Chen, Y., Sun, L., Wang, W., and Pei, Z.: Application of Sentinel 2 data for drought monitoring in Texas, America, in: 2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics), 1–4,
https://doi.org/10.1109/Agro-Geoinformatics.2019.8820491, 2019. a
Chew, C. and Small, E.: Estimating inundation extent using CYGNSS data: A
conceptual modeling study, Remote Sens. Environ., 246, 111869,
https://doi.org/10.1016/j.rse.2020.111869, 2020. a, b
Colliander, A., Jackson, T., Bindlish, R., Chan, S., Das, N., Kim, S., Cosh,
M., Dunbar, R., Dang, L., Pashaian, L., Asanuma, J., Aida, K., Berg, A.,
Rowlandson, T., Bosch, D., Caldwell, T., Caylor, K., Goodrich, D., al Jassar,
H., Lopez-Baeza, E., Martínez-Fernández, J., González-Zamora, A., Livingston, S., McNairn, H., Pacheco, A., Moghaddam, M., Montzka, C., Notarnicola, C., Niedrist, G., Pellarin, T., Prueger, J., Pulliainen, J., Rautiainen, K., Ramos, J., Seyfried, M., Starks, P., Su, Z., Zeng, Y., van der Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M., Walker, J., Wu, X., Monerris, A., O'Neill, P., Entekhabi, D., Njoku, E., and Yueh, S.: Validation of SMAP surface soil moisture products with core validation sites, Remote Sens. Environ., 191, 215–231, https://doi.org/10.1016/j.rse.2017.01.021, 2017. a, b, c, d, e
Cook, D. R.: Soil temperature and moisture profile (STAMP) system handbook,
Tech. rep., DOE Office of Science Atmospheric Radiation Measurement (ARM)
Program, available at: https://www.osti.gov/biblio/1332724 (last access: 1 November 2021), 2016a. a
Cook, D. R. and Sullivan, R. C.: Surface Energy Balance System (SEBS)
Instrument Handbook, Tech. rep., DOE Office of Science Atmospheric Radiation
Measurement (ARM) Program, available at: https://www.osti.gov/biblio/1004944 (last access: 1 November 2021), 2018. a
Coopersmith, E. J., Cosh, M. H., Bindlish, R., and Bell, J.: Comparing AMSR-E
soil moisture estimates to the extended record of the U.S. Climate Reference
Network (USCRN), Adv. Water Resour., 85, 79–85, https://doi.org/10.1016/j.advwatres.2015.09.003, 2015. a
Crow, W. T., Berg, A. A., Cosh, M. H., Loew, A., Mohanty, B. P., Panciera, R., de Rosnay, P., Ryu, D., and Walker, J. P.: Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products: Upscaling Soil Moisture, Rev. Geophys., 50,
RG2002, https://doi.org/10.1029/2011RG000372, 2012. a, b
Cui, C., Xu, J., Zeng, J., Chen, K.-S., Bai, X., Lu, H., Chen, Q., and Zhao,
T.: Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS,
FY3B, AMSR2, and ESA CCI over Two Dense Network Regions at Different Spatial
Scales, Remote Sens., 10, 33, https://doi.org/10.3390/rs10010033, 2017. a, b, c, d, e
Dabrowska-Zielinska, K., Musial, J., Malinska, A., Budzynska, M., Gurdak, R.,
Kiryla, W., Bartold, M., and Grzybowski, P.: Soil Moisture in the Biebrza
Wetlands Retrieved from Sentinel-1 Imagery, Remote Sens., 10, 1979,
https://doi.org/10.3390/rs10121979, 2018. a
de Jeu, R. and Dorigo, W.: On the importance of satellite observed soil
moisture, Int. J. Appl. Earth Obs. Geoinf., 45, 107–109, https://doi.org/10.1016/j.jag.2015.10.007, 2016. a
de Jeu, R. A., Holmes, T. R., Parinussa, R. M., and Owe, M.: A spatially
coherent global soil moisture product with improved temporal resolution, J. Hydrol., 516, 284–296, https://doi.org/10.1016/j.jhydrol.2014.02.015, 2014. a
Deng, Y., Wang, S., Bai, X., Luo, G., Wu, L., Chen, F., Wang, J., Li, C., Yang, Y., Hu, Z., Tian, S., and Lu, Q.: Vegetation greening intensified soil drying in some semi-arid and arid areas of the world, Agr. Forest Meteorol., 292–293, 108103, https://doi.org/10.1016/j.agrformet.2020.108103, 2020a. a
Deng, Y., Wang, S., Bai, X., Luo, G., Wu, L., Chen, F., Wang, J., Li, Q., Li,
C., Yang, Y., Hu, Z., and Tian, S.: Spatiotemporal dynamics of soil moisture
in the karst areas of China based on reanalysis and observations data, J. Hydrol., 585, 124744, https://doi.org/10.1016/j.jhydrol.2020.124744, 2020b. a
Deng, Y., Wang, S., Bai, X., Wu, L., Cao, Y., Li, H., Wang, M., Li, C., Yang,
Y., Hu, Z., Tian, S., and Lu, Q.: Comparison of soil moisture products from
microwave remote sensing, land model, and reanalysis using global ground
observations, Hydrol. Process., 34, 836–851, https://doi.org/10.1002/hyp.13636, 2020c. a, b, c, d
Dente, L., Su, Z., and Wen, J.: Validation of SMOS soil moisture products over the Maqu and Twente regions, Sensors, 12, 9965–9986, 2012. a
Dente, L., Vekerdy, Z., de Jeu, R., and Su, Z.: Seasonality and autocorrelation of satellite-derived soil moisture products, Int. J. Remote Sens., 34, 3231–3247, https://doi.org/10.1080/01431161.2012.716923, 2013. a, b
de Rosnay, P., Muñoz, J., Sabater, C. A., Lawrence, H., Isaksen, L., and
English, S.: ECMWF Final Report on SMOS brightness temperature activities
over land: Monitoring and Data Assimilation, ESA Contract Report, available at: https://www.ecmwf.int/node/19531 (last access: 8 November 2021), 2019. a, b
Dirmeyer, P. A., Wu, J., Norton, H. E., Dorigo, W. A., Quiring, S. M., Ford,
T. W., Santanello, J. A., Bosilovich, M. G., Ek, M. B., Koster, R. D., Balsamo, G., and Lawrence, D. M.: Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States, J. Hydrometeorol., 17, 1049–1067, https://doi.org/10.1175/JHM-D-15-0196.1, 2016. a, b, c, d, e
Domínguez-Niño, J. M., Bogena, H. R., Huisman, J. A., Schilling, B., and Casadesús, J.: On the Accuracy of Factory-Calibrated Low-Cost Soil Water Content Sensors, Sensors, 19, 3101, https://doi.org/10.3390/s19143101, 2019. a
Dong, J., Crow, W. T., Tobin, K. J., Cosh, M. H., Bosch, D. D., Starks, P. J., Seyfried, M., and Collins, C. H.: Comparison of microwave remote sensing and land surface modeling for surface soil moisture climatology estimation,
Remote Sens. Environ., 242, 111756, https://doi.org/10.1016/j.rse.2020.111756, 2020. a, b, c, d, e, f, g, h
Dorigo, W., van Oevelen, P., Wagner, W., Drusch, M., Mecklenburg, S., Robock,
A., and Jackson, T.: A New International Network for in Situ Soil Moisture
Data, EOS Trans. Am. Geophys. Union, 92, 141–142, https://doi.org/10.1029/2011EO170001, 2011a. a, b
Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A.,
Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and
Jackson, T.: The International Soil Moisture Network: a data hosting facility
for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675–1698, https://doi.org/10.5194/hess-15-1675-2011, 2011b. a, b, c, d, e, f, g, h, i
Dorigo, W., Xaver, A., Vreugdenhil, M., Gruber, A., Dostálová, A.,
Sanchis-Dufau, A. D., Zamojski, D., Cordes, C., Wagner, W., and Drusch, M.:
Global Automated Quality Control of In Situ Soil Moisture Data from the
International Soil Moisture Network, Vadose Zone J., 12, vzj2012.0097, https://doi.org/10.2136/vzj2012.0097, 2013. a, b, c, d, e, f, g, h
Dorigo, W., Gruber, A., Jeu, R. D., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R., and Kidd, R.: Evaluation of the ESA CCI soil moisture product using ground-based observations, Remote
Sens. Environ., 162, 380–395, https://doi.org/10.1016/j.rse.2014.07.023, 2015. a, b, c, d
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L.,
Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi,
M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y., Miralles, D.,
Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C.,
van der Schalie, R., Seneviratne, S. I., Smolander, T., and Lecomte, P.: ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, Remote Sens. Environ., 203, 185–215, https://doi.org/10.1016/j.rse.2017.07.001, 2017. a, b, c, d, e
Dorigo, W. A., Scipal, K., Parinussa, R. M., Liu, Y. Y., Wagner, W., de Jeu, R. A. M., and Naeimi, V.: Error characterisation of global active and passive
microwave soil moisture datasets, Hydrol. Earth Syst. Sci., 14, 2605–2616, https://doi.org/10.5194/hess-14-2605-2010, 2010. a
Draper, C. and Reichle, R. H.: Assimilation of Satellite Soil Moisture for Improved Atmospheric Reanalyses, Mon. Weather Rev., 147, 2163–2188,
https://doi.org/10.1175/MWR-D-18-0393.1, 2019. a
Du, J., Kimball, J. S., and Jones, L. A.: Passive Microwave Remote Sensing of Soil Moisture Based on Dynamic Vegetation Scattering Properties for AMSR-E, IEEE T. Geosci. Remote, 54, 597–608, 2016. a
Ebrahimi, M., Alavipanah, S. K., Hamzeh, S., Amiraslani, F., Neysani Samany,
N., and Wigneron, J.-P.: Exploiting the synergy between SMAP and SMOS to
improve brightness temperature simulations and soil moisture retrievals in
arid regions, J. Hydrol., 557, 740–752, https://doi.org/10.1016/j.jhydrol.2017.12.051, 2018. a, b
Ebrahimi-Khusfi, M., Alavipanah, S. K., Hamzeh, S., Amiraslani, F., Neysani Samany, N., and Wigneron, J.-P.: Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC, Int. J. Appl. Earth Obs. Geoinf., 67, 148–160, https://doi.org/10.1016/j.jag.2017.12.005, 2018. a, b
Ebtehaj, A. and Bras, R. L.: A physically constrained inversion for
high-resolution passive microwave retrieval of soil moisture and vegetation
water content in L-band, Remote Sens. Environ., 233, 111346, https://doi.org/10.1016/j.rse.2019.111346, 2019. a
Enenkel, M., Reimer, C., Dorigo, W., Wagner, W., Pfeil, I., Parinussa, R., and De Jeu, R.: Combining satellite observations to develop a global soil
moisture product for near-real-time applications, Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, 2016. a
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J., Kimball, J., Piepmeier, J. R., Koster, R. D., Martin, N., McDonald, K. C., Moghaddam, M., Moran, S., Reichle, R., Shi, J. C., Spencer, M. W., Thurman, S. W., Tsang, L., and Van Zyl, J.: The Soil Moisture Active Passive (SMAP) Mission, Proc. IEEE, 98, 704–716, https://doi.org/10.1109/JPROC.2010.2043918, 2010. a
Erlingis, J. M., Rodell, M., Peters-Lidard, C. D., Li, B., Kumar, S. V.,
Famiglietti, J. S., Granger, S. L., Hurley, J. V., Liu, P.-W., and Mocko, D. M.: A High-Resolution Land Data Assimilation System Optimized for the Western United States, J. Am. Water Resour. Assoc., https://doi.org/10.1111/1752-1688.12910, in press, 2021. a, b, c, d, e, f, g
Eroglu, O., Kurum, M., Boyd, D., and Gurbuz, A. C.: High spatio-temporal
resolution CYGNSS soil moisture estimates using artificial neural networks,
Remote Sens., 11, 2272, https://doi.org/10.3390/rs11192272, 2019. a, b
Esposito, G., Matano, F., and Scepi, G.: Analysis of Increasing Flash Flood
Frequency in the Densely Urbanized Coastline of the Campi Flegrei Volcanic
Area, Italy, Front. Earth Sci., 6, 63, https://doi.org/10.3389/feart.2018.00063, 2018. a
Fairbairn, D., Barbu, A. L., Mahfouf, J.-F., Calvet, J.-C., and Gelati, E.:
Comparing the ensemble and extended Kalman filters for in situ soil moisture
assimilation with contrasting conditions, Hydrol. Earth Syst. Sci., 19, 4811–4830, https://doi.org/10.5194/hess-19-4811-2015, 2015. a
Fairbairn, D., de Rosnay, P., and Browne, P. A.: The New Stand-Alone Surface
Analysis at ECMWF: Implications for Land–Atmosphere DA Coupling, J. Hydrometeorol., 20, 2023–2042, https://doi.org/10.1175/JHM-D-19-0074.1, 2019. a, b, c
Famiglietti, J. S., Ryu, D., Berg, A. A., Rodell, M., and Jackson, T. J.: Field observations of soil moisture variability across scales: Soil Moisture Variabilty Across Scales, Water Resour. Res., 44, W01423, https://doi.org/10.1029/2006WR005804, 2008. a
Fang, B., Lakshmi, V., Bindlish, R., and Jackson, T.: AMSR2 Soil Moisture
Downscaling Using Temperature and Vegetation Data, Remote Sens., 10, 1575,
https://doi.org/10.3390/rs10101575, 2018. a
Fang, B., Lakshmi, V., Bindlish, R., Jackson, T. J., and Liu, P.-W.:
Downscaling and Validation of SMAP Radiometer Soil Moisture in CONUS, in:
IEEE, 39th annual IGARSS symposium, 28 July–2 August 2019, Yokohama, Japan, 6194–6197, 2019. a
Fang, B., Lakshmi, V., Bindlish, R., Jackson, T. J., and Liu, P.-W.: Evaluation and validation of a high spatial resolution satellite soil moisture product over the Continental United States, J. Hydrol., 588, 125043,
https://doi.org/10.1016/j.jhydrol.2020.125043, 2020. a
Fang, B., Kansara, P., Dandridge, C., and Lakshmi, V.: Drought monitoring using high spatial resolution soil moisture data over Australia in 2015–2019, J. Hydrol., 594, 125960, https://doi.org/10.1016/j.jhydrol.2021.125960,
2021a. a, b
Fang, B., Lakshmi, V., Cosh, M. H., and Hain, C.: Very High Spatial Resolution Downscaled SMAP Radiometer Soil Moisture in the CONUS Using VIIRS/MODIS Data, IEEE J. Select. Top. App. Earth Obs. Remote Sens., 14, 4946–4965, https://doi.org/10.1109/JSTARS.2021.3076026, 2021b. a
FAO/IIASA/ISRIC/ISS-CAS/JRC: Harmonized World Soil Database (version 1.1), FAO, Rome, Italy and IIASA, Laxenburg, Austria, available at:
http://www.fao.org/3/a-aq361e.pdf (last access: 1 November 2021), 2009. a
Fascetti, F., Pierdicca, N., Crapolicchio, R., Pulvirenti, L., and Muoz-Sabater, J.: An assessment of SMOS version 6.20 products through
Triple and Quadruple Collocation techniques considering ASCAT, ERA/Interim
LAND, ISMNand SMAP soil moisture data, in: 14th Specialist Meetingon Microwave Radiometry and Remote Sensing of the Environment (MicroRad 2016), 11–14 April 2016, Espoo, Finland, 91–94, 2016. a, b, c
Fascetti, F., Pierdicca, N., Pulvirenti, L., Crapolicchio, R., and
Muñoz-Sabater, J.: A comparison of ASCAT and SMOS soil moisture retrievals over Europe and Northern Africa from 2010 to 2013, Int. J. Appl. Earth Obs. Geoinf., 45, 135–142, https://doi.org/10.1016/j.jag.2015.09.008, 2016. a, b
Fascetti, F., Pierdicca, N., Pulvirenti, L., and Crapolicchio, R.: Error characterization of SMOS, ASCAT, SMAP, ERA and ISMN soil moisture products: Automatic detection of cross-correlation error through extended quadruple collocation, in: 37th annual IGARSS symposium, 23–28 July 2017, Fort Worth, TX, USA, 4154–4157, https://doi.org/10.1109/IGARSS.2017.8127916, 2017. a, b, c
Fernandez-Moran, R., Al-Yaari, A., Mialon, A., Mahmoodi, A., Al Bitar, A.,
De Lannoy, G., Rodriguez-Fernandez, N., Lopez-Baeza, E., Kerr, Y., and
Wigneron, J.-P.: SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation
Optical Depth Product, Remote Sens., 9, 457, https://doi.org/10.3390/rs9050457, 2017a. a
Fernandez-Moran, R., Wigneron, J.-P., De Lannoy, G., Lopez-Baeza, E., Parrens, M., Mialon, A., Mahmoodi, A., Al-Yaari, A., Bircher, S., Al Bitar,
A., Richaume, P., and Kerr, Y.: A new calibration of the effective scattering
albedo and soil roughness parameters in the SMOS SM retrieval algorithm, Int. J. Appl. Earth Obs. Geoinf., 62, 27–38, https://doi.org/10.1016/j.jag.2017.05.013, 2017b. a
Flammini, A., Corradini, C., Morbidelli, R., Saltalippi, C., Picciafuoco, T.,
and Giráldez, J. V.: Experimental analyses of the evaporation dynamics in
bare soils under natural conditions, Water Resour. Manage., 32, 1153–1166, 2018a. a
Flammini, A., Morbidelli, R., Saltalippi, C., Picciafuoco, T., Corradini, C.,
and Govindaraju, R. S.: Reassessment of a semi-analytical field-scale
infiltration model through experiments under natural rainfall events, J. Hydrol., 565, 835–845, 2018b. a
Foucras, M., Zribi, M., Albergel, C., Baghdadi, N., Calvet, J.-C., and
Pellarin, T.: Estimating 500-m Resolution Soil Moisture Using Sentinel-1 and
Optical Data Synergy, Water, 12, 866, https://doi.org/10.3390/w12030866, 2020. a, b
Fritz, S., Fonte, C., and See, L.: The Role of Citizen Science in Earth
Observation, Remote Sens., 9, 357, https://doi.org/10.3390/rs9040357, 2017. a
Fuchsberger, J., Kirchengast, G., and Kabas, T.: WegenerNet high-resolution
weather and climate data from 2007 to 2020, Earth Syst. Sci. Data, 13, 1307–1334, https://doi.org/10.5194/essd-13-1307-2021, 2021. a
Galle, S., Manuela, G., Peugeot, C., Bouzou-Moussa, I., Cappelaere, B.,
Demarty, J., Mougin, E., Panthou, G., Adjomayi, P., Agbossou, E., Abdramane,
B., Boucher, M., Cohard, J.-M., Descloitres, M., Descroix, L., Diawara, M.,
Do, M., Favreau, G., Fabrice, G., and Wilcox, C.: AMMA-CATCH, a critical zone
observatory in West Africa monitoring a region in transition, Vadose Zone J., 17, 1–24, https://doi.org/10.2136/vzj2018.03.0062, 2018. a
Gao, L., Sadeghi, M., and Ebtehaj, A.: Microwave retrievals of soil moisture
and vegetation optical depth with improved resolution using a combined constrained inversion algorithm: Application for SMAP satellite, Remote Sens. Environ., 239, 111662, https://doi.org/10.1016/j.rse.2020.111662, 2020a. a
Gao, L., Sadeghi, M., Feldman, A. F., and Ebtehaj, A.: A Spatially
Constrained Multichannel Algorithm for Inversion of a First-Order Microwave
Emission Model at L-Band, IEEE T. Geosci. Remote, 58, 8134–8146, https://doi.org/10.1109/TGRS.2020.2987490, 2020b. a
Gardner, W. and Kirkham, D.: Determination of soil moisture by neutron
scattering, Soil Sci., 73, 391–401, 1952. a
GCOS: The Global Climate Observing System, available at:
https://gcos.wmo.int/en/gcos-implementation-plan (last access: 1 November 2021), 2016. a
Ghilain, N., Arboleda, A., Batelaan, O., Ardö, J., Trigo, I., Barrios,
J.-M., and Gellens-Meulenberghs, F.: A new retrieval algorithm for soil
moisture index from thermal infrared sensor on-board geostationary satellites
over Europe and Africa and its validation, Remote Sens., 11, 1968, https://doi.org/10.3390/rs11171968, 2019. a
González-Teruel, J., Torres-Sánchez, R., Blaya-Ros, P., Toledo-Moreo, A., Jiménez-Buendía, M., and Soto-Valles, F.: Design and Calibration of a Low-Cost SDI-12 Soil Moisture Sensor, Sensors, 19, 491, https://doi.org/10.3390/s19030491, 2019. a
González-Zamora, A., Sánchez, N., Gumuzzio, A., Piles, M., Olmedo, E., and Martínez-Fernández, J.: Validation of SMOS L2 and L3 soil moisture products over the Duero Basin at different spatial scales, ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial
Information Sciences, XL-7/W3, 1183–1188,
https://doi.org/10.5194/isprsarchives-XL-7-W3-1183-2015, 2015. a
González-Zamora, Á., Sanchez, N., Pablos, M., and Martínez-Fernández, J.: CCI soil moisture assessment with SMOS
soil moisture and in situ data under different environmental conditions and
spatial scales in Spain, Remote Sens. Environ., 225, 469–482, https://doi.org/10.1016/j.rse.2018.02.010, 2018. a
González-Zamora, Á., Sánchez, N., Pablos, M., and
Martínez-Fernández, J.: CCI soil moisture assessment with SMOS soil moisture and in situ data under different environmental conditions and spatial scales in Spain, Remote Sens. Environ., 225, 469–482,
https://doi.org/10.1016/j.rse.2018.02.010, 2019. a, b
Grainger, A.: Citizen Observatories and the New Earth Observation Science,
Remote Sens., 9, 153, https://doi.org/10.3390/rs9020153, 2017. a
Greifeneder, F., Khamala, E., Sendabo, D., Wagner, W., Zebisch, M., Farah, H., and Notarnicola, C.: Detection of soil moisture anomalies based on Sentinel-1, Phys. Chem. Earth Pt. A/B/C, 112, 75–82, https://doi.org/10.1016/j.pce.2018.11.009, 2019. a
Greifeneder, F., Notarnicola, C., and Wagner, W.: A Machine Learning-Based
Approach for Surface Soil Moisture Estimations with Google Earth Engine, Remote Sens., 13, 2099, https://doi.org/10.3390/rs13112099, 2021. a, b
Grillakis, M. G., Koutroulis, A. G., Alexakis, D. D., Polykretis, C., and
Daliakopoulos, I. N.: Regionalizing Root-Zone Soil Moisture Estimates From
ESA CCI Soil Water Index Using Machine Learning and Information on Soil,
Vegetation, and Climate, Water Resour. Res., 57, e2020WR029249,
https://doi.org/10.1029/2020WR029249, 2021. a, b, c
Gruber, A., Dorigo, W., Zwieback, S., Xaver, A., and Wagner, W.: Characterizing Coarse-Scale Representativeness of in situ Soil Moisture Measurements from the International Soil Moisture Network, Vadose Zone J., 12, vzj2012.0170, https://doi.org/10.2136/vzj2012.0170, 2013. a, b, c, d, e, f, g, h, i, j
Gruber, A., Paloscia, S., Santi, E., Notarnicola, C., Pasolli, L., Smolander, T., Pulliainen, J., Mittelbach, H., Dorigo, W., and Wagner, W.: Performance inter-comparison of soil moisture retrieval models for the MetOp-A ASCAT instrument, in: 34th annual IGARSS symposium, 13–18 July 2014, Quebec City, Canada, 2455–2458, https://doi.org/10.1109/IGARSS.2014.6946969, 2014. a
Gruber, A., Crow, W., Dorigo, W., and Wagner, W.: The potential of 2D Kalman
filtering for soil moisture data assimilation, Remote Sens. Environ., 171, 137–148, https://doi.org/10.1016/j.rse.2015.10.019, 2015. a, b, c, d
Gruber, A., Su, C.-H., Crow, W. T., Zwieback, S., Dorigo, W. A., and Wagner,
W.: Estimating error cross-correlations in soil moisture data sets using
extended collocation analysis, J. Geophys. Res.-Atmos., 121, 1208–1219, https://doi.org/10.1002/2015JD024027, 2016. a
Gruber, A., Dorigo, W. A., Crow, W., and Wagner, W.: Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals, IEEE T. Geosci. Remote, 55, 6780–6792, https://doi.org/10.1109/TGRS.2017.2734070, 2017. a, b, c
Gruber, A., Crow, W. T., and Dorigo, W. A.: Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain, Water Resour.
Res., 54, 1353–1367, https://doi.org/10.1002/2017WR021277, 2018. a, b, c, d
Gruber, A., De Lannoy, G., and Crow, W.: A Monte Carlo based adaptive Kalman
filtering framework for soil moisture data assimilation, Remote Sens.
Environ., 228, 105–114, 2019a. a
Gruber, A., De Lannoy, G., Albergel, C., Al-Yaari, A., Brocca, L., Calvet,
J.-C., Colliander, A., Cosh, M., Crow, W., Dorigo, W., Draper, C., Hirschi,
M., Kerr, Y., Konings, A., Lahoz, W., McColl, K., Montzka, C.,
Muñoz-Sabater, J., Peng, J., Reichle, R., Richaume, P., Rüdiger, C., Scanlon, T., van der Schalie, R., Wigneron, J.-P., and Wagner, W.: Validation practices for satellite soil moisture retrievals: What are (the) errors?, Remote Sens. Environ., 244, 111806, https://doi.org/10.1016/j.rse.2020.111806, 2020. a, b, c, d, e, f, g
Guevara, M. and Vargas, R.: Downscaling satellite soil moisture using
geomorphometry and machine learning, PloS One, 14, e0219639, https://doi.org/10.1371/journal.pone.0219639, 2019. a
Guevara, M., Taufer, M., and Vargas, R.: Gap-free global annual soil moisture: 15 km grids for 1991–2018, Earth Syst. Sci. Data, 13, 1711–1735,
https://doi.org/10.5194/essd-13-1711-2021, 2021. a
Gumbricht, T.: Detecting Trends in Wetland Extent from MODIS Derived Soil
Moisture Estimates, Remote Sens., 10, 611, https://doi.org/10.3390/rs10040611, 2018. a, b
Gumbricht, T., Roman-Cuesta, R. M., Verchot, L., Herold, M., Wittmann, F.,
Householder, E., Herold, N., and Murdiyarso, D.: An expert system model for
mapping tropical wetlands and peatlands reveals South America as the largest
contributor, Global Change Biol., 23, 3581–3599, https://doi.org/10.1111/gcb.13689,
2017. a
Gupta, D. K., Srivastava, P. K., Singh, A., Petropoulos, G. P., Stathopoulos,
N., and Prasad, R.: SMAP Soil Moisture Product Assessment over Wales, U.K.,
Using Observations from the WSMN Ground Monitoring Network, Sustainability,
13, 11, https://doi.org/10.3390/su13116019, 2021. a
Hajdu, I., Yule, I., Bretherton, M., Singh, R., and Hedley, C.: Field performance assessment and calibration of multi-depth AquaCheck capacitance-based soil moisture probes under permanent pasture for hill
country soils, Agr. Water Manage., 217, 332–345, https://doi.org/10.1016/j.agwat.2019.03.002, 2019. a
Han, M., Lu, H., and Yang, K.: Development of passive microwave retrieval
algorithm for estimation of surface soil temperature from AMSR-E data, in:
36th annual IGARSS symposium, 10–15 July 2016, Beijing, China, 1671–1674, 2016. a
Han, M., Lu, H., Yang, K., Qin, J., Chen, Y., Zhao, L., and Lazhu Lab: A surface soil temperature retrieval algorithm based on AMSR-E multi-frequency brightness temperatures, Int. J. Remote Sens., 38, 6735–6754, https://doi.org/10.1080/01431161.2017.1363438, 2017. a
Han, Y., Bai, X., Shao, W., and Wang, J.: Retrieval of Soil Moisture by
Integrating Sentinel-1A and MODIS Data over Agricultural Fields, Water, 12,
1726, https://doi.org/10.3390/w12061726, 2020. a, b
Hartmann, A., Gleeson, T., Rosolem, R., Pianosi, F., Wada, Y., and Wagener, T.: A large-scale simulation model to assess karstic groundwater recharge over Europe and the Mediterranean, Geosci. Model Dev., 8, 1729–1746,
https://doi.org/10.5194/gmd-8-1729-2015, 2015. a
He, L., Chen, J. M., Mostovoy, G., and Gonsamo, A.: Soil Moisture Active
Passive Improves Global Soil Moisture Simulation in a Land Surface Scheme and
Reveals Strong Irrigation Signals Over Farmlands, Geophys. Res. Lett., 48, e2021GL092658, https://doi.org/10.1029/2021GL092658, 2021. a, b
Helgert, S. and Khodayar, S.: Improvement of the soil-atmosphere interactions
and subsequent heavy precipitation modelling by enhanced initialization using
remotely sensed 1 km soil moisture information, Remote Sens. Environ., 246, 111812, https://doi.org/10.1016/j.rse.2020.111812, 2020. a, b
Herbert, C., Pablos, M., Vall-llossera, M., Camps, A., and
Martínez-Fernández, J.: Analyzing Spatio-Temporal Factors to Estimate the Response Time between SMOS and In-Situ Soil Moisture at Different Depths, Remote Sens., 12, 2614, https://doi.org/10.3390/rs12162614, 2020. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hóm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 Global Reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b, c
Hirschi, M., Mueller, B., Dorigo, W., and Seneviratne, S.: Using remotely
sensed soil moisture for land–atmosphere coupling diagnostics: The role of
surface vs. root-zone soil moisture variability, Remote Sens. Environ., 154, 246–252, https://doi.org/10.1016/j.rse.2014.08.030, 2014. a
Hoang, K. O. and Lu, M.: Impacts of temperature effect removal on rainfall
estimation from soil water content by using SM2RAIN algorithm, IOP Conf. Ser.: Earth Environ. Sci., 344, 012046, https://doi.org/10.1088/1755-1315/344/1/012046, 2019. a
Hollinger, S. and Isard, S.: A Soil Moisture Climatology of Illinois, J.
Climate, 7, 822–833, https://doi.org/10.1175/1520-0442(1994)007<0822:ASMCOI>2.0.CO;2, 1994. a
Hottenstein, J. D., Ponce-Campos, G. E., Moguel-Yanes, J., and Moran, M. S.:
Impact of Varying Storm Intensity and Consecutive Dry Days on Grassland Soil
Moisture, J. Hydrometeorol., 16, 106–117, https://doi.org/10.1175/JHM-D-14-0057.1, 2015. a, b
Hu, T., Zhao, T., Zhao, K., and Shi, J.: A continuous global record of
near-surface soil freeze/thaw status from AMSR-E and AMSR2 data, Int. J. Remote Sens., 40, 6993–7016, https://doi.org/10.1080/01431161.2019.1597307, 2019. a, b, c
Ikonen, J., Vehviläinen, J., Rautiainen, K., Smolander, T., Lemmetyinen, J., Bircher, S., and Pulliainen, J.: The Sodankylä in situ soil moisture observation network: an example application of ESA CCI soil moisture product evaluation, Geosci. Instrum. Method. Data Syst., 5, 95–108, https://doi.org/10.5194/gi-5-95-2016, 2016. a
Ikonen, J., Smolander, T., Rautiainen, K., Cohen, J., Lemmetyinen, J.,
Salminen, M., and Pulliainen, J.: Spatially distributed evaluation of ESA CCI
Soil Moisture products in a northern boreal forest environment, Geosciences,
8, 51, https://doi.org/10.3390/geosciences8020051, 2018. a
ISMN: ISMN stated terms and conditions for data use, available at:
https://ismn.geo.tuwien.ac.at/en/terms-and-conditions/, last access: 20 August 2020. a
ISMN: Welcome to the International Soil Moisture Network, available at: https://ismn.earth, last access: 28 October 2021. a
Jackson, T., Cosh, M., Bindlish, R., Starks, P., Bosch, D., Seyfried, M.,
Goodrich, D., Moran, M., and Du, J.: Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products, IEEE T. Geosci. Remote, 48, 4256–4272, https://doi.org/10.1109/TGRS.2010.2051035, 2011. a
Jalilvand, E., Tajrishy, M., Brocca, L., Massari, C., Ghazi Zadeh Hashemi,
S., and Ciabatta, L.: Estimating the drainage rate from surface soil moisture
drydowns: Application of DfD model to in situ soil moisture data, J. Hydrol., 565, 489–501, https://doi.org/10.1016/j.jhydrol.2018.08.035, 2018. a
Jensen, K. and Refsgaard, J.: HOBE: The Danish Hydrological Observatory, Vadose Zone J., 17, 180059, https://doi.org/10.2136/vzj2018.03.0059, 2018. a
Ji, P., Yuan, X., and Liang, X.-Z.: Do Lateral Flows Matter for the
Hyperresolution Land Surface Modeling?, J. Geophys. Res.-Atmos., 122, 12077–12092, https://doi.org/10.1002/2017JD027366, 2017. a
Jin, R., Li, X., Yan, B., Li, X., Luo, W., Ma, M., Guo, J., Kang, J., Zhu, Z., and Zhao, S.: A Nested Ecohydrological Wireless Sensor Network for Capturing the Surface Heterogeneity in the Midstream Areas of the Heihe River Basin, China, IEEE Geosci. Remote Sens. Lett., 11, 2015–2019, https://doi.org/10.1109/LGRS.2014.2319085, 2014. a
Kang, J., Li, X., Jin, R., Ge, Y., Wang, J., and Wang, J.: Hybrid Optimal
Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of
the Heihe River Basin, China, Sensors, 14, 19095–19114, https://doi.org/10.3390/s141019095, 2014. a
Kapilaratne, R. J. and Lu, M.: Automated general temperature correction method for dielectric soil moisture sensors, J. Hydrol., 551, 203–216,
https://doi.org/10.1016/j.jhydrol.2017.05.050, 2017. a
Karthikeyan, L., Pan, M., Wanders, N., Kumar, D. N., and Wood, E. F.: Four
decades of microwave satellite soil moisture observations: Part 2. Product
validation and inter-satellite comparisons, Adv. Water Resour., 109, 236–252, https://doi.org/10.1016/j.advwatres.2017.09.010, 2017. a, b, c, d, e, f, g, h, i, j, k
Kędzior, M. and Zawadzki, J.: Comparative study of soil moisture
estimations from SMOS satellite mission, GLDAS database, and cosmic-ray
neutrons measurements at COSMOS station in Eastern Poland, Geoderma, 283,
21–31, https://doi.org/10.1016/j.geoderma.2016.07.023, 2016. a, b
Kerr, Y., Al-Yaari, A., Rodriguez-Fernandez, N., Parrens, M., Molero, B.,
Leroux, D., Bircher, S., Mahmoodi, A., Mialon, A., Richaume, P., Delwart, S.,
Al Bitar, A., Pellarin, T., Bindlish, R., Jackson, T., Rüdiger, C.,
Waldteufel, P., Mecklenburg, S., and Wigneron, J.-P.: Overview of SMOS
performance in terms of global soil moisture monitoring after six years in
operation, Remote Sens. Environ., 180, 40–63, https://doi.org/10.1016/j.rse.2016.02.042, 2016. a, b
Khaki, M., Hoteit, I., Kuhn, M., Forootan, E., and Awange, J.: Assessing data
assimilation frameworks for using multi-mission satellite products in a
hydrological context, Sci. Total Environ., 647, 1031–1043, https://doi.org/10.1016/j.scitotenv.2018.08.032, 2019. a, b
Kim, H. and Lakshmi, V.: Use of Cyclone Global Navigation Satellite System (CyGNSS) Observations for Estimation of Soil Moisture, Geophys. Res.
Lett., 45, 8272–8282, https://doi.org/10.1029/2018GL078923, 2018. a, b, c
Kim, H., Parinussa, R., Konings, A. G., Wagner, W., Cosh, M. H., Lakshmi, V.,
Zohaib, M., and Choi, M.: Global-scale assessment and combination of SMAP
with ASCAT (active) and AMSR2 (passive) soil moisture products, Remote
Sens. Environ., 204, 260–275, https://doi.org/10.1016/j.rse.2017.10.026, 2018. a, b, c
Kim, K., Jung, S., and Lee, Y.: A Study for establishment of soil moisture
station in mountain terrain (1): the representative analysis of soil moisture
for construction of Cosmic-ray verification system, J. Korea Water Resour. Assoc., 52, 51–60, 2019. a
Kim, S., Liu, Y., Johnson, F. M., Parinussa, R. M., and Sharma, A.: A global
comparison of alternate AMSR2 soil moisture products: Why do they differ?,
Remote Sens. Environ., 161, 43–62, https://doi.org/10.1016/j.rse.2015.02.002, 2015a. a
Kim, S., Parinussa, R. M., Liu, Y. Y., Johnson, F. M., and Sharma, A.: A
framework for combining multiple soil moisture retrievals based on maximizing
temporal correlation, Geophys. Res. Lett., 42, 6662–6670, https://doi.org/10.1002/2015GL064981, 2015b. a
Kim, S., Parinussa, R., Liu, Y., Johnson, F., and Sharma, A.: Merging Alternate Remotely-Sensed Soil Moisture Retrievals Using a Non-Static Model Combination Approach, Remote Sens., 8, 518, https://doi.org/10.3390/rs8060518, 2016. a, b, c
Kim, S., Sharma, A., Liu, Y., and Young, S.: Rethinking Satellite Data Merging: From Averaging to SNR Optimization, IEEE T. Geosci. Remote, https://doi.org/10.36227/techrxiv.14214035, in press, 2021. a, b
Kirchengast, G., Kabas, T., Leuprecht, A., Bichler, C., and Truhetz, H.:
WegenerNet: A Pioneering High-Resolution Network for Monitoring Weather and
Climate, B. Am. Meteorol. Soc., 95, 227–242, https://doi.org/10.1175/BAMS-D-11-00161.1, 2014. a
Kizito, F., Campbell, C., Campbell, G., Cobos, D., Teare, B., Carter, B., and
Hopmans, J.: Frequency, electrical conductivity and temperature analysis of a
low-cost capacitance soil moisture sensor, J. Hydrol., 352, 367–378, https://doi.org/10.1016/j.jhydrol.2008.01.021, 2008. a
Kojima, Y., Shigeta, R., Miyamoto, N., Shirahama, Y., Nishioka, K., Mizoguchi, M., and Kawahara, Y.: Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor, Sensors, 16, 1292,
https://doi.org/10.3390/s16081292, 2016. a
Kolassa, J., Aires, F., Polcher, J., Prigent, C., Jimenez, C., and Pereira,
J. M.: Soil moisture retrieval from multi-instrument observations: Information content analysis and retrieval methodology, J. Geophys. Res.-Atmos., 118, 4847–4859, https://doi.org/10.1029/2012JD018150, 2013. a, b
Kolassa, J., Gentine, P., Prigent, C., Aires, F., and Alemohammad, S.: Soil
moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 2: Product evaluation, Remote Sens. Environ., 195, 202–217,
https://doi.org/10.1016/j.rse.2017.04.020, 2017. a, b
Kolassa, J., Aires, F., Polcher, J., Prigent, C., Jimenez, C., and Pereira, J. M.: Estimating surface soil moisture from SMAP observations using a Neural Network technique, Remote Sens. Environ., 204, 43–59, https://doi.org/10.1016/j.rse.2017.10.045, 2018. a
Kornelsen, K. C. and Coulibaly, P.: Root-zone soil moisture estimation using
data-driven methods, Water Resour. Res., 50, 2946–2962, https://doi.org/10.1002/2013WR014127, 2014. a
Kornelsen, K. C. and Coulibaly, P.: Reducing multiplicative bias of satellite
soil moisture retrievals, Remote Sens. Environ., 165, 109–122,
https://doi.org/10.1016/j.rse.2015.04.031, 2015. a
Kosmala, M., Wiggins, A., Swanson, A., and Simmons, B.: Assessing data quality in citizen science, Front. Ecol. Environ., 14, 551–560, https://doi.org/10.1002/fee.1436, 2016. a
Kovačević, J., Cvijetinović, Z., Stančić, N., Brodić, N., and Mihajlović, D.: New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture, Remote Sens., 12, 1119, https://doi.org/10.3390/rs12071119, 2020. a
Kovács, K. Z., Hemment, D., Woods, M., van der Velden, N. K., Xaver, A.,
Giesen, R. H., Burton, V. J., Garrett, N. L., Zappa, L., Long, D., Dobos, E.,
and Skalsky, R.: Citizen observatory based soil moisture monitoring – the
GROW example, Hungar. Geogr. Bull., 68, 119–139, https://doi.org/10.15201/hungeobull.68.2.2, 2019. a, b
Krueger, E. S., Ochsner, T. E., and Quiring, S. M.: Development and Evaluation of Soil Moisture-Based Indices for Agricultural Drought Monitoring, Agron. J., 111, 1392–1406, https://doi.org/10.2134/agronj2018.09.0558, 2019. a
Kumar, M. S., Chandra, T. R., Kumar, D. P., and Manikandan, M. S.: Monitoring
moisture of soil using low cost homemade Soil moisture sensor and Arduino
UNO, in: IEEE 2016 3rd International Conference on Advanced Computing and
Communication Systems (ICACCS), Coimbatore, India, 1–4,
https://doi.org/10.1109/ICACCS.2016.7586312, 2016. a
Kumar, S., Newman, M., Wang, Y., and Livneh, B.: Potential Reemergence of
Seasonal Soil Moisture Anomalies in North America, Journal of Climate, 32,
2707–2734, https://doi.org/10.1175/JCLI-D-18-0540.1, 2019a. a
Kumar, S. V., M. Mocko, D., Wang, S., Peters-Lidard, C. D., and Borak, J.:
Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land
Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental United States, J. Hydrometeorol., 20, 1359–1377,
https://doi.org/10.1175/JHM-D-18-0237.1, 2019b. a
Kumar, S. V., Peters-Lidard, C. D., Santanello, J., Harrison, K., Liu, Y., and Shaw, M.: Land surface Verification Toolkit (LVT) – a generalized framework for land surface model evaluation, Geosci. Model Dev., 5, 869–886, https://doi.org/10.5194/gmd-5-869-2012, 2012. a
Larson, K., Small, E., Gutmann, E., Bilich, A., Braun, J., Zavorotny, V., and
Larson, C.: Use of GPS receivers as a soil moisture network for water cycle
studies, Geophys. Res. Lett., 35, L24405, https://doi.org/10.1029/2008GL036013, 2008. a, b, c
Leavesley, G., David, O., Garen, D., Lea, J., Marron, J., Pagano, T., Perkins, T., and Strobel, M.: A Modeling Framework for Improved Agricultural Water Supply Forecasting, in: AGU Fall Meeting Abstracts, 2008. a
Lee, J.: The consecutive dry days to trigger rainfall over West Africa, J.
Hydrol., 556, 934–943, https://doi.org/10.1016/j.jhydrol.2016.06.003, 2018. a, b, c
Lee, J. and Im, J.: A Novel Bias Correction Method for Soil Moisture and Ocean Salinity (SMOS) Soil Moisture: Retrieval Ensembles, Remote Sens., 7,
16045–16061, https://doi.org/10.3390/rs71215824, 2015. a
L'Heureux, J. L.: 2011 Installation Report for AAFC- SAGES Soil Moisture Stations in Kenaston, SK, Agriculture, 2011. a
Lei, F., Crow, W. T., Shen, H., Su, C.-H., Holmes, T. R., Parinussa, R. M., and Wang, G.: Assessment of the impact of spatial heterogeneity on microwave
satellite soil moisture periodic error, Remote Sens. Environ., 205,
85–99, https://doi.org/10.1016/j.rse.2017.11.002, 2018. a
Leng, P., Song, X., Li, Z.-L., Wang, Y., and Wang, R.: Toward the Estimation of Surface Soil Moisture Content Using Geostationary Satellite Data over
Sparsely Vegetated Area, Remote Sens., 7, 4112–4138,
https://doi.org/10.3390/rs70404112, 2015. a, b
Leng, P., Song, X., Duan, S.-B., and Li, Z.-L.: Preliminary validation of two
temporal parameter-based soil moisture retrieval models using a satellite
product and in situ soil moisture measurements over the REMEDHUS network, Int. J. Remote Sens., 37, 5902–5917, https://doi.org/10.1080/01431161.2016.1253896, 2016. a
Leng, P., Song, X., Duan, S.-B., and Li, Z.-L.: Generation of continuous
surface soil moisture dataset using combined optical and thermal infrared
images, Hydrol. Process., 31, 1398–1407, https://doi.org/10.1002/hyp.11113, 2017. a, b
Li, M., Wu, P., Sexton, D. M., and Ma, Z.: Potential shifts in climate zones
under a future global warming scenario using soil moisture classification,
Clim. Dynam., 56, 2071–2092, https://doi.org/10.1007/s00382-020-05576-w, 2021. a, b
Li, P., Zha, Y., Tso, C.-H. M., Shi, L., Yu, D., Zhang, Y., and Zeng, W.: Data assimilation of uncalibrated soil moisture measurements from frequency-domain reflectometry, Geoderma, 374, 114432, https://doi.org/10.1016/j.geoderma.2020.114432, 2020. a, b
Li, X., Al-Yaari, A., Schwank, M., Fan, L., Frappart, F., Swenson, J., and
Wigneron, J.-P.: Compared performances of SMOS-IC soil moisture and
vegetation optical depth retrievals based on Tau-Omega and Two-Stream
microwave emission models, Remote Sens. Environ., 236, 111502,
https://doi.org/10.1016/j.rse.2019.111502, 2020. a
Liao, W., Wang, D., Wang, G., Xia, Y., and Liu, X.: Quality Control and
Evaluation of the Observed Daily Data in the North American Soil Moisture
Database, J. Meteorol. Res., 33, 501–518, https://doi.org/10.1007/s13351-019-8121-2, 2019. a
Lievens, H., Martens, B., Verhoest, N., Hahn, S., Reichle, R., and Miralles,
D.: Assimilation of global radar backscatter and radiometer brightness
temperature observations to improve soil moisture and land evaporation estimates, Remote Sens. Environ., 189, 194–210, https://doi.org/10.1016/j.rse.2016.11.022, 2017. a, b, c, d
Lin, L.-F. and Pu, Z.: Examining the Impact of SMAP Soil Moisture Retrievals
on Short-Range Weather Prediction under Weakly and Strongly Coupled Data
Assimilation with WRF-Noah, Mon. Weather Rev., 147, 4345–4366,
https://doi.org/10.1175/MWR-D-19-0017.1, 2019. a, b
Lin, L.-F. and Pu, Z.: Improving Near-Surface Short-Range Weather Forecasts
Using Strongly Coupled Land–Atmosphere Data Assimilation with GSI-EnKF,
Mon. Weather Rev., 148, 2863–2888, https://doi.org/10.1175/MWR-D-19-0370.1, 2020. a
Liu, G., Chen, J.-M., Ji, L.-R., and Sun, S.-Q.: Relationship of summer soil
moisture with early winter monsoon and air temperature over eastern China,
Int. J. Climatol., 32, 1513–1519, https://doi.org/10.1002/joc.2352, 2012. a, b
Liu, S., Mo, X., Li, H., Peng, G., and Robock, A.: Spatial Variation of Soil
Moisture in China: Geostatistical Characterization, J. Meteorol. Soc. Jpn., 79, 555–574, https://doi.org/10.2151/jmsj.79.555, 2001. a
Liu, S., Roujean, J.-L., Kaptue Tchuente, A. T., Ceamanos, X., and Calvet,
J.-C.: A parameterization of SEVIRI and MODIS daily surface albedo with soil
moisture: Calibration and validation over southwestern France, Remote Sens.
Environ., 144, 137–151, https://doi.org/10.1016/j.rse.2014.01.016, 2014. a, b, c
Liu, Y., Yang, Y., and Yue, X.: Evaluation of Satellite-Based Soil Moisture
Products over Four Different Continental In-Situ Measurements, Remote Sens., 10, 1161, https://doi.org/10.3390/rs10071161, 2018. a, b, c, d
Liu, Y., Jing, W., Wang, Q., and Xia, X.: Generating high-resolution daily soil moisture by using spatial downscaling techniques: a comparison of six machine learning algorithms, Adv. Water Resour., 141, 103601,
https://doi.org/10.1016/j.advwatres.2020.103601, 2020. a
Liu, Y., Zhou, Y., Lu, N., Tang, R., Liu, N., Li, Y., Yang, J., Jing, W., and
Zhou, C.: Comprehensive assessment of Fengyun-3 satellites derived soil
moisture with in-situ measurements across the globe, J. Hydrol., 594, 125949, https://doi.org/10.1016/j.jhydrol.2020.125949, 2021. a, b
Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.: Developing an improved soil moisture dataset by blending passive and active microwave
satellite-based retrievals, Hydrol. Earth Syst. Sci., 15, 425–436, https://doi.org/10.5194/hess-15-425-2011, 2011. a, b, c, d
Liu, Z., Li, P., and Yang, J.: Soil Moisture Retrieval and Spatiotemporal
Pattern Analysis Using Sentinel-1 Data of Dahra, Senegal, Remote Sens., 9,
1197, https://doi.org/10.3390/rs9111197, 2017. a
Loew, A., dall'Amico, J., Schlenz, F., and Mauser, W.: The Upper Danube soil
moisture validation site: measurements and activities, in: Earth Observation and Water Cycle Science, edited by: Lacoste, H., vol. 674 of ESA Special Publication, p. 56, 2009. a
Loew, A., Bell, W., Brocca, L., Bulgin, C. E., Burdanowitz, J., Calbet, X.,
Donner, R. V., Ghent, D., Gruber, A., Kaminski, T., Kinzel, J., Klepp, C.,
Lambert, J.-C., Schaepman-Strub, G., Schröder, M., and Verhoelst, T.:
Validation practices for satellite-based Earth observation data across
communities, Rev. Geophys., 55, 779–817, https://doi.org/10.1002/2017RG000562, 2017. a
Lu, Y., Jin, J., and Kueppers, L.: Crop growth and irrigation interact to
influence surface fluxes in a regional climate-cropland model (WRF3.3-CLM4crop), Clim. Dynam., 45, 3347–3363, https://doi.org/10.1007/s00382-015-2543-z, 2015. a
Lukyanenko, R., Wiggins, A., and Rosser, H. K.: Citizen Science: An Information Quality Research Frontier, Inform. Syst. Front., 22, 961–983,
https://doi.org/10.1007/s10796-019-09915-z, 2020. a
Ma, C., Li, X., and McCabe, M. F.: Retrieval of High-Resolution Soil Moisture
through Combination of Sentinel-1 and Sentinel-2 Data, Remote Sens., 12, 2303, https://doi.org/10.3390/rs12142303, 2020. a
Ma, H., Zeng, J., Chen, N., Zhang, X., Cosh, M. H., and Wang, W.: Satellite
surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive
assessment using global ground-based observations, Remote Sens. Environ., 231, 111215, https://doi.org/10.1016/j.rse.2019.111215, 2019. a, b, c, d
Mahecha, M., Gans, F., Sippel, S., Donges, J., Kaminski, T., Metzger, S.,
Migliavacca, M., Papale, D., Rammig, A., and Zscheischler, J.: Detecting
impacts of extreme events with ecological in-situ monitoring networks,
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, 2017. a
Majone, B., Viani, F., Filippi, E., Bellin, A., Massa, A., Toller, G., Robol,
F., and Salucci, M.: Wireless Sensor Network Deployment for Monitoring Soil
Moisture Dynamics at the Field Scale, Proced. Environ. Sci., 19, 426–435, https://doi.org/10.1016/j.proenv.2013.06.049, 2013. a
Manfreda, S., Brocca, L., Moramarco, T., Melone, F., and Sheffield, J.: A
physically based approach for the estimation of root-zone soil moisture from
surface measurements, Hydrol. Earth Syst. Sci., 18, 1199–1212,
https://doi.org/10.5194/hess-18-1199-2014, 2014. a
Mao, F., Khamis, K., Krause, S., Clark, J., and Hannah, D. M.: Low-Cost
Environmental Sensor Networks: Recent Advances and Future Directions, Front. Earth Sci., 7, 221, https://doi.org/10.3389/feart.2019.00221, 2019. a
Marczewski, W., Slominski, J., Slominska, E., Usowicz, B., Usowicz, J., Romanov, S., Maryskevych, O., Nastula, J., and Zawadzki, J.: Strategies for validating and directions for employing SMOS data, in the Cal-Val project SWEX (3275) for wetlands, Hydrol. Earth Syst. Sci. Discuss., 7, 7007–7057, https://doi.org/10.5194/hessd-7-7007-2010, 2010. a
Martens, B., Miralles, D., Lievens, H., van der Schalie, R., de Jeu, R. A.,
Fernández-Prieto, D., Beck, H. E., Dorigo, W., and Verhoest, N.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture,
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017. a, b, c, d
Martens, B., de Jeu, R., Verhoest, N., Schuurmans, H., Kleijer, J., and
Miralles, D.: Towards Estimating Land Evaporation at Field Scales Using GLEAM, Remote Sens., 10, 1720, https://doi.org/10.3390/rs10111720, 2018. a
Martínez-Fernández, J., González-Zamora, A., and Almendra-Martín, L.: Soil moisture memory and soil properties: An analysis with the stored precipitation fraction, J. Hydrol., 593, 125622, https://doi.org/10.1016/j.jhydrol.2020.125622, 2021. a
Massari, C., Su, C.-H., Brocca, L., Sang, Y.-F., Ciabatta, L., Ryu, D., and
Wagner, W.: Near real time de-noising of satellite-based soil moisture retrievals: An intercomparison among three different techniques, Remote Sens. Environ., 198, 17–29, https://doi.org/10.1016/j.rse.2017.05.037, 2017. a, b
Mattar, C., Santamaría-Artigas, A., Durán-Alarcón, C.,
Olivera-Guerra, L., and Fuster, R.: LAB-net the first Chilean soil moisture
network for remote sensing applications, in: Quantitative Remote Sensing
Symposium (RAQRS), 22–26, 2014. a
Mattar, C., Santamaría-Artigas, A., Durán-Alarcón, C.,
Olivera-Guerra, L., Fuster, R., and Borvarán, D.: The LAB-Net Soil
Moisture Network: Application to Thermal Remote Sensing and Surface Energy
Balance, Data, 1, 6, https://doi.org/10.3390/data1010006, 2016. a
McDonough, K. R., Hutchinson, S. L., Hutchinson, J. S., Case, J. L., and
Rahmani, V.: Validation and assessment of SPoRT-LIS surface soil moisture
estimates for water resources management applications, J. Hydrol., 566, 43–54, https://doi.org/10.1016/j.jhydrol.2018.09.007, 2018. a, b
Mecklenburg, S., Drusch, M., Kerr, Y. H., Font, J., Martin-Neira, M., Delwart, S., Buenadicha, G., Reul, N., Daganzo-Eusebio, E., Oliva, R., and Crapolicchio, R.: ESA's Soil Moisture and Ocean Salinity Mission: Mission Performance and Operations, IEEE T. Geosci. Remote, 50, 1354–1366, https://doi.org/10.1109/TGRS.2012.2187666, 2012. a, b
Mimeau, L., Tramblay, Y., Brocca, L., Massari, C., Camici, S., and Finaud-Guyot, P.: Modeling the response of soil moisture to climate variability in the Mediterranean region, Hydrol. Earth Syst. Sci., 25, 653–669, https://doi.org/10.5194/hess-25-653-2021, 2021. a
Miralles, D. G., Crow, W. T., and Cosh, M. H.: Estimating Spatial Sampling
Errors in Coarse-Scale Soil Moisture Estimates Derived from Point-Scale
Observations, J. Hydrometeorol., 11, 1423–1429, https://doi.org/10.1175/2010JHM1285.1, 2010. a
Mishra, V., Shah, R., and Thrasher, B.: Soil Moisture Droughts under the
Retrospective and Projected Climate in India, J. Hydrometeorol., 15, 2267–2292, https://doi.org/10.1175/JHM-D-13-0177.1, 2014. a
Mishra, V., Shah, R., Azhar, S., Shah, H., Modi, P., and Kumar, R.:
Reconstruction of droughts in India using multiple land-surface models (1951–2015), Hydrol. Earth Syst. Sci., 22, 2269–2284,
https://doi.org/10.5194/hess-22-2269-2018, 2018. a, b, c, d
Mittelbach, H., Lehner, I., and Seneviratne, S. I.: Comparison of four soil
moisture sensor types under field conditions in Switzerland, J. Hydrol., 430–431, 39–49, https://doi.org/10.1016/j.jhydrol.2012.01.041, 2012. a
Moghaddam, M., Entekhabi, D., Goykhman, Y., Li, K., Liu, M., Mahajan, A.,
Nayyar, A., Shuman, D., and Teneketzis, D.: A Wireless Soil Moisture Smart
Sensor Web Using Physics-Based Optimal Control: Concept and Initial
Demonstrations, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 3, 522–535, https://doi.org/10.1109/JSTARS.2010.2052918, 2011. a
Moghaddam, M., Silva, A., Clewley, D., Akbar, R., Hussaini, S., Whitcomb, J.,
Devarakonda, R., Shrestha, R., Cook, R., Prakash, G., Santhana Vannan, S.,
and Boyer, A.: Soil Moisture Profiles and Temperature Data from SoilSCAPE
Sites, USA, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1339, 2016. a
Mohanty, B. P., Cosh, M. H., Lakshmi, V., and Montzka, C.: Soil Moisture Remote Sensing: State-of-the-Science, Vadose Zone J., 16, vzj2016.10.0105,
https://doi.org/10.2136/vzj2016.10.0105, 2017. a, b, c, d
Molero, B., Leroux, D. J., Richaume, P., Kerr, Y. H., Merlin, O., Cosh, M. H., and Bindlish, R.: Multi-Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints: Soil Moisture Time and Spatial Scales, J. Geophys. Res.-Atmos., 123, 3–21,
https://doi.org/10.1002/2017JD027478, 2018. a, b
Montzka, C., Bogena, H., Zreda, M., Monerris, A., Morrison, R., Muddu, S., and Vereecken, H.: Validation of Spaceborne and Modelled Surface Soil Moisture Products with Cosmic-Ray Neutron Probes, Remote Sens., 9, 103,
https://doi.org/10.3390/rs9020103, 2017. a, b, c, d
Montzka, C., Cosh, M., Bayat, B., Bitar, A. A., Berg, A., Bindlish, R., Bogena, H. R., Bolton, J. D., Cabot, F., Caldwell, T., Chan, S., Colliander, A., Crow, W., Das, N., Lannoy, G. D., Dorigo, W., Evett, S. R., Gruber, A., Hahn, S., Jagdhuber, T., Jones, S., Kerr, Y., Kim, S., Koyama, C., Kurum, M.,
Lopez-Baeza, E., Mattia, F., McColl, K., Mecklenburg, S., Mohanty, B., O'Neill, P., Or, D., Pellarin, T., Petropoulos, G. P., Piles, M., Reichle, R. H., Rodriguez-Fernandez, N., Rüdiger, C., Scanlon, T., Schwartz, R. C., Spengler, D., Srivastava, P., Suman, S., van der Schalie, R., Wagner, W., Wegmüller, U., Camacho, F., and Nickeson, J.: Soil Moisture Product Validation Best Practice Protocol, Version 1.0, available at: https://pubs.er.usgs.gov/publication/70216425 (last access: 1 November 2021), 2020. a, b, c
Moradizadeh, M. and Srivastava, P. K.: A new model for an improved AMSR2
satellite soil moisture retrieval over agricultural areas, Comput. Electron. Agricult., 186, 106205, https://doi.org/10.1016/j.compag.2021.106205, 2021. a, b
Morbidelli, R., Corradini, C., Saltalippi, C., Flammini, A., and Rossi, E.: Infiltration-soil moisture redistribution under natural conditions: experimental evidence as a guideline for realizing simulation models, Hydrol. Earth Syst. Sci., 15, 2937–2945, https://doi.org/10.5194/hess-15-2937-2011, 2011. a
Morbidelli, R., Saltalippi, C., Flammini, A., Rossi, E., and Corradini, C.:
Soil water content vertical profiles under natural conditions: matching of
experiments and simulations by a conceptual model, Hydrol. Process., 28, 4732–4742, https://doi.org/10.1002/hyp.9973, 2014a. a
Morbidelli, R., Saltalippi, C., Flammini, A., Rossi, E., and Corradini, C.:
Soil water content vertical profiles under natural conditions: Matching of
experiments and simulations by a conceptual model, Hydrol. Process., 28, 4732–4742, 2014b. a
Morbidelli, R., Saltalippi, C., Flammini, A., Cifrodelli, M., Picciafuoco, T., Corradini, C., and Govindaraju, R. S.: In situ measurements of soil saturated hydraulic conductivity: Assessment of reliability through rainfall–runoff experiments, Hydrol. Process., 31, 3084–3094, https://doi.org/10.1002/hyp.11247, 2017. a
Moreno-Martínez, Á., Piles, M., Muñoz-Marí, J., Campos-Taberner, M., Adsuara, J. E., Mateo, A., Perez-Suay, A., Javier García-Haro, F., Camps-Valls, G., Prasad, S., and Chanussot, J.: Machine Learning Methods for Spatial and Temporal Parameter Estimation,
Springer International Publishing, Cham, 5–35, https://doi.org/10.1007/978-3-030-38617-7_2, 2020. a, b, c
Mu, L., Li, S., Qin, B., and Liu, K.: Drought Monitoring Using Tiangong-2
Wide-Band Spectrometer Data, in: Proceedings of the Tiangong-2 Remote Sensing
Application Conference, edited by: Gu, Y., Gao, M., and Zhao, G., Springer, Singapore, 277–285, https://doi.org/10.1007/978-981-13-3501-3_26, 2019. a
Muñoz Sabater, J., Rodriguez-Fernandez, N., Sabater, J. M., Richaume, P.,
De Rosnay, P., Kerr, Y., Albergel, C., Drusch, M., and Mecklenburg, S.: SMOS
near-real-time soil moisture product: processor overview and first validation
results, Hydrol. Earth Syst. Sci., 21, 5201–5216, https://doi.org/10.5194/hess-21-5201-2017, 2017. a
Musial, J. P., Dabrowska-Zielinska, K., Kiryla, W., Oleszczuk, R., Gnatowski,
T., and Jaszczynski, J.: Derivation and validation of the high resolution
satellite soil moisture products: a case study of the Biebrza Sentinel-1
validation sites, Geoinform. Issues, 8, 37–53, 2016. a
Nair, A. and Indu, J.: Enhancing Noah Land Surface Model Prediction Skill over Indian Subcontinent by Assimilating SMOPS Blended Soil Moisture, Remote
Sens., 8, 976, https://doi.org/10.3390/rs8120976, 2016. a
Nair, A. S., Mangla, R. P. T., and Indu, J.: Remote sensing data assimilation, Hydrolog. Sci. J., 0, 1–33, https://doi.org/10.1080/02626667.2020.1761021, 2020. a, b
Naz, B. S., Kollet, S., Franssen, H.-J. H., Montzka, C., and Kurtz, W.: A
3 km spatially and temporally consistent European daily soil moisture reanalysis from 2000 to 2015, Scient. Data, 7, 111,
https://doi.org/10.1038/s41597-020-0450-6, 2020. a, b
Nguyen, H. H., Kim, H., and Choi, M.: Evaluation of the soil water content
using cosmic-ray neutron probe in a heterogeneous monsoon climate-dominated
region, Adv. Water Resour., 108, 125–138, https://doi.org/10.1016/j.advwatres.2017.07.020, 2017. a, b
Nicolai-Shaw, N., Hirschi, M., Mittelbach, H., and Seneviratne, S. I.: Spatial representativeness of soil moisture using in situ, remote sensing, and land reanalysis data, J. Geophys. Res.-Atmos., 120, 9955–9964, https://doi.org/10.1002/2015JD023305, 2015a. a
Nicolai-Shaw, N., Hirschi, M., Mittelbach, H., and Seneviratne, S. I.: Spatial representativeness of soil moisture using in situ, remote sensing, and land reanalysis data, J. Geophys. Res.-Atmos., 120, 9955–9964, https://doi.org/10.1002/2015JD023305, 2015b. a, b, c, d
Notarnicola, C., Caporaso, L., Giuseppe, F. D., Temimi, M., Ventura, B., and
Zebisch, M.: Inferring soil moisture variability in the Mediterrean Sea area
using infrared and passive microwave observations, Can. J. Remote Sens., 38, 46–59, https://doi.org/10.5589/m12-011, 2012. a
O, S. and Orth, R.: Global soil moisture data derived through machine learning trained with in-situ measurements, Scient. Data, 8, 1–14,
https://doi.org/10.1038/s41597-021-00964-1, 2021. a, b, c, d
Ochsner, T., Cosh, M., Cuenca, R., Dorigo, W., Draper, C., Hagimoto, Y., Kerr, Y., Larson, K., Njoku, E., Small, E., and Zreda, M.: State of the Art in Large-Scale Soil Moisture Monitoring, Soil Sci. Soc. Am. J., 77, 1888–1919, https://doi.org/10.2136/sssaj2013.03.0093, 2013. a
Ojha, N., Merlin, O., Suere, C., and Escorihuela, M. J.: Extending the
Spatio-Temporal Applicability of DISPATCH Soil Moisture Downscaling Algorithm: A Study Case Using SMAP, MODIS and Sentinel-3 Data, Front. Environ. Sci., 9, 40, https://doi.org/10.3389/fenvs.2021.555216, 2021. a, b, c, d
Ojha, R., Morbidelli, R., Saltalippi, C., Flammini, A., and Govindaraju, R. S.: Scaling of surface soil moisture over heterogeneous fields subjected to a
single rainfall event, J. Hydrol., 516, 21–36, https://doi.org/10.1016/j.jhydrol.2014.01.057, 2014. a
Ojo, E. R., Bullock, P., L'Heureux, J., Powers, J., McNairn, H., and Pacheco,
A.: Calibration and Evaluation of a Frequency Domain Reflectometry Sensor for
Real-Time Soil Moisture Monitoring, Vadose Zone J., 14, vzj2014.08.0114, https://doi.org/10.2136/vzj2014.08.0114, 2015. a
Osenga, E., Arnott, J., Endsley, K., and Katzenberger, J.: Bioclimatic and Soil Moisture Monitoring Across Elevation in a Mountain Watershed: Opportunities for Research and Resource Management, Water Resour. Res.,
2493–2503, https://doi.org/10.1029/2018WR023653, 2019. a
Pablos, M., Martínez-Fernández, J., Piles, M., Sánchez, N.,
Vall-llossera, M., and Camps, A.: Multi-Temporal Evaluation of Soil Moisture
and Land Surface Temperature Dynamics Using in Situ and Satellite Observations, Remote Sens., 8, 587, https://doi.org/10.3390/rs8070587, 2016. a, b
Pablos, M., González-Zamora, Á., Sánchez, N., and
Martínez-Fernández, J.: Assessment of Root Zone Soil Moisture
Estimations from SMAP, SMOS and MODIS Observations, Remote Sens., 10, 981,
https://doi.org/10.3390/rs10070981, 2018. a, b, c, d
Pacheco, A., L'Heureux, J., McNairn, H., Powers, J., Howard, A., Geng, X., Rollin, P., Gottfried, K., Freeman, J., and Ojo, R.: Real-time in-situ soil monitoring for agriculture (RISMA) network metadata, Science and Technology Branch Agriculture and Agri-Food Canada, Edmonton, AB, Canada, 2014. a
Pal, M., Maity, R., and Dey, S.: Statistical Modelling of Vertical Soil
Moisture Profile: Coupling of Memory and Forcing, Water Resour. Manage., 30, 1973–1986, https://doi.org/10.1007/s11269-016-1263-4, 2016. a
Palmer, J. R. B., Oltra, A., Collantes, F., Delgado, J. A., Lucientes, J.,
Delacour, S., Bengoa, M., Eritja, R., and Bartumeus, F.: Citizen science
provides a reliable and scalable tool to track disease-carrying mosquitoes,
Nat. Commun., 8, 916, https://doi.org/10.1038/s41467-017-00914-9, 2017. a
Paloscia, S., Pettinato, S., Santi, E., Notarnicola, C., Pasolli, L., and
Reppucci, A.: Soil moisture mapping using Sentinel-1 images: Algorithm and
preliminary validation, Remote Sens. Environ., 134, 234–248,
https://doi.org/10.1016/j.rse.2013.02.027, 2013. a
Pan, X., Kornelsen, K. C., and Coulibaly, P.: Estimating Root Zone Soil
Moisture at Continental Scale Using Neural Networks, J. Am. Water Resour. Assoc., 53, 220–237, https://doi.org/10.1111/1752-1688.12491, 2017. a, b, c
Parinussa, R., Wang, G., Holmes, T., Liu, Y., Dolman, A., de Jeu, R., Jiang,
T., Zhang, P., and Shi, J.: Global surface soil moisture from the Microwave Radiation Imager onboard the Fengyun-3B satellite, Int. J. Remote Sens., 35, 7007–7029, https://doi.org/10.1080/01431161.2014.960622, 2014a. a, b
Parinussa, R. M., Yilmaz, M. T., Anderson, M. C., Hain, C. R., and de Jeu, R.
A. M.: An intercomparison of remotely sensed soil moisture products at various spatial scales over the Iberian Peninsula, Hydrol. Process., 28, 4865–4876, https://doi.org/10.1002/hyp.9975, 2014b. a, b
Parinussa, R., de Jeu, R., van der Schalie, R., Crow, W., Lei, F., and Holmes, T.: A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input, Climate, 4, 50, https://doi.org/10.3390/cli4040050, 2016. a
Parinussa, R. M., Holmes, T. R. H., and de Jeu, R. A. M.: Soil Moisture
Retrievals From the WindSat Spaceborne Polarimetric Microwave Radiometer, IEEE T. Geosci. Remote, 50, 2683–2694, https://doi.org/10.1109/TGRS.2011.2174643, 2012. a, b
Parinussa, R. M., Holmes, T. R. H., Wanders, N., Dorigo, W. A., and de Jeu, R. A. M.: A Preliminary Study toward Consistent Soil Moisture from AMSR2, J. Hydrometeorol., 16, 932–947, https://doi.org/10.1175/JHM-D-13-0200.1, 2015. a, b, c, d
Parinussa, R. M., Wang, G., Liu, Y., Lou, D., Hagan, D. F. T., Zhan, M., Su,
B., and Jiang, T.: Improved surface soil moisture anomalies from Fengyun-3B
over the Jiangxi province of the People's Republic of China, Int. J. Remote Sens., 39, 8950–8962, https://doi.org/10.1080/01431161.2018.1500729, 2018. a, b
Park, C.-H., Montzka, C., Jagdhuber, T., Jonard, F., De Lannoy, G., Hong, J.,
Jackson, T. J., and Wulfmeyer, V.: A Dielectric Mixing Model Accounting for
Soil Organic Matter, Vadose Zone J., 18, 190036, https://doi.org/10.2136/vzj2019.04.0036, 2019. a, b, c
Park, C.-H., Jagdhuber, T., Colliander, A., Lee, J., Berg, A., Cosh, M., Kim,
S.-B., Kim, Y., and Wulfmeyer, V.: Parameterization of Vegetation Scattering
Albedo in the Tau-Omega Model for Soil Moisture Retrieval on Croplands,
Remote Sens., 12, https://doi.org/10.20944/preprints202007.0717.v1, 2020. a
Parrens, M., Zakharova, E., Lafont, S., Calvet, J.-C., Kerr, Y., Wagner, W.,
and Wigneron, J.-P.: Comparing soil moisture retrievals from SMOS and ASCAT
over France, Hydrol. Earth Syst. Sci., 16, 423–440, https://doi.org/10.5194/hess-16-423-2012, 2012. a, b, c
Paulik, C., Dorigo, W., Wagner, W., and Kidd, R.: Validation of the ASCAT Soil Water Index using in situ data from the International Soil Moisture Network, Int. J. Appl. Earth Obs. Geoinf., 30, 1–8, https://doi.org/10.1016/j.jag.2014.01.007, 2014. a, b, c
Peel, M. C., Finlayson, B. L., and McMahon, T. A.: Updated world map of the Köppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633–1644, https://doi.org/10.5194/hess-11-1633-2007, 2007. a
Peischl, S., Walker, J. P., Rüdiger, C., Ye, N., Kerr, Y. H., Kim, E., Bandara, R., and Allahmoradi, M.: The AACES field experiments: SMOS calibration and validation across the Murrumbidgee River catchment, Hydrol. Earth Syst. Sci., 16, 1697–1708, https://doi.org/10.5194/hess-16-1697-2012, 2012. a
Pellarin, T., de Rosnay, P., Albergel, C., Abdalla, S., and al Bitar, A.:
Root-zone soil moisture index complementary validation at global scale based
on triple collocation method. Comparison with State-OfThe-Art global scale
root-zone soil moisture products, in: H-SAF Visiting Scientist Program
HSAF_CDOP2_VS12_02, semanticscholar, available at: https://www.semanticscholar.org/paper/CDOP-2-_-VS-12-_-02-Root-zone-soil-moisture-index-.-Pellarin-Rosnay/b6b862c72ebd8862798516e4b3ce089d55a9b083 (last access: 1 November 2021), 2013. a, b, c, d
Peng, J., Loew, A., Merlin, O., and Verhoest, N. E. C.: A review of spatial
downscaling of satellite remotely sensed soil moisture: Downscale Satellite-Based Soil Moisture, Rev. Geophys., 55, 341–366, https://doi.org/10.1002/2016RG000543, 2017. a
Petropoulos, G. P. and McCalmont, J. P.: An operational in situ soil moisture & soil temperature monitoring network for West Wales, UK: The WSMN network, Sensors, 17, 1481, https://doi.org/10.3390/s17071481, 2017. a, b
Petropoulos, G. P., Ireland, G., Srivastava, P. K., and Ioannou-Katidis, P.: An appraisal of the accuracy of operational soil moisture estimates from SMOS
MIRAS using validated in situ observations acquired in a Mediterranean
environment, Int. J. Remote Sens., 35, 5239–5250, https://doi.org/10.1080/2150704X.2014.933277, 2014. a
Pierdicca, N., Pulvirenti, L., and Fascetti, F.: Multitemporal soil moisture retrieval from 3-days ERS-2 data: Comparison with ASCAT, SMOS and in situ measurements, in: 34th annual IGARSS symposium, 13–18 July 2014, Quebec City, Canada, 2459–2462, https://doi.org/10.1109/IGARSS.2014.6946970, 2014. a, b, c
Pierdicca, N., Fascetti, F., Pulvirenti, L., Crapolicchio, R., and
Muñoz Sabater, J.: Quadruple Collocation Analysis for Soil Moisture Product Assessment, IEEE Geosci. Remote Sens. Lett., 12, 1595–1599, https://doi.org/10.1109/LGRS.2015.2414654, 2015a. a, b, c
Pierdicca, N., Fascetti, F., Pulvirenti, L., Crapolicchio, R., and
Muñoz-Sabater, J.: Analysis of ASCAT, SMOS, in-situ and land model soil
moisture as a regionalized variable over Europe and North Africa, Remote Sens. Environ., 170, 280–289, https://doi.org/10.1016/j.rse.2015.09.005, 2015b. a, b, c, d
Pierdicca, N., Fascetti, F., Pulvirenti, L., and Crapolicchio, R.: Error Characterization of Soil Moisture Satellite Products: Retrieving Error
Cross-Correlation Through Extended Quadruple Collocation, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 10, 4522–4530, https://doi.org/10.1109/JSTARS.2017.2714025, 2017. a, b, c
Piles, M., Petropoulos, G. P., Sánchez, N., Ángel González-Zamora, and Ireland, G.: Towards improved spatio-temporal resolution soil moisture retrievals from the synergy of SMOS and MSG SEVIRI spaceborne observations, Remote Sens. Environ., 180, 403–417,
https://doi.org/10.1016/j.rse.2016.02.048, 2016. a, b
Piles, M., Ballabrera-Poy, J., and Muñoz-Sabater, J.: Dominant features of global surface soil moisture variability observed by the SMOS satellite,
Remote Sens., 11, 95, https://doi.org/10.3390/rs11010095, 2019. a
Portal, G., Jagdhuber, T., Vall-llossera, M., Camps, A., Pablos, M., Entekhabi, D., and Piles, M.: Assessment of Multi-Scale SMOS and SMAP Soil Moisture Products across the Iberian Peninsula, Remote Sens., 12, 570,
https://doi.org/10.3390/rs12030570, 2020. a, b
Pratola, C., Barrett, B., Gruber, A., and Dwyer, E.: Quality Assessment of the CCI ECV Soil Moisture Product Using ENVISAT ASAR Wide Swath Data over Spain, Ireland and Finland, Remote Sens., 7, 15388–15423, https://doi.org/10.3390/rs71115388, 2015. a
Preimesberger, W.: Validation of C3S v202012 vs C3S v201912 vs ISMN 20210131 global, Zenodo [data set], https://doi.org/10.5281/zenodo.4736927, 2021. a
Preimesberger, W., Buttinger, P., Paulik, C., Scanlon, T., Aberer, D., Schmitzer, M., Baum, D., Zappa, L., Hahn, S., and Crezee, B.: TUW-GEO/ismn: v1.1.0, Zenodo [data set], https://doi.org/10.5281/zenodo.5095509, 2021. a
Przeździecki, K., Zawadzki, J., Cieszewski, C., and Bettinger, P.:
Estimation of soil moisture across broad landscapes of Georgia and South
Carolina using the triangle method applied to MODIS satellite imagery, Silva
Fennica, 51, 1683, https://doi.org/10.14214/sf.1683, 2017. a
Qin, M., Giménez, D., and Miskewitz, R.: Temporal dynamics of subsurface
soil water content estimated from surface measurement using wavelet transform, J. Hydrol., 563, 834–850, https://doi.org/10.1016/j.jhydrol.2018.06.023, 2018. a
Raffelli, G., Id, M., Previati, M., Id, D., Canone, D., Gisolo, D., Bevilacqua, I., Capello, G., Biddoccu, M., Cavallo, E., Id, R., Deiana, R., Id, G., Cassiani, G., and Ferraris, S.: Local-and Plot-Scale Measurements of Soil Moisture: Time and Spatially Resolved Field Techniques in Plain, Hill and Mountain Sites, Water, 9, 706, https://doi.org/10.3390/w9090706, 2018. a
Rains, D., Han, X., Lievens, H., Montzka, C., and Verhoest, N.: SMOS brightness temperature assimilation into the Community Land Model, Hydrol. Earth Syst. Sci., 21, 5929–5951, https://doi.org/10.5194/hess-21-5929-2017, 2017. a
Ramsauer, T., Weiß, T., Löw, A., and Marzahn, P.: RADOLAN_API: An Hourly Soil Moisture Data Set Based on Weather Radar, Soil Properties and Reanalysis Temperature Data, Remote Sens., 13, 1712, https://doi.org/10.3390/rs13091712, 2021. a
Raoult, N., Ottlé, C., Peylin, P., Bastrikov, V., and Maugis, P.:
Evaluating and Optimizing Surface Soil Moisture Drydowns in the ORCHIDEE Land
Surface Model at In Situ Locations, J. Hydrometeorol., 22, 1025–1043, https://doi.org/10.1175/JHM-D-20-0115.1, 2021. a
Rautiainen, K., Parkkinen, T., Lemmetyinen, J., Schwank, M., Wiesmann, A.,
Ikonen, J., Derksen, C., Davydov, S., Davydova, A., Boike, J., Langer, M.,
Drusch, M., and Pulliainen, J.: SMOS prototype algorithm for detecting autumn
soil freezing, Remote Sens. Environ., 180, 346–360, https://doi.org/10.1016/j.rse.2016.01.012, 2016. a, b
Reichle, R. H., Koster, R. D., Dong, J., and Berg, A. A.: Global Soil Moisture from Satellite Observations, Land Surface Models, and Ground Data:
Implications for Data Assimilation, J. Hydrometeorol., 5, 430–442, https://doi.org/10.1175/1525-7541(2004)005<0430:GSMFSO>2.0.CO;2, 2004. a
Reichle, R. H., Draper, C. S., Liu, Q., Girotto, M., Mahanama, S. P. P.,
Koster, R. D., and De Lannoy, G. J. M.: Assessment of MERRA-2 Land Surface
Hydrology Estimates, J. Climate, 30, 2937–2960, https://doi.org/10.1175/JCLI-D-16-0720.1, 2017. a, b
Reimer, A. C., Melzer, B. T., Kidd, C. R., and Wagner, D. W.: Validation of the enhanced resolution ERS-2 scatterometer soil moisture product, in: 2012 IEEE International Geoscience and Remote Sensing Symposium, 22–27 July 2012, Munich, Germany, 1208–1211, https://doi.org/10.1109/IGARSS.2012.6351330, 2012. a
Rinollo, A., Vulpiani, G., Puca, S., Pagliara, P., Kaňák, J., Labo,
E., Okon, L., Roulin, E., Baguis, P., Cattani, E., Laviola, S., and Levizzani, V.: Definition and impact of a quality index for radar-based
reference measurements in the H-SAF precipitation product validation, Nat. Hazards Earth Syst. Sci., 13, 2695–2705, https://doi.org/10.5194/nhess-13-2695-2013, 2013. a
Robinson, D. A., Campbell, C. S., Hopmans, J. W., Hornbuckle, B. K., Jones,
S. B., Knight, R., Ogden, F., Selker, J., and Wendroth, O.: Soil Moisture
Measurement for Ecological and Hydrological Watershed-Scale Observatories: A
Review, Vadose Zone J., 7, 358–389, https://doi.org/10.2136/vzj2007.0143, 2008. a
Rodionova, N.: Correlation of the Sentinel 1 Radar Data with Ground-Based
Measurements of the Soil Temperature and Moisture, Izvest. Atmos. Ocean. Phys., 55, 939–948, 2019a. a
Rodionova, N. V.: Backscattering from the near-surface layer of Thawed/Frozen
Soils of Alaska from Sentinel 1 Radar Data, Rensit, 11, 21–30,
https://doi.org/10.17725/rensit.2019.11.021, 2019b. a, b
Rodriguez-Fernandez, N., Aires, F., Richaume, P., Kerr, Y., Prigent, C.,
Kolassa, J., Cabot, F., Jimenez, C., Mahmoodi, A., and Drusch, M.: Soil
Moisture Retrieval Using Neural Networks: Application to SMOS, IEEE T. Geosci. Remote, 53, 5991–6007, https://doi.org/10.1109/TGRS.2015.2430845, 2015. a, b
Rodriguez-Fernandez, N., de Rosnay, P., Albergel, C., Richaume, P., Aires, F., Prigent, C., and Kerr, Y.: SMOS Neural Network Soil Moisture Data
Assimilation in a Land Surface Model and Atmospheric Impact, Remote Sens.,
11, 1334, https://doi.org/10.3390/rs11111334, 2019. a, b
Romano, N.: Soil moisture at local scale: Measurements and simulations, J. Hydrol., 516, 6–20, https://doi.org/10.1016/j.jhydrol.2014.01.026, 2014. a, b, c
Rüdiger, C., Hancock, G., Hemakumara, H., Jacobs, B., Kalma, J., Martinez, C., Thyer, M., Walker, J., Wells, T., and Willgoose, G.: Goulburn
River experimental catchment data set, Water Resour. Res., 43, W10403,
https://doi.org/10.1029/2006WR005837, 2007. a, b
Sadeghi, M., Gao, L., Ebtehaj, A., Wigneron, J.-P., Crow, W. T., Reager, J. T., and Warrick, A. W.: Retrieving global surface soil moisture from GRACE
satellite gravity data, J. Hydrol., 584, 124717, https://doi.org/10.1016/j.jhydrol.2020.124717, 2020. a
Sadri, S., Pan, M., Wada, Y., Vergopolan, N., Sheffield, J., Famiglietti, J. S., Kerr, Y., and Wood, E.: A global near-real-time soil moisture index monitor for food security using integrated SMOS and SMAP, Remote Sens. Environ., 246, 111864, https://doi.org/10.1016/j.rse.2020.111864, 2020. a, b, c
Sanchez, N., Martinez-Fernandez, J., Scaini, A., and Perez-Gutierrez, C.: Validation of the SMOS L2 Soil Moisture Data in the REMEDHUS Network
(Spain), IEEE T. Geosci. Remote, 50, 1602–1611,
https://doi.org/10.1109/TGRS.2012.2186971, 2012. a
Santi, E., Paloscia, S., Pettinato, S., Brocca, L., and Ciabatta, L.: Robust Assessment of an Operational Algorithm for the Retrieval of Soil Moisture From AMSR-E Data in Central Italy, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 9, 2478–2492, 2016. a
Santi, E., Paloscia, S., Pettinato, S., Brocca, L., Ciabatta, L., and
Entekhabi, D.: Integration of microwave data from SMAP and AMSR2 for soil
moisture monitoring in Italy, Remote Sens. Environ., 212, 21–30,
https://doi.org/10.1016/j.rse.2018.04.039, 2018. a, b
Sawada, Y.: Quantifying Drought Propagation from Soil Moisture to Vegetation
Dynamics Using a Newly Developed Ecohydrological Land Reanalysis, Remote Sens., 10, 1197, https://doi.org/10.3390/rs10081197, 2018. a
Scaini, A., Sánchez, N., Vicente-Serrano, S. M., and Martínez-Fernández, J.: SMOS-derived soil moisture anomalies and
drought indices: a comparative analysis using in situ measurements, Hydrol. Process., 29, 373–383, https://doi.org/10.1002/hyp.10150, 2015. a, b
Scanlon, T.: Validation of ESA CCI SM combined v04.7 vs ESA CCI SM combined v05.2 vs ISMN 20191211 global, Zenodo [data set], https://doi.org/10.5281/zenodo.4120205, 2020. a
Scanlon, T., Dorigo, W., Baum, D., Preimesberger, W., Buttinger, P., Bakcsa, Z., van der Schalie, R., Reimer, C., Hirschi, M., Kidd, R., de Jeu, R., and Boresch, A.: ESA CCI and C3S Soil Moisture-Recent advances and quality assurance based on the online validation platform QA4SM, in: EGU General Assembly Conference Abstracts, EGU General Assembly Conference Abstracts, p. 14629, available at: https://ui.adsabs.harvard.edu/abs/2019EGUGA..2114629S (last access: 1 November 2021), 2019. a, b
Schaefer, G., Cosh, M., and Jackson, T.: The USDA natural resources conservation service soil climate analysis network (SCAN), J. Atmos. Ocean. Tech., 24, 2073–2077, https://doi.org/10.1175/2007JTECHA930.1, 2007. a
Schellekens, J., Dutra, E., Martínez-de la Torre, A., Balsamo, G., van Dijk, A., Sperna Weiland, F., Minvielle, M., Calvet, J.-C., Decharme, B.,
Eisner, S., Fink, G., Flörke, M., Peßenteiner, S., van Beek, R.,
Polcher, J., Beck, H., Orth, R., Calton, B., Burke, S., Dorigo, W., and
Weedon, G. P.: A global water resources ensemble of hydrological models: the
eartH2Observe Tier-1 dataset, Earth Syst. Sci. Data, 9, 389–413,
https://doi.org/10.5194/essd-9-389-2017, 2017. a
Schlenz, F., dall'Amico, J. T., Loew, A., and Mauser, W.: Uncertainty
Assessment of the SMOS Validation in the Upper Danube Catchment, IEEE T. Geosci. Remote, 50, 1517–1529, 2012a. a
Schlenz, F., dall'Amico, J. T., Mauser, W., and Loew, A.: Analysis of SMOS
brightness temperature and vegetation optical depth data with coupled land
surface and radiative transfer models in Southern Germany, Hydrol. Earth Syst. Sci., 16, 3517–3533, https://doi.org/10.5194/hess-16-3517-2012, 2012b. a
Scholze, M., Kaminski, T., Knorr, W., Blessing, S., Vossbeck, M., Grant, J.,
and Scipal, K.: Simultaneous assimilation of SMOS soil moisture and
atmospheric CO2 in-situ observations to constrain the global terrestrial carbon cycle, Remote Sens. Environ., 180, 334–345,
https://doi.org/10.1016/j.rse.2016.02.058, 2016. a, b
Senanayake, I., Yeo, I.-Y., Tangdamrongsub, N., Willgoose, G., Hancock, G.,
Wells, T., Fang, B., Lakshmi, V., and Walker, J.: An in-situ data based model
to downscale radiometric satellite soil moisture products in the Upper Hunter
Region of NSW, Australia, J. Hydrol., 572, 820–838,
https://doi.org/10.1016/j.jhydrol.2019.03.014, 2019. a
Senyurek, V., Lei, F., Boyd, D., Kurum, M., Gurbuz, A. C., and Moorhead, R.:
Machine Learning-Based CYGNSS Soil Moisture Estimates over ISMN sites in
CONUS, Remote Sens., 12, 1168, https://doi.org/10.3390/rs12071168, 2020. a
Shin, Y., Lim, K., Park, K., and Jung, Y.: Development of Dynamic Ground Water Data Assimilation for Quantifying Soil Hydraulic Properties from Remotely Sensed Soil Moisture, Water, 8, 311, https://doi.org/10.3390/w8070311, 2016. a
Shin, Y., Mohanty, B. P., and Ines, A. V.: Development of non-parametric
evolutionary algorithm for predicting soil moisture dynamics, J. Hydrol., 564, 208–221, https://doi.org/10.1016/j.jhydrol.2018.07.003, 2018. a
Shuman, D. I., Nayyar, A., Mahajan, A., Goykhman, Y., Li, K., Liu, M., Teneketzis, D., Moghaddam, M., and Entekhabi, D.: Measurement Scheduling for Soil Moisture Sensing: From Physical Models to Optimal Control, Proc. IEEE, 98, 1918–1933, https://doi.org/10.1109/JPROC.2010.2052532, 2010. a
Skierucha, W., Sławiński, C., Wilczek, A., Żyromski, A., and Biniak-Pieróg, M.: Telemetric system for the measurement of soil moisture based on the TDR technique, Woda Środowisko Obszary Wiejskie, 12, 257–267, 2012a. a
Skierucha, W., Wilczek, A., Szypłowska, A., Sławiński, C., and Lamorski, K.: A TDR-Based Soil Moisture Monitoring System with Simultaneous Measurement of Soil Temperature and Electrical Conductivity, Sensors, 12, 13545–13566, https://doi.org/10.3390/s121013545, 2012b. a
Smith, A., Walker, J., Western, A., Young, R., Ellett, K., Pipunic, R.,
Grayson, R., Siriwardena, L., Chiew, F., and Richter, H.: The Murrumbidgee
Soil Moisture Monitoring Network data set, Water Resour. Res., 48,
W07701, https://doi.org/10.1029/2012WR011976, 2012. a
Solander, K. C., Newman, B. D., Carioca de Araujo, A., Barnard, H. R., Berry,
Z. C., Bonal, D., Bretfeld, M., Burban, B., Antonio Candido, L., Célleri,
R., Chambers, J. Q., Christoffersen, B. O., Detto, M., Dorigo, W. A., Ewers,
B. E., José Filgueiras Ferreira, S., Knohl, A., Leung, L. R., McDowell,
N. G., Miller, G. R., Terezinha Ferreira Monteiro, M., Moore, G. W.,
Negron-Juarez, R., Saleska, S. R., Stiegler, C., Tomasella, J., and Xu, C.:
The pantropical response of soil moisture to El Niño, Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, 2020. a, b, c
Steele-Dunne, S. C., Hahn, S., Wagner, W., and Vreugdenhil, M.: Towards
Including Dynamic Vegetation Parameters in the EUMETSAT H SAF ASCAT Soil
Moisture Products, Remote Sens., 13, 1463, https://doi.org/10.3390/rs13081463, 2021. a
Su, C.-H., Narsey, S. Y., Gruber, A., Xaver, A., Chung, D., Ryu, D., and
Wagner, W.: Evaluation of post-retrieval de-noising of active and passive
microwave satellite soil moisture, Remote Sens. Environ., 163, 127–139, https://doi.org/10.1016/j.rse.2015.03.010, 2015. a, b
Su, C.-H., Ryu, D., Dorigo, W., Zwieback, S., Gruber, A., Albergel, C.,
Reichle, R. H., and Wagner, W.: Homogeneity of a global multisatellite soil
moisture climate data record, Geophys. Res. Lett., 43, 11245–11252, https://doi.org/10.1002/2016GL070458, 2016. a
Su, Y., Chen, X., Su, H., Liu, L., and Liao, J.: Digitizing the thermal and
hydrological parameters of land surface in subtropical China using AMSR-E
brightness temperatures, Int. J. Digit. Earth, 10, 687–700, https://doi.org/10.1080/17538947.2016.1247472, 2017. a
Su, Z., Wen, J., Dente, L., van der Velde, R., Wang, L., Ma, Y., Yang, K., and Hu, Z.: The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) for quantifying uncertainties in coarse resolution satellite and model products, Hydrol. Earth Syst. Sci., 15, 2303–2316, https://doi.org/10.5194/hess-15-2303-2011, 2011. a, b, c
Suman, S., Srivastava, P. K., Petropoulos, G. P., Pandey, D. K., and O'Neill, P. E.: Appraisal of SMAP Operational Soil Moisture Product from a Global Perspective, Remote Sens., 12, 1977, https://doi.org/10.3390/rs12121977, 2020. a
Sun, H. and Cui, Y.: Evaluating Downscaling Factors of Microwave Satellite Soil Moisture Based on Machine Learning Method, Remote Sens., 13, 133, https://doi.org/10.3390/rs13010133, 2021. a, b
Sun, H., Zhou, B., Zhang, C., Liu, H., and Yang, B.: DSCALE_mod16: A Model for Disaggregating Microwave Satellite Soil Moisture with Land Surface
Evapotranspiration Products and Gridded Meteorological Data, Remote Sens., 12, 980, https://doi.org/10.3390/rs12060980, 2020. a
Sure, A., Varade, D., and Dikshit, O.: Factors determining spatio-temporal variations of soil moisture using microwave data, in: 2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT), 17–18 November 2017, Dehradun, India, 1–5, https://doi.org/10.1109/ICETCCT.2017.8280301, 2017. a, b
Szczypta, C., Calvet, J.-C., Maignan, F., Dorigo, W., Baret, F., and Ciais, P.: Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts, Geosci. Model Dev., 7,
931–946, https://doi.org/10.5194/gmd-7-931-2014, 2014. a
Tagesson, T., Fensholt, R., Guiro, I., Rasmussen, M., Huber, S., Mbow, C.,
Garcia, M., Horion, S., Sandholt, I., Holm-Rasmussen, B., Göttsche, F.-M., Ridler, M., Boke-Olén, N., Olsen, J., Ehammer, A., Madsen, M.,
Olesen, F., and Ardö, J.: Ecosystem properties of semi-arid savanna
grassland in West Africa and its relationship to environmental variability,
Global Change Biol., 21, 250–264, https://doi.org/10.1111/gcb.12734, 2014. a
Tagesson, T., Horion, S., Nieto, H., Zaldo Fornies, V., Mendiguren González, G., Bulgin, C., Ghent, D., and Fensholt, R.: Disaggregation of SMOS soil moisture over West Africa using the Temperature and Vegetation Dryness Index based on SEVIRI land surface parameters, Remote Sens. Environ., 206, 424–441, https://doi.org/10.1016/j.rse.2017.12.036, 2018. a, b
Teuling, A. J., Uijlenhoet, R., Hupet, F., van Loon, E. E., and Troch, P. A.: Estimating spatial mean root-zone soil moisture from point-scale observations, Hydrol. Earth Syst. Sci., 10, 755–767, https://doi.org/10.5194/hess-10-755-2006, 2006. a
Tian, J., Zhang, B., He, C., Han, Z., Bogena, H. R., and Huisman, J. A.:
Dynamic response patterns of profile soil moisture wetting events under
different land covers in the Mountainous area of the Heihe River Watershed,
Northwest China, Agr. Forest Meteorol., 271, 225–239, 2019. a
Tian, S.: Monitoring and forecasting drought through the assimilation of
satellite water observations, PhD thesis, Research School of Earth Sciences, The Australian National University, available at: https://openresearch-repository.anu.edu.au/handle/1885/157222 (last access: 1 November 2021), 2018. a
Tian, S., Renzullo, L. J., van Dijk, A. I. J. M., Tregoning, P., and Walker,
J. P.: Global joint assimilation of GRACE and SMOS for improved estimation of
root-zone soil moisture and vegetation response, Hydrol. Earth Syst. Sci., 23, 1067–1081, https://doi.org/10.5194/hess-23-1067-2019, 2019. a
Tobin, K. J., Torres, R., Crow, W. T., and Bennett, M. E.: Multi-decadal
analysis of root-zone soil moisture applying the exponential filter across
CONUS, Hydrol. Earth Syst. Sci., 21, 4403–4417, https://doi.org/10.5194/hess-21-4403-2017, 2017. a, b, c
Vachaud, G., Passerat De Silans, A., Balabanis, P., and Vauclin, M.: Temporal
Stability of Spatially Measured Soil Water Probability Density Function, Soil
Sci. Soc. Am. J., 49, 822–828, https://doi.org/10.2136/sssaj1985.03615995004900040006x, 1985. a
Van Cleve, K., Chapin, F. S. S., and Ruess, R. W.: Bonanza Creek Long Term
Ecological Research Project Climate Database, University of Alaska,
Fairbanks, available at: http://www.lter.uaf.edu/ (last access: 3 November 2021), 2015. a
van der Schalie, R., Kerr, Y., Wigneron, J., Rodríguez-Fernández, N., Al-Yaari, A., and Jeu, R.: Global SMOS Soil Moisture Retrievals from The
Land Parameter Retrieval Model, Int. J. Appl. Earth Obs. Geoinf., 45, 125–134, https://doi.org/10.1016/j.jag.2015.08.005, 2016. a
van der Schalie, R., de Jeu, R., Kerr, Y., Wigneron, J., Rodríguez-Fernández, N., Al-Yaari, A., Parinussa, R., Mecklenburg, S., and Drusch, M.: The merging of radiative transfer based surface soil moisture data from SMOS and AMSR-E, Remote Sens. Environ., 189, 180–193, https://doi.org/10.1016/j.rse.2016.11.026, 2017. a, b
van der Schalie, R., de Jeu, R., Parinussa, R., Rodríguez-Fernández, N., Kerr, Y., Al-Yaari, A., Wigneron, J.-P., and Drusch, M.: The Effect of Three Different Data Fusion Approaches on the Quality of Soil Moisture Retrievals from Multiple Passive Microwave Sensors, Remote Sens., 10, 107, https://doi.org/10.3390/rs10010107, 2018. a, b
van der Schalie, R., van der Vliet, M., Rodríguez-Fernández, N.,
Dorigo, W. A., Scanlon, T., Preimesberger, W., Madelon, R., and de Jeu, R. A. M.: L-Band Soil Moisture Retrievals Using Microwave Based Temperature and
Filtering. Towards Model-Independent Climate Data Records, Remote Sens., 13, 2480, https://doi.org/10.3390/rs13132480, 2021. a, b, c
Van doninck, J., Peters, J., Lievens, H., De Baets, B., and Verhoest, N.:
Accounting for seasonality in a soil moisture change detection algorithm for
ASAR Wide Swath time series, Hydrol. Earth Syst. Sci., 16, 773–786, https://doi.org/10.5194/hess-16-773-2012, 2012. a
Verrier, S.: Multifractal and multiscale entropy scaling of in-situ soil
moisture time series: Study of SMOSMANIA network data, southwestern France, J. Hydrol., 585, 124821, https://doi.org/10.1016/j.jhydrol.2020.124821, 2020. a
Vicente-Serrano, S. M., Beguería, S., Lorenzo-Lacruz, J., Camarero, J. J., López-Moreno, J. I., Azorin-Molina, C., Revuelto, J., Morán-Tejeda, E., and Sanchez-Lorenzo, A.: Performance of Drought Indices for Ecological, Agricultural, and Hydrological Applications, Earth Interact., 16, 1–27, https://doi.org/10.1175/2012EI000434.1, 2012. a
Vreugdenhil, M., Dorigo, W., Broer, M., Haas, P., Eder, A., Hogan, P., Bloeschl, G., and Wagner, W.: Towards a high-density soil moisture network for the validation of SMAP in Petzenkirchen, Austria, in: 2013 IEEE International Geoscience and Remote Sensing Symposium – IGARSS, 21–26 July 2013, Melbourne, VIC, Australia, 1865–1868, https://doi.org/10.1109/IGARSS.2013.6723166, 2013. a
Wanders, N., Karssenberg, D., Bierkens, M., Parinussa, R., de Jeu, R., van Dam, J., and de Jong, S.: Observation uncertainty of satellite soil moisture products determined with physically-based modeling, Remote Sens.
Environ., 127, 341–356, https://doi.org/10.1016/j.rse.2012.09.004, 2012. a, b, c
Wang, L., Li, X., Chen, Y., Yang, K., Chen, D., Zhou, J., Liu, W., Qi, J., and Huang, J.: Validation of the global land data assimilation system based on measurements of soil temperature profiles, Agr. Forest Meteorol., 218–219, 288–297, https://doi.org/10.1016/j.agrformet.2016.01.003, 2016. a
Wang, L., He, B., Bai, X., and Xing, M.: Assessment of different vegetation
parameters for parameterizing the coupled water cloud model and advanced
integral equation model for soil moisture retrieval using time series
Sentinel-1A data, Photogram. Eng. Remote Sens., 85, 43–54, 2019a. a
Wang, L., Xie, Z., Jia, B., Xie, J., Wang, Y., Liu, B., Li, R., and Chen, S.:
Contributions of climate change and groundwater extraction to soil moisture
trends, Earth Syst. Dynam., 10, 599–615, https://doi.org/10.5194/esd-10-599-2019, 2019b. a
Wang, L., Fang, S., Pei, Z., Zhu, Y., Khoi, D. N., and Han, W.: Using
FengYun-3C VSM Data and Multivariate Models to Estimate Land Surface Soil
Moisture, Remote Sens., 12, 1038, https://doi.org/10.3390/rs12061038, 2020. a
Wang, R., Zhu, Q., Ma, H., and Wang, Y.: Spatial and temporal variations of the surface soil moisture in the source re-gion of the Yellow River from 2003 to 2010 based on AMSR-E[J], Sci. Soil Water Conserv., 15, 22–32, https://doi.org/10.16843/j.sswc.2017.01.004, 2017, 2017. a
Wang, T., Franz, T. E., Li, R., You, J., Shulski, M. D., and Ray, C.:
Evaluating climate and soil effects on regional soil moisture spatial
variability using EOFs, Water Resour. Res., 53, 4022–4035,
https://doi.org/10.1002/2017WR020642, 2017. a
Wang, Y., Yang, J., Chen, Y., Fang, G., Duan, W., Li, Y., and De Maeyer, P.:
Quantifying the Effects of Climate and Vegetation on Soil Moisture in an Arid
Area, China, Water, 11, 767, https://doi.org/10.3390/w11040767, 2019. a
Wang, Y., Shi, L., Lin, L., Holzman, M., Carmona, F., and Zhang, Q.: A robust
data-worth analysis framework for soil moisture flow by hybridizing sequential data assimilation and machine learning, Vadose Zone J., 19, e20026, https://doi.org/10.1002/vzj2.20026, 2020. a
Wang, Y., Leng, P., Peng, J., Marzahn, P., and Ludwig, R.: Global assessments
of two blended microwave soil moisture products CCI and SMOPS with in-situ
measurements and reanalysis data, Int. J. Appl.Earth Obs. Geoinf., 94, 102234, https://doi.org/10.1016/j.jag.2020.102234, 2021. a, b
Western, A. W., Grayson, R. B., and Blöschl, G.: Scaling of Soil Moisture: A Hydrologic Perspective, Annu. Rev. Earth Planet. Sci., 30, 149–180, https://doi.org/10.1146/annurev.earth.30.091201.140434, 2002. a
Wigneron, J.-P., Dayan, S., Kruszewski, A., Aluome, C., Al-Yaari, A., Fan, L., Guven, S., Chipeaux, C., Moisy, C., Guyon, D., and Loustau, D.: The Aqui
Network: Soil Moisture Sites in the “Les Landes” Forest and Graves
Vineyards (Bordeaux Aquitaine Region, France), in: IGARSS 2018 – 2018 IEEE International Geoscience and Remote Sensing Symposium, 22–27 Juy 2018, Valencia, Spain, 3739–3742, https://doi.org/10.1109/IGARSS.2018.8517392, 2018. a
Wigneron, J.-P., Li, X., Frappart, F., Fan, L., Al-Yaari, A., De Lannoy, G.,
Liu, X., Wang, M., Le Masson, E., and Moisy, C.: SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives, Remote Sens. Environ., 254, 112238, https://doi.org/10.1016/j.rse.2020.112238, 2021. a
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M.,
Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E.,
Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O.,
Edmunds, S., Evelo, C. T., Finkers, R., Gonzalez-Beltran, A., Gray, A. J.,
Groth, P., Goble, C., Grethe, J. S., Heringa, J., 't Hoen, P. A., Hooft, R.,
Kuhn, T., Kok, R., Kok, J., Lusher, S. J., Martone, M. E., Mons, A., Packer,
A. L., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R., Sansone, S.-A., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz, M. A.,
Thompson, M., van der Lei, J., van Mulligen, E., Velterop, J., Waagmeester,
A., Wittenburg, P., Wolstencroft, K., Zhao, J., and Mons, B.: The FAIR Guiding Principles for scientific data management and stewardship, Scient.
Data, 3, 160018, https://doi.org/10.1038/sdata.2016.18, 2016. a
Wu, K., Ryu, D., Nie, L., and Shu, H.: Time-variant error characterization of
SMAP and ASCAT soil moisture using Triple Collocation Analysis, Remote Sens. Environ., 256, 112324, https://doi.org/10.1016/j.rse.2021.112324, 2021. a, b, c, d
Wu, M., Scholze, M., Voßbeck, M., Kaminski, T., and Hoffmann, G.:
Simultaneous Assimilation of Remotely Sensed Soil Moisture and FAPAR for
Improving Terrestrial Carbon Fluxes at Multiple Sites Using CCDAS, Remote
Sens., 11, 27, https://doi.org/10.3390/rs11010027, 2018. a
Wu, Q., Liu, H., Wang, L., and Deng, C.: Evaluation of AMSR2 soil moisture
products over the contiguous United States using in situ data from the
International Soil Moisture Network, Int. J. Appl. Earth Obs. Geoinf., 45, 187–199, https://doi.org/10.1016/j.jag.2015.10.011, 2016. a
Xaver, A., Zappa, L., Rab, G., Pfeil, I., Vreugdenhil, M., Hemment, D., and Dorigo, W. A.: Evaluating the suitability of the consumer low-cost Parrot Flower Power soil moisture sensor for scientific environmental applications, Geosci. Instrum. Method. Data Syst., 9, 117–139, https://doi.org/10.5194/gi-9-117-2020, 2020. a, b, c, d, e, f
Xia, Y., Ford, T. W., Wu, Y., Quiring, S. M., and Ek, M. B.: Automated Quality Control of In Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products, J. Appl. Meteorol. Clim., 54, 1267–1282, https://doi.org/10.1175/JAMC-D-14-0275.1, 2015. a
Xia, Y., Hao, Z., Shi, C., Li, Y., Meng, J., Xu, T., Wu, X., and Zhang, B.:
Regional and Global Land Data Assimilation Systems: Innovations, Challenges,
and Prospects, J. Meteorol. Res., 33, 159–189, https://doi.org/10.1007/s13351-019-8172-4, 2019. a, b
Xie, Q., Menenti, M., and Jia, L.: Improving the AMSR-E/NASA Soil Moisture Data Product Using In-Situ Measurements from the Tibetan Plateau, Remote Sens., 11, 2748, https://doi.org/10.3390/rs11232748, 2019. a
Xing, C., Chen, N., Zhang, X., and Gong, J.: A Machine Learning Based
Reconstruction Method for Satellite Remote Sensing of Soil Moisture Images
with In Situ Observations, Remote Sens., 9, 484, https://doi.org/10.3390/rs9050484, 2017. a, b
Xu, H., Yuan, Q., Li, T., Shen, H., Zhang, L., and Jiang, H.: Quality
Improvement of Satellite Soil Moisture Products by Fusing with In-Situ
Measurements and GNSS-R Estimates in the Western Continental U.S., Remote
Sens., 10, 1351, https://doi.org/10.3390/rs10091351, 2018. a, b, c
Yang, K., Qin, J., Zhao, L., Chen, Y., Tang, W., Han, M., Zhu, l., Chen, Z.,
Lv, N., Ding, B., Wu, H., and Lin, C.: A Multi-Scale Soil Moisture and
Freeze-Thaw Monitoring Network on the Third Pole, B. Am. Meteorol. Soc., 94, 1907–1916, https://doi.org/10.1175/BAMS-D-12-00203.1, 2013. a
Yao, P., Shi, J., Zhao, T., Lu, H., and Al-Yaari, A.: Rebuilding Long Time
Series Global Soil Moisture Products Using the Neural Network Adopting the
Microwave Vegetation Index, Remote Sens., 9, 35, https://doi.org/10.3390/rs9010035, 2017. a, b, c
Yin, Z., Ottlé, C., Ciais, P., Guimberteau, M., Wang, X., Zhu, D., Maignan, F., Peng, S., Piao, S., Polcher, J., Zhou, F., Kim, H., and other
China-Trend-Stream project members: Evaluation of ORCHIDEE-MICT-simulated
soil moisture over China and impacts of different atmospheric forcing data,
Hydrol. Earth Syst. Sci., 22, 5463–5484, https://doi.org/10.5194/hess-22-5463-2018, 2018. a
Young, R., Walker, J., Yeoh, N., Smith, A., Ellett, K., Merlin, O., and
Western, A.: Soil moisture and meteorological observations from the
Murrumbidgee catchment, Department of Civil and Environmental Engineering,
The University of Melbourne, Melbourne, 2008. a
Zacharias, S., Bogena, H., Samaniego, L., Mauder, M., Fuß, R., Pütz,
T., Frenzel, M., Schwank, M., Baessler, C., Butterbach-Bahl, K., Bens, O.,
Borg, E., Brauer, A., Dietrich, P., Hajnsek, I., Helle, G., Kiese, R.,
Kunstmann, H., Klotz, S., and Vereecken, H.: A Network of Terrestrial
Environmental Observatories in Germany, Vadose Zone J., 10, 955–973,
https://doi.org/10.2136/vzj2010.0139, 2011. a
Zappa, L., Forkel, M., Xaver, A., and Dorigo, W.: Deriving Field Scale Soil
Moisture from Satellite Observations and Ground Measurements in a Hilly
Agricultural Region, Remote Sens., 11, 2596, https://doi.org/10.3390/rs11222596, 2019. a, b, c
Zawadzki, J. and Kędzior, M.: Soil moisture variability over Odra
watershed: Comparison between SMOS and GLDAS data, Int. J. Appl. Earth Obs. Geoinf., 45, 110–124, https://doi.org/10.1016/j.jag.2015.03.005, 2016. a
Zeng, J., Li, Z., Quan, C., and Bi, H.: A simplified physically-based algorithm for surface soil moisture retrieval using AMSR-E data, Front. Earth Sci., 8, 427–438, https://doi.org/10.1007/s11707-014-0412-4, 2014. a, b
Zeng, J., Chen, K., Bi, H., and Chen, Q.: A Preliminary Evaluation of the SMAP Radiometer Soil Moisture Product Over United States and Europe Using
Ground-Based Measurements, IEEE T. Geosci. Remote, 54, 4929–4940, 2016. a
Zhang, Q., Shi, L., Holzman, M., Ye, M., Wang, Y., Carmona, F., and Zha, Y.: A dynamic data-driven method for dealing with model structural error in soil
moisture data assimilation, Adv. Water Resour., 132, 103407, https://doi.org/10.1016/j.advwatres.2019.103407, 2019. a
Zhang, Q., Yuan, Q., Li, J., Wang, Y., Sun, F., and Zhang, L.: Generating
seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the
years 2013–2019, Earth Syst. Sci. Data, 13, 1385–1401,
https://doi.org/10.5194/essd-13-1385-2021, 2021. a
Zhang, R., Kim, S., and Sharma, A.: A comprehensive validation of the SMAP
Enhanced Level-3 Soil Moisture product using ground measurements over varied
climates and landscapes, Remote Sens. Environ., 223, 82–94, 2019. a
Zhang, R., Kim, S., Sharma, A., and Lakshmi, V.: Identifying relative strengths of SMAP, SMOS-IC, and ASCAT to capture temporal variability, Remote Sens. Environ., 252, 112126, https://doi.org/10.1016/j.rse.2020.112126, 2021. a, b, c
Zhang, S., Calvet, J.-C., Darrozes, J., Roussel, N., Frappart, F., and
Bouhours, G.: Deriving surface soil moisture from reflected GNSS signal
observations from a grassland site in southwestern France, Hydrol. Earth Syst. Sci., 22, 1931–1946, https://doi.org/10.5194/hess-22-1931-2018, 2018. a
Zhang, S., Meurey, C., and Calvet, J.-C.: Identification of soil-cooling rains in southern France from soil temperature and soil moisture observations, Atmos. Chem. Phys., 19, 5005–5020, https://doi.org/10.5194/acp-19-5005-2019, 2019. a
Zhang, X., Chen, N., Chen, Z., Wu, L., Li, X., Zhang, L., Di, L., Gong, J., and Li, D.: Geospatial sensor web: A cyber-physical infrastructure for geoscience research and application, Earth-Sci. Rev., 185, 684–703, 2018. a
Zhao, L. and Yang, Z.-L.: Multi-sensor land data assimilation: Toward a robust global soil moisture and snow estimation, Remote Sens. Environ., 216, 13–27, https://doi.org/10.1016/j.rse.2018.06.033, 2018. a, b
Zhao, L., Yang, Z.-L., and Hoar, T. J.: Global Soil Moisture Estimation by
Assimilating AMSR-E Brightness Temperatures in a Coupled CLM4–RTM–DART
System, J. Hydrometeorol., 17, 2431–2454, https://doi.org/10.1175/JHM-D-15-0218.1, 2016. a
Zhao, T., Shi, J., Lin, M., Yin, X., Liu, Y., Lan, H., and Xiong, C.:
Potential soil moisture product from the Chinese HY-2 scanning microwave
radiometer and its initial assessment, J. Appl. Remote Sens., 8, 1–12, https://doi.org/10.1117/1.JRS.8.083560, 2014. a, b
Zhao, W. and Li, A.: A Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data, Remote Sens., 5, 6790–6811, https://doi.org/10.3390/rs5126790, 2013. a, b
Zhao, W. and Li, A.: A comparison study on empirical microwave soil moisture
downscaling methods based on the integration of microwave-optical/IR data on
the Tibetan Plateau, Int. J. Remote Sens., 36, 4986–5002,
https://doi.org/10.1080/01431161.2015.1041178, 2015. a, b
Zhao, W., Li, A., Jin, H., Zhang, Z., Bian, J., and Yin, G.: Performance Evaluation of the Triangle-Based Empirical Soil Moisture Relationship Models Based on Landsat-5 TM Data and In Situ Measurements, IEEE T. Geosci. Remote, 55, 2632–2645, https://doi.org/10.1109/TGRS.2017.2649522, 2017. a, b
Zhao, W., Sánchez, N., Lu, H., and Li, A.: A spatial downscaling approach
for the SMAP passive surface soil moisture product using random forest regression, J. Hydrol., 563, 1009–1024, https://doi.org/10.1016/j.jhydrol.2018.06.081, 2018. a
Zhu, L., Wang, H., Tong, C., Liu, W., and Du, B.: Evaluation of ESA Active,
Passive and Combined Soil Moisture Products Using Upscaled Ground
Measurements, Sensors, 19, 2718, https://doi.org/10.3390/s19122718, 2019. a
Zreda, M., Desilets, D., Ferré, T., and Scott, R.: Measuring soil moisture content non-invasively at intermediate spatial scale using cosmic-ray neutrons, Geophys. Res. Lett., 35, L21402, https://doi.org/10.1029/2008GL035655, 2008.
a, b
Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T.,
and Rosolem, R.: COSMOS: the COsmic-ray Soil Moisture Observing System,
Hydrol. Earth Syst. Sci., 16, 4079–4099, https://doi.org/10.5194/hess-16-4079-2012, 2012. a, b
Zwieback, S., Dorigo, W., and Wagner, W.: Estimation of the temporal
autocorrelation structure by the collocation technique with an emphasis on
soil moisture studies, Hydrolog. Sci. J., 58, 1729–1747, https://doi.org/10.1080/02626667.2013.839876, 2013. a, b, c
Zwieback, S., Paulik, C., and Wagner, W.: Frozen Soil Detection Based on
Advanced Scatterometer Observations and Air Temperature Data as Part of Soil
Moisture Retrieval, Remote Sens., 7, 3206–3231, https://doi.org/10.3390/rs70303206,
2015. a, b
Zwieback, S., Su, C.-H., Gruber, A., Dorigo, W. A., and Wagner, W.: The Impact of Quadratic Nonlinear Relations between Soil Moisture Products on
Uncertainty Estimates from Triple Collocation Analysis and Two Quadratic
Extensions, J. Hydrometeorol., 17, 1725–1743, https://doi.org/10.1175/JHM-D-15-0213.1, 2016. a
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for...
