Articles | Volume 22, issue 10
https://doi.org/10.5194/hess-22-5341-2018
© Author(s) 2018. 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-22-5341-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Oct 2018
Research article |
| 17 Oct 2018
| 17 Oct 2018
Global downscaling of remotely sensed soil moisture using neural networks
Seyed Hamed Alemohammad
Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
Columbia Water Center, Columbia University, New York, NY, USA
Radiant Earth Foundation, Washington, DC, USA
Jana Kolassa
Universities Space Research Association, Columbia, MD, USA
Global Modelling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Catherine Prigent
Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
Columbia Water Center, Columbia University, New York, NY, USA
Observatoire de Paris, 75014 Paris, France
Filipe Aires
Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
Columbia Water Center, Columbia University, New York, NY, USA
Observatoire de Paris, 75014 Paris, France
Pierre Gentine
CORRESPONDING AUTHOR
Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
Columbia Water Center, Columbia University, New York, NY, USA
Earth Institute, Columbia University, New York, NY, USA
Related authors
Pierre Gentine, Adam Massmann, Benjamin R. Lintner, Sayed Hamed Alemohammad, Rong Fu, Julia K. Green, Daniel Kennedy, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, https://doi.org/10.5194/hess-23-4171-2019, 2019
Short summary
Short summary
Land–atmosphere interactions are key for the exchange of water, energy, and carbon dioxide, especially in the tropics. We here review some of the recent findings on land–atmosphere interactions in the tropics and where we see potential challenges and paths forward.
Yao Zhang, Joanna Joiner, Seyed Hamed Alemohammad, Sha Zhou, and Pierre Gentine
Biogeosciences, 15, 5779–5800, https://doi.org/10.5194/bg-15-5779-2018, https://doi.org/10.5194/bg-15-5779-2018, 2018
Short summary
Short summary
Using satellite reflectance measurements and a machine learning algorithm, we generated a new solar-induced chlorophyll fluorescence (SIF) dataset that is closely linked to plant photosynthesis. This new dataset has higher spatial and temporal resolutions, and lower uncertainty compared to the existing satellite retrievals. We also demonstrated its application in monitoring drought and improving the understanding of the SIF–photosynthesis relationship.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
Short summary
Short summary
Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
R. Obringer, X. Zhang, K. Mallick, S. H. Alemohammad, and D. Niyogi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 747–751, https://doi.org/10.5194/isprs-archives-XLI-B2-747-2016, https://doi.org/10.5194/isprs-archives-XLI-B2-747-2016, 2016
S. H. Alemohammad, K. A. McColl, A. G. Konings, D. Entekhabi, and A. Stoffelen
Hydrol. Earth Syst. Sci., 19, 3489–3503, https://doi.org/10.5194/hess-19-3489-2015, https://doi.org/10.5194/hess-19-3489-2015, 2015
Short summary
Short summary
This paper introduces a new variant of the triple collocation technique with multiplicative error model. The method is applied, for the first time, to precipitation products across the central part of continental USA. Results show distinctive patterns of error variance in each product that are estimated without a priori assumption of any of the error distributions. The correlation coefficients between each product and the truth are also estimated, which provides another performance perspective.
Juliette Bernard, Catherine Prigent, Carlos Jimenez, Etienne Fluet-Chouinard, Bernhard Lehner, Elodie Salmon, Philippe Ciais, Zhen Zhang, Shushi Peng, and Marielle Saunois
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-466, https://doi.org/10.5194/essd-2024-466, 2024
Preprint under review for ESSD
Short summary
Short summary
Wetlands are responsible for about a third of global emissions of methane, a potent greenhouse gas. We have developed the GIEMS-MethaneCentric (GIEMS-MC) dataset to represent the dynamics of wetland extent on a global scale (0.25°x0.25° resolution, monthly time step). This updated resource combines satellite data and existing wetland databases, covering 1992 to 2020. Consistent maps of other methane-emitting surface waters (lakes, rivers, reservoirs, rice paddies) are also provided.
Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
The Cryosphere, 18, 4137–4163, https://doi.org/10.5194/tc-18-4137-2024, https://doi.org/10.5194/tc-18-4137-2024, 2024
Short summary
Short summary
Passive microwave observations from satellites are crucial for monitoring Arctic sea ice and atmosphere. To do this effectively, it is important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we improved our understanding, identified four distinct emission types, and expanded current knowledge to include higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Pilippe Bousquet, Josep G. Canadell, Nick Davidson, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, and Michele Thieme
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-204, https://doi.org/10.5194/essd-2024-204, 2024
Preprint under review for ESSD
Short summary
Short summary
The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies—that is, the maximum extent—covers 18.2 million km2, equivalent to 13.4 % of total global land area.
Jiabo Yin, Louise J. Slater, Abdou Khouakhi, Le Yu, Pan Liu, Fupeng Li, Yadu Pokhrel, and Pierre Gentine
Earth Syst. Sci. Data, 15, 5597–5615, https://doi.org/10.5194/essd-15-5597-2023, https://doi.org/10.5194/essd-15-5597-2023, 2023
Short summary
Short summary
This study presents long-term (i.e., 1940–2022) and high-resolution (i.e., 0.25°) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). Our proposed GTWS-MLrec performs overall as well as, or is more reliable than, previous TWS datasets.
Jatan Buch, A. Park Williams, Caroline S. Juang, Winslow D. Hansen, and Pierre Gentine
Geosci. Model Dev., 16, 3407–3433, https://doi.org/10.5194/gmd-16-3407-2023, https://doi.org/10.5194/gmd-16-3407-2023, 2023
Short summary
Short summary
We leverage machine learning techniques to construct a statistical model of grid-scale fire frequencies and sizes using climate, vegetation, and human predictors. Our model reproduces the observed trends in fire activity across multiple regions and timescales. We provide uncertainty estimates to inform resource allocation plans for fuel treatment and fire management. Altogether the accuracy and efficiency of our model make it ideal for coupled use with large-scale dynamical vegetation models.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
Short summary
Short summary
Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
Short summary
Short summary
Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Thi Lan Anh Dinh and Filipe Aires
Geosci. Model Dev., 15, 3519–3535, https://doi.org/10.5194/gmd-15-3519-2022, https://doi.org/10.5194/gmd-15-3519-2022, 2022
Short summary
Short summary
We proposed the leave-two-out method (i.e. one particular implementation of the nested cross-validation) to determine the optimal statistical crop model (using the validation dataset) and estimate its true generalization ability (using the testing dataset). This approach is applied to two examples (robusta coffee in Cu M'gar and grain maize in France). The results suggested that the simple models are more suitable in crop modelling where a limited number of samples is available.
Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Stephane Calmant, Ayan Santos Fleischmann, Frederic Frappart, Melanie Becker, Mohammad J. Tourian, Catherine Prigent, and Johary Andriambeloson
Hydrol. Earth Syst. Sci., 26, 1857–1882, https://doi.org/10.5194/hess-26-1857-2022, https://doi.org/10.5194/hess-26-1857-2022, 2022
Short summary
Short summary
This study presents a better characterization of surface hydrology variability in the Congo River basin, the second largest river system in the world. We jointly use a large record of in situ and satellite-derived observations to monitor the spatial distribution and different timings of the Congo River basin's annual flood dynamic, including its peculiar bimodal pattern.
Marie Bouillon, Sarah Safieddine, Simon Whitburn, Lieven Clarisse, Filipe Aires, Victor Pellet, Olivier Lezeaux, Noëlle A. Scott, Marie Doutriaux-Boucher, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 1779–1793, https://doi.org/10.5194/amt-15-1779-2022, https://doi.org/10.5194/amt-15-1779-2022, 2022
Short summary
Short summary
The IASI instruments have been observing Earth since 2007. We use a neural network to retrieve atmospheric temperatures. This new temperature data record is validated against other datasets and shows good agreement. We use this new dataset to compute trends over the 2008–2020 period. We found a warming of the troposphere, more important at the poles. In the stratosphere, we found that temperatures decrease everywhere except at the South Pole. The cooling is more pronounced at the South pole.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
Short summary
Short summary
We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Martina Klose, Oriol Jorba, María Gonçalves Ageitos, Jeronimo Escribano, Matthew L. Dawson, Vincenzo Obiso, Enza Di Tomaso, Sara Basart, Gilbert Montané Pinto, Francesca Macchia, Paul Ginoux, Juan Guerschman, Catherine Prigent, Yue Huang, Jasper F. Kok, Ron L. Miller, and Carlos Pérez García-Pando
Geosci. Model Dev., 14, 6403–6444, https://doi.org/10.5194/gmd-14-6403-2021, https://doi.org/10.5194/gmd-14-6403-2021, 2021
Short summary
Short summary
Mineral soil dust is a major atmospheric airborne particle type. We present and evaluate MONARCH, a model used for regional and global dust-weather prediction. An important feature of the model is that it allows different approximations to represent dust, ranging from more simplified to more complex treatments. Using these different treatments, MONARCH can help us better understand impacts of dust in the Earth system, such as its interactions with radiation.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
Short summary
Short summary
Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Ren Wang, Pierre Gentine, Jiabo Yin, Lijuan Chen, Jianyao Chen, and Longhui Li
Hydrol. Earth Syst. Sci., 25, 3805–3818, https://doi.org/10.5194/hess-25-3805-2021, https://doi.org/10.5194/hess-25-3805-2021, 2021
Short summary
Short summary
Assessment of changes in the global water cycle has been a challenge. This study estimated long-term global latent heat and sensible heat fluxes for recent decades using machine learning and ground observations. The results found that the decline in evaporative fraction was typically accompanied by an increase in long-term runoff in over 27.06 % of the global land areas. The observation-driven findings emphasized that surface vegetation has great impacts in regulating water and energy cycles.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
Short summary
Short summary
The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Lise Kilic, Catherine Prigent, Carlos Jimenez, and Craig Donlon
Ocean Sci., 17, 455–461, https://doi.org/10.5194/os-17-455-2021, https://doi.org/10.5194/os-17-455-2021, 2021
Short summary
Short summary
The Copernicus Imaging Microwave Radiometer (CIMR) is one of the high-priority satellite missions of the Copernicus program within the European Space Agency. It is designed to respond to the European Union Arctic policy. Its channels, incidence angle, precisions, and spatial resolutions have been selected to observe the Arctic Ocean with the recommendations expressed by the user communities.
In this note, we present the sensitivity analysis that has led to the choice of the CIMR channels.
Andrew F. Feldman, Daniel J. Short Gianotti, Alexandra G. Konings, Pierre Gentine, and Dara Entekhabi
Biogeosciences, 18, 831–847, https://doi.org/10.5194/bg-18-831-2021, https://doi.org/10.5194/bg-18-831-2021, 2021
Short summary
Short summary
We quantify global plant water uptake durations after rainfall using satellite-based plant water content measurements. In wetter regions, plant water uptake occurs within a day due to rapid coupling between soil and plant water content. Drylands show multi-day plant water uptake after rain pulses, providing widespread evidence for slow rehydration responses and pulse-driven growth responses. Our results suggest that drylands are sensitive to projected shifts in rainfall intensity and frequency.
Manuel Schlund, Axel Lauer, Pierre Gentine, Steven C. Sherwood, and Veronika Eyring
Earth Syst. Dynam., 11, 1233–1258, https://doi.org/10.5194/esd-11-1233-2020, https://doi.org/10.5194/esd-11-1233-2020, 2020
Short summary
Short summary
As an important measure of climate change, the Equilibrium Climate Sensitivity (ECS) describes the change in surface temperature after a doubling of the atmospheric CO2 concentration. Climate models from the Coupled Model Intercomparison Project (CMIP) show a wide range in ECS. Emergent constraints are a technique to reduce uncertainties in ECS with observational data. Emergent constraints developed with data from CMIP phase 5 show reduced skill and higher ECS ranges when applied to CMIP6 data.
Samuel Favrichon, Carlos Jimenez, and Catherine Prigent
Atmos. Meas. Tech., 13, 5481–5490, https://doi.org/10.5194/amt-13-5481-2020, https://doi.org/10.5194/amt-13-5481-2020, 2020
Short summary
Short summary
Long-term monitoring of satellite-derived variables is necessary for a better understanding of the evolution of Earth parameters at global scale. However different instruments' observations used over the years need to be inter-calibrated with each other to provide meaningful information. This paper describes how a linear correction can improve the observations from the Scanning Multichannel Microwave Radiometer over continental surfaces to be more consistent with more recent radiometers.
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.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
Short summary
Short summary
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Victor Pellet, Filipe Aires, Fabrice Papa, Simon Munier, and Bertrand Decharme
Hydrol. Earth Syst. Sci., 24, 3033–3055, https://doi.org/10.5194/hess-24-3033-2020, https://doi.org/10.5194/hess-24-3033-2020, 2020
Short summary
Short summary
The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.
Altug Ekici, Hanna Lee, David M. Lawrence, Sean C. Swenson, and Catherine Prigent
Geosci. Model Dev., 12, 5291–5300, https://doi.org/10.5194/gmd-12-5291-2019, https://doi.org/10.5194/gmd-12-5291-2019, 2019
Short summary
Short summary
Ice-rich permafrost thaw can create expanding thermokarst lakes as well as shrinking large wetlands. Such processes can have major biogeochemical implications and feedbacks to climate systems by altering the pathways and rates of permafrost carbon release. We developed a new model parameterization that allows a direct representation of surface water dynamics with subsidence. Our results show increased surface water fractions around western Siberian plains and northeastern territories of Canada.
Pierre Gentine, Adam Massmann, Benjamin R. Lintner, Sayed Hamed Alemohammad, Rong Fu, Julia K. Green, Daniel Kennedy, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, https://doi.org/10.5194/hess-23-4171-2019, 2019
Short summary
Short summary
Land–atmosphere interactions are key for the exchange of water, energy, and carbon dioxide, especially in the tropics. We here review some of the recent findings on land–atmosphere interactions in the tropics and where we see potential challenges and paths forward.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
Short summary
Short summary
Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Sarah Safieddine, Ana Claudia Parracho, Maya George, Filipe Aires, Victor Pellet, Lieven Clarisse, Simon Whitburn, Olivier Lezeaux, Jean-Noel Thepaut, Hans Hersbach, Gabor Radnoti, Frank Goettsche, Maria Martin, Marie Doutriaux Boucher, Dorothee Coppens, Thomas August, and Cathy Clerbaux
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-185, https://doi.org/10.5194/amt-2019-185, 2019
Preprint withdrawn
Short summary
Short summary
Skin temperature is one of the essential climate variables (ECVs), and is relevant for the current and future understanding of our climate. This work presents a method to retrieve skin temperature from the thermal infrared sounder IASI that provides a global observation of Earth’s surface and atmosphere twice a day. With this method, the first consistent long-term [2007-present] skin temperature record from IASI can be constructed.
Wen Li Zhao, Yu Jiu Xiong, Kyaw Tha Paw U, Pierre Gentine, Baoyu Chen, and Guo Yu Qiu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-160, https://doi.org/10.5194/hess-2019-160, 2019
Manuscript not accepted for further review
Short summary
Short summary
Accurate evapotranspiration (ET) estimation requires an in-depth identification of uncertainty sources. Using high density eddy covariance observations, we evaluated the effects of resistances on ET estimation and discussed possible solutions. The results show that more complex resistance parameterizations leads to more uncertainty, although prior calibration can improve the ET estimates and that a new model without resistance parameterization introduces less uncertainty into the ET estimation.
Lise Kilic, Rasmus Tage Tonboe, Catherine Prigent, and Georg Heygster
The Cryosphere, 13, 1283–1296, https://doi.org/10.5194/tc-13-1283-2019, https://doi.org/10.5194/tc-13-1283-2019, 2019
Short summary
Short summary
In this study, we develop and present simple algorithms to derive the snow depth, the snow–ice interface temperature, and the effective temperature of Arctic sea ice. This is achieved using satellite observations collocated with buoy measurements. The errors of the retrieved parameters are estimated and compared with independent data. These parameters are useful for sea ice concentration mapping, understanding sea ice properties and variability, and for atmospheric sounding applications.
Samuel Favrichon, Catherine Prigent, Carlos Jimenez, and Filipe Aires
Atmos. Meas. Tech., 12, 1531–1543, https://doi.org/10.5194/amt-12-1531-2019, https://doi.org/10.5194/amt-12-1531-2019, 2019
Short summary
Short summary
Land surface parameters (such as temperature) can be extracted from passive microwave satellite observations, with less cloud contamination than in the infrared. A cloud contamination index is proposed to detect cloud contamination for multiple frequency ranges (from 10 to 190 GHz), to be applicable to the successive generations of MW instruments. Even with a reduced number of low-frequency channels over land, the index reaches an accuracy of ≥ 70 % in detecting contaminated observations.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 23, 925–948, https://doi.org/10.5194/hess-23-925-2019, https://doi.org/10.5194/hess-23-925-2019, 2019
Short summary
Short summary
Potential evaporation (Ep) is the amount of water an ecosystem would consume if it were not limited by water availability or other stress factors. In this study, we compared several methods to estimate Ep using a global dataset of 107 FLUXNET sites. A simple radiation-driven method calibrated per biome consistently outperformed more complex approaches and makes a suitable tool to investigate the impact of water use and demand, drought severity and biome productivity.
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.
Adam Massmann, Pierre Gentine, and Changjie Lin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-553, https://doi.org/10.5194/hess-2018-553, 2018
Revised manuscript not accepted
Short summary
Short summary
Plants can sense increasing dryness in the air and close up the pores
on their leaves, preventing water loss. However, drier air also
naturally demands more water from the land surface. Here we develop a
simplified theory for when land surface water loss increases
(atmospheric demand dominates) or decreases (plant response dominates)
in response to increased dryness in the air. This theory provides
intuition for how ecosystems regulate water in response to changes in
atmospheric dryness.
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.
Yao Zhang, Joanna Joiner, Seyed Hamed Alemohammad, Sha Zhou, and Pierre Gentine
Biogeosciences, 15, 5779–5800, https://doi.org/10.5194/bg-15-5779-2018, https://doi.org/10.5194/bg-15-5779-2018, 2018
Short summary
Short summary
Using satellite reflectance measurements and a machine learning algorithm, we generated a new solar-induced chlorophyll fluorescence (SIF) dataset that is closely linked to plant photosynthesis. This new dataset has higher spatial and temporal resolutions, and lower uncertainty compared to the existing satellite retrievals. We also demonstrated its application in monitoring drought and improving the understanding of the SIF–photosynthesis relationship.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-682, https://doi.org/10.5194/hess-2017-682, 2018
Revised manuscript not accepted
Short summary
Short summary
Potential evaporation is a key parameter in numerous models used for assessing water use and drought severity. Yet, multiple incompatible methods have been proposed, thus estimates of potential evaporation remain uncertain. Based on the largest available dataset of FLUXNET data, we identify the best method to calculate potential evaporation globally. A simple radiation-driven method calibrated per biome consistently performed best; more complex models did not perform as good.
Victoria Sol Galligani, Die Wang, Milagros Alvarez Imaz, Paola Salio, and Catherine Prigent
Atmos. Meas. Tech., 10, 3627–3649, https://doi.org/10.5194/amt-10-3627-2017, https://doi.org/10.5194/amt-10-3627-2017, 2017
Short summary
Short summary
Three meteorological events with deep convection and severe weather, characteristic of the SESA region, are considered. High-resolution models, a powerful tool to study convection, can be operated with different microphysics schemes (predict the development of hydrometeors, their interactions, growth, precipitation). We present a systematic evaluation of the microphysical schemes available in the WRF model by a direct comparison between satellite-based simulated and observed microwave radiances.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
Short summary
Short summary
Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
Carolin Klinger, Bernhard Mayer, Fabian Jakub, Tobias Zinner, Seung-Bu Park, and Pierre Gentine
Atmos. Chem. Phys., 17, 5477–5500, https://doi.org/10.5194/acp-17-5477-2017, https://doi.org/10.5194/acp-17-5477-2017, 2017
Short summary
Short summary
Radiation is driving weather and climate. Yet, the effect of radiation on clouds is not fully understood and often only poorly represented in models. Better understanding and better parameterizations of the radiation–cloud interaction are therefore essential. Using our newly developed fast
neighboring column approximationfor 3-D thermal heating and cooling rates, we show that thermal radiation changes cloud circulation and causes organization and a deepening of the clouds.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
Short summary
Short summary
An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Nir Y. Krakauer, Michael J. Puma, Benjamin I. Cook, Pierre Gentine, and Larissa Nazarenko
Earth Syst. Dynam., 7, 863–876, https://doi.org/10.5194/esd-7-863-2016, https://doi.org/10.5194/esd-7-863-2016, 2016
Short summary
Short summary
We simulated effects of irrigation on climate with the NASA GISS global climate model. Present-day irrigation levels affected air pressures and temperatures even in non-irrigated land and ocean areas. The simulated effect was bigger and more widespread when ocean temperatures in the climate model could change, rather than being fixed. We suggest that expanding irrigation may affect global climate more than previously believed.
R. Obringer, X. Zhang, K. Mallick, S. H. Alemohammad, and D. Niyogi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 747–751, https://doi.org/10.5194/isprs-archives-XLI-B2-747-2016, https://doi.org/10.5194/isprs-archives-XLI-B2-747-2016, 2016
S. H. Alemohammad, K. A. McColl, A. G. Konings, D. Entekhabi, and A. Stoffelen
Hydrol. Earth Syst. Sci., 19, 3489–3503, https://doi.org/10.5194/hess-19-3489-2015, https://doi.org/10.5194/hess-19-3489-2015, 2015
Short summary
Short summary
This paper introduces a new variant of the triple collocation technique with multiplicative error model. The method is applied, for the first time, to precipitation products across the central part of continental USA. Results show distinctive patterns of error variance in each product that are estimated without a priori assumption of any of the error distributions. The correlation coefficients between each product and the truth are also estimated, which provides another performance perspective.
B. R. Lintner, P. Gentine, K. L. Findell, and G. D. Salvucci
Hydrol. Earth Syst. Sci., 19, 2119–2131, https://doi.org/10.5194/hess-19-2119-2015, https://doi.org/10.5194/hess-19-2119-2015, 2015
V. S. Galligani, C. Prigent, E. Defer, C. Jimenez, P. Eriksson, J.-P. Pinty, and J.-P. Chaboureau
Atmos. Meas. Tech., 8, 1605–1616, https://doi.org/10.5194/amt-8-1605-2015, https://doi.org/10.5194/amt-8-1605-2015, 2015
H. Norouzi, M. Temimi, C. Prigent, J. Turk, R. Khanbilvardi, Y. Tian, F. A. Furuzawa, and H. Masunaga
Atmos. Meas. Tech., 8, 1197–1205, https://doi.org/10.5194/amt-8-1197-2015, https://doi.org/10.5194/amt-8-1197-2015, 2015
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
Short summary
Short summary
Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 2014
R. Briant, L. Menut, G. Siour, and C. Prigent
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-3441-2014, https://doi.org/10.5194/gmdd-7-3441-2014, 2014
Revised manuscript not accepted
I. Pison, B. Ringeval, P. Bousquet, C. Prigent, and F. Papa
Atmos. Chem. Phys., 13, 11609–11623, https://doi.org/10.5194/acp-13-11609-2013, https://doi.org/10.5194/acp-13-11609-2013, 2013
V. Beck, C. Gerbig, T. Koch, M. M. Bela, K. M. Longo, S. R. Freitas, J. O. Kaplan, C. Prigent, P. Bergamaschi, and M. Heimann
Atmos. Chem. Phys., 13, 7961–7982, https://doi.org/10.5194/acp-13-7961-2013, https://doi.org/10.5194/acp-13-7961-2013, 2013
R. Wania, J. R. Melton, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, G. Chen, A. V. Eliseev, P. O. Hopcroft, W. J. Riley, Z. M. Subin, H. Tian, P. M. van Bodegom, T. Kleinen, Z. C. Yu, J. S. Singarayer, S. Zürcher, D. P. Lettenmaier, D. J. Beerling, S. N. Denisov, C. Prigent, F. Papa, and J. O. Kaplan
Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, https://doi.org/10.5194/gmd-6-617-2013, 2013
Related subject area
Subject: Global hydrology | Techniques and Approaches: Remote Sensing and GIS
Interannual variations of terrestrial water storage in the East African Rift region
Technical note: Surface fields for global environmental modelling
Benchmarking multimodel terrestrial water storage seasonal cycle against Gravity Recovery and Climate Experiment (GRACE) observations over major global river basins
Increasing seasonal variation in the extent of rivers and lakes from 1984 to 2022
Investigating sources of variability in closing the terrestrial water balance with remote sensing
Characterising recent drought events in the context of dry-season trends using state-of-the-art reanalysis and remote-sensing soil moisture products
Dynamic rainfall erosivity estimates derived from IMERG data
A global analysis of water storage variations from remotely sensed soil moisture and daily satellite gravimetry
Soil moisture estimates at 1 km resolution making a synergistic use of Sentinel data
Global evaluation of the “dry gets drier, and wet gets wetter” paradigm from a terrestrial water storage change perspective
Global assessment of subnational drought impact based on the Geocoded Disasters dataset and land reanalysis
Scaling methods of leakage correction in GRACE mass change estimates revisited for the complex hydro-climatic setting of the Indus Basin
Remotely sensed reservoir water storage dynamics (1984–2015) and the influence of climate variability and management at a global scale
Characterizing natural variability in complex hydrological systems using passive microwave-based climate data records: a case study for the Okavango Delta
High-resolution (1 km) satellite rainfall estimation from SM2RAIN applied to Sentinel-1: Po River basin as a case study
The accuracy of temporal upscaling of instantaneous evapotranspiration to daily values with seven upscaling methods
Global component analysis of errors in three satellite-only global precipitation estimates
Estimation of hydrological drought recovery based on precipitation and Gravity Recovery and Climate Experiment (GRACE) water storage deficit
Intercomparison of freshwater fluxes over ocean and investigations into water budget closure
Widespread decline in terrestrial water storage and its link to teleconnections across Asia and eastern Europe
Assimilation of vegetation optical depth retrievals from passive microwave radiometry
Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins
Global partitioning of runoff generation mechanisms using remote sensing data
Land–atmosphere interactions in the tropics – a review
Global-scale human pressure evolution imprints on sustainability of river systems
Using GRACE in a streamflow recession to determine drainable water storage in the Mississippi River basin
A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region
Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response
Using modelled discharge to develop satellite-based river gauging: a case study for the Amazon Basin
Global 5 km resolution estimates of secondary evaporation including irrigation through satellite data assimilation
Exploring the merging of the global land evaporation WACMOS-ET products based on local tower measurements
Estimating time-dependent vegetation biases in the SMAP soil moisture product
Daily GRACE gravity field solutions track major flood events in the Ganges–Brahmaputra Delta
Controls on surface soil drying rates observed by SMAP and simulated by the Noah land surface model
Quantification of surface water volume changes in the Mackenzie Delta using satellite multi-mission data
Microwave implementation of two-source energy balance approach for estimating evapotranspiration
A global approach to estimate irrigated areas – a comparison between different data and statistics
The future of Earth observation in hydrology
Validation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observations
MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data
Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data
Evaluating the strength of the land–atmosphere moisture feedback in Earth system models using satellite observations
Cloud tolerance of remote-sensing technologies to measure land surface temperature
Dynamic changes in terrestrial net primary production and their effects on evapotranspiration
Assessing changes in urban flood vulnerability through mapping land use from historical information
SACRA – a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI
A global data set of the extent of irrigated land from 1900 to 2005
Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors
Spatial patterns in timing of the diurnal temperature cycle
Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies
Eva Boergens, Andreas Güntner, Mike Sips, Christian Schwatke, and Henryk Dobslaw
Hydrol. Earth Syst. Sci., 28, 4733–4754, https://doi.org/10.5194/hess-28-4733-2024, https://doi.org/10.5194/hess-28-4733-2024, 2024
Short summary
Short summary
The satellites GRACE and GRACE-FO observe continental terrestrial water storage (TWS) changes. With over 20 years of data, we can look into long-term variations in the East Africa Rift region. We focus on analysing the interannual TWS variations compared to meteorological data and observations of the water storage compartments. We found strong influences of natural precipitation variability and human actions over Lake Victoria's water level.
Margarita Choulga, Francesca Moschini, Cinzia Mazzetti, Stefania Grimaldi, Juliana Disperati, Hylke Beck, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 28, 2991–3036, https://doi.org/10.5194/hess-28-2991-2024, https://doi.org/10.5194/hess-28-2991-2024, 2024
Short summary
Short summary
CEMS_SurfaceFields_2022 dataset is a new set of high-resolution maps for land type (e.g. lake, forest), soil properties and population water needs at approximately 2 and 6 km at the Equator, covering Europe and the globe (excluding Antarctica). We describe what and how new high-resolution information can be used to create the dataset. The paper suggests that the dataset can be used as input for river, weather or other models, as well as for statistical descriptions of the region of interest.
Sadia Bibi, Tingju Zhu, Ashraf Rateb, Bridget R. Scanlon, Muhammad Aqeel Kamran, Abdelrazek Elnashar, Ali Bennour, and Ci Li
Hydrol. Earth Syst. Sci., 28, 1725–1750, https://doi.org/10.5194/hess-28-1725-2024, https://doi.org/10.5194/hess-28-1725-2024, 2024
Short summary
Short summary
We assessed 13 global models using GRACE satellite data over 29 river basins. Simulated seasonal water storage cycles showed discrepancies compared to GRACE. The models overestimated seasonal amplitude in boreal basins and showed underestimation in tropical, arid, and temperate zones, with phase differences of 2–3 months compared to GRACE in cold basins and of 1 month in temperate, arid, and semi-arid basins. Seasonal amplitude and phase differences provide insights for model improvement.
Björn Nyberg, Roger Sayre, and Elco Luijendijk
Hydrol. Earth Syst. Sci., 28, 1653–1663, https://doi.org/10.5194/hess-28-1653-2024, https://doi.org/10.5194/hess-28-1653-2024, 2024
Short summary
Short summary
Understanding the spatial and temporal distribution of surface water is crucial for effective water resource management, maintaining ecosystem health and assessing flood risks. This study examined permanent and seasonal rivers and lakes globally over 38 years, uncovering a statistically significant expansion in seasonal extent captured in the new SARL database. The findings offer valuable resources for assessing the impact of changing river and lake extents on ecosystems and human livelihoods.
Claire I. Michailovsky, Bert Coerver, Marloes Mul, and Graham Jewitt
Hydrol. Earth Syst. Sci., 27, 4335–4354, https://doi.org/10.5194/hess-27-4335-2023, https://doi.org/10.5194/hess-27-4335-2023, 2023
Short summary
Short summary
Many remote sensing products for precipitation, evapotranspiration, and water storage variations exist. However, when these are used with in situ runoff data in water balance closure studies, no single combination of products consistently outperforms others. We analyzed the water balance closure using different products in catchments worldwide and related the results to catchment characteristics. Our results can help identify the dataset combinations best suited for use in different catchments.
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.
Robert A. Emberson
Hydrol. Earth Syst. Sci., 27, 3547–3563, https://doi.org/10.5194/hess-27-3547-2023, https://doi.org/10.5194/hess-27-3547-2023, 2023
Short summary
Short summary
Soil can be eroded by rainfall, and this is a major threat to agricultural sustainability. Estimating the erosivity of rainfall is essential as a first step to determine how much soil might be lost. Until recently, satellite data have not been used to estimate rainfall erosivity, but the data quality is now sufficient to do so. In this study, I test several methods to calculate rainfall erosivity using satellite rainfall data and contrast this with ground-based estimates.
Daniel Blank, Annette Eicker, Laura Jensen, and Andreas Güntner
Hydrol. Earth Syst. Sci., 27, 2413–2435, https://doi.org/10.5194/hess-27-2413-2023, https://doi.org/10.5194/hess-27-2413-2023, 2023
Short summary
Short summary
Soil moisture (SM), a key variable of the global water cycle, is analyzed using two types of satellite observations; microwave sensors measure the top few centimeters and satellite gravimetry (GRACE) the full vertical water column. As SM can change very fast, non-standard daily GRACE data are applied for the first time for this analysis. Jointly analyzing these data gives insight into the SM dynamics at different soil depths, and time shifts indicate the infiltration time into deeper layers.
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.
Jinghua Xiong, Shenglian Guo, Abhishek, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 26, 6457–6476, https://doi.org/10.5194/hess-26-6457-2022, https://doi.org/10.5194/hess-26-6457-2022, 2022
Short summary
Short summary
Although the "dry gets drier, and wet gets wetter (DDWW)" paradigm is prevalent in summarizing wetting and drying trends, we show that only 11.01 %–40.84 % of the global land confirms and 10.21 %–35.43 % contradicts the paradigm during 1985–2014 from a terrestrial water storage change perspective. Similar proportions that intensify with the increasing emission scenarios persist until the end of the 21st century. Findings benefit understanding of global hydrological responses to climate change.
Yuya Kageyama and Yohei Sawada
Hydrol. Earth Syst. Sci., 26, 4707–4720, https://doi.org/10.5194/hess-26-4707-2022, https://doi.org/10.5194/hess-26-4707-2022, 2022
Short summary
Short summary
This study explores the link between hydrometeorological droughts and their socioeconomic impact at a subnational scale based on the newly developed disaster dataset with subnational location information. Hydrometeorological drought-prone areas were generally consistent with socioeconomic drought-prone areas in the disaster dataset. Our analysis clarifies the importance of the use of subnational disaster information.
Vasaw Tripathi, Andreas Groh, Martin Horwath, and Raaj Ramsankaran
Hydrol. Earth Syst. Sci., 26, 4515–4535, https://doi.org/10.5194/hess-26-4515-2022, https://doi.org/10.5194/hess-26-4515-2022, 2022
Short summary
Short summary
GRACE/GRACE-FO provided global observations of water storage change since 2002. Scaling is a common approach to compensate for the spatial filtering inherent to the results. However, for complex hydrological basins, the compatibility of scaling with the characteristics of regional hydrology has been rarely assessed. We assess traditional scaling approaches and a new scaling approach for the Indus Basin. Our results will help users with regional focus understand implications of scaling choices.
Jiawei Hou, Albert I. J. M. van Dijk, Hylke E. Beck, Luigi J. Renzullo, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 26, 3785–3803, https://doi.org/10.5194/hess-26-3785-2022, https://doi.org/10.5194/hess-26-3785-2022, 2022
Short summary
Short summary
We used satellite imagery to measure monthly reservoir water volumes for 6695 reservoirs worldwide for 1984–2015. We investigated how changing precipitation, streamflow, evaporation, and human activity affected reservoir water storage. Almost half of the reservoirs showed significant increasing or decreasing trends over the past three decades. These changes are caused, first and foremost, by changes in precipitation rather than by changes in net evaporation or dam release patterns.
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.
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.
Zhaofei Liu
Hydrol. Earth Syst. Sci., 25, 4417–4433, https://doi.org/10.5194/hess-25-4417-2021, https://doi.org/10.5194/hess-25-4417-2021, 2021
Short summary
Short summary
Instantaneous evapotranspiration (ET), which is detected by the remote sensing technique, needs to be upscaled to daily values in order to practical applications. The accuracy of seven upscaling methods is evaluated by using global observations. The sine function and the evaporative fraction method using extraterrestrial solar irradiance are recommended. Although every upscaling scheme has high accuracy at most sites, it is less accurate at tropical rainforest and tropical monsoon sites.
Hanqing Chen, Bin Yong, Pierre-Emmanuel Kirstetter, Leyang Wang, and Yang Hong
Hydrol. Earth Syst. Sci., 25, 3087–3104, https://doi.org/10.5194/hess-25-3087-2021, https://doi.org/10.5194/hess-25-3087-2021, 2021
Alka Singh, John Thomas Reager, and Ali Behrangi
Hydrol. Earth Syst. Sci., 25, 511–526, https://doi.org/10.5194/hess-25-511-2021, https://doi.org/10.5194/hess-25-511-2021, 2021
Short summary
Short summary
The study demonstrates the utility of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage anomalies (TWSAs) for obtaining statistics of hydrological droughts, i.e., recovery periods and required precipitation in different precipitation scenarios. The findings of this study are that the GRACE-based drought index is valid for estimating the required precipitation for drought recovery, and the period of drought recovery depends on the intensity of the precipitation.
Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
Hydrol. Earth Syst. Sci., 25, 121–146, https://doi.org/10.5194/hess-25-121-2021, https://doi.org/10.5194/hess-25-121-2021, 2021
Short summary
Short summary
The net exchange of water between the surface and atmosphere is mainly determined by the freshwater flux: the difference between evaporation (E) and precipitation (P), or E−P. Although there is consensus among modelers that with a warming climate E−P will increase, evidence from satellite data is still not conclusive, mainly due to sensor calibration issues. We here investigate the degree of correspondence among six recent
satellite-based climate data records and ERA5 reanalysis E−P data.
Xianfeng Liu, Xiaoming Feng, Philippe Ciais, and Bojie Fu
Hydrol. Earth Syst. Sci., 24, 3663–3676, https://doi.org/10.5194/hess-24-3663-2020, https://doi.org/10.5194/hess-24-3663-2020, 2020
Short summary
Short summary
Freshwater availability is crucial for sustainable development across the Asian and eastern European regions. Our results indicate widespread decline in terrestrial water storage (TWS) over the region during 2002–2017, primarily due to the intensive over-extraction of groundwater and warmth-induced surface water loss. The findings provide insights into changes in TWS and its components over the Asian and eastern European regions, where there is growing demand for food grains and water supplies.
Sujay V. Kumar, Thomas R. Holmes, Rajat Bindlish, Richard de Jeu, and Christa Peters-Lidard
Hydrol. Earth Syst. Sci., 24, 3431–3450, https://doi.org/10.5194/hess-24-3431-2020, https://doi.org/10.5194/hess-24-3431-2020, 2020
Short summary
Short summary
Vegetation optical depth (VOD) is a byproduct of the soil moisture retrieval from passive microwave instruments. This study demonstrates that VOD information can be utilized for improving land surface water budget and carbon conditions through data assimilation.
Victor Pellet, Filipe Aires, Fabrice Papa, Simon Munier, and Bertrand Decharme
Hydrol. Earth Syst. Sci., 24, 3033–3055, https://doi.org/10.5194/hess-24-3033-2020, https://doi.org/10.5194/hess-24-3033-2020, 2020
Short summary
Short summary
The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.
Joseph T. D. Lucey, John T. Reager, and Sonya R. Lopez
Hydrol. Earth Syst. Sci., 24, 1415–1427, https://doi.org/10.5194/hess-24-1415-2020, https://doi.org/10.5194/hess-24-1415-2020, 2020
Short summary
Short summary
This work relates total water storage (TWS) and rainfall to surface water inundation (SWI) using NASA satellite data. We determine whether TWS and/or rainfall control global SWI developments. Regression methods and cross-correlations were used to relate the measurements and correct for time differences among peaks. Results show TWS and rainfall control most global SWI developments. To our knowledge, this is the first global study on SWI controls and validates previous findings.
Pierre Gentine, Adam Massmann, Benjamin R. Lintner, Sayed Hamed Alemohammad, Rong Fu, Julia K. Green, Daniel Kennedy, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, https://doi.org/10.5194/hess-23-4171-2019, 2019
Short summary
Short summary
Land–atmosphere interactions are key for the exchange of water, energy, and carbon dioxide, especially in the tropics. We here review some of the recent findings on land–atmosphere interactions in the tropics and where we see potential challenges and paths forward.
Serena Ceola, Francesco Laio, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 3933–3944, https://doi.org/10.5194/hess-23-3933-2019, https://doi.org/10.5194/hess-23-3933-2019, 2019
Short summary
Short summary
A simple and effective index for the quantitative estimation of the evolution of human pressure on rivers at global scale is proposed. This index, based on nightlights and river discharge data, shows a significant increase from 1992 to 2013 worldwide. The most notable changes are found in river basins across Africa and Asia, where human pressure on rivers is growing markedly. This index identifies priority areas that can be targeted for the implementation of mitigation strategies and plans.
Heloisa Ehalt Macedo, Ralph Edward Beighley, Cédric H. David, and John T. Reager
Hydrol. Earth Syst. Sci., 23, 3269–3277, https://doi.org/10.5194/hess-23-3269-2019, https://doi.org/10.5194/hess-23-3269-2019, 2019
Short summary
Short summary
The water stored under the surface is very important for defining the amount of water available for human and environmental applications; however, it is still a challenge to obtain such measurements. NASA's GRACE satellites provide information on total terrestrial water storage based on observations of gravity changes. Here, we relate GRACE data to streamflow measurements, providing estimations of the fraction of baseflow and total drainable storage for the Mississippi River basin.
Linlin Li, Andrew Skidmore, Anton Vrieling, and Tiejun Wang
Hydrol. Earth Syst. Sci., 23, 3037–3056, https://doi.org/10.5194/hess-23-3037-2019, https://doi.org/10.5194/hess-23-3037-2019, 2019
Short summary
Short summary
We derived an 8 d, 500 m resolution surface water fraction product over the Mediterranean region for 2000–2017 based on MODIS data. This dataset complements existing surface water/wetland datasets by adding more temporal detail. It allows for the seasonal, inter-annual, and long-term dynamics of the surface water extent to be monitored, inclusive of small-sized and highly dynamic water bodies; it can also contribute to biodiversity and climate change assessment.
Siyuan Tian, Luigi J. Renzullo, Albert I. J. M. van Dijk, Paul Tregoning, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 1067–1081, https://doi.org/10.5194/hess-23-1067-2019, https://doi.org/10.5194/hess-23-1067-2019, 2019
Jiawei Hou, Albert I. J. M. van Dijk, Luigi J. Renzullo, and Robert A. Vertessy
Hydrol. Earth Syst. Sci., 22, 6435–6448, https://doi.org/10.5194/hess-22-6435-2018, https://doi.org/10.5194/hess-22-6435-2018, 2018
Short summary
Short summary
Satellite-based river gauging can be constructed based on remote-sensing-derived surface water extent and modelled discharge, and used to estimate river discharges with satellite observations only. This provides opportunities for monitoring river discharge in the absence of a real-time hydrological model or gauging stations.
Albert I. J. M. van Dijk, Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts
Hydrol. Earth Syst. Sci., 22, 4959–4980, https://doi.org/10.5194/hess-22-4959-2018, https://doi.org/10.5194/hess-22-4959-2018, 2018
Short summary
Short summary
Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
Short summary
Short summary
Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
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.
Ben T. Gouweleeuw, Andreas Kvas, Christian Gruber, Animesh K. Gain, Thorsten Mayer-Gürr, Frank Flechtner, and Andreas Güntner
Hydrol. Earth Syst. Sci., 22, 2867–2880, https://doi.org/10.5194/hess-22-2867-2018, https://doi.org/10.5194/hess-22-2867-2018, 2018
Short summary
Short summary
Daily GRACE gravity field solutions have been evaluated against daily river runoff data for major flood events in the Ganges–Brahmaputra Delta in 2004 and 2007. Compared to the monthly gravity field solutions, the trends over periods of a few days in the daily gravity field solutions are able to reflect temporal variations in river runoff during major flood events. This implies that daily gravity field solutions released in near-real time may support flood monitoring for large events.
Peter J. Shellito, Eric E. Small, and Ben Livneh
Hydrol. Earth Syst. Sci., 22, 1649–1663, https://doi.org/10.5194/hess-22-1649-2018, https://doi.org/10.5194/hess-22-1649-2018, 2018
Short summary
Short summary
After soil gets wet, much of the surface moisture evaporates directly back into the air. Recent satellite data show that this process is enhanced when there is more water in the soil, less humidity in the air, and less vegetation covering the ground. A widely used model shows similar effects of soil water and humidity, but it largely misses the role of vegetation and assigns outsized importance to soil type. These results are encouraging evidence that the satellite can be used to improve models.
Cassandra Normandin, Frédéric Frappart, Bertrand Lubac, Simon Bélanger, Vincent Marieu, Fabien Blarel, Arthur Robinet, and Léa Guiastrennec-Faugas
Hydrol. Earth Syst. Sci., 22, 1543–1561, https://doi.org/10.5194/hess-22-1543-2018, https://doi.org/10.5194/hess-22-1543-2018, 2018
Thomas R. H. Holmes, Christopher R. Hain, Wade T. Crow, Martha C. Anderson, and William P. Kustas
Hydrol. Earth Syst. Sci., 22, 1351–1369, https://doi.org/10.5194/hess-22-1351-2018, https://doi.org/10.5194/hess-22-1351-2018, 2018
Short summary
Short summary
In an effort to apply cloud-tolerant microwave data to satellite-based monitoring of evapotranspiration (ET), this study reports on an experiment where microwave-based land surface temperature is used as the key diagnostic input to a two-source energy balance method for the estimation of ET. Comparisons of this microwave ET with the conventional thermal infrared estimates show widespread agreement in spatial and temporal patterns from seasonal to inter-annual timescales over Africa and Europe.
Jonas Meier, Florian Zabel, and Wolfram Mauser
Hydrol. Earth Syst. Sci., 22, 1119–1133, https://doi.org/10.5194/hess-22-1119-2018, https://doi.org/10.5194/hess-22-1119-2018, 2018
Short summary
Short summary
The following study extends existing irrigation maps based on official reports. The main idea was to extend the reported irrigated areas using agricultural suitability data and compare them with remote sensing information about plant conditions. The analysis indicates an increase in irrigated land by 18 % compared to the reported statistics. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated.
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.
Liangjing Zhang, Henryk Dobslaw, Tobias Stacke, Andreas Güntner, Robert Dill, and Maik Thomas
Hydrol. Earth Syst. Sci., 21, 821–837, https://doi.org/10.5194/hess-21-821-2017, https://doi.org/10.5194/hess-21-821-2017, 2017
Short summary
Short summary
Global numerical models perform differently, as has been found in some model intercomparison studies, which mainly focused on components like evapotranspiration, soil moisture or runoff. We have applied terrestrial water storage that is estimated from a GRACE-based state-of-art post-processing method to validate four global numerical models and try to identify the advantages and deficiencies of a certain model. GRACE-based TWS demonstrates its additional benefits to improve the models in future.
Hylke E. Beck, Albert I. J. M. van Dijk, Vincenzo Levizzani, Jaap Schellekens, Diego G. Miralles, Brecht Martens, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, https://doi.org/10.5194/hess-21-589-2017, 2017
Short summary
Short summary
MSWEP (Multi-Source Weighted-Ensemble Precipitation) is a new global terrestrial precipitation dataset with a high 3-hourly temporal and 0.25° spatial resolution. The dataset is unique in that it takes advantage of a wide range of data sources, including gauge, satellite, and reanalysis data, to obtain the best possible precipitation estimates at global scale. The dataset outperforms existing gauge-adjusted precipitation datasets.
Oliver López, Rasmus Houborg, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 21, 323–343, https://doi.org/10.5194/hess-21-323-2017, https://doi.org/10.5194/hess-21-323-2017, 2017
Short summary
Short summary
The study evaluated the spatial and temporal consistency of satellite-based hydrological products based on the water budget equation, including three global evaporation products. The products were spatially matched using spherical harmonics analysis. The results highlighted the difficulty in obtaining agreement between independent satellite products, even over regions with simple water budgets. However, imposing a time lag on water storage data improved results considerably.
Paul A. Levine, James T. Randerson, Sean C. Swenson, and David M. Lawrence
Hydrol. Earth Syst. Sci., 20, 4837–4856, https://doi.org/10.5194/hess-20-4837-2016, https://doi.org/10.5194/hess-20-4837-2016, 2016
Short summary
Short summary
We demonstrate a new approach to assess the strength of feedbacks resulting from land–atmosphere coupling on decadal timescales. Our approach was tailored to enable evaluation of Earth system models (ESMs) using data from Earth observation satellites that measure terrestrial water storage anomalies and relevant atmospheric variables. Our results are consistent with previous work demonstrating that ESMs may be overestimating the strength of land surface feedbacks compared with observations.
Thomas R. H. Holmes, Christopher R. Hain, Martha C. Anderson, and Wade T. Crow
Hydrol. Earth Syst. Sci., 20, 3263–3275, https://doi.org/10.5194/hess-20-3263-2016, https://doi.org/10.5194/hess-20-3263-2016, 2016
Short summary
Short summary
We test the cloud tolerance of two technologies to estimate land surface temperature (LST) from space: microwave (MW) and thermal infrared (TIR). Although TIR has slightly lower errors than MW with ground data under clear-sky conditions, it suffers increasing negative bias as cloud cover increases. In contrast, we find no direct impact of clouds on the accuracy and bias of MW-LST. MW-LST can therefore be used to improve TIR cloud screening and increase sampling in clouded regions.
Zhi Li, Yaning Chen, Yang Wang, and Gonghuan Fang
Hydrol. Earth Syst. Sci., 20, 2169–2178, https://doi.org/10.5194/hess-20-2169-2016, https://doi.org/10.5194/hess-20-2169-2016, 2016
Short summary
Short summary
Global net primary production (NPP) slightly increased in 2000–2014. More than 64 % of vegetated land in the Northern Hemisphere (NH) showed increased NPP, while 60.3 % in Southern Hemisphere (SH) showed a decreasing trend. Vegetation greening and climate change promote rises of global evapotranspiration (ET). The increased rate of ET in the NH is faster than that in the SH. Meanwhile, global warming and vegetation greening accelerate evaporation in soil moisture. Continuation of these trends will likely exacerbate the risk of ecological drought.
M. Boudou, B. Danière, and M. Lang
Hydrol. Earth Syst. Sci., 20, 161–173, https://doi.org/10.5194/hess-20-161-2016, https://doi.org/10.5194/hess-20-161-2016, 2016
Short summary
Short summary
This paper presents an appraisal of flood vulnerability of two French cities, Besançon and Moissac, which have been largely impacted by two ancient major floods (resp. in January 1910 and March 1930). An analysis of historical sources allows the mapping of land use and occupation within the flood extent of the two historical floods, both in past and present contexts. It gives an insight into the complexity of flood risk evolution, at a local scale.
S. Kotsuki and K. Tanaka
Hydrol. Earth Syst. Sci., 19, 4441–4461, https://doi.org/10.5194/hess-19-4441-2015, https://doi.org/10.5194/hess-19-4441-2015, 2015
Short summary
Short summary
This study aims to develop a new global data set of a satellite-derived crop calendar (SACRA) and to reveal its advantages and disadvantages compared to other global products. The cultivation period of SACRA is identified from the time series of NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (< 62 days) in most areas.
S. Siebert, M. Kummu, M. Porkka, P. Döll, N. Ramankutty, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 19, 1521–1545, https://doi.org/10.5194/hess-19-1521-2015, https://doi.org/10.5194/hess-19-1521-2015, 2015
Short summary
Short summary
We developed the historical irrigation data set (HID) depicting the spatio-temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5arcmin resolution.
The HID reflects very well the spatial patterns of irrigated land as shown on two historical maps for 1910 and 1960.
Global AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. Mean aridity on irrigated land increased and mean natural river discharge decreased from 1900 to 1950.
B. Revilla-Romero, J. Thielen, P. Salamon, T. De Groeve, and G. R. Brakenridge
Hydrol. Earth Syst. Sci., 18, 4467–4484, https://doi.org/10.5194/hess-18-4467-2014, https://doi.org/10.5194/hess-18-4467-2014, 2014
Short summary
Short summary
One of the main challenges in global hydrological modelling is the limited availability of observational data for calibration and model verification. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System (GFDS) for converting the flood detection signal into river discharge values. This work also provides a first analysis of the local factors influencing the accuracy of discharge measurement as provided by this system.
T. R. H. Holmes, W. T. Crow, and C. Hain
Hydrol. Earth Syst. Sci., 17, 3695–3706, https://doi.org/10.5194/hess-17-3695-2013, https://doi.org/10.5194/hess-17-3695-2013, 2013
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
Cited articles
Aires, F., Aznay, O., Prigent, C., Paul, M., and Bernardo, F.: Synergistic
multi-wavelength remote sensing versus a posteriori combination of retrieved
products: Application for the retrieval of atmospheric profiles using
MetOp-A, J. Geophys. Res., 117, D18304, https://doi.org/10.1029/2011JD017188, 2012.
Aires, F., Miolane, L., Prigent, C., Pham, B., Fluet-Chouinard, E., Lehner,
B., and Papa, F.: A Global Dynamic Long-Term Inundation Extent Dataset at
High Spatial Resolution Derived through Downscaling of Satellite
Observations, J. Hydrometeorol., 18, 1305–1325,
https://doi.org/10.1175/JHM-D-16-0155.1, 2017.
Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N.,
Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From
near-surface to root-zone soil moisture using an exponential filter: an
assessment of the method based on in-situ observations and model simulations,
Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008,
2008.
Alemohammad, S. H., Kolassa, J., Prigent, C., Aires, F., and Gentine, P.:
Statistical retrieval of surface and root zone soil moisture using synergy of
multi-frequency remotely-sensed observations, in: 2017 IEEE International
Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 23–28
July 2017, IEEE, 4943–4946, https://doi.org/10.1109/IGARSS.2017.8128113, 2017a.
Alemohammad, S. H., Fang, B., Konings, A. G., Aires, F., Green, J. K.,
Kolassa, J., Miralles, D., Prigent, C., and Gentine, P.: Water, Energy, and
Carbon with Artificial Neural Networks (WECANN): a statistically based
estimate of global surface turbulent fluxes and gross primary productivity
using solar-induced fluorescence, Biogeosciences, 14, 4101–4124,
https://doi.org/10.5194/bg-14-4101-2017, 2017b.
Bell, J. E., Palecki, M. A., Baker, C. B., Collins, W. G., Lawrimore, J. H.,
Leeper, R. D., Hall, M. E., Kochendorfer, J., Meyers, T. P., Wilson, T., and
Diamond, H. J.: 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.
Berg, A., Lintner, B. R., Findell, K. L., Malyshev, S., Loikith, P. C., and
Gentine, P.: Impact of Soil Moisture–Atmosphere Interactions on Surface
Temperature Distribution, J. Climate, 27, 7976–7993,
https://doi.org/10.1175/JCLI-D-13-00591.1, 2014.
Béziat, P., Rivalland, V., Tallec, T., Jarosz, N., Boulet, G., Gentine,
P., and Ceschia, E.: Evaluation of a simple approach for crop
evapotranspiration partitioning and analysis of the water budget distribution
for several crop species, Agr. Forest Meteorol., 177, 46–56,
https://doi.org/10.1016/j.agrformet.2013.03.013, 2013.
Blöschl, G. and Sivapalan, M.: Scale issues in hydrological modelling: A
review, Hydrol. Process., 9, 251–290, https://doi.org/10.1002/hyp.3360090305, 1995.
Brodzik, M. J., Billingsley, B., Haran, T., Raup, B., and Savoie, M. H.:
EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded
Data Sets, ISPRS Int. J. Geo-Inf., 1, 32–45, https://doi.org/10.3390/ijgi1010032,
2012.
Brodzik, M. J., Billingsley, B., Haran, T., Raup, B. and Savoie, M. H.:
Correction: Brodzik, M. J., et al. EASE-Grid 2.0: Incremental but Significant
Improvements for Earth-Gridded Data Sets, ISPRS Int. J. Geo-Inf., 1, 32–45,
2012, ISPRS Int. J. Geo-Inf., 3, 1154–1156, https://doi.org/10.3390/ijgi3031154, 2014.
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,
Barcelona, Spain, 23–28 July 2007, IEEE, https://doi.org/10.1109/IGARSS.2007.4423019,
1196–1199, 2007.
Chakrabarti, S., Judge, J., Bongiovanni, T., Rangarajan, A., and Ranka, S.:
Disaggregation of Remotely Sensed Soil Moisture in Heterogeneous Landscapes
Using Holistic Structure-Based Models, IEEE T. Geosci. Remote, 54,
4629–4641, https://doi.org/10.1109/TGRS.2016.2547389, 2016.
Chakrabarti, S., Judge, J., Rangarajan, A., and Ranka, S.: Utilizing
Self-Regularized Regressive Models to Downscale Microwave Brightness
Temperatures for Agricultural Land Covers in the SMAPVEX-12 Region, IEEE
J. Sel. Top. Appl., 10, 478–488, https://doi.org/10.1109/JSTARS.2016.2637927, 2017.
Chan, S. K., Bindlish, R., E. O'Neill, P., Njoku, E., Jackson, T.,
Colliander, A., Chen, F., Burgin, M., Dunbar, S., Piepmeier, J., Yueh, S.,
Entekhabi, D., Cosh, M. H., Caldwell, T., Walker, J., Wu, X., Berg, A.,
Rowlandson, T., Pacheco, A., McNairn, H., Thibeault, M., Martinez-Fernandez,
J., Gonzalez-Zamora, A., Seyfried, M., Bosch, D., Starks, P., Goodrich, D.,
Prueger, J., Palecki, M., Small, E. E., Zreda, M., Calvet, J.-C., Crow, W.
T., and Kerr, Y.: Assessment of the SMAP Passive Soil Moisture Product, IEEE
T. Geosci. Remote, 54, 4994–5007, https://doi.org/10.1109/TGRS.2016.2561938, 2016.
Chan, S. K., Bindlish, R., O'Neill, P., Jackson, T., Njoku, E., Dunbar, S.,
Chaubell, J., Piepmeier, J., Yueh, S., Entekhabi, D., Colliander, A., Chen,
F., Cosh, M. H., Caldwell, T., Walker, J., Berg, A., McNairn, H., Thibeault,
M., Martínez-Fernández, J., Uldall, F., Seyfried, M., Bosch, D.,
Starks, P., Holifield Collins, C., Prueger, J., van der Velde, R., Asanuma,
J., Palecki, M., Small, E. E., Zreda, M., Calvet, J., Crow, W. T., and Kerr,
Y.: Development and assessment of the SMAP enhanced passive soil moisture
product, Remote Sens. Environ., 204, 931–941,
https://doi.org/10.1016/j.rse.2017.08.025, 2017.
Chaubell, J., Yueh, S., Entekhabi, D., and Peng, J.: Resolution enhancement
of SMAP radiometer data using the Backus Gilbert optimum interpolation
technique, in: 2016 IEEE International Geoscience and Remote Sensing
Symposium (IGARSS), Beijing, China, 10–15 July 2016, IEEE, 284–287,
https://doi.org/10.1109/IGARSS.2016.7729065, 2016.
Coenders-Gerrits, A. M. J., Hopp, L., Savenije, H. H. G., and Pfister, L.:
The effect of spatial throughfall patterns on soil moisture patterns at the
hillslope scale, Hydrol. Earth Syst. Sci., 17, 1749–1763,
https://doi.org/10.5194/hess-17-1749-2013, 2013.
Colliander, A., Fisher, J. B., Halverson, G., Merlin, O., Misra, S.,
Bindlish, R., Jackson, T. J., and Yueh, S.: Spatial Downscaling of SMAP Soil
Moisture Using MODIS Land Surface Temperature and NDVI During SMAPVEX15, IEEE
Geosci. Remote S., 14, 2107–2111, https://doi.org/10.1109/LGRS.2017.2753203, 2017a.
Colliander, A., Jackson, T. J., Bindlish, R., Chan, S., Das, N., Kim, S. B.,
Cosh, M. H., Dunbar, R. S., 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. P., Wu, X., Monerris, A., O'Neill, P. E., Entekhabi, D., Njoku, E.
G., 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, 2017b.
Cybenko, G.: Approximation by superpositions of a sigmoidal function, Math.
Control. Signal., 2, 303–314, https://doi.org/10.1007/BF02551274, 1989.
Das, N. N., Entekhabi, D., and Njoku, E. G.: An Algorithm for Merging SMAP
Radiometer and Radar Data for High-Resolution Soil-Moisture Retrieval, IEEE
T. Geosci. Remote, 49, 1504–1512, https://doi.org/10.1109/TGRS.2010.2089526, 2011.
Didan, K.: MYD13A3 MODIS/Aqua Vegetation Indices Monthly L3 Global 1 km SIN
Grid V006, NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/modis/myd13a3.006,
2015.
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, 2011.
Dorigo, W. A., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiová, 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,
https://doi.org/10.2136/vzj2012.0097, 2013.
Entekhabi, D., Rodríguez-Iturbe, I., and Castelli, F.: Mutual
interaction of soil moisture state and atmospheric processes, J. Hydrol.,
184, 3–17, https://doi.org/10.1016/0022-1694(95)02965-6, 1996.
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, in: Proc. IEEE, 98, 704–716, https://doi.org/10.1109/JPROC.2010.2043918,
2010.
Famiglietti, J. S., Ryu, D., Berg, A. A., Rodell, M., and Jackson, T. J.:
Field observations of soil moisture variability across scales, Water Resour.
Res., 44, W01423, https://doi.org/10.1029/2006WR005804, 2008.
Gedney, N. and Cox, P. M.: The Sensitivity of Global Climate Model
Simulations to the Representation of Soil Moisture Heterogeneity,
J. Hydrometeorol., 4, 1265–1275,
https://doi.org/10.1175/1525-7541(2003)004<1265:TSOGCM>2.0.CO;2,
2003.
Gentine, P., Entekhabi, D., Chehbouni, A., Boulet, G., and Duchemin, B.:
Analysis of evaporative fraction diurnal behaviour, Agr. Forest Meteorol.,
143, 13–29, https://doi.org/10.1016/j.agrformet.2006.11.002, 2007.
Gentine, P., Entekhabi, D., and Polcher, J.: The Diurnal Behavior of
Evaporative Fraction in the Soil–Vegetation–Atmospheric Boundary Layer
Continuum, J. Hydrometeorol., 12, 1530–1546, https://doi.org/10.1175/2011JHM1261.1,
2011.
Hagan, M. T. and Menhaj, M. B.: Training feedforward networks with the
Marquardt algorithm, IEEE T. Neural Networ., 5, 989–993,
https://doi.org/10.1109/72.329697, 1994.
Hatfield, J. L.: Upscaling and Downscaling Methods for Environmental
Research, J. Environ. Qual., 30, 1100, https://doi.org/10.2134/jeq2001.3031100x, 2001.
Ines, A. V. M., Mohanty, B. P., and Shin, Y.: An unmixing algorithm for
remotely sensed soil moisture, Water Resour. Res., 49, 408–425,
https://doi.org/10.1029/2012WR012379, 2013.
Jackson, T. J.: III. Measuring surface soil moisture using passive microwave
remote sensing, Hydrol. Process., 7, 139–152, https://doi.org/10.1002/hyp.3360070205,
1993.
Jackson, T. J. and Schmugge, T. J.: Vegetation effects on the microwave
emission of soils, Remote Sens. Environ., 36, 203–212,
https://doi.org/10.1016/0034-4257(91)90057-D, 1991.
Jagdhuber, T., Entekhabi, D., Hajnsek, I., Konings, A. G., McColl, K. A.,
Alemohammad, S. H., Das, N. N., and Montzka, C.: Physically-based
active-passive modelling and retrieval for SMAP soil moisture inversion
algorithm, in: 2015 IEEE International Geoscience and Remote Sensing
Symposium (IGARSS), Milan, Italy 26–31 July 2015, IEEE, 1300–1303,
https://doi.org/10.1109/IGARSS.2015.7326013, 2015.
Jagdhuber, T., Entekhabi, D., Konings, A. G., McColl, K. A., Alemohammad, S.
H., Das, N. N., Montzka, C., and Piles, M.: Physically-based retrieval of
SMAP active-passive measurements covariation and vegetation structure
parameters, in: 2016 IEEE International Geoscience and Remote Sensing
Symposium (IGARSS), Beijing, China, 10–15 July 2016, IEEE, 3078–3081,
https://doi.org/10.1109/IGARSS.2016.7729796, 2016.
Jiménez, C., Prigent, C., and Aires, F.: Toward an estimation of global
land surface heat fluxes from multisatellite observations, J. Geophys. Res.,
114, D06305, https://doi.org/10.1029/2008JD011392, 2009.
Jiménez, C., Clark, D. B., Kolassa, J., Aires, F., and Prigent, C.: A
joint analysis of modeled soil moisture fields and satellite observations,
J. Geophys. Res.-Atmos., 118, 6771–6782, https://doi.org/10.1002/jgrd.50430, 2013.
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.
Kolassa, J., Gentine, P., Prigent, C., and Aires, F.: Soil moisture retrieval
from AMSR-E and ASCAT microwave observation synergy. Part 1: Satellite data
analysis, Remote Sens. Environ., 173, 1–14, https://doi.org/10.1016/j.rse.2015.11.011,
2016.
Kolassa, J., Gentine, P., Prigent, C., Aires, F., Alemohammad, S. H.,
Prigent, C., Aires, F., Prigent, C., and Aires, F.: 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.
Kolassa, J., Reichle, R. H., Liu, Q., Alemohammad, S. H., Gentine, P., Aida,
K., Asanuma, J., Bircher, S., Caldwell, T., Colliander, A., Cosh, M.,
Holifield Collins, C., Jackson, T. J., Martínez-Fernández, J.,
McNairn, H., Pacheco, A., Thibeault, M., and Walker, J. P.: 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.
Kool, D., Agam, N., Lazarovitch, N., Heitman, J. L., Sauer, T. J., and
Ben-Gal, A.: A review of approaches for evapotranspiration partitioning, Agr.
Forest Meteorol., 184, 56–70, https://doi.org/10.1016/j.agrformet.2013.09.003, 2014.
Koster, R. D., Mahanama, S. P. P., Yamada, T. J., Balsamo, G., Berg, A. A.,
Boisserie, M., Dirmeyer, P. A., Doblas-Reyes, F. J., Drewitt, G., Gordon, C.
T., Guo, Z., Jeong, J.-H., Lawrence, D. M., Lee, W.-S., Li, Z., Luo, L.,
Malyshev, S., Merryfield, W. J., Seneviratne, S. I., Stanelle, T., van den
Hurk, B. J. J. M., Vitart, F., and Wood, E. F.: Contribution of land surface
initialization to subseasonal forecast skill: First results from a
multi-model experiment, Geophys. Res. Lett., 37, L02402,
https://doi.org/10.1029/2009GL041677, 2010.
Kurum, M., Lang, R. H., O'Neill, P. E., Joseph, A. T., Jackson, T. J., and
Cosh, M. H.: A First-Order Radiative Transfer Model for Microwave Radiometry
of Forest Canopies at L-Band, IEEE T. Geosci. Remote, 49, 3167–3179,
https://doi.org/10.1109/TGRS.2010.2091139, 2011.
Leroux, D. J., Das, N. N., Entekhabi, D., Colliander, A., Njoku, E., Jackson,
T. J., and Yueh, S.: Active–Passive Soil Moisture Retrievals During the SMAP
Validation Experiment 2012, IEEE Geosci. Remote S., 13, 475–479,
https://doi.org/10.1109/LGRS.2015.2491643, 2016.
Manfreda, S., McCabe, M. F., Fiorentino, M., Rodríguez-Iturbe, I., and
Wood, E. F.: Scaling characteristics of spatial patterns of soil moisture
from distributed modelling, Adv. Water Resour., 30 2145–2150,
https://doi.org/10.1016/j.advwatres.2006.07.009, 2007.
Markewitz, D., Devine, S., Davidson, E. A., Brando, P., and Nepstad, D. C.:
Soil moisture depletion under simulated drought in the Amazon: impacts on
deep root uptake, New Phytol., 187, 592–607,
https://doi.org/10.1111/j.1469-8137.2010.03391.x, 2010.
Marthews, T. R., Dadson, S. J., Lehner, B., Abele, S., and Gedney, N.:
High-resolution global topographic index values for use in large-scale
hydrological modelling, Hydrol. Earth Syst. Sci., 19, 91–104,
https://doi.org/10.5194/hess-19-91-2015, 2015.
Mascaro, G., Vivoni, E. R., and Deidda, R.: Soil moisture downscaling across
climate regions and its emergent properties, J. Geophys. Res., 116, D22114,
https://doi.org/10.1029/2011JD016231, 2011.
McColl, K. A., Alemohammad, S. H., Akbar, R., Konings, A. G., Yueh, S., and
Entekhabi, D.: The global distribution and dynamics of surface soil moisture,
Nat. Geosci., 10, 100–104, https://doi.org/10.1038/ngeo2868, 2017.
Merlin, O., Chehbouni, A. G., Kerr, Y. H., Njoku, E. G., and Entekhabi, D.: A
combined modeling and multispectral/multiresolution remote sensing approach
for disaggregation of surface soil moisture: application to SMOS
configuration, IEEE T. Geosci. Remote, 43, 2036–2050,
https://doi.org/10.1109/TGRS.2005.853192, 2005.
Merlin, O., Chehbouni, A., Kerr, Y. H., and Goodrich, D. C.: A downscaling
method for distributing surface soil moisture within a microwave pixel:
Application to the Monsoon '90 data, Remote Sens. Environ., 101, 379–389,
https://doi.org/10.1016/j.rse.2006.01.004, 2006.
Merlin, O., Chehbouni, A., Walker, J. P., Panciera, R., and Kerr, Y. H.: A
Simple Method to Disaggregate Passive Microwave-Based Soil Moisture, IEEE
T. Geosci. Remote, 46, 786–796, https://doi.org/10.1109/TGRS.2007.914807, 2008a.
Merlin, O., Walker, J. P., Kalma, J. D., Kim, E. J., Hacker, J., Panciera,
R., Young, R., Summerell, G., Hornbuckle, J., Hafeez, M., and Jackson, T.:
The NAFE'06 data set: Towards soil moisture retrieval at intermediate
resolution, Adv. Water Resour., 31, 1444–1455,
https://doi.org/10.1016/j.advwatres.2008.01.018, 2008b.
Merlin, O., Walker, J. P., Chehbouni, A., and Kerr, Y. H.: Towards
deterministic downscaling of SMOS soil moisture using MODIS derived soil
evaporative efficiency, Remote Sens. Environ., 112, 3935–3946,
https://doi.org/10.1016/j.rse.2008.06.012, 2008c.
Merlin, O., Al Bitar, A., Walker, J. P., and Kerr, Y.: A sequential model for
disaggregating near-surface soil moisture observations using multi-resolution
thermal sensors, Remote Sens. Environ., 113, 2275–2284,
https://doi.org/10.1016/j.rse.2009.06.012, 2009.
Merlin, O., Escorihuela, M. J., Mayoral, M. A., Hagolle, O., Al Bitar, A.,
and Kerr, Y.: Self-calibrated evaporation-based disaggregation of SMOS soil
moisture: An evaluation study at 3 km and 100 m resolution in Catalunya,
Spain, Remote Sens. Environ., 130, 25–38, https://doi.org/10.1016/j.rse.2012.11.008,
2013.
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. Sel. Top. Appl., 3, 522–535,
https://doi.org/10.1109/JSTARS.2010.2052918, 2010.
Moghaddam, M., Silva, A. R., Clewley, D., Akbar, R., Hussaini, S. A.,
Whitcomb, J. B., Devarakonda, R., Shrestha, R., Cook, R. B., Prakash, G.,
Santhana Vannan, S. K., and Boyer, A. G.: Soil Moisture Profiles and
Temperature Data from SoilSCAPE Sites, USA, ORNL DAAC, Oak Ridge, Tennessee,
USA, https://doi.org/10.3334/ORNLDAAC/1339, 2016.
Montzka, C., Jagdhuber, T., Horn, R., Bogena, H. R., Hajnsek, I., Reigber,
A., and Vereecken, H.: Investigation of SMAP Fusion Algorithms With Airborne
Active and Passive L-Band Microwave Remote Sensing, IEEE T. Geosci. Remote,
54, 3878–3889, https://doi.org/10.1109/TGRS.2016.2529659, 2016.
Morton, D. C., Nagol, J., Carabajal, C. C., Rosette, J., Palace, M., Cook, B.
D., Vermote, E. F., Harding, D. J., and North, P. R. J.: Amazon forests
maintain consistent canopy structure and greenness during the dry season,
Nature, 506, 221–224, https://doi.org/10.1038/nature13006, 2014.
Njoku, E. G., Wilson, W. J., Yueh, S. H., Dinardo, S. J., Li, F. K., Jackson,
T. J., Lakshmi, V., and Bolten, J.: Observations of soil moisture using a
passive and active low-frequency microwave airborne sensor during SGP99, IEEE
T. Geosci. Remote, 40, 2659–2673, https://doi.org/10.1109/TGRS.2002.807008, 2002.
O'Neill, P. E., Njoku, E. G., Jackson, T. J., Chan, S., and Bindlish, R.:
SMAP algorithm theoretical basis document: Level 2 & 3 soil moisture
(passive) data products, Jet Propulsion Lab., California Inst. Technol.,
Pasadena, CA, USA, JPL D-66480, 2015.
O'Neill, P. E., Chan, S. K., Njoku, E. G., Jackson, T. J., and Bindlish, R.:
SMAP Enhanced L3 Radiometer Global Daily 9 km EASE-Grid Soil Moisture,
Version 1, Boulder, Colorado USA, NASA National Snow and Ice Data Center
Distributed Active Archive Center, https://doi.org/10.5067/ZRO7EXJ8O3XI (last access:
30 May 2017), 2016a.
O'Neill, P. E., Chan, S. K., Njoku, E. G., Jackson, T., and Bindlish, R.:
SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 4,
Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed
Active Archive Center, https://doi.org/10.5067/OBBHQ5W22HME (last access: 30 May 2017),
2016b.
Peng, J., Loew, A., Merlin, O., and Verhoest, N. E. C.: A review of spatial
downscaling of satellite remotely sensed soil moisture, Rev. Geophys., 55,
341–366, https://doi.org/10.1002/2016RG000543, 2017.
Piles, M., Entekhabi, D., and Camps, A.: A change detection algorithm for
retrieving high-resolution soil moisture from SMAP radar and radiometer
observations, IEEE T. Geosci. Remote Sens., 47, 4125–4131,
https://doi.org/10.1109/TGRS.2009.2022088, 2009.
Piles, M., Camps, A., Vall-llossera, M., Corbella, I., Panciera, R., Rudiger,
C., Kerr, Y. H., and Walker, J.: Downscaling SMOS-Derived Soil Moisture Using
MODIS Visible/Infrared Data, IEEE T. Geosci. Remote Sens., 49, 3156–3166,
https://doi.org/10.1109/TGRS.2011.2120615, 2011.
Piles, M., Sanchez, N., Vall-llossera, M., Camps, A., Martinez-Fernandez, J.,
Martinez, J., and Gonzalez-Gambau, V.: A Downscaling Approach for SMOS Land
Observations: Evaluation of High-Resolution Soil Moisture Maps Over the
Iberian Peninsula, IEEE J. Sel. Top. Appl., 7, 3845–3857,
https://doi.org/10.1109/JSTARS.2014.2325398, 2014.
Rodriíguez-Fernández, N. J., Aires, F., Richaume, P., Kerr, Y. H.,
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.
Rodríguez-Fernández, N. J., Muñoz Sabater, J., Richaume, P., de
Rosnay, P., Kerr, Y. H., 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.
Rodríguez-Iturbe, I. and Porporato, A.: Ecohydrology of water-controlled
ecosystems: soil moisture and plant dynamics, Cambridge University Press,
Cambridge, UK, 2007.
Roerink, G. J., Su, Z., and Menenti, M.: S-SEBI: A simple remote sensing
algorithm to estimate the surface energy balance, Phys. Chem. Earth Pt. B,
25, 147–157, https://doi.org/10.1016/S1464-1909(99)00128-8, 2000.
Rumelhart, D. E., Hinton, G. E., and Williams, R. J.: Learning internal
representations by error propagation, No. ICS-8506, La Jolla Inst. for
Cognitive Science, California Univ., San Diego, 1985.
Salvucci, G. D.: An approximate solution for steady vertical flux of moisture
through an unsaturated homogeneous soil, Water Resour. Res., 29, 3749–3753,
https://doi.org/10.1029/93WR02068, 1993.
Salvucci, G. D. and Entekhabi, D.: Equivalent steady soil moisture profile
and the time compression approximation in water balance modeling, Water
Resour. Res., 30, 2737–2749, https://doi.org/10.1029/94WR00948, 1994.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B.,
Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil
moisture–climate interactions in a changing climate: A review, Earth-Sci.
Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010.
Shin, Y. and Mohanty, B. P.: Development of a deterministic downscaling
algorithm for remote sensing soil moisture footprint using soil and
vegetation classifications, Water Resour. Res., 49, 6208–6228,
https://doi.org/10.1002/wrcr.20495, 2013.
Srivastava, P. K., Han, D., Ramirez, M. R., and Islam, T.: Machine Learning
Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land
Surface Temperature for Hydrological Application, Water Resour. Manag., 27,
3127–3144, https://doi.org/10.1007/s11269-013-0337-9, 2013.
Sun, J., Salvucci, G. D., Entekhabi, D., and Farhadi, L.: Parameter
estimation of coupled water and energy balance models based on stationary
constraints of surface states, Water Resour. Res., 47, W02512,
https://doi.org/10.1029/2010WR009293, 2011.
Verhoest, N. E. C., van den Berg, M. J., Martens, B., Lievens, H., Wood, E.
F., Pan, M., Kerr, Y. H., Al Bitar, A., Tomer, S. K., Drusch, M., Vernieuwe,
H., De Baets, B., Walker, J. P., Dumedah, G., and Pauwels, V. R. N.:
Copula-Based Downscaling of Coarse-Scale Soil Moisture Observations With
Implicit Bias Correction, IEEE T. Geosci. Remote, 53, 3507–3521,
https://doi.org/10.1109/TGRS.2014.2378913, 2015.
Volk, M., Niklaus, P. A., and Körner, C.: Soil moisture effects determine
CO2 responses of grassland species, Oecologia, 125, 380–388,
https://doi.org/10.1007/s004420000454, 2000.
Wang, L., Good, S. P., and Caylor, K. K.: Global synthesis of vegetation
control on evapotranspiration partitioning, Geophys. Res. Lett., 41,
6753–6757, https://doi.org/10.1002/2014GL061439, 2014.
Western, A. W. and Blöschl, G.: On the spatial scaling of soil moisture,
J. Hydrol., 217, 203–224, https://doi.org/10.1016/S0022-1694(98)00232-7, 1999.
Wu, X., Walker, J. P., Rudiger, C., Panciera, R., and Gao, Y.:
Intercomparison of Alternate Soil Moisture Downscaling Algorithms Using
Active–Passive Microwave Observations, IEEE Geosci. Remote S., 14, 179–183,
https://doi.org/10.1109/LGRS.2016.2633521, 2017.
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., Munch, J. C., Papen, H., Priesack, E., Schmid, H.
P., Steinbrecher, R., Rosenbaum, U., Teutsch, G., and Vereecken, H.: A
Network of Terrestrial Environmental Observatories in Germany, Vadose
Zone J., 10, 955, https://doi.org/10.2136/vzj2010.0139, 2011.
Short summary
A new machine learning algorithm is developed to downscale satellite-based soil moisture estimates from their native spatial scale of 9 km to 2.25 km.
A new machine learning algorithm is developed to downscale satellite-based soil moisture...
