Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-207-2019
© Author(s) 2019. 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-23-207-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS
Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
Tirthankar Roy
Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
Graham P. Weedon
Met Office, JCHMR, Maclean Building, Benson Lane, Crowmarsh Gifford, Oxfordshire, UK
Florian Pappenberger
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Albert I. J. M. van Dijk
Fenner School for Environment and Society, Australian National University, Canberra, Australia
George J. Huffman
NASA Goddard Space Flight Center (GSFC), Greenbelt, Maryland, USA
Robert F. Adler
University of Maryland, Earth System Science Interdisciplinary Center, College Park, Maryland, USA
Eric F. Wood
Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
Related authors
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 17, 7181–7198, https://doi.org/10.5194/gmd-17-7181-2024, https://doi.org/10.5194/gmd-17-7181-2024, 2024
Short summary
Short summary
Accurate hydrologic modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall–runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional modeling approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
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.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Diego G. Miralles, Hylke E. Beck, Jonatan F. Siegmund, Camila Alvarez-Garreton, Koen Verbist, René Garreaud, Juan Pablo Boisier, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, https://doi.org/10.5194/hess-28-1415-2024, 2024
Short summary
Short summary
Various drought indices exist, but there is no consensus on which index to use to assess streamflow droughts. This study addresses meteorological, soil moisture, and snow indices along with their temporal scales to assess streamflow drought across hydrologically diverse catchments. Using data from 100 Chilean catchments, findings suggest that there is not a single drought index that can be used for all catchments and that snow-influenced areas require drought indices with larger temporal scales.
Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 27, 2357–2373, https://doi.org/10.5194/hess-27-2357-2023, https://doi.org/10.5194/hess-27-2357-2023, 2023
Short summary
Short summary
Powerful hybrid models (called δ or delta models) embrace the fundamental learning capability of AI and can also explain the physical processes. Here we test their performance when applied to regions not in the training data. δ models rivaled the accuracy of state-of-the-art AI models under the data-dense scenario and even surpassed them for the data-sparse one. They generalize well due to the physical structure included. δ models could be ideal candidates for global hydrologic assessment.
Sara Sadri, James S. Famiglietti, Ming Pan, Hylke E. Beck, Aaron Berg, and Eric F. Wood
Hydrol. Earth Syst. Sci., 26, 5373–5390, https://doi.org/10.5194/hess-26-5373-2022, https://doi.org/10.5194/hess-26-5373-2022, 2022
Short summary
Short summary
A farm-scale hydroclimatic machine learning framework to advise farmers was developed. FarmCan uses remote sensing data and farmers' input to forecast crop water deficits. The 8 d composite variables are better than daily ones for forecasting water deficit. Evapotranspiration (ET) and potential ET are more effective than soil moisture at predicting crop water deficit. FarmCan uses a crop-specific schedule to use surface or root zone soil moisture.
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.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Pablo A. Mendoza, Ian McNamara, Hylke E. Beck, Joschka Thurner, Alexandra Nauditt, Lars Ribbe, and Nguyen Xuan Thinh
Hydrol. Earth Syst. Sci., 25, 5805–5837, https://doi.org/10.5194/hess-25-5805-2021, https://doi.org/10.5194/hess-25-5805-2021, 2021
Short summary
Short summary
Most rivers worldwide are ungauged, which hinders the sustainable management of water resources. Regionalisation methods use information from gauged rivers to estimate streamflow over ungauged ones. Through hydrological modelling, we assessed how the selection of precipitation products affects the performance of three regionalisation methods. We found that a precipitation product that provides the best results in hydrological modelling does not necessarily perform the best for regionalisation.
Peter Uhe, Daniel Mitchell, Paul D. Bates, Nans Addor, Jeff Neal, and Hylke E. Beck
Geosci. Model Dev., 14, 4865–4890, https://doi.org/10.5194/gmd-14-4865-2021, https://doi.org/10.5194/gmd-14-4865-2021, 2021
Short summary
Short summary
We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs, e.g., rainfall and temperature from observations or climate models, and takes them through a series of modeling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data sets, allowing it to be applied anywhere in the world.
Yuting Yang, Tim R. McVicar, Dawen Yang, Yongqiang Zhang, Shilong Piao, Shushi Peng, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 25, 3411–3427, https://doi.org/10.5194/hess-25-3411-2021, https://doi.org/10.5194/hess-25-3411-2021, 2021
Short summary
Short summary
This study developed an analytical ecohydrological model that considers three aspects of vegetation response to eCO2 (i.e., stomatal response, LAI response, and rooting depth response) to detect the impact of eCO2 on continental runoff over the past 3 decades globally. Our findings suggest a minor role of eCO2 on the global runoff changes, yet highlight the negative runoff–eCO2 response in semiarid and arid regions which may further threaten the limited water resource there.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
Short summary
Short summary
Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
Short summary
Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Sanaa Hobeichi, Gab Abramowitz, Jason Evans, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 23, 851–870, https://doi.org/10.5194/hess-23-851-2019, https://doi.org/10.5194/hess-23-851-2019, 2019
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.
Yu Zhang, Ming Pan, Justin Sheffield, Amanda L. Siemann, Colby K. Fisher, Miaoling Liang, Hylke E. Beck, Niko Wanders, Rosalyn F. MacCracken, Paul R. Houser, Tian Zhou, Dennis P. Lettenmaier, Rachel T. Pinker, Janice Bytheway, Christian D. Kummerow, and Eric F. Wood
Hydrol. Earth Syst. Sci., 22, 241–263, https://doi.org/10.5194/hess-22-241-2018, https://doi.org/10.5194/hess-22-241-2018, 2018
Short summary
Short summary
A global data record for all four terrestrial water budget variables (precipitation, evapotranspiration, runoff, and total water storage change) at 0.5° resolution and monthly scale for the period of 1984–2010 is developed by optimally merging a series of remote sensing products, in situ measurements, land surface model outputs, and atmospheric reanalysis estimates and enforcing the mass balance of water. Initial validations show the data record is reliable for climate related analysis.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
Short summary
Short summary
This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
Short summary
Short summary
The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Hylke E. Beck, Albert I. J. M. van Dijk, Ad de Roo, Emanuel Dutra, Gabriel Fink, Rene Orth, and Jaap Schellekens
Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, https://doi.org/10.5194/hess-21-2881-2017, 2017
Short summary
Short summary
Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
Short summary
Short summary
Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
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.
Chad A. Burton, Sami W. Rifai, Luigi J. Renzullo, and Albert I. J. M. Van Dijk
Earth Syst. Sci. Data, 16, 4389–4416, https://doi.org/10.5194/essd-16-4389-2024, https://doi.org/10.5194/essd-16-4389-2024, 2024
Short summary
Short summary
Understanding vegetation response to environmental change requires accurate, long-term data on vegetation condition (VC). We evaluated existing satellite VC datasets over Australia and found them lacking, so we developed a new VC dataset for Australia, AusENDVI. It can be used for studying Australia's changing vegetation dynamics and downstream impacts on the carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change.
Liqing Peng, Justin Sheffield, Zhongwang Wei, Michael Ek, and Eric F. Wood
Earth Syst. Dynam., 15, 1277–1300, https://doi.org/10.5194/esd-15-1277-2024, https://doi.org/10.5194/esd-15-1277-2024, 2024
Short summary
Short summary
Integrating evaporative demand into drought indicators is effective, but the choice of method and the effectiveness of surface features remain undocumented. We evaluate various methods and surface features for predicting soil moisture dynamics. Using minimal ancillary information alongside meteorological and vegetation data, we develop a simple land-cover-based method that improves soil moisture drought predictions, especially in forests, showing promise for better real-time drought forecasting.
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 17, 7181–7198, https://doi.org/10.5194/gmd-17-7181-2024, https://doi.org/10.5194/gmd-17-7181-2024, 2024
Short summary
Short summary
Accurate hydrologic modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall–runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional modeling approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
Short summary
Short summary
Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, Margarita Choulga, Souhail Boussetta, Maria Kalweit, Joschka Bödecker, Carsten F. Dormann, Florian Pappenberger, and Gianpaolo Balsamo
EGUsphere, https://doi.org/10.5194/egusphere-2024-2081, https://doi.org/10.5194/egusphere-2024-2081, 2024
Short summary
Short summary
We compared spatio-temporal forecast performances of three popular machine learning approaches that learned processes of water and energy exchange on the earth surface from a large physical model. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the Globe. We found that all approaches deliver highly accurate predictions until long time horizons, implying their usefulness to advance land surface forecasting when data is available.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
Short summary
Short summary
We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
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.
Yi Y. Liu, Albert I. J. M. van Dijk, Patrick Meir, and Tim R. McVicar
Biogeosciences, 21, 2273–2295, https://doi.org/10.5194/bg-21-2273-2024, https://doi.org/10.5194/bg-21-2273-2024, 2024
Short summary
Short summary
Greenness of the Amazon forest fluctuated during the 2015–2016 drought, but no satisfactory explanation has been found. Based on water storage, temperature, and atmospheric moisture demand, we developed a method to delineate the regions where forests were under stress. These drought-affected regions were mainly identified at the beginning and end of the drought, resulting in below-average greenness. For the months in between, without stress, greenness responded positively to intense sunlight.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Diego G. Miralles, Hylke E. Beck, Jonatan F. Siegmund, Camila Alvarez-Garreton, Koen Verbist, René Garreaud, Juan Pablo Boisier, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, https://doi.org/10.5194/hess-28-1415-2024, 2024
Short summary
Short summary
Various drought indices exist, but there is no consensus on which index to use to assess streamflow droughts. This study addresses meteorological, soil moisture, and snow indices along with their temporal scales to assess streamflow drought across hydrologically diverse catchments. Using data from 100 Chilean catchments, findings suggest that there is not a single drought index that can be used for all catchments and that snow-influenced areas require drought indices with larger temporal scales.
Jiawei Hou, Albert I. J. M. Van Dijk, Luigi J. Renzullo, and Pablo R. Larraondo
Earth Syst. Sci. Data, 16, 201–218, https://doi.org/10.5194/essd-16-201-2024, https://doi.org/10.5194/essd-16-201-2024, 2024
Short summary
Short summary
The GloLakes dataset provides historical and near-real-time time series of relative (i.e. storage change) and absolute (i.e. total stored volume) storage for more than 27 000 lakes worldwide using multiple sources of satellite data, including laser and radar altimetry and optical remote sensing. These data can help us understand the influence of climate variability and anthropogenic activities on water availability and system ecology over the last 4 decades.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
Short summary
Short summary
Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 27, 2357–2373, https://doi.org/10.5194/hess-27-2357-2023, https://doi.org/10.5194/hess-27-2357-2023, 2023
Short summary
Short summary
Powerful hybrid models (called δ or delta models) embrace the fundamental learning capability of AI and can also explain the physical processes. Here we test their performance when applied to regions not in the training data. δ models rivaled the accuracy of state-of-the-art AI models under the data-dense scenario and even surpassed them for the data-sparse one. They generalize well due to the physical structure included. δ models could be ideal candidates for global hydrologic assessment.
Kieran M. R. Hunt, Gwyneth R. Matthews, Florian Pappenberger, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 5449–5472, https://doi.org/10.5194/hess-26-5449-2022, https://doi.org/10.5194/hess-26-5449-2022, 2022
Short summary
Short summary
In this study, we use three models to forecast river streamflow operationally for 13 months (September 2020 to October 2021) at 10 gauges in the western US. The first model is a state-of-the-art physics-based streamflow model (GloFAS). The second applies a bias-correction technique to GloFAS. The third is a type of neural network (an LSTM). We find that all three are capable of producing skilful forecasts but that the LSTM performs the best, with skilful 5 d forecasts at nine stations.
Sara Sadri, James S. Famiglietti, Ming Pan, Hylke E. Beck, Aaron Berg, and Eric F. Wood
Hydrol. Earth Syst. Sci., 26, 5373–5390, https://doi.org/10.5194/hess-26-5373-2022, https://doi.org/10.5194/hess-26-5373-2022, 2022
Short summary
Short summary
A farm-scale hydroclimatic machine learning framework to advise farmers was developed. FarmCan uses remote sensing data and farmers' input to forecast crop water deficits. The 8 d composite variables are better than daily ones for forecasting water deficit. Evapotranspiration (ET) and potential ET are more effective than soil moisture at predicting crop water deficit. FarmCan uses a crop-specific schedule to use surface or root zone soil moisture.
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.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
Short summary
Short summary
Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Pablo A. Mendoza, Ian McNamara, Hylke E. Beck, Joschka Thurner, Alexandra Nauditt, Lars Ribbe, and Nguyen Xuan Thinh
Hydrol. Earth Syst. Sci., 25, 5805–5837, https://doi.org/10.5194/hess-25-5805-2021, https://doi.org/10.5194/hess-25-5805-2021, 2021
Short summary
Short summary
Most rivers worldwide are ungauged, which hinders the sustainable management of water resources. Regionalisation methods use information from gauged rivers to estimate streamflow over ungauged ones. Through hydrological modelling, we assessed how the selection of precipitation products affects the performance of three regionalisation methods. We found that a precipitation product that provides the best results in hydrological modelling does not necessarily perform the best for regionalisation.
Chloe Brimicombe, Claudia Di Napoli, Rosalind Cornforth, Florian Pappenberger, Celia Petty, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-242, https://doi.org/10.5194/nhess-2021-242, 2021
Revised manuscript not accepted
Short summary
Short summary
Heatwaves are an increasing risk to African communities. This hazard can have a negative impact on peoples lives and in some cases results in their death. This study shows new information about heatwave characteristics through a list of heatwave events that have been reported for the African continent from 1980 until 2020. Case studies are useful helps to inform the development of early warning systems and forecasting, which is an urgent priority and needs significant improvement.
Peter Uhe, Daniel Mitchell, Paul D. Bates, Nans Addor, Jeff Neal, and Hylke E. Beck
Geosci. Model Dev., 14, 4865–4890, https://doi.org/10.5194/gmd-14-4865-2021, https://doi.org/10.5194/gmd-14-4865-2021, 2021
Short summary
Short summary
We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs, e.g., rainfall and temperature from observations or climate models, and takes them through a series of modeling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data sets, allowing it to be applied anywhere in the world.
Florian Pappenberger, Florence Rabier, and Fabio Venuti
Nat. Hazards Earth Syst. Sci., 21, 2163–2167, https://doi.org/10.5194/nhess-21-2163-2021, https://doi.org/10.5194/nhess-21-2163-2021, 2021
Short summary
Short summary
The European Centre for Medium-Range Weather Forecasts mission is to deliver high-quality global medium‐range (3–15 d ahead of time) weather forecasts and monitoring of the Earth system. We have published a new strategy, and in this paper we discuss what this means for forecasting and monitoring natural hazards.
Yuting Yang, Tim R. McVicar, Dawen Yang, Yongqiang Zhang, Shilong Piao, Shushi Peng, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 25, 3411–3427, https://doi.org/10.5194/hess-25-3411-2021, https://doi.org/10.5194/hess-25-3411-2021, 2021
Short summary
Short summary
This study developed an analytical ecohydrological model that considers three aspects of vegetation response to eCO2 (i.e., stomatal response, LAI response, and rooting depth response) to detect the impact of eCO2 on continental runoff over the past 3 decades globally. Our findings suggest a minor role of eCO2 on the global runoff changes, yet highlight the negative runoff–eCO2 response in semiarid and arid regions which may further threaten the limited water resource there.
Sarah Sparrow, Andrew Bowery, Glenn D. Carver, Marcus O. Köhler, Pirkka Ollinaho, Florian Pappenberger, David Wallom, and Antje Weisheimer
Geosci. Model Dev., 14, 3473–3486, https://doi.org/10.5194/gmd-14-3473-2021, https://doi.org/10.5194/gmd-14-3473-2021, 2021
Short summary
Short summary
This paper describes how the research version of the European Centre for Medium-Range Weather Forecasts’ Integrated Forecast System is combined with climateprediction.net’s public volunteer computing resource to develop OpenIFS@home. Thousands of volunteer personal computers simulated slightly different realizations of Tropical Cyclone Karl to demonstrate the performance of the large-ensemble forecast. OpenIFS@Home offers researchers a new tool to study weather forecasts and related questions.
André Almagro, Paulo Tarso S. Oliveira, Antônio Alves Meira Neto, Tirthankar Roy, and Peter Troch
Hydrol. Earth Syst. Sci., 25, 3105–3135, https://doi.org/10.5194/hess-25-3105-2021, https://doi.org/10.5194/hess-25-3105-2021, 2021
Short summary
Short summary
We have collected and synthesized catchment attributes from multiple sources into an extensive dataset, the Catchment Attributes for Brazil (CABra). CABra contains streamflow and climate daily series for 735 catchments in the 1980–2010 period, aside from dozens of attributes of topography, climate, streamflow, groundwater, soil, geology, land cover, and hydrologic disturbance. The CABra intends to pave the way for a better understanding of catchments' behavior in Brazil and the world.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
Short summary
Short summary
Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
Short summary
Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Peng Ji, Xing Yuan, Feng Ma, and Ming Pan
Hydrol. Earth Syst. Sci., 24, 5439–5451, https://doi.org/10.5194/hess-24-5439-2020, https://doi.org/10.5194/hess-24-5439-2020, 2020
Short summary
Short summary
By performing high-resolution land surface modeling driven by the latest CMIP6 climate models, we find both the dry streamflow extreme over the drought-prone Yellow River headwater and the wet streamflow extreme over the flood-prone Yangtze River headwater will increase under 1.5, 2.0 and 3.0 °C global warming levels and emphasize the importance of considering ecological changes (i.e., vegetation greening and CO2 physiological forcing) in the hydrological projection.
Songyan Yu, Hong Xuan Do, Albert I. J. M. van Dijk, Nick R. Bond, Peirong Lin, and Mark J. Kennard
Hydrol. Earth Syst. Sci., 24, 5279–5295, https://doi.org/10.5194/hess-24-5279-2020, https://doi.org/10.5194/hess-24-5279-2020, 2020
Short summary
Short summary
There is a growing interest globally in the spatial distribution and temporal dynamics of intermittently flowing streams and rivers. We developed an approach to quantify catchment-wide flow intermittency over long time frames. Modelled patterns of flow intermittency in eastern Australia revealed highly dynamic behaviour in space and time. The developed approach is transferable to other parts of the world and can inform hydro-ecological understanding and management of intermittent streams.
Marco Cucchi, Graham P. Weedon, Alessandro Amici, Nicolas Bellouin, Stefan Lange, Hannes Müller Schmied, Hans Hersbach, and Carlo Buontempo
Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, https://doi.org/10.5194/essd-12-2097-2020, 2020
Short summary
Short summary
WFDE5 is a novel meteorological forcing dataset for running land surface and global hydrological models. It has been generated using the WATCH Forcing Data methodology applied to surface meteorological variables from the ERA5 reanalysis. It is publicly available, along with its source code, through the C3S Climate Data Store at ECMWF. Results of the evaluations described in the paper highlight the benefits of using WFDE5 compared to both ERA5 and its predecessor WFDEI.
Shaun Harrigan, Ervin Zsoter, Lorenzo Alfieri, Christel Prudhomme, Peter Salamon, Fredrik Wetterhall, Christopher Barnard, Hannah Cloke, and Florian Pappenberger
Earth Syst. Sci. Data, 12, 2043–2060, https://doi.org/10.5194/essd-12-2043-2020, https://doi.org/10.5194/essd-12-2043-2020, 2020
Short summary
Short summary
A new river discharge reanalysis dataset is produced operationally by coupling ECMWF's latest global atmospheric reanalysis, ERA5, with the hydrological modelling component of the Global Flood Awareness System (GloFAS). The GloFAS-ERA5 reanalysis is a global gridded dataset with a horizontal resolution of 0.1° at a daily time step and is freely available from 1979 until near real time. The evaluation against observations shows that the GloFAS-ERA5 reanalysis was skilful in 86 % of catchments.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
Short summary
Short summary
Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Colby K. Fisher, Ming Pan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 24, 293–305, https://doi.org/10.5194/hess-24-293-2020, https://doi.org/10.5194/hess-24-293-2020, 2020
Short summary
Short summary
Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage. In this paper we present a method to derive continuous records of streamflow from a set of in situ gauges. Applying this method to the Ohio River basin, we found that we could reliably generate estimates of streamflow throughout the basin using only a small set of streamflow gauges, which can be useful for global river basins where we do not have good observations.
Jiawei Hou, Albert I. J. M. van Dijk, Luigi J. Renzullo, Robert A. Vertessy, and Norman Mueller
Earth Syst. Sci. Data, 11, 1003–1015, https://doi.org/10.5194/essd-11-1003-2019, https://doi.org/10.5194/essd-11-1003-2019, 2019
Short summary
Short summary
Hydromorphological data including temporal and spatial river width dynamics, flow regime, and river gradient for 1.4 x 106 Australian river reaches are presented. We propose a parameter which can be used to classify reaches by the degree to which flow regime tends towards permanent, frequent, intermittent, or ephemeral. This dataset provides fundamental information for understanding hydrological, biogeochemical, and ecological processes in floodplain–river systems.
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, https://doi.org/10.5194/os-15-669-2019, 2019
Short summary
Short summary
Forecasts of ocean temperature, salinity, currents, and sea height can be improved by linking state-of-the-art ocean and wave models, so that they can interact to better represent the real world. We test this approach in an ocean model of north-west Europe which can simulate small-scale details of the ocean state. The intention is to implement the system described in this study for operational use so that improved information can be provided to users of ocean forecast data.
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
Alberto Martínez-de la Torre, Eleanor M. Blyth, and Graham P. Weedon
Geosci. Model Dev., 12, 765–784, https://doi.org/10.5194/gmd-12-765-2019, https://doi.org/10.5194/gmd-12-765-2019, 2019
Short summary
Short summary
Land–surface interactions with the atmosphere are key for weather and climate modelling studies, both in research and in the operational systems that provide scientific tools for decision makers. Regional assessments will be influenced by the characteristics of the land. We improved the representation of river flows in Great Britain by including a dependency on the terrain slope. This development will be reflected not only in river flows, but in the whole water cycle represented by the model.
Sanaa Hobeichi, Gab Abramowitz, Jason Evans, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 23, 851–870, https://doi.org/10.5194/hess-23-851-2019, https://doi.org/10.5194/hess-23-851-2019, 2019
Sara Sadri, Eric F. Wood, and Ming Pan
Hydrol. Earth Syst. Sci., 22, 6611–6626, https://doi.org/10.5194/hess-22-6611-2018, https://doi.org/10.5194/hess-22-6611-2018, 2018
Short summary
Short summary
Of particular interest to NASA's SMAP-based agricultural applications is a monitoring product that assesses near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for the meaningful assessment of its indices. This study presents initial insights about using SMAP Level 3 and Level 4 for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS).
Christophe Lavaysse, Jürgen Vogt, Andrea Toreti, Marco L. Carrera, and Florian Pappenberger
Nat. Hazards Earth Syst. Sci., 18, 3297–3309, https://doi.org/10.5194/nhess-18-3297-2018, https://doi.org/10.5194/nhess-18-3297-2018, 2018
Short summary
Short summary
Forecasting droughts in Europe 1 month in advance would provide valuable information for decision makers. However, these extreme events are still difficult to predict. In this study, we develop forecasts based on predictors using the geopotential anomalies, generally more predictable than precipitation, derived from the ECMWF model. Results show that this approach outperforms the prediction using precipitation, especially in winter and in northern Europe, where 65 % of droughts are predicted.
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.
Peter A. Troch, Ravindra Dwivedi, Tao Liu, Antonio Alves Meira Neto, Tirthankar Roy, Rodrigo Valdés-Pineda, Matej Durcik, Saúl Arciniega-Esparza, and José Agustín Breña-Naranjo
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-449, https://doi.org/10.5194/hess-2018-449, 2018
Revised manuscript not accepted
Short summary
Short summary
Recharge to bedrock aquifers is an important source of water availability and sustains streamflow during long dry periods. It is therefore an important component in the catchment water balance that sustains aquatic ecosystems. Our study shows that it is possible to predict average recharge rates at the catchment scale using only climate and landscape properties. This is an important finding as it is notoriously difficult to measure and/or estimate recharge rates at large spatial scales.
Anouk I. Gevaert, Luigi J. Renzullo, Albert I. J. M. van Dijk, Hans J. van der Woerd, Albrecht H. Weerts, and Richard A. M. de Jeu
Hydrol. Earth Syst. Sci., 22, 4605–4619, https://doi.org/10.5194/hess-22-4605-2018, https://doi.org/10.5194/hess-22-4605-2018, 2018
Short summary
Short summary
We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.
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.
Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah L. Cloke, Davide Muraro, Christel Prudhomme, Elisabeth M. Stephens, Peter Salamon, and Florian Pappenberger
Geosci. Model Dev., 11, 3327–3346, https://doi.org/10.5194/gmd-11-3327-2018, https://doi.org/10.5194/gmd-11-3327-2018, 2018
Short summary
Short summary
Global overviews of upcoming flood and drought events are key for many applications from agriculture to disaster risk reduction. Seasonal forecasts are designed to provide early indications of such events weeks or even months in advance. This paper introduces GloFAS-Seasonal, the first operational global-scale seasonal hydro-meteorological forecasting system producing openly available forecasts of high and low river flow out to 4 months ahead.
Emiliano Gelati, Bertrand Decharme, Jean-Christophe Calvet, Marie Minvielle, Jan Polcher, David Fairbairn, and Graham P. Weedon
Hydrol. Earth Syst. Sci., 22, 2091–2115, https://doi.org/10.5194/hess-22-2091-2018, https://doi.org/10.5194/hess-22-2091-2018, 2018
Short summary
Short summary
We compared land surface model simulations forced by several meteorological datasets with observations over the Euro-Mediterranean area, for the 1979–2012 period. Precipitation was the most uncertain forcing variable. The impacts of forcing uncertainty were larger on the mean and standard deviation rather than the timing, shape and inter-annual variability of simulated discharge. Simulated leaf area index and surface soil moisture were relatively insensitive to these uncertainties.
Louise Arnal, Hannah L. Cloke, Elisabeth Stephens, Fredrik Wetterhall, Christel Prudhomme, Jessica Neumann, Blazej Krzeminski, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 22, 2057–2072, https://doi.org/10.5194/hess-22-2057-2018, https://doi.org/10.5194/hess-22-2057-2018, 2018
Short summary
Short summary
This paper presents a new operational forecasting system (driven by atmospheric forecasts), predicting river flow in European rivers for the next 7 months. For the first month only, these river flow forecasts are, on average, better than predictions that do not make use of atmospheric forecasts. Overall, this forecasting system can predict whether abnormally high or low river flows will occur in the next 7 months in many parts of Europe, and could be valuable for various applications.
Alberto Martínez-de la Torre, Eleanor M. Blyth, and Graham P. Weedon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-750, https://doi.org/10.5194/hess-2017-750, 2018
Manuscript not accepted for further review
Short summary
Short summary
Land surface interactions with the atmosphere are key for weather and climate modelling studies, both in research and in the operational systems that provide scientific tools for decision makers. Regional assessments will be influenced by the characteristics of the land. We improved the representation of Great Britain river flows by including a dependency on terrain slope. This development will be reflected not only in river flows, but in the whole water cycle represented by the model/system.
Andreas Marx, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Niko Wanders, Matthias Zink, Eric F. Wood, Ming Pan, Justin Sheffield, and Luis Samaniego
Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, https://doi.org/10.5194/hess-22-1017-2018, 2018
Short summary
Short summary
Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.
Yu Zhang, Ming Pan, Justin Sheffield, Amanda L. Siemann, Colby K. Fisher, Miaoling Liang, Hylke E. Beck, Niko Wanders, Rosalyn F. MacCracken, Paul R. Houser, Tian Zhou, Dennis P. Lettenmaier, Rachel T. Pinker, Janice Bytheway, Christian D. Kummerow, and Eric F. Wood
Hydrol. Earth Syst. Sci., 22, 241–263, https://doi.org/10.5194/hess-22-241-2018, https://doi.org/10.5194/hess-22-241-2018, 2018
Short summary
Short summary
A global data record for all four terrestrial water budget variables (precipitation, evapotranspiration, runoff, and total water storage change) at 0.5° resolution and monthly scale for the period of 1984–2010 is developed by optimally merging a series of remote sensing products, in situ measurements, land surface model outputs, and atmospheric reanalysis estimates and enforcing the mass balance of water. Initial validations show the data record is reliable for climate related analysis.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
Short summary
Short summary
This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Erin Coughlan de Perez, Elisabeth Stephens, Konstantinos Bischiniotis, Maarten van Aalst, Bart van den Hurk, Simon Mason, Hannah Nissan, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 21, 4517–4524, https://doi.org/10.5194/hess-21-4517-2017, https://doi.org/10.5194/hess-21-4517-2017, 2017
Short summary
Short summary
Disaster managers would like to use seasonal forecasts to anticipate flooding months in advance. However, current seasonal forecasts give information on rainfall instead of flooding. Here, we find that the number of extreme events, rather than total rainfall, is most related to flooding in different regions of Africa. We recommend several forecast adjustments and research opportunities that would improve flood information at the seasonal timescale in different regions.
Yoshihide Wada, Marc F. P. Bierkens, Ad de Roo, Paul A. Dirmeyer, James S. Famiglietti, Naota Hanasaki, Megan Konar, Junguo Liu, Hannes Müller Schmied, Taikan Oki, Yadu Pokhrel, Murugesu Sivapalan, Tara J. Troy, Albert I. J. M. van Dijk, Tim van Emmerik, Marjolein H. J. Van Huijgevoort, Henny A. J. Van Lanen, Charles J. Vörösmarty, Niko Wanders, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 4169–4193, https://doi.org/10.5194/hess-21-4169-2017, https://doi.org/10.5194/hess-21-4169-2017, 2017
Short summary
Short summary
Rapidly increasing population and human activities have altered terrestrial water fluxes on an unprecedented scale. Awareness of potential water scarcity led to first global water resource assessments; however, few hydrological models considered the interaction between terrestrial water fluxes and human activities. Our contribution highlights the importance of human activities transforming the Earth's water cycle, and how hydrological models can include such influences in an integrated manner.
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.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
Short summary
Short summary
The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Hylke E. Beck, Albert I. J. M. van Dijk, Ad de Roo, Emanuel Dutra, Gabriel Fink, Rene Orth, and Jaap Schellekens
Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, https://doi.org/10.5194/hess-21-2881-2017, 2017
Short summary
Short summary
Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.
Lan T. Ha, Wim G. M. Bastiaanssen, Ann van Griensven, Albert I. J. M. van Dijk, and Gabriel B. Senay
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-251, https://doi.org/10.5194/hess-2017-251, 2017
Preprint withdrawn
Short summary
Short summary
The paper shows a new approach in calibrating hydrological model using remote sensing data from open access sources. The innovation is that the parameters of the soil-vegetation processes were optimized that will make SWAT a useful tool for optimizing water conservation, agricultural outputs, and ecosystem services such as reduced soil erosion, better water quality standards, carbon sequestration, micro-climate cooling and appraising scenarios of green growth.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
Short summary
Short summary
Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Louise Crochemore, Maria-Helena Ramos, Florian Pappenberger, and Charles Perrin
Hydrol. Earth Syst. Sci., 21, 1573–1591, https://doi.org/10.5194/hess-21-1573-2017, https://doi.org/10.5194/hess-21-1573-2017, 2017
Short summary
Short summary
The use of general circulation model outputs for streamflow forecasting has developed in the last decade. In parallel, traditional streamflow forecasting is commonly based on historical data. This study investigates the impact of conditioning historical data based on circulation model precipitation forecasts on seasonal streamflow forecast quality. Results highlighted a trade-off between the sharpness and reliability of forecasts.
Di Tian, Eric F. Wood, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 1477–1490, https://doi.org/10.5194/hess-21-1477-2017, https://doi.org/10.5194/hess-21-1477-2017, 2017
Short summary
Short summary
This study evaluated dynamic climate model sub-seasonal forecasts for important precipitation and temperature indices over the contiguous United States. The presence of active Madden-Julian Oscillation (MJO) events improved weekly mean precipitation forecast skill over most regions. Sub-seasonal forecast indices calculated from the daily forecast showed higher skill than temporally downscaled forecasts, suggesting the usefulness of the daily forecast for sub-seasonal hydrological forecasting.
Tirthankar Roy, Hoshin V. Gupta, Aleix Serrat-Capdevila, and Juan B. Valdes
Hydrol. Earth Syst. Sci., 21, 879–896, https://doi.org/10.5194/hess-21-879-2017, https://doi.org/10.5194/hess-21-879-2017, 2017
Short summary
Short summary
This study presents and compares two different approaches to using satellite-derived estimates of actual evapotranspiration (ET) to improve the performance of a conceptual rainfall–runoff model. In the first approach, the ET process within the model is constrained using the satellite ET estimates, while in the second one, the model structure is altered. Results indicate that both the approaches improve streamflow forecasting, while the second one also improves the ET simulations significantly.
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.
Caitlin E. Moore, Tim Brown, Trevor F. Keenan, Remko A. Duursma, Albert I. J. M. van Dijk, Jason Beringer, Darius Culvenor, Bradley Evans, Alfredo Huete, Lindsay B. Hutley, Stefan Maier, Natalia Restrepo-Coupe, Oliver Sonnentag, Alison Specht, Jeffrey R. Taylor, Eva van Gorsel, and Michael J. Liddell
Biogeosciences, 13, 5085–5102, https://doi.org/10.5194/bg-13-5085-2016, https://doi.org/10.5194/bg-13-5085-2016, 2016
Short summary
Short summary
Australian vegetation phenology is highly variable due to the diversity of ecosystems on the continent. We explore continental-scale variability using satellite remote sensing by broadly classifying areas as seasonal, non-seasonal, or irregularly seasonal. We also examine ecosystem-scale phenology using phenocams and show that some broadly non-seasonal ecosystems do display phenological variability. Overall, phenocams are useful for understanding ecosystem-scale Australian vegetation phenology.
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
Short summary
Short summary
In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
Louise Crochemore, Maria-Helena Ramos, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3601–3618, https://doi.org/10.5194/hess-20-3601-2016, https://doi.org/10.5194/hess-20-3601-2016, 2016
Short summary
Short summary
This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.
Erin Coughlan de Perez, Bart van den Hurk, Maarten K. van Aalst, Irene Amuron, Deus Bamanya, Tristan Hauser, Brenden Jongma, Ana Lopez, Simon Mason, Janot Mendler de Suarez, Florian Pappenberger, Alexandra Rueth, Elisabeth Stephens, Pablo Suarez, Jurjen Wagemaker, and Ervin Zsoter
Hydrol. Earth Syst. Sci., 20, 3549–3560, https://doi.org/10.5194/hess-20-3549-2016, https://doi.org/10.5194/hess-20-3549-2016, 2016
Short summary
Short summary
Many flood disaster impacts could be avoided by preventative action; however, early action is not guaranteed. This article demonstrates the design of a new system of forecast-based financing, which automatically triggers action when a flood forecast arrives, before a potential disaster. We establish "action triggers" for northern Uganda based on a global flood forecasting system, verifying these forecasts and assessing the uncertainties inherent in setting a trigger in a data-scarce location.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
Short summary
Short summary
This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
Louise Arnal, Maria-Helena Ramos, Erin Coughlan de Perez, Hannah Louise Cloke, Elisabeth Stephens, Fredrik Wetterhall, Schalk Jan van Andel, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3109–3128, https://doi.org/10.5194/hess-20-3109-2016, https://doi.org/10.5194/hess-20-3109-2016, 2016
Short summary
Short summary
Forecasts are produced as probabilities of occurrence of specific events, which is both an added value and a challenge for users. This paper presents a game on flood protection, "How much are you prepared to pay for a forecast?", which investigated how users perceive the value of forecasts and are willing to pay for them when making decisions. It shows that users are mainly influenced by the perceived quality of the forecasts, their need for the information and their degree of risk tolerance.
Dave MacLeod, Hannah Cloke, Florian Pappenberger, and Antje Weisheimer
Hydrol. Earth Syst. Sci., 20, 2737–2743, https://doi.org/10.5194/hess-20-2737-2016, https://doi.org/10.5194/hess-20-2737-2016, 2016
Short summary
Short summary
Soil moisture memory is a key aspect of seasonal climate predictions, through feedback between the land surface and the atmosphere. Estimates have been made of the length of soil moisture memory; however, we show here how estimates of memory show large variation with uncertain model parameters. Explicit representation of model uncertainty may then improve the realism of simulations and seasonal climate forecasts.
Jon Olav Skøien, Konrad Bogner, Peter Salamon, Paul Smith, and Florian Pappenberger
Proc. IAHS, 373, 109–114, https://doi.org/10.5194/piahs-373-109-2016, https://doi.org/10.5194/piahs-373-109-2016, 2016
Lan Wang-Erlandsson, Wim G. M. Bastiaanssen, Hongkai Gao, Jonas Jägermeyr, Gabriel B. Senay, Albert I. J. M. van Dijk, Juan P. Guerschman, Patrick W. Keys, Line J. Gordon, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 20, 1459–1481, https://doi.org/10.5194/hess-20-1459-2016, https://doi.org/10.5194/hess-20-1459-2016, 2016
Short summary
Short summary
We present an "Earth observation-based" method for estimating root zone storage capacity – a critical parameter in land surface modelling that represents the maximum amount of soil moisture available for vegetation. Variability within a land cover type is captured, and a global model evaporation simulation is overall improved, particularly in sub-humid to humid regions with seasonality. This new method can eliminate the need for unreliable soil and root depth data in land surface modelling.
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
Short summary
Short summary
The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
Short summary
Short summary
In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood
Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, https://doi.org/10.5194/gmd-9-283-2016, 2016
Short summary
Short summary
In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
W. Zhan, M. Pan, N. Wanders, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 4275–4291, https://doi.org/10.5194/hess-19-4275-2015, https://doi.org/10.5194/hess-19-4275-2015, 2015
V. Thiemig, B. Bisselink, F. Pappenberger, and J. Thielen
Hydrol. Earth Syst. Sci., 19, 3365–3385, https://doi.org/10.5194/hess-19-3365-2015, https://doi.org/10.5194/hess-19-3365-2015, 2015
C. Lavaysse, J. Vogt, and F. Pappenberger
Hydrol. Earth Syst. Sci., 19, 3273–3286, https://doi.org/10.5194/hess-19-3273-2015, https://doi.org/10.5194/hess-19-3273-2015, 2015
Short summary
Short summary
This paper assesses the predictability of meteorological droughts over Europe 1 month in advance using ensemble prediction systems.
It has been shown that, on average and using the most relevant method, 40 % of droughts in Europe are correctly forecasted, with less than 25 % false alarms.
This study is a reference for other studies that are motivated to improving the drought forecasting.
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
Short summary
Short summary
Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
R. D. Field, A. C. Spessa, N. A. Aziz, A. Camia, A. Cantin, R. Carr, W. J. de Groot, A. J. Dowdy, M. D. Flannigan, K. Manomaiphiboon, F. Pappenberger, V. Tanpipat, and X. Wang
Nat. Hazards Earth Syst. Sci., 15, 1407–1423, https://doi.org/10.5194/nhess-15-1407-2015, https://doi.org/10.5194/nhess-15-1407-2015, 2015
Short summary
Short summary
We have developed a global database of daily, gridded Fire Weather Index System calculations beginning in 1980. Input data and two different estimates of precipitation from rain gauges were obtained from the NASA Modern Era Retrospective-Analysis for Research and Applications. This data set can be used for analyzing historical relationships between fire weather and fire activity, and in identifying large-scale atmosphere–ocean controls on fire weather.
F. Wetterhall, H. C. Winsemius, E. Dutra, M. Werner, and E. Pappenberger
Hydrol. Earth Syst. Sci., 19, 2577–2586, https://doi.org/10.5194/hess-19-2577-2015, https://doi.org/10.5194/hess-19-2577-2015, 2015
Short summary
Short summary
Dry spells can have a devastating impact on agricuture in areas where irrigation is not available. Forecasting these dry spells could enhance preparedness in sensitive regions and avoid economic loss due to harvest failure. In this study, ECMWF seasonal forecasts are applied in the Limpopo basin in southeastern Africa to forecast dry spells in the seasonal rains. The results indicate skill in the forecast which is further improved by post-processing of the precipitation forecasts.
A. C. Spessa, R. D. Field, F. Pappenberger, A. Langner, S. Englhart, U. Weber, T. Stockdale, F. Siegert, J. W. Kaiser, and J. Moore
Nat. Hazards Earth Syst. Sci., 15, 429–442, https://doi.org/10.5194/nhess-15-429-2015, https://doi.org/10.5194/nhess-15-429-2015, 2015
G. Balsamo, C. Albergel, A. Beljaars, S. Boussetta, E. Brun, H. Cloke, D. Dee, E. Dutra, J. Muñoz-Sabater, F. Pappenberger, P. de Rosnay, T. Stockdale, and F. Vitart
Hydrol. Earth Syst. Sci., 19, 389–407, https://doi.org/10.5194/hess-19-389-2015, https://doi.org/10.5194/hess-19-389-2015, 2015
Short summary
Short summary
ERA-Interim/Land is a global land surface reanalysis covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim and a precipitation bias correction based on GPCP. A selection of verification results show the added value in representing the terrestrial water cycle and its main land surface storages and fluxes.
K. Guan, S. P. Good, K. K. Caylor, H. Sato, E. F. Wood, and H. Li
Biogeosciences, 11, 6939–6954, https://doi.org/10.5194/bg-11-6939-2014, https://doi.org/10.5194/bg-11-6939-2014, 2014
Short summary
Short summary
Climate change is expected to modify the way that rainfall arrives, namely the frequency and intensity of rainfall events and rainy season length. Yet, the quantification of the impact of these possible rainfall changes across large biomes is lacking. Our study fills this gap by developing a new modeling framework, applying it to continental Africa. We show that African ecosystems are highly sensitive to these rainfall variabilities, with esp. large sensitivity to changes in rainy season length.
A. I. J. M. van Dijk, L. J. Renzullo, Y. Wada, and P. Tregoning
Hydrol. Earth Syst. Sci., 18, 2955–2973, https://doi.org/10.5194/hess-18-2955-2014, https://doi.org/10.5194/hess-18-2955-2014, 2014
P. Trambauer, S. Maskey, M. Werner, F. Pappenberger, L. P. H. van Beek, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 18, 2925–2942, https://doi.org/10.5194/hess-18-2925-2014, https://doi.org/10.5194/hess-18-2925-2014, 2014
E. Dutra, F. Wetterhall, F. Di Giuseppe, G. Naumann, P. Barbosa, J. Vogt, W. Pozzi, and F. Pappenberger
Hydrol. Earth Syst. Sci., 18, 2657–2667, https://doi.org/10.5194/hess-18-2657-2014, https://doi.org/10.5194/hess-18-2657-2014, 2014
E. Dutra, W. Pozzi, F. Wetterhall, F. Di Giuseppe, L. Magnusson, G. Naumann, P. Barbosa, J. Vogt, and F. Pappenberger
Hydrol. Earth Syst. Sci., 18, 2669–2678, https://doi.org/10.5194/hess-18-2669-2014, https://doi.org/10.5194/hess-18-2669-2014, 2014
C. C. Sampson, T. J. Fewtrell, F. O'Loughlin, F. Pappenberger, P. B. Bates, J. E. Freer, and H. L. Cloke
Hydrol. Earth Syst. Sci., 18, 2305–2324, https://doi.org/10.5194/hess-18-2305-2014, https://doi.org/10.5194/hess-18-2305-2014, 2014
L. Alfieri, F. Pappenberger, and F. Wetterhall
Nat. Hazards Earth Syst. Sci., 14, 1505–1515, https://doi.org/10.5194/nhess-14-1505-2014, https://doi.org/10.5194/nhess-14-1505-2014, 2014
G. Naumann, E. Dutra, P. Barbosa, F. Pappenberger, F. Wetterhall, and J. V. Vogt
Hydrol. Earth Syst. Sci., 18, 1625–1640, https://doi.org/10.5194/hess-18-1625-2014, https://doi.org/10.5194/hess-18-1625-2014, 2014
H. C. Winsemius, E. Dutra, F. A. Engelbrecht, E. Archer Van Garderen, F. Wetterhall, F. Pappenberger, and M. G. F. Werner
Hydrol. Earth Syst. Sci., 18, 1525–1538, https://doi.org/10.5194/hess-18-1525-2014, https://doi.org/10.5194/hess-18-1525-2014, 2014
E. Mwangi, F. Wetterhall, E. Dutra, F. Di Giuseppe, and F. Pappenberger
Hydrol. Earth Syst. Sci., 18, 611–620, https://doi.org/10.5194/hess-18-611-2014, https://doi.org/10.5194/hess-18-611-2014, 2014
P. Trambauer, E. Dutra, S. Maskey, M. Werner, F. Pappenberger, L. P. H. van Beek, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 18, 193–212, https://doi.org/10.5194/hess-18-193-2014, https://doi.org/10.5194/hess-18-193-2014, 2014
M. Pan and E. F. Wood
Hydrol. Earth Syst. Sci., 17, 4577–4588, https://doi.org/10.5194/hess-17-4577-2013, https://doi.org/10.5194/hess-17-4577-2013, 2013
F. Wetterhall, F. Pappenberger, L. Alfieri, H. L. Cloke, J. Thielen-del Pozo, S. Balabanova, J. Daňhelka, A. Vogelbacher, P. Salamon, I. Carrasco, A. J. Cabrera-Tordera, M. Corzo-Toscano, M. Garcia-Padilla, R. J. Garcia-Sanchez, C. Ardilouze, S. Jurela, B. Terek, A. Csik, J. Casey, G. Stankūnavičius, V. Ceres, E. Sprokkereef, J. Stam, E. Anghel, D. Vladikovic, C. Alionte Eklund, N. Hjerdt, H. Djerv, F. Holmberg, J. Nilsson, K. Nyström, M. Sušnik, M. Hazlinger, and M. Holubecka
Hydrol. Earth Syst. Sci., 17, 4389–4399, https://doi.org/10.5194/hess-17-4389-2013, https://doi.org/10.5194/hess-17-4389-2013, 2013
N. Andela, Y. Y. Liu, A. I. J. M. van Dijk, R. A. M. de Jeu, and T. R. McVicar
Biogeosciences, 10, 6657–6676, https://doi.org/10.5194/bg-10-6657-2013, https://doi.org/10.5194/bg-10-6657-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
S. Shukla, J. Sheffield, E. F. Wood, and D. P. Lettenmaier
Hydrol. Earth Syst. Sci., 17, 2781–2796, https://doi.org/10.5194/hess-17-2781-2013, https://doi.org/10.5194/hess-17-2781-2013, 2013
H. E. Beck, L. A. Bruijnzeel, A. I. J. M. van Dijk, T. R. McVicar, F. N. Scatena, and J. Schellekens
Hydrol. Earth Syst. Sci., 17, 2613–2635, https://doi.org/10.5194/hess-17-2613-2013, https://doi.org/10.5194/hess-17-2613-2013, 2013
E. Dutra, F. Di Giuseppe, F. Wetterhall, and F. Pappenberger
Hydrol. Earth Syst. Sci., 17, 2359–2373, https://doi.org/10.5194/hess-17-2359-2013, https://doi.org/10.5194/hess-17-2359-2013, 2013
M. H. Ramos, S. J. van Andel, and F. Pappenberger
Hydrol. Earth Syst. Sci., 17, 2219–2232, https://doi.org/10.5194/hess-17-2219-2013, https://doi.org/10.5194/hess-17-2219-2013, 2013
L. Alfieri, P. Burek, E. Dutra, B. Krzeminski, D. Muraro, J. Thielen, and F. Pappenberger
Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, https://doi.org/10.5194/hess-17-1161-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Instruments and observation techniques
Technical note: A guide to using three open-source quality control algorithms for rainfall data from personal weather stations
Technical note: Investigating the potential for smartphone-based monitoring of evapotranspiration and land surface energy-balance partitioning
Exploring patterns in precipitation intensity–duration–area–frequency relationships using weather radar data
Technical Note: A simple feedforward artificial neural network for high temporal resolution classification of wet and dry periods using signal attenuation from commercial microwave links
An intercomparison of four gridded precipitation products over Europe using the three-cornered-hat method
Merging with crowdsourced rain gauge data improves pan-European radar precipitation estimates
Statistical characteristics of raindrop size distribution during rainy seasons in complicated mountain terrain
Evaluation of precipitation measurement methods using data from a precision lysimeter network
Quantitative rainfall analysis of the 2021 mid-July flood event in Belgium
Multi-scale temporal analysis of evaporation on a saline lake in the Atacama Desert
Coastal and orographic effects on extreme precipitation revealed by weather radar observations
Unshielded precipitation gauge collection efficiency with wind speed and hydrometeor fall velocity
Evaluation of Integrated Nowcasting through Comprehensive Analysis (INCA) precipitation analysis using a dense rain-gauge network in southeastern Austria
Microphysical features of typhoon and non-typhoon rainfall observed in Taiwan, an island in the northwestern Pacific
Partial energy balance closure of eddy covariance evaporation measurements using concurrent lysimeter observations over grassland
Rivers in the sky, flooding on the ground: the role of atmospheric rivers in inland flooding in central Europe
Evaluation of the WMO Solid Precipitation Intercomparison Experiment (SPICE) transfer functions for adjusting the wind bias in solid precipitation measurements
Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data
Radar-based characterisation of heavy precipitation in the eastern Mediterranean and its representation in a convection-permitting model
Effect of disdrometer type on rain drop size distribution characterisation: a new dataset for south-eastern Australia
Quantitative precipitation estimation with weather radar using a data- and information-based approach
Continuous, near-real-time observations of water stable isotope ratios during rainfall and throughfall events
Rain erosivity map for Germany derived from contiguous radar rain data
Citizen science flow – an assessment of simple streamflow measurement methods
Exploring the use of underground gravity monitoring to evaluate radar estimates of heavy rainfall
The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset
Precipitation characteristics and associated weather conditions on the eastern slopes of the Canadian Rockies during March–April 2015
Dendrohydrology and water resources management in south-central Chile: lessons from the Río Imperial streamflow reconstruction
Comparison of precipitation measurements by OTT Parsivel2 and Thies LPM optical disdrometers
Obtaining sub-daily new snow density from automated measurements in high mountain regions
Deriving surface soil moisture from reflected GNSS signal observations from a grassland site in southwestern France
Testing and development of transfer functions for weighing precipitation gauges in WMO-SPICE
Technical note: Using distributed temperature sensing for Bowen ratio evaporation measurements
Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria
The 2010–2015 megadrought in central Chile: impacts on regional hydroclimate and vegetation
Measuring precipitation with a geolysimeter
Convective rainfall in a dry climate: relations with synoptic systems and flash-flood generation in the Dead Sea region
Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop
Water-use dynamics of an alien-invaded riparian forest within the Mediterranean climate zone of the Western Cape, South Africa
Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds
Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis
Analysis of single-Alter-shielded and unshielded measurements of mixed and solid precipitation from WMO-SPICE
Analysing surface energy balance closure and partitioning over a semi-arid savanna FLUXNET site in Skukuza, Kruger National Park, South Africa
Rainfall and streamflow sensor network design: a review of applications, classification, and a proposed framework
The quantification and correction of wind-induced precipitation measurement errors
Response of water vapour D-excess to land–atmosphere interactions in a semi-arid environment
Areal rainfall estimation using moving cars – computer experiments including hydrological modeling
Recent changes and drivers of the atmospheric evaporative demand in the Canary Islands
A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland
Making rainfall features fun: scientific activities for teaching children aged 5–12 years
Abbas El Hachem, Jochen Seidel, Tess O'Hara, Roberto Villalobos Herrera, Aart Overeem, Remko Uijlenhoet, András Bárdossy, and Lotte de Vos
Hydrol. Earth Syst. Sci., 28, 4715–4731, https://doi.org/10.5194/hess-28-4715-2024, https://doi.org/10.5194/hess-28-4715-2024, 2024
Short summary
Short summary
This study presents an overview of open-source quality control (QC) algorithms for rainfall data from personal weather stations (PWSs). The methodology and usability along technical and operational guidelines for using every QC algorithm are presented. All three QC algorithms are available for users to explore in the OpenSense sandbox. They were applied in a case study using PWS data from the Amsterdam region in the Netherlands. The results highlight the necessity for data quality control.
Adriaan J. Teuling, Belle Holthuis, and Jasper F. D. Lammers
Hydrol. Earth Syst. Sci., 28, 3799–3806, https://doi.org/10.5194/hess-28-3799-2024, https://doi.org/10.5194/hess-28-3799-2024, 2024
Short summary
Short summary
The understanding of spatio-temporal variability of evapotranspiration (ET) is currently limited by a lack of measurement techniques that are low cost and that can be applied anywhere at any time. Here we show that evapotranspiration can be estimated accurately using observations made by smartphone sensors, suggesting that smartphone-based ET monitoring could provide a realistic and low-cost alternative for real-time ET estimation in the field.
Talia Rosin, Francesco Marra, and Efrat Morin
Hydrol. Earth Syst. Sci., 28, 3549–3566, https://doi.org/10.5194/hess-28-3549-2024, https://doi.org/10.5194/hess-28-3549-2024, 2024
Short summary
Short summary
Knowledge of extreme precipitation probability at various spatial–temporal scales is crucial. We estimate extreme precipitation return levels at multiple scales (10 min–24 h, 0.25–500 km2) in the eastern Mediterranean using radar data. We show our estimates are comparable to those derived from averaged daily rain gauges. We then explore multi-scale extreme precipitation across coastal, mountainous, and desert regions.
Erlend Øydvin, Maximilian Graf, Christian Chwala, Mareile Astrid Wolff, Nils-Otto Kitterød, and Vegard Nilsen
EGUsphere, https://doi.org/10.5194/egusphere-2024-647, https://doi.org/10.5194/egusphere-2024-647, 2024
Short summary
Short summary
Two simple neural networks are trained to detect rainfall events using signal loss from commercial microwave links. Whereas existing rainfall event detection methods have focused on hourly resolution reference data, this study uses weather radar and rain gauges with 5 minutes and 1 minute temporal resolution respectively. Our results show that the developed neural networks can detect rainfall events with a higher temporal precision than existing methods.
Llorenç Lledó, Thomas Haiden, and Matthieu Chevallier
EGUsphere, https://doi.org/10.5194/egusphere-2024-807, https://doi.org/10.5194/egusphere-2024-807, 2024
Short summary
Short summary
High-quality observational datasets are essential to perform forecast verification and improve weather forecast services. When it comes to verifying precipitation, a high-resolution, global-coverage and good-quality dataset is not yet available. This research analyses the strengths and shortcomings of four observational products that employ complementary measurement techniques to estimate surface precipitation. Satellites provide good spatial coverage, but other products are still more accurate.
Aart Overeem, Hidde Leijnse, Gerard van der Schrier, Else van den Besselaar, Irene Garcia-Marti, and Lotte Wilhelmina de Vos
Hydrol. Earth Syst. Sci., 28, 649–668, https://doi.org/10.5194/hess-28-649-2024, https://doi.org/10.5194/hess-28-649-2024, 2024
Short summary
Short summary
Ground-based radar precipitation products typically need adjustment with rain gauge accumulations to achieve a reasonable accuracy. Crowdsourced rain gauge networks have a much higher density than conventional ones. Here, a 1-year personal weather station (PWS) gauge dataset is obtained. After quality control, the 1 h PWS gauge accumulations are merged with pan-European radar accumulations. The potential of crowdsourcing to improve radar precipitation products in (near) real time is confirmed.
Wenqian Mao, Wenyu Zhang, and Menggang Kou
Hydrol. Earth Syst. Sci., 27, 3895–3910, https://doi.org/10.5194/hess-27-3895-2023, https://doi.org/10.5194/hess-27-3895-2023, 2023
Short summary
Short summary
Drop size distribution characteristics vary with microphysical characteristics. We choose the Qilian mountains and represent the southern and northern slopes and the interior. To investigate discrepancies, DSD characteristics and Z–R relationships are analyzed based on continuous observations in the rainy season. We obtain the finer precipitation of mountains and refine the accuracy of quantitative precipitation estimation, which would help develop cloud water resources in mountainous areas.
Tobias Schnepper, Jannis Groh, Horst H. Gerke, Barbara Reichert, and Thomas Pütz
Hydrol. Earth Syst. Sci., 27, 3265–3292, https://doi.org/10.5194/hess-27-3265-2023, https://doi.org/10.5194/hess-27-3265-2023, 2023
Short summary
Short summary
We compared hourly data from precipitation gauges with lysimeter reference data at three sites under different climatic conditions. Our results show that precipitation gauges recorded 33–96 % of the reference precipitation data for the period under consideration (2015–2018). Correction algorithms increased the registered precipitation by 9–14 %. It follows that when using point precipitation data, regardless of the precipitation measurement method used, relevant uncertainties must be considered.
Michel Journée, Edouard Goudenhoofdt, Stéphane Vannitsem, and Laurent Delobbe
Hydrol. Earth Syst. Sci., 27, 3169–3189, https://doi.org/10.5194/hess-27-3169-2023, https://doi.org/10.5194/hess-27-3169-2023, 2023
Short summary
Short summary
The exceptional flood of July 2021 in central Europe impacted Belgium severely. This study aims to characterize rainfall amounts in Belgium from 13 to 16 July 2021 based on observational data (i.e., rain gauge data and a radar-based rainfall product). The spatial and temporal distributions of rainfall during the event aredescribed. In order to document such a record-breaking event as much as possible, the rainfall data are shared with the scientific community on Zenodo for further studies.
Felipe Lobos-Roco, Oscar Hartogensis, Francisco Suárez, Ariadna Huerta-Viso, Imme Benedict, Alberto de la Fuente, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 26, 3709–3729, https://doi.org/10.5194/hess-26-3709-2022, https://doi.org/10.5194/hess-26-3709-2022, 2022
Short summary
Short summary
This research brings a multi-scale temporal analysis of evaporation in a saline lake of the Atacama Desert. Our findings reveal that evaporation is controlled differently depending on the timescale. Evaporation is controlled sub-diurnally by wind speed, regulated seasonally by radiation and modulated interannually by ENSO. Our research extends our understanding of evaporation, contributing to improving the climate change assessment and efficiency of water management in arid regions.
Francesco Marra, Moshe Armon, and Efrat Morin
Hydrol. Earth Syst. Sci., 26, 1439–1458, https://doi.org/10.5194/hess-26-1439-2022, https://doi.org/10.5194/hess-26-1439-2022, 2022
Short summary
Short summary
We present a new method for quantifying the probability of occurrence of extreme rainfall using radar data, and we use it to examine coastal and orographic effects on extremes. We identify three regimes, directly related to precipitation physical processes, which respond differently to these forcings. The methods and results are of interest for researchers and practitioners using radar for the analysis of extremes, risk managers, water resources managers, and climate change impact studies.
Jeffery Hoover, Michael E. Earle, Paul I. Joe, and Pierre E. Sullivan
Hydrol. Earth Syst. Sci., 25, 5473–5491, https://doi.org/10.5194/hess-25-5473-2021, https://doi.org/10.5194/hess-25-5473-2021, 2021
Short summary
Short summary
Transfer functions with dependence on wind speed and precipitation fall velocity are evaluated alongside transfer functions with wind speed and temperature dependence for unshielded precipitation gauges. The transfer functions with fall velocity dependence reduced the RMSE of unshielded gauge measurements relative to the functions based on wind speed and temperature, demonstrating the importance of fall velocity for precipitation gauge collection efficiency and transfer functions.
Esmail Ghaemi, Ulrich Foelsche, Alexander Kann, and Jürgen Fuchsberger
Hydrol. Earth Syst. Sci., 25, 4335–4356, https://doi.org/10.5194/hess-25-4335-2021, https://doi.org/10.5194/hess-25-4335-2021, 2021
Short summary
Short summary
We assess an operational merged gauge–radar precipitation product over a period of 12 years, using gridded precipitation fields from a dense gauge network (WegenerNet) in southeastern Austria. We analyze annual data, seasonal data, and extremes using different metrics. We identify individual events using a simple threshold based on the interval between two consecutive events and evaluate the events' characteristics in both datasets.
Jayalakshmi Janapati, Balaji Kumar Seela, Pay-Liam Lin, Meng-Tze Lee, and Everette Joseph
Hydrol. Earth Syst. Sci., 25, 4025–4040, https://doi.org/10.5194/hess-25-4025-2021, https://doi.org/10.5194/hess-25-4025-2021, 2021
Short summary
Short summary
Typhoon (TY) and non-typhoon (NTY) rainy days in northern Taiwan summer seasons showed more large drops on NTY than TY rainy days. Relatively higher convective activity and drier conditions in NTY than TY lead to variations in microphysical characteristics between TY and NTY rainy days. The raindrop size distribution and kinetic energy relations assessed for TY and NTY rainfall can be useful for evaluating the radar rainfall estimation algorithms, cloud modeling, and rainfall erosivity studies.
Peter Widmoser and Dominik Michel
Hydrol. Earth Syst. Sci., 25, 1151–1163, https://doi.org/10.5194/hess-25-1151-2021, https://doi.org/10.5194/hess-25-1151-2021, 2021
Short summary
Short summary
With respect to ongoing discussions about the causes of energy imbalance, a method for closing the latent heat flux gap based on lysimeter measurements is assessed at four measurement stations over grassland in humid and semiarid climates. The applied partial closure yields excellent adjustments of eddy covariance data as compared to results found in the literature. The method also allows a distinction between systematic and random deviation of eddy covariance and lysimeter measurements.
Monica Ionita, Viorica Nagavciuc, and Bin Guan
Hydrol. Earth Syst. Sci., 24, 5125–5147, https://doi.org/10.5194/hess-24-5125-2020, https://doi.org/10.5194/hess-24-5125-2020, 2020
Short summary
Short summary
Analysis of the largest 10 floods in the lower Rhine, between 1817 and 2015, shows that all these extreme flood peaks have been preceded, up to 7 d in advance, by intense moisture transport from the tropical North Atlantic basin in the form of narrow bands also known as atmospheric rivers. The results presented in this study offer new insights regarding the importance of moisture transport as the driver of extreme flooding in the lower part of the Rhine catchment area.
Craig D. Smith, Amber Ross, John Kochendorfer, Michael E. Earle, Mareile Wolff, Samuel Buisán, Yves-Alain Roulet, and Timo Laine
Hydrol. Earth Syst. Sci., 24, 4025–4043, https://doi.org/10.5194/hess-24-4025-2020, https://doi.org/10.5194/hess-24-4025-2020, 2020
Short summary
Short summary
During the World Meteorological Organization Solid Precipitation Intercomparison Experiment (SPICE), transfer functions were developed to adjust automated gauge measurements of solid precipitation for systematic bias due to wind. The transfer functions were developed by combining data from eight sites, attempting to make them more universally applicable in a range of climates. This analysis is an assessment of the performance of those transfer functions, using data collected when SPICE ended.
Maximilian Graf, Christian Chwala, Julius Polz, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 24, 2931–2950, https://doi.org/10.5194/hess-24-2931-2020, https://doi.org/10.5194/hess-24-2931-2020, 2020
Short summary
Short summary
Commercial microwave links (CMLs), which form large parts of the backhaul from the ubiquitous cellular communication networks, can be used to estimate path-integrated rainfall rates. This study presents the processing and evaluation of the largest CML data set to date, covering the whole of Germany with almost 4000 CMLs. The CML-derived rainfall information compares well to a standard precipitation data set from the German Meteorological Service, which combines radar and rain gauge data.
Moshe Armon, Francesco Marra, Yehouda Enzel, Dorita Rostkier-Edelstein, and Efrat Morin
Hydrol. Earth Syst. Sci., 24, 1227–1249, https://doi.org/10.5194/hess-24-1227-2020, https://doi.org/10.5194/hess-24-1227-2020, 2020
Short summary
Short summary
Heavy precipitation events (HPEs), occurring around the globe, lead to natural hazards as well as to water resource recharge. Rainfall patterns during HPEs vary from one case to another and govern their effect. Thus, correct prediction of these patterns is crucial for coping with HPEs. However, the ability of weather models to generate such patterns is unclear. Here, we characterise rainfall patterns during HPEs based on weather radar data and evaluate weather model simulations of these events.
Adrien Guyot, Jayaram Pudashine, Alain Protat, Remko Uijlenhoet, Valentijn R. N. Pauwels, Alan Seed, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 4737–4761, https://doi.org/10.5194/hess-23-4737-2019, https://doi.org/10.5194/hess-23-4737-2019, 2019
Short summary
Short summary
We characterised for the first time the rainfall microphysics for Southern Hemisphere temperate latitudes. Co-located instruments were deployed to provide information on the sampling effect and spatio-temporal variabilities at micro scales. Substantial differences were found across the instruments, increasing with increasing values of the rain rate. Specific relations for reflectivity–rainfall are presented together with related uncertainties for drizzle and stratiform and convective rainfall.
Malte Neuper and Uwe Ehret
Hydrol. Earth Syst. Sci., 23, 3711–3733, https://doi.org/10.5194/hess-23-3711-2019, https://doi.org/10.5194/hess-23-3711-2019, 2019
Short summary
Short summary
In this study, we apply a data-driven approach to quantitatively estimate precipitation using weather radar data. The method is based on information theory concepts. It uses predictive relations expressed by empirical discrete probability distributions, which are directly derived from data rather than the standard deterministic functions.
Barbara Herbstritt, Benjamin Gralher, and Markus Weiler
Hydrol. Earth Syst. Sci., 23, 3007–3019, https://doi.org/10.5194/hess-23-3007-2019, https://doi.org/10.5194/hess-23-3007-2019, 2019
Short summary
Short summary
We describe a novel technique for the precise, quasi real-time observation of water-stable isotopes in gross precipitation and throughfall from tree canopies in parallel. Various processes (e.g. rainfall intensity, evapotranspiration, exchange with ambient vapour) thereby control throughfall intensity and isotopic composition. The achieved temporal resolution now competes with common meteorological measurements, thus enabling new ways to employ water-stable isotopes in forested catchments.
Karl Auerswald, Franziska K. Fischer, Tanja Winterrath, and Robert Brandhuber
Hydrol. Earth Syst. Sci., 23, 1819–1832, https://doi.org/10.5194/hess-23-1819-2019, https://doi.org/10.5194/hess-23-1819-2019, 2019
Short summary
Short summary
Radar rain data enable for the first time portraying the erosivity pattern with high spatial and temporal resolution. This allowed quantification of erosivity in Germany with unprecedented detail. Compared to previous estimates, erosivity has strongly increased and its seasonal distribution has changed, presumably due to climate change. As a consequence, erosion for some crops is 4 times higher than previously estimated.
Jeffrey C. Davids, Martine M. Rutten, Anusha Pandey, Nischal Devkota, Wessel David van Oyen, Rajaram Prajapati, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 23, 1045–1065, https://doi.org/10.5194/hess-23-1045-2019, https://doi.org/10.5194/hess-23-1045-2019, 2019
Short summary
Short summary
Wise management of water resources requires data. Nevertheless, the amount of water data being collected continues to decline. We evaluated potential citizen science approaches for measuring flows of headwater streams and springs. After selecting salt dilution as the preferred approach, we partnered with Nepali students to cost-effectively measure flows and water quality with smartphones at 264 springs and streams which provide crucial water supplies to the rapidly expanding Kathmandu Valley.
Laurent Delobbe, Arnaud Watlet, Svenja Wilfert, and Michel Van Camp
Hydrol. Earth Syst. Sci., 23, 93–105, https://doi.org/10.5194/hess-23-93-2019, https://doi.org/10.5194/hess-23-93-2019, 2019
Short summary
Short summary
In this study, we explore the use of an underground superconducting gravimeter as a new source of in situ observations for the evaluation of radar-based precipitation estimates. The comparison of radar and gravity time series over 15 years shows that short-duration intense rainfall events cause a rapid decrease in the measured gravity. Rainfall amounts can be derived from this decrease. The gravimeter allows capture of rainfall at a much larger spatial scale than a traditional rain gauge.
Camila Alvarez-Garreton, Pablo A. Mendoza, Juan Pablo Boisier, Nans Addor, Mauricio Galleguillos, Mauricio Zambrano-Bigiarini, Antonio Lara, Cristóbal Puelma, Gonzalo Cortes, Rene Garreaud, James McPhee, and Alvaro Ayala
Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, https://doi.org/10.5194/hess-22-5817-2018, 2018
Short summary
Short summary
CAMELS-CL provides a catchment dataset in Chile, including 516 catchment boundaries, hydro-meteorological time series, and 70 catchment attributes quantifying catchments' climatic, hydrological, topographic, geological, land cover and anthropic intervention features. By using CAMELS-CL, we characterise hydro-climatic regional variations, assess precipitation and potential evapotranspiration uncertainties, and analyse human intervention impacts on catchment response.
Julie M. Thériault, Ida Hung, Paul Vaquer, Ronald E. Stewart, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 22, 4491–4512, https://doi.org/10.5194/hess-22-4491-2018, https://doi.org/10.5194/hess-22-4491-2018, 2018
Short summary
Short summary
Precipitation events associated with rain and snow on the eastern slopes of the Rocky Mountains, Canada, are a critical aspect of the regional water cycle. The goal is to characterize the precipitation and weather conditions in the Kananaskis Valley, Alberta, during a field experiment. Mainly dense solid precipitation reached the surface and occurred during downslope and upslope conditions. The precipitation phase has critical implications on the severity of flooding events in the area.
Alfonso Fernández, Ariel Muñoz, Álvaro González-Reyes, Isabella Aguilera-Betti, Isadora Toledo, Paulina Puchi, David Sauchyn, Sebastián Crespo, Cristian Frene, Ignacio Mundo, Mauro González, and Raffaele Vignola
Hydrol. Earth Syst. Sci., 22, 2921–2935, https://doi.org/10.5194/hess-22-2921-2018, https://doi.org/10.5194/hess-22-2921-2018, 2018
Short summary
Short summary
Short-term river discharge records hamper assessment of the severity of modern droughts in south-central Chile, making effective water management difficult. To support decision-making, we present a ~300-year tree-ring reconstruction of summer discharge for this region. Results show that since 1980, droughts have become more frequent and are related to a shift in large-scale climate. We argue that water managers should use this long-term view to better allocate water rights.
Marta Angulo-Martínez, Santiago Beguería, Borja Latorre, and María Fernández-Raga
Hydrol. Earth Syst. Sci., 22, 2811–2837, https://doi.org/10.5194/hess-22-2811-2018, https://doi.org/10.5194/hess-22-2811-2018, 2018
Short summary
Short summary
Two optical disdrometers, OTT Parsivel2 disdrometer and Thies Clima laser precipitation monitor (LPM), are compared. Analysis of 2 years of one-minute replicated data showed significant differences. Thies LPM recorded a larger number of particles than Parsivel2 and a higher proportion of small particles, resulting in higher rain rates and amounts and differences in radar reflectivity and kinetic energy. Possible causes for these differences, and their practical consequences, are discussed.
Kay Helfricht, Lea Hartl, Roland Koch, Christoph Marty, and Marc Olefs
Hydrol. Earth Syst. Sci., 22, 2655–2668, https://doi.org/10.5194/hess-22-2655-2018, https://doi.org/10.5194/hess-22-2655-2018, 2018
Short summary
Short summary
We calculated hourly new snow densities from automated measurements. This time interval reduces the influence of settling of the freshly deposited snow. We found an average new snow density of 68 kg m−3. The observed variability could not be described using different parameterizations, but a relationship to temperature is partly visible at hourly intervals. Wind speed is a crucial parameter for the inter-station variability. Our findings are relevant for snow models working on hourly timescales.
Sibo Zhang, Jean-Christophe Calvet, José Darrozes, Nicolas Roussel, Frédéric Frappart, and Gilles Bouhours
Hydrol. Earth Syst. Sci., 22, 1931–1946, https://doi.org/10.5194/hess-22-1931-2018, https://doi.org/10.5194/hess-22-1931-2018, 2018
Short summary
Short summary
Surface soil moisture was retrieved from a grassland site in southwestern France using the GNSS-IR technique. In order to efficiently limit the impact of perturbing vegetation effects, the grass growth period and the senescence period are treated separately. While the vegetation biomass effect can be corrected for, the litter water interception influences the observations and cannot be easily accounted for.
John Kochendorfer, Rodica Nitu, Mareile Wolff, Eva Mekis, Roy Rasmussen, Bruce Baker, Michael E. Earle, Audrey Reverdin, Kai Wong, Craig D. Smith, Daqing Yang, Yves-Alain Roulet, Tilden Meyers, Samuel Buisan, Ketil Isaksen, Ragnar Brækkan, Scott Landolt, and Al Jachcik
Hydrol. Earth Syst. Sci., 22, 1437–1452, https://doi.org/10.5194/hess-22-1437-2018, https://doi.org/10.5194/hess-22-1437-2018, 2018
Short summary
Short summary
Due to the effects of wind, precipitation gauges typically underestimate the amount of precipitation that occurs as snow. Measurements recorded during a World Meteorological Organization intercomparison of precipitation gauges were used to evaluate and improve the adjustments that are available to address this issue. Adjustments for specific types of precipitation gauges and wind shields were tested and recommended.
Bart Schilperoort, Miriam Coenders-Gerrits, Willem Luxemburg, César Jiménez Rodríguez, César Cisneros Vaca, and Hubert Savenije
Hydrol. Earth Syst. Sci., 22, 819–830, https://doi.org/10.5194/hess-22-819-2018, https://doi.org/10.5194/hess-22-819-2018, 2018
Short summary
Short summary
Using the
DTStechnology, we measured the evaporation of a forest using fibre optic cables. The cables work like long thermometers, with a measurement every 12.5 cm. We placed the cables vertically along the tower, one cable being dry, the other kept wet. By looking at the dry and wet cable temperatures over the height we are able to study heat storage and the amount of water the forest is evaporating. These results can be used to better understand the storage and heat exchange of forests.
Sungmin O, Ulrich Foelsche, Gottfried Kirchengast, Juergen Fuchsberger, Jackson Tan, and Walter A. Petersen
Hydrol. Earth Syst. Sci., 21, 6559–6572, https://doi.org/10.5194/hess-21-6559-2017, https://doi.org/10.5194/hess-21-6559-2017, 2017
Short summary
Short summary
We evaluate gridded satellite rainfall estimates, from GPM IMERG, through a direct grid-to-grid comparison with gauge data from the WegenerNet Feldbach (WEGN) network in southeastern Austria. As the WEGN data are independent of the IMERG gauge adjustment process, we could analyze the IMERG estimates across its three different runs. Our results show the effects of additional retrieval processes on the final rainfall estimates, and consequently provide IMERG accuracy information for data users.
René D. Garreaud, Camila Alvarez-Garreton, Jonathan Barichivich, Juan Pablo Boisier, Duncan Christie, Mauricio Galleguillos, Carlos LeQuesne, James McPhee, and Mauricio Zambrano-Bigiarini
Hydrol. Earth Syst. Sci., 21, 6307–6327, https://doi.org/10.5194/hess-21-6307-2017, https://doi.org/10.5194/hess-21-6307-2017, 2017
Short summary
Short summary
This work synthesizes an interdisciplinary research on the megadrought (MD) that has afflicted central Chile since 2010. Although 1- or 2-year droughts are not infrequent in this Mediterranean-like region, the ongoing dry period stands out because of its longevity and large extent, leading to unseen hydrological effects and vegetation impacts. Understanding the nature and biophysical impacts of the MD contributes to confronting a dry, warm future regional climate scenario in subtropical regions.
Craig D. Smith, Garth van der Kamp, Lauren Arnold, and Randy Schmidt
Hydrol. Earth Syst. Sci., 21, 5263–5272, https://doi.org/10.5194/hess-21-5263-2017, https://doi.org/10.5194/hess-21-5263-2017, 2017
Short summary
Short summary
This research provides an example of how groundwater pressures measured in deep observation wells can be used as a reliable estimate, and perhaps as a reference, for event-based precipitation. Changes in loading at the surface due to the weight of precipitation are transferred to the groundwater formation and can be measured in the observation well. Correlations in precipitation measurements made with the
geolysimeterand the co-located sheltered precipitation gauge are high.
Idit Belachsen, Francesco Marra, Nadav Peleg, and Efrat Morin
Hydrol. Earth Syst. Sci., 21, 5165–5180, https://doi.org/10.5194/hess-21-5165-2017, https://doi.org/10.5194/hess-21-5165-2017, 2017
Short summary
Short summary
Spatiotemporal rainfall patterns in arid environments are not well-known. We derived properties of convective rain cells over the arid Dead Sea region from a long-term radar archive. We found differences in cell properties between synoptic systems and between flash-flood and non-flash-flood events. Large flash floods are associated with slow rain cells, directed downstream with the main catchment axis. Results from this work can be used for hydrological models and stochastic storm simulations.
Sibo Zhang, Nicolas Roussel, Karen Boniface, Minh Cuong Ha, Frédéric Frappart, José Darrozes, Frédéric Baup, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4767–4784, https://doi.org/10.5194/hess-21-4767-2017, https://doi.org/10.5194/hess-21-4767-2017, 2017
Short summary
Short summary
GNSS SNR data were obtained from an intensively cultivated wheat field in southwestern France. The data were used to retrieve soil moisture and vegetation characteristics during the growing period of wheat. Vegetation growth broke up the constant height assumption used in soil moisture retrieval algorithms. Soil moisture could not be retrieved after wheat tillering. A new algorithm based on a wavelet analysis was implemented and used to retrieve vegetation height.
Bruce C. Scott-Shaw, Colin S. Everson, and Alistair D. Clulow
Hydrol. Earth Syst. Sci., 21, 4551–4562, https://doi.org/10.5194/hess-21-4551-2017, https://doi.org/10.5194/hess-21-4551-2017, 2017
Short summary
Short summary
In South Africa, the invasion of riparian forests by alien trees has the potential to affect the limited water resources. To justify alien clearing programs, hydrological benefits are required. Spatial upscaling of measured sapflows showed that an alien stand used 6 times more water per unit area than the indigenous stand. A gain in groundwater recharge and/or streamflow would be achieved if the alien species were removed from riparian forests and rehabilitated back to their natural state.
Francesco Marra, Elisa Destro, Efthymios I. Nikolopoulos, Davide Zoccatelli, Jean Dominique Creutin, Fausto Guzzetti, and Marco Borga
Hydrol. Earth Syst. Sci., 21, 4525–4532, https://doi.org/10.5194/hess-21-4525-2017, https://doi.org/10.5194/hess-21-4525-2017, 2017
Short summary
Short summary
Previous studies have reported a systematic underestimation of debris flow occurrence thresholds, due to the use of sparse networks in non-stationary rain fields. We analysed high-resolution radar data to show that spatially aggregated estimates (e.g. satellite data) largely reduce this issue, in light of a reduced estimation variance. Our findings are transferable to other situations in which lower envelope curves are used to predict point-like events in the presence of non-stationary fields.
Feinan Xu, Weizhen Wang, Jiemin Wang, Ziwei Xu, Yuan Qi, and Yueru Wu
Hydrol. Earth Syst. Sci., 21, 4037–4051, https://doi.org/10.5194/hess-21-4037-2017, https://doi.org/10.5194/hess-21-4037-2017, 2017
John Kochendorfer, Rodica Nitu, Mareile Wolff, Eva Mekis, Roy Rasmussen, Bruce Baker, Michael E. Earle, Audrey Reverdin, Kai Wong, Craig D. Smith, Daqing Yang, Yves-Alain Roulet, Samuel Buisan, Timo Laine, Gyuwon Lee, Jose Luis C. Aceituno, Javier Alastrué, Ketil Isaksen, Tilden Meyers, Ragnar Brækkan, Scott Landolt, Al Jachcik, and Antti Poikonen
Hydrol. Earth Syst. Sci., 21, 3525–3542, https://doi.org/10.5194/hess-21-3525-2017, https://doi.org/10.5194/hess-21-3525-2017, 2017
Short summary
Short summary
Precipitation measurements were combined from eight separate precipitation testbeds to create multi-site transfer functions for the correction of unshielded and single-Alter-shielded precipitation gauge measurements. Site-specific errors and more universally applicable corrections were created from these WMO-SPICE measurements. The importance and magnitude of such wind speed corrections were demonstrated.
Nobuhle P. Majozi, Chris M. Mannaerts, Abel Ramoelo, Renaud Mathieu, Alecia Nickless, and Wouter Verhoef
Hydrol. Earth Syst. Sci., 21, 3401–3415, https://doi.org/10.5194/hess-21-3401-2017, https://doi.org/10.5194/hess-21-3401-2017, 2017
Short summary
Short summary
The study analysed the quality and partitioning of a 15-year surface energy dataset from Skukuza flux tower. The yearly mean energy balance ratio (EBR) was 0.93, with the dry season having the lowest ratio. Night ratio was lower than daytime, with analysis showing an increase in EBR with increase in friction velocity, which is also linked to time of day. The energy partitioning showed that sensible heat flux is the dominant portion in the dry season, and latent heat flux during the wet season.
Juan C. Chacon-Hurtado, Leonardo Alfonso, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 21, 3071–3091, https://doi.org/10.5194/hess-21-3071-2017, https://doi.org/10.5194/hess-21-3071-2017, 2017
Short summary
Short summary
This paper compiles most of the studies (as far as the authors are aware) on the design of sensor networks for measurement of precipitation and streamflow. The literature shows that there is no overall consensus on the methods for the evaluation of sensor networks, as different design criteria often lead to different solutions. This paper proposes a methodology for the classification of methods, and a general framework for the design of sensor networks.
John Kochendorfer, Roy Rasmussen, Mareile Wolff, Bruce Baker, Mark E. Hall, Tilden Meyers, Scott Landolt, Al Jachcik, Ketil Isaksen, Ragnar Brækkan, and Ronald Leeper
Hydrol. Earth Syst. Sci., 21, 1973–1989, https://doi.org/10.5194/hess-21-1973-2017, https://doi.org/10.5194/hess-21-1973-2017, 2017
Short summary
Short summary
Snowfall measurements recorded using precipitation gauges are subject to significant underestimation due to the effects of wind. Using measurements recorded at two different precipitation test beds, corrections for unshielded gauges and gauges within different types of windshields were developed and tested. Using the new corrections, uncorrectable errors were quantified, and measurement biases were successfully eliminated.
Stephen D. Parkes, Matthew F. McCabe, Alan D. Griffiths, Lixin Wang, Scott Chambers, Ali Ershadi, Alastair G. Williams, Josiah Strauss, and Adrian Element
Hydrol. Earth Syst. Sci., 21, 533–548, https://doi.org/10.5194/hess-21-533-2017, https://doi.org/10.5194/hess-21-533-2017, 2017
Short summary
Short summary
Determining atmospheric moisture sources is required for understanding the water cycle. The role of land surface fluxes is a particular source of uncertainty for moisture budgets. Water vapour isotopes have the potential to improve constraints on moisture sources. In this work relationships between water vapour isotopes and land–atmosphere exchange are studied. Results show that land surface evaporative fluxes play a minor role in the daytime water and isotope budgets in semi-arid environments.
Ehsan Rabiei, Uwe Haberlandt, Monika Sester, Daniel Fitzner, and Markus Wallner
Hydrol. Earth Syst. Sci., 20, 3907–3922, https://doi.org/10.5194/hess-20-3907-2016, https://doi.org/10.5194/hess-20-3907-2016, 2016
Short summary
Short summary
The value of using moving cars for rainfall measurement purposes (RCs) was investigated with laboratory experiments by Rabiei et al. (2013). They analyzed the Hydreon and Xanonex optical sensors against different rainfall intensities. A continuous investigation of using RCs with the derived uncertainties from laboratory experiments for areal rainfall estimation as well as implementing the data in a hydrological model are addressed in this study.
Sergio M. Vicente-Serrano, Cesar Azorin-Molina, Arturo Sanchez-Lorenzo, Ahmed El Kenawy, Natalia Martín-Hernández, Marina Peña-Gallardo, Santiago Beguería, and Miquel Tomas-Burguera
Hydrol. Earth Syst. Sci., 20, 3393–3410, https://doi.org/10.5194/hess-20-3393-2016, https://doi.org/10.5194/hess-20-3393-2016, 2016
Short summary
Short summary
In this work we analyse the recent evolution and meteorological drivers of the atmospheric evaporative demand in the Canary Islands. We found that the reference evapotranspiration increased by 18.2 mm decade−1 – on average – between 1961 and 2013, with the highest increase recorded during summer. This increase was mainly driven by changes in the aerodynamic component, caused by a statistically significant reduction of the relative humidity.
Luca Panziera, Marco Gabella, Stefano Zanini, Alessandro Hering, Urs Germann, and Alexis Berne
Hydrol. Earth Syst. Sci., 20, 2317–2332, https://doi.org/10.5194/hess-20-2317-2016, https://doi.org/10.5194/hess-20-2317-2016, 2016
Short summary
Short summary
This paper presents a novel system to issue heavy rainfall alerts for predefined geographical regions by evaluating the sum of precipitation fallen in the immediate past and expected in the near future. In order to objectively define the thresholds for the alerts, an extreme rainfall analysis for the 159 regions used for official warnings in Switzerland was developed. It is shown that the system has additional lead time with respect to thunderstorm tracking tools targeted for convective storms.
Auguste Gires, Catherine L. Muller, Marie-Agathe le Gueut, and Daniel Schertzer
Hydrol. Earth Syst. Sci., 20, 1751–1763, https://doi.org/10.5194/hess-20-1751-2016, https://doi.org/10.5194/hess-20-1751-2016, 2016
Short summary
Short summary
Educational activities are now a common channel to increase impact of research projects. Here, we present innovative activities for young children that aim to help them (and their teachers) grasp some of the complex underlying scientific issues in environmental fields. The activities developed are focused on rainfall: observation and modeling of rain drop size and the succession of dry and rainy days, and writing of a scientific book. All activities were implemented in classrooms.
Cited articles
Adam, J. C., Clark, E. A., Lettenmaier, D. P., and Wood, E. F.: Correction of
global precipitation products for orographic effects, J. Climate, 19,
15–38, https://doi.org/10.1175/JCLI3604.1, 2006. a
Adler, R. F. and Negri, A. J.: A satellite infrared technique to estimate
tropical convective and stratiform rainfall, J. Appl. Meteorol.,
27, 30–51, 1988. a
Adler, R. F., Sapiano, M. R. P., Huffman, G. J., Wang, J.-J., Gu, G., Bolvin,
D., Chiu, L., Schneider, U., Becker, A., Nelkin, E., Xie, P., Ferraro, R.,
and Shin, D.-B.: The Global Precipitation Climatology Project
(GPCP) monthly analysis (new version 2.3) and a review of 2017 global
precipitation, Atmosphere, 9, 138, https://doi.org/10.3390/atmos9040138, 2018. a
AghaKouchak, A., Behrangi, A., Sorooshian, S., Hsu, K., and Amitai, E.:
Evaluation of satellite retrieved extreme precipitation rates across the
central United States, J. Geophys. Res.-Atmos., 116,
https://doi.org/10.1029/2010JD014741, 2011. a, b
AghaKouchak, A., Mehran, A., Norouzi, H., and Behrangi, A.: Systematic and
random error components in satellite precipitation data sets, Geophys. Res. Lett., 39,
https://doi.org/10.1029/2012GL051592, 2012. a, b
Albergel, C., Dutra, E., Munier, S., Calvet, J.-C., Munoz-Sabater, J., de Rosnay, P., and Balsamo, G.: ERA-5 and ERA-Interim
driven ISBA land surface model simulations: which one performs better?, Hydrol. Earth Syst. Sci., 22, 3515–3532,
https://doi.org/10.5194/hess-22-3515-2018, 2018. a
Ashouri, H., Hsu, K., Sorooshian, S., Braithwaite, D. K., Knapp, K. R.,
Cecil,
L. D., Nelson, B. R., and Pratt, O. P.: PERSIANN-CDR: daily precipitation
climate data record from multisatellite observations for hydrological and
climate studies, B. Am. Meteorol. Soc., 96, 69–83,
2015. a
Beck, H. E., van Dijk, A. I. J. M., Miralles, D. G., de Jeu, R. A. M.,
Bruijnzeel, L. A., McVicar, T. R., and Schellekens, J.: Global patterns in
baseflow index and recession based on streamflow observations from 3394
catchments, Water Resour. Res., 49, 7843–7863, 2013. a
Beck, H. E., van Dijk, A. I. J. M., de Roo, A., Dutra, E., Fink, G., Orth,
R., and Schellekens, J.: Global evaluation of runoff from 10 state-of-the-art
hydrological models, Hydrol. Earth Syst. Sci., 21, 2881–2903,
https://doi.org/10.5194/hess-21-2881-2017, 2017a. a, b
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles,
D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25∘ global
gridded precipitation (1979–2015) by merging gauge, satellite, and
reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615,
https://doi.org/10.5194/hess-21-589-2017, 2017b. a, b, c, d
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M.,
Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.:
Global-scale evaluation of 22 precipitation datasets using gauge observations
and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217,
https://doi.org/10.5194/hess-21-6201-2017, 2017c. a, b, c, d, e, f, g, h
Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. M., van
Dijk,
A. I. J. M., McVicar, T. R., and Adler, R. F.: MSWEP V2 global 3-hourly
0.1∘ precipitation: methodology and quantitative assessment, B. Am. Meteorol. Soc., in press,
https://doi.org/10.1175/BAMS-D-17-0138.1, 2019. a, b, c, d, e, f
Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer,
S.,
Kidd, R., Dorigo, W., Wagner, W., and Levizzani, V.: Soil as a natural rain
gauge: estimating global rainfall from satellite soil moisture data, J. Geophys. Res.-Atmos., 119, 5128–5141, 2014. a
Brocca, L., Tarpanelli, A., Filippucci, P., Dorigo, W., Zaussinger, F.,
Gruber,
A., and Fernández-Prieto, D.: How much water is used for irrigation?
A new approach exploiting coarse resolution satellite soil moisture
products, Int. J. Appl. Earth Obs., 73, 752–766, https://doi.org/10.1016/j.jag.2018.08.023, 2018. a
Brown, G., Wyatt, J. L., and Tin̆o, P.: Managing Diversity in Regression
Ensembles, J. Mach. Learn. Res., 6, 1621–1650, 2005. a
Cao, Q., Painter, T. H., Currier, W. R., Lundquist, J. D., and Lettenmaier,
D. P.: Estimation of Precipitation over the OLYMPEX Domain during Winter
2015/16, J. Hydrometeorol., 19, 143–160, 2018. a
Cattani, E., Merino, A., and Levizzani, V.: Evaluation of monthly
satellite-derived precipitation products over East Africa, J. Hydrometeorol., 17, 2555–2573, 2016. a
Chen, M., Shi, W., Xie, P., Silva, V. B. S., Kousky, V. E., Higgins, R. W.,
and
Janowiak, J. E.: Assessing objective techniques for gauge-based analyses of
global daily precipitation, J. Geophys. Res., 113, D04110,
https://doi.org/10.1029/2007JD009132, 2008. a, b
Chen, S., Hong, Y., Gourley, J. J., Huffman, G. J., Tian, Y., Cao, Q., Yong,
B., Kirstetter, P.-E., Hu, J., Hardy, J., Li, Z., Khan, S. I., and Xue, X.:
Evaluation of the successive V6 and V7 TRMM multisatellite
precipitation analysis over the Continental United States, Water Resour. Res., 49, https://doi.org/10.1002/2012WR012795, 2013. a
Cheng, S., Li, L., Chen, D., and Li, J.: A neural network based ensemble
approach for improving the accuracy of meteorological fields used for
regional air quality modeling, J. Environ. Manage., 112,
404–414, https://doi.org/10.1016/j.jenvman.2012.08.020, 2012. a
Ciabatta, L., Massari, C., Brocca, L., Gruber, A., Reimer, C., Hahn, S.,
Paulik, C., Dorigo, W., Kidd, R., and Wagner, W.: SM2RAIN-CCI: a new global
long-term rainfall data set derived from ESA CCI soil moisture, Earth Syst.
Sci. Data, 10, 267–280, https://doi.org/10.5194/essd-10-267-2018, 2018. a, b
Coiffier, J.: Fundamentals of Numerical Weather Prediction, Cambridge
University Press, Cambridge, UK, 2011. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kallberg, P., Köhler, M.,
Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and
Vitart, F.: The ERA-Interim reanalysis: configuration and performance of
the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, 2011. a, b
DelSole, T., Nattala, J., and Tippett, M. K.: Skill improvement from
increased ensemble size and model diversity, Geophys. Res. Lett.,
41, 7331–7342, 2014. a
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L.,
Chung, D., Ert, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi,
M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y., Miralles, D.,
Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimerak,
C., van der Schalie, R., Seneviratne, S. I., Smolander, T., and Lecomte,
P.: ESA CCI Soil Moisture for improved Earth system understanding:
State-of-the art and future directions, Remote Sens. Environ., 203,
185–215, https://doi.org/10.1016/j.rse.2017.07.001, 2017. a
Doyle, J. D.: The Influence of Mesoscale Orography on a Coastal Jet and
Rainband, Mon. Weather Rev., 125, 1465–1488, 1997. a
Eldardiry, H., Habib, E., Zhang, Y., and Graschel, J.: Artifacts in
Stage IV
NWS real-time multisensor precipitation estimates and impacts on
identification of maximum series, J. Hydrol. Eng., 22,
E4015003, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001291, 2017. a, b, c
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S.,
Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The
climate hazards infrared precipitation with stations – a new environmental
record for monitoring extremes, Scientific Data, 2, 150066,
https://doi.org/10.1038/sdata.2015.66, 2015a. a, b, c
Funk, C., Verdin, A., Michaelsen, J., Peterson, P., Pedreros, D., and Husak,
G.: A global satellite-assisted precipitation climatology, Earth Syst. Sci.
Data, 7, 275–287, https://doi.org/10.5194/essd-7-275-2015, 2015b. a, b
Gebremichael, M.: Framework for satellite rainfall product evaluation, in:
Rainfall: State of the Science, edited by: Testik, F. Y. and Gebremichael, M.,
Geophysical Monograph Series, American Geophysical Union, Washington, D.C.,
https://doi.org/10.1029/2010GM000974, 2010. a
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K.,
Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da
Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert,
S. D., Sienkiewicz, M., and Zhao, N.: The Modern-Era Retrospective
Analysis for Research and Applications, Version 2 (MERRA-2),
J. Climate, 30, 5419–5454, 2017. a, b
Gneiting, T. and Raftery, A. E.: Weather Forecasting with Ensemble Methods,
Science, 310, 248–249, 2005. a
Gottschalck, J., Meng, J., Rodell, M., and Houser, P.: Analysis of Multiple
Precipitation Products and Preliminary Assessment of Their Impact on Global
Land Data Assimilation System Land Surface States, J. Hydrometeorol., 6, 573–598, 2005. a
Groisman, P. Y. and Legates, D. R.: The accuracy of United States
precipitation data, B. Am. Meteorol. Soc., 72,
215–227, 1994. a
Herold, N., Alexander, L. V., Donat, M. G., Contractor, S., and Becker, A.:
How
much does it rain over land?, Geophys. Res. Lett., 43, 341–348,
2016. a
Hersbach, H., de Rosnay, P., Bell, B., Schepers, D., Simmons, A., Soci, C.,
Abdalla, S., Alonso-Balmaseda, M., Balsamo, G., Bechtold, P., Berrisford,
P., Bidlot, J.-R., de Boisséson, E., Bonavita, M., Browne, P., Buizza,
R., Dahlgren, P., Dee, D., Dragani, R., Diamantakis, M., Flemming, J.,
Forbes, R., Geer, A. J., Haiden, T., Hólm, E., Haimberger, L., Hogan, R.,
Horányi, A., Janiskova, M., Laloyaux, P., Lopez, P.,
Muñoz-Sabater, J., Peubey, C., Radu, R., Richardson, D., Thépaut,
J.-N., Vitart, F., Yang, X., Zsótér, E., and Zuo, H.: Operational
global reanalysis: progress, future directions and synergies with NWP, ERA
Report Series 27, ECMWF, Reading, UK, 2018. a, b, c, d, e
Hirpa, F. A., Gebremichael, M., and Hopson, T.: Evaluation of high-resolution
satellite precipitation products over very complex terrain in Ethiopia,
J. Appl. Meteorol. Clim., 49, 1044–1051, 2010. a
Hong, Y., Hsu, K., Moradkhani, H., and Sorooshian, S.: Uncertainty
quantification of satellite precipitation estimation and Monte Carlo
assessment of the error propagation into hydrologic response, Water Resour. Res., 42, https://doi.org/10.1029/2005WR004398,
2006. a
Huffman, G. J., Adler, R. F., Morrissey, M. M., Bolvin, D. T., Curtis, S.,
Joyce, R., McGavock, B., and Susskind, J.: Global precipitation at
one-degree daily resolution from multi-satellite observations, J. Hydrometeorol., 2, 36–50, 2001. a
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu,
G., Hong, Y., Bowman, K. P., and Stocker, E. F.: The TRMM Multisatellite
Precipitation Analysis (TMPA): quasi-global, multiyear, combined-sensor
precipitation estimates at fine scales, J. Hydrometeorol., 8,
38–55, 2007. a, b, c
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C.,
Nelkin, E. J., and Xie, P.: NASA Global Precipitation Measurement
(GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG),
Algorithm Theoretical Basis Document (ATBD), NASA/GSFC, Greenbelt, MD
20771, USA, 2014. a, b, c, d, e, f, g
Kauffeldt, A., Halldin, S., Rodhe, A., Xu, C.-Y., and Westerberg, I. K.:
Disinformative data in large-scale hydrological modelling, Hydrol. Earth
Syst. Sci., 17, 2845–2857, https://doi.org/10.5194/hess-17-2845-2013, 2013. a
Kendon, E. J., Roberts, N. M., Senior, C. A., and Roberts, M. J.: Realism of
Rainfall in a Very High-Resolution Regional Climate Model, J. Climate, 25, 5791–5806, 2012. a
Kidd, C., Becker, A., Huffman, G. J., Muller, C. L., Joe, P.,
Skofronick-Jackson, G., and Kirschbaum, D. B.: So, how much of the
Earth's surface is covered by rain gauges?, B. Am. Meteorol. Soc., 98, 69–78, 2017. a
Kirschbaum, D. B., Huffman, G. J., Adler, R. F., Braun, S., Garrett, K.,
Jones,
E., McNally, A., Skofronick-Jackson, G., Stocker, E., Wu, H., and
Zaitchik, B. F.: NASA's Remotely Sensed Precipitation: A Reservoir for
Applications Users, B. Am. Meteorol. Soc., 98,
1169–1184, 2017. a
Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube
basin under an ensemble of climate change scenarios, J. Hydrol.,
424–425, 264–277, https://doi.org/10.1016/j.hydrol.2012.01.011, 2012. a, b
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi,
K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahashi, K.:
The JRA-55 reanalysis: General specifications and basic characteristics,
J. Meteorol. Soc. Jpn., 93, 5–48,
https://doi.org/10.2151/jmsj.2015-001, 2015. a, b
Kongoli, C., Pellegrino, P., Ferraro, R. R., Grody, N. C., and Meng, H.: A
new
snowfall detection algorithm over land using measurements from the Advanced
Microwave Sounding Unit (AMSU), Geophys. Res. Lett., 30,
https://doi.org/10.1029/2003GL017177, 2003. a
Kubota, T., Ushio, T., Shige, S., Kida, S., Kachi, M., and Okamoto, K.:
Verification of high-resolution satellite-based rainfall estimates around
Japan using a gauge-calibrated ground-radar dataset, J. Meteorol. Soc. Jpn., 87A, 203–222, 2009. a
Kucera, P. A., Ebert, E. E., Turk, F. J., Levizzani, V., Kirschbaum, D.,
Tapiador, F. J., Loew, A., and Borsche, M.: Precipitation from space:
Advancing Earth system science, B. Am. Meteorol. Soc., 94, 365–375, 2013. a
Leutbecher, M., Lock, S.-J., Ollinaho, P., Lang, S. T., Balsamo, G.,
Bechtold,
P., Bonavita, M., Christensen, H. M., Diamantakis, M., Dutra, E., English,
S., Fisher, M., Forbes, R. M., Goddard, J., Haiden, T., Hogan, R. J.,
Juricke, S., Lawrence, H., MacLeod, D., Magnusson, L., Malardel, S.,
Massart, S., Sandu, I., Smolarkiewicz, P. K., Subramanian, A., Vitart, F.,
Wedi, N., and Weisheimer, A.: Stochastic representations of model
uncertainties at ECMWF: state of the art and future vision, Q. J. Roy. Meteor. Soc., 143, 2315–2339, 2017. a
Liu, C., Ikeda, K., Rasmussen, R., Barlage, M., Newman, A. J., Prein, A. F.,
Chen, F., Chen, L., Clark, M., Dai, A., Dudhia, J., Eidhammer, T., Gochis,
D., Gutmann, E., Kurkute, S., Li, Y., Thompson, G., and Yates, D.:
Continental-scale convection-permitting modeling of the current and future
climate of North America, Clim. Dynam., 49, 71–95, 2017. a, b, c, d, e, f, g
Liu, G. and Seo, E.-K.: Detecting snowfall over land by satellite
high-frequency microwave observations: The lack of scattering signature and a
statistical approach, J. Geophys. Res.-Atmos., 118,
1376–1387, 2013. a
Lopez, P.: Cloud and precipitation parameterizations in modeling and
variational data assimilation: a review, J. Atmos. Sci.,
64, 3766–3784, 2007. a
Lu, D. and Yong, B.: Evaluation and hydrological utility of the latest GPM
IMERG V5 and GSMaP V7 precipitation products over the Tibetan
Plateau, Remote Sens., 10, https://doi.org/10.3390/rs10122022, 2018. a
Maggioni, V., Meyers, P. C., and Robinson, M. D.: A review of merged high
resolution satellite precipitation product accuracy during the Tropical
Rainfall Measuring Mission (TRMM)-era, J. Hydrometeorol.,
17, 1101–1117, https://doi.org/10.1175/JHM-D-15-0190.1, 2016. a
Manz, B., Páez-Bimos, S., Horna, N., Buytaert, W., Ochoa-Tocachi, B.,
Lavado-Casimiro, W., and Willems, B.: Comparative Ground Validation of
IMERG and TMPA at Variable Spatiotemporal Scales in the Tropical Andes,
J. Hydrometeorol., 18, 2469–2489, 2017. a
Massari, C., Crow, W., and Brocca, L.: An assessment of the performance of
global rainfall estimates without ground-based observations, Hydrol. Earth
Syst. Sci., 21, 4347–4361, https://doi.org/10.5194/hess-21-4347-2017, 2017. a, b
Massari, C., Camici, S., Ciabatta, L., and Brocca, L.: Exploiting
Satellite-Based Surface Soil Moisture for Flood Forecasting in the
Mediterranean Area: State Update Versus Rainfall Correction, Remote
Sens., 10, https://doi.org/10.3390/rs10020292, 2018. a
Mega, T., Ushio, T., Kubota, T., Kachi, M., Aonashi, K., and Shige, S.: Gauge
adjusted global satellite mapping of precipitation (GSMaP_Gauge), in: 2014
XXXIth URSI General Assembly and Scientific Symposium (URSI GASS), 1–4, Beijing,
China, https://doi.org/10.1109/URSIGASS.2014.6929683, 2014. a
Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., and Houston, T. G.: An
overview of the Global Historical Climatology Network-Daily
database, J. Atmos. Ocean. Tech., 29, 897–910, 2012. a
Mizukami, N. and Smith, M. B.: Analysis of inconsistencies in multi-year
gridded quantitative precipitation estimate over complex terrain and its
impact on hydrologic modeling, J. Hydrol., 428–429, 129–141,
2012. a
Nelson, B. R., Prat, O. P., Seo, D.-J., and Habib, E.: Assessment and
implications of NCEP Stage IV quantitative precipitation estimates for
product intercomparisons, Weather Forecast., 31, 371–394, 2016. a
Nikulin, G., Jones, C., Giorgi, F., Asrar, G., Büchner, M.,
Cerezo-Mota,
R., Christensen, O. B., Déqué, M., Fernandez, J., Hänsler, A.,
van Meijgaard, E., Samuelsson, P., Sylla, M. B., and Sushama, L.:
Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate
Simulations, J. Climate, 25, 6057–6078, 2012. a
Ollinaho, P., Lock, S.-J., Leutbecher, M., Bechtold, P., Beljaars, A., Bozzo,
A., Forbes, R. M., Haiden, T., Hogan, R. J., and Sandu, I.: Towards
process-level representation of model uncertainties: stochastically perturbed
parametrizations in the ECMWF ensemble, Q. J. Roy. Meteor. Soc., 143, 408–422, 2016. a
Palerme, C., Claud, C., Dufour, A., Genthon, C., Wood, N. B., and
L'Ecuyer,
T.: Evaluation of Antarctic snowfall in global meteorological reanalyses,
Atmos. Res., 190, 104–112, 2017. a
Prakash, S., Mitra, A. K., Pai, D. S., and AghaKouchak, A.: From TRMM to
GPM: How well can heavy rainfall be detected from space?, Adv. Water Resour., 88, 1–7, https://doi.org/10.1016/j.advwatres.2015.11.008, 2016. a
Prakash, S., Mitra, A. K., AghaKouchak, A., Liu, Z., Norouzi, H., and Pai,
D. S.: A preliminary assessment of GPM-based multi-satellite precipitation
estimates over a monsoon dominated region, J. Hydrol., 556,
865–876, https://doi.org/10.1016/j.jhydrol.2016.01.029, 2018. a
Prat, O. P. and Nelson, B. R.: Evaluation of precipitation estimates over
CONUS derived from satellite, radar, and rain gauge data sets at daily to
annual scales (2002–2012), Hydrol. Earth Syst. Sci., 19, 2037–2056,
https://doi.org/10.5194/hess-19-2037-2015, 2015. a
Prein, A. F. and Gobiet, A.: Impacts of uncertainties in European gridded
precipitation observations on regional climate analysis, Int. J. Climatol., 37, 305–327, 2017. a
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S.,
Schmidli, J., van Lipzig, N. P. M., and Leung, R.: A review on regional
convection-permitting climate modeling: demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, 2015. a, b
Ran, X., Fuqiang, T., Long, Y., Hongchang, H., Hui, L., and Aizhong, H.:
Ground
validation of GPM IMERG and TRMM 3B42V7 rainfall products over
southern Tibetan Plateau based on a high-density rain gauge network,
J. Geophys. Res.-Atmos., 122, 910–924, 2017. a
Rasmussen, R. M., Baker, B., Kochendorfer, J., Meyers, T., Landolt, S.,
Fischer, A. P., Black, J., Thériault, J. M., Kucera, P., Gochis, D.,
Smith, C., Nitu, R., Hall, M., Ikeda, K., and Gutmann, E.: How well are we
measuring snow: The NOAA/FAA/NCAR winter precipitation test bed, B. Am. Meteorol. Soc., 93, 811–829,
https://doi.org/10.1175/BAMS-D-11-00052.1, 2012. a
Roe, G. H.: Orographic precipitation, Annu. Rev. Earth Pl. Sc., 33, 645–671, 2005. a
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P.,
Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R.,
Gayno, G., Wang, J., Hou, Y.-T., Chuang, H.-Y., Juang, H.-M. H., Sela, J.,
Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber,
J., Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., Van Den Dool, H., Kumar,
A., Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.-K.,
Ebisuzaki, W., Lin, R., Xie, P., Chen, M., Zhou, S., Higgins, W., Zou, C.-Z.,
Liu, Q., Chen, Y., Han, Y., Cucurull, L., Reynolds, R. W., Rutledge, G., and
Goldberg, M.: The NCEP climate forecast system reanalysis, B. Am. Meteorol. Soc., 91, 1015–1057, 2010. a, b
Sapiano, M. R. P., Smith, T. M., and Arkin, P. A.: A new merged analysis of
precipitation utilizing satellite and reanalysis data, J. Geophys. Res.-Atmos., 113, https://doi.org/10.1029/2008JD010310,
2008. a
Satgé, F., Xavier, A., Zolá, R. P., Hussain, Y., Timouk, F., Garnier,
J., and Bonnet, M.-P.: Comparative assessments of the latest GPM mission's
spatially enhanced satellite rainfall products over the main Bolivian
watersheds, Remote Sens., 9, https://doi.org/10.3390/rs9040369, 2017. a
Scofield, R. A. and Kuligowski, R. J.: Status and Outlook of Operational
Satellite Precipitation Algorithms for Extreme-Precipitation Events, Weather
Forecast., 18, 1037–1051, 2003. a
Sharifi, E., Steinacker, R., and Saghafian, B.: Assessment of GPM-IMERG and
Other Precipitation Products against Gauge Data under Different Topographic
and Climatic Conditions in Iran: Preliminary Results, Remote Sens., 8, https://doi.org/10.3390/rs8020135, 2016. a
Skofronick-Jackson, G., Hudak, D., Petersen, W., Nesbitt, S. W.,
Chandrasekar, V., Durden, S., Gleicher, K. J., Huang, G.-J., Joe, P.,
Kollias, P., Reed, K. A., Schwaller, M. R., Stewart, R., Tanelli, S., Tokay,
A., Wang, J. R., and Wolde, M.: Global Precipitation Measurement Cold
Season Precipitation Experiment (GCPEX): for measurement's sake, let it
snow, B. Am. Meteorol. Soc., 96, 1719–1741, 2015. a
Skok, G., Žagar, N., Honzak, L., Žabkar, R., Rakovec, J., and
Ceglar, A.: Precipitation intercomparison of a set of satellite- and
raingauge-derived datasets, ERA Interim reanalysis, and a single WRF
regional climate simulation over Europe and the North Atlantic,
Theor. Appl. Climatol., 123, 217–232, 2015. a
Sorooshian, S., Hsu, K.-L., Gao, X., Gupta, H. V., Imam, B., and Braithwaite,
D.: Evaluation of PERSIANN system satellite-based estimates of tropical
rainfall, B. Am. Meteorol. Soc., 81, 2035–2046,
2000. a
Stephens, G. L., L'Ecuyer, T., Forbes, R., Gettelmen, A., Golaz, J.-C.,
Bodas-Salcedo, A., Suzuki, K., Gabriel, P., and Haynes, J.: Dreary state of
precipitation in global models, J. Geophys. Res.-Atmos.,
115, https://doi.org/10.1029/2010JD014532, 2010. a, b
Strauch, M., Bernhofer, C., Koide, S., Volk, M., Lorz, C., and Makeschin, F.:
Using precipitation data ensemble for uncertainty analysis in SWAT
streamflow simulation, J. Hydrol., 414–415, 413–424,
https://doi.org/10.1016/j.jhydrol.2011.11.014, 2012. a
Sun, Y., Solomon, S., Dai, A., and Portmann, R. W.: How often does it rain?,
J. Climate, 19, 916–934, 2006. a
Tan, M. L. and Santo, H.: Comparison of GPM IMERG, TMPA 3B42 and
PERSIANN-CDR satellite precipitation products over Malaysia, Atmos. Res., 202, 63–76, https://doi.org/10.1016/j.atmosres.2017.11.006, 2018. a
Tang, G., Ma, Y., Long, D., Zhong, L., and Hong, Y.: Evaluation of GPM
Day-1 IMERG and TMPA Version-7 legacy products over Mainland
China at multiple spatiotemporal scales, J. Hydrol., 533,
152–167, 2016a. a
Tang, G., Zeng, Z., Long, D., Guo, X., Yong, B., Zhang, W., and Hong, Y.:
Statistical and Hydrological Comparisons between TRMM and GPM Level-3
Products over a Midlatitude Basin: Is Day-1 IMERG a Good Successor for
TMPA 3B42V7?, J. Hydrometeorol., 17, 121–137,
2016b. a
Tapiador, F. J., Turk, F. J., Petersen, W., Hou, A. Y., García-Ortega,
E., Machado, L. A. T., Angelis, C. F., Salio, P., Kidd, C., Huffman, G. J.,
and de Castro, M.: Global precipitation measurement: Methods, datasets and
applications, Atmos. Res., 104–105, 70–97, 2012. a
Tarpanelli, A., Massari, C., Ciabatta, L., Filippucci, P., Amarnath, G., and
Brocca, L.: Exploiting a constellation of satellite soil moisture sensors for
accurate rainfall estimation, Adv. Water Resour., 108, 249–255,
2017. a
Tian, Y. and Peters-Lidard, C. D.: A global map of uncertainties in
satellite-based precipitation measurements, Geophys. Res. Lett., 37,
https://doi.org/10.1029/2010GL046008, 2010. a, b
Tian, Y., Peters-Lidard, C. D., Choudhury, B. J., and Garcia, M.:
Multitemporal analysis of TRMM-based satellite precipitation products for
land data assimilation applications, J. Hydrometeorol., 8,
1165–1183, 2007. a
Tian, Y., Peters-Lidard, C. D., Eylander, J. B., Joyce, R. J., Huffman,
G. J., Adler, R. F., Hsu, K., Turk, F. J., Garcia, M., and Zeng, J.:
Component analysis of errors in satellite-based precipitation estimates,
J. Geophys. Res.-Atmos., 114,
https://doi.org/10.1029/2009JD011949, 2009. a
Urraca, R., Huld, T., Gracia-Amillo, A., de Pison, F. J. M., Kaspar, F.,
and Sanz-Garcia, A.: Evaluation of global horizontal irradiance estimates
from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based
data, Sol. Energy, 164, 339–354, 2018. a
Ushio, T., Kubota, T., Shige, S., Okamoto, K., Aonashi, K., Inoue, T.,
Takahashi, N., Iguchi, T., Kachi, M., Oki, R., Morimoto, T., and Kawasaki,
Z.: A Kalman filter approach to the Global Satellite Mapping of
Precipitation (GSMaP) from combined passive microwave and infrared
radiometric data, J. Meteorol. Soc. Jpn., 87A,
137–151, 2009. a, b
Vicente, G. A., Scofield, R. A., and Menzel, W. P.: The operational GOES
infrared rainfall estimation technique, B. Am. Meteorol. Soc., 79, 1883–1898, 1998. a
Wanders, N., Pan, M., and Wood, E. F.: Correction of real-time satellite
precipitation with multi-sensor satellite observations of land surface
variables, Remote Sens. Environ., 160, 206–221,
https://doi.org/10.1016/j.rse.2015.01.016, 2015. a
Wang, W., Lu, H., Zhao, T., Jiang, L., and Shi, J.: Evaluation and comparison
of daily rainfall from latest GPM and TRMM products over the Mekong
River Basin, IEEE J.-STARS, 10, 2540–2549, 2017. a
Wardah, T., Abu Bakar, S. H., Bardossy, A., and Maznorizan, M.: Use of
geostationary meteorological satellite images in convective rain estimation
for flash-flood forecasting, J. Hydrol., 356, 283–298, 2008. a
Xie, P. and Arkin, P. A.: Analyses of global monthly precipitation using
gauge
observations, satellite estimates, and numerical model predictions, J. Climate., 9, 840–858, 1996. a
You, Y., Wang, N.-Y., Ferraro, R., and Rudlosky, S.: Quantifying the snowfall
detection performance of the GPM microwave imager channels over land,
J. Hydrometeorol., 18, 729–751, 2017. a
Zhan, W., Pan, M., Wanders, N., and Wood, E. F.: Correction of real-time
satellite precipitation with satellite soil moisture observations, Hydrol.
Earth Syst. Sci., 19, 4275–4291, https://doi.org/10.5194/hess-19-4275-2015,
2015. a
Zhang, Q., Ye, J., Zhang, S., and Han, F.: Precipitable water vapor retrieval
and analysis by multiple data sources: ground-based GNSS, radio
occultation, radiosonde, microwave satellite, and NWP reanalysis data,
J. Sensors, 3428303, https://doi.org/10.1155/2018/3428303, 2018a. a
Zhang, X., Liang, S., Wang, G., Yao, Y., Jiang, B., and Cheng, J.: Evaluation
of the Reanalysis Surface Incident Shortwave Radiation Products from NCEP,
ECMWF, GSFC, and JMA Using Satellite and Surface Observations, Remote
Sens., 8, https://doi.org/10.3390/rs8030225, 2016. a
Zhang, X., Anagnostou, E. N., and Schwartz, C. S.: NWP-based adjustment of
IMERG precipitation for flood-inducing complex terrain storms: evaluation
over CONUS, Remote Sens., 10, 642, https://doi.org/10.3390/rs10040642, 2018b. a, b
Zolina, O., Kapala, A., Simmer, C., and Gulev, S. K.: Analysis of extreme
precipitation over Europe from different reanalyses: a comparative
assessment, Global Planet. Change, 44, 129–161, 2004. a
Zuo, H., Alonso-Balmaseda, M., de Boisseson, E., Hirahara, S., Chrust,
M.,
and de Rosnay, P.: A generic ensemble generation scheme for data
assimilation and ocean analysis, ECMWF Technical Memorandum 795, ECMWF, Reading, UK, 2017. a
Short summary
We conducted a comprehensive evaluation of 26 precipitation datasets for the US using the Stage-IV gauge-radar dataset as a reference. The best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for reporting times. Our findings can be used as a guide to choose the most suitable precipitation dataset for a particular application.
We conducted a comprehensive evaluation of 26 precipitation datasets for the US using the...