Articles | Volume 21, issue 12
https://doi.org/10.5194/hess-21-6201-2017
https://doi.org/10.5194/hess-21-6201-2017
Research article
 | 
08 Dec 2017
Research article |  | 08 Dec 2017

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

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

Related authors

On the timescale of drought indices for monitoring streamflow drought considering catchment hydrological regimes
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
Deep Dive into Global Hydrologic Simulations: Harnessing the Power of Deep Learning and Physics-informed Differentiable Models (δHBV-globe1.0-hydroDL)
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. Discuss., https://doi.org/10.5194/gmd-2023-190,https://doi.org/10.5194/gmd-2023-190, 2023
Revised manuscript under review for GMD
Short summary
Technical note: Surface fields for global environmental modelling
Margarita Choulga, Francesca Moschini, Cinzia Mazzetti, Stefania Grimaldi, Juliana Disperati, Hylke Beck, Peter Salamon, and Christel Prudhomme
EGUsphere, https://doi.org/10.5194/egusphere-2023-1306,https://doi.org/10.5194/egusphere-2023-1306, 2023
Short summary
The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment
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
FarmCan: a physical, statistical, and machine learning model to forecast crop water deficit for farms
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

Related subject area

Subject: Global hydrology | Techniques and Approaches: Instruments and observation techniques
Evaluation of reanalysis soil moisture products using Cosmic Ray Neutron Sensor observations across the globe
Yanchen Zheng, Gemma Coxon, Ross Woods, Daniel Power, Miguel Angel Rico-Ramirez, David McJannet, Rafael Rosolem, Jianzhu Li, and Ping Feng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-224,https://doi.org/10.5194/hess-2023-224, 2023
Revised manuscript accepted for HESS
Short summary
Evaporation enhancement drives the European water-budget deficit during multi-year droughts
Christian Massari, Francesco Avanzi, Giulia Bruno, Simone Gabellani, Daniele Penna, and Stefania Camici
Hydrol. Earth Syst. Sci., 26, 1527–1543, https://doi.org/10.5194/hess-26-1527-2022,https://doi.org/10.5194/hess-26-1527-2022, 2022
Short summary
Combining passive and active distributed temperature sensing measurements to locate and quantify groundwater discharge variability into a headwater stream
Nataline Simon, Olivier Bour, Mikaël Faucheux, Nicolas Lavenant, Hugo Le Lay, Ophélie Fovet, Zahra Thomas, and Laurent Longuevergne
Hydrol. Earth Syst. Sci., 26, 1459–1479, https://doi.org/10.5194/hess-26-1459-2022,https://doi.org/10.5194/hess-26-1459-2022, 2022
Short summary
Technical note: Evaluation and bias correction of an observation-based global runoff dataset using streamflow observations from small tropical catchments in the Philippines
Daniel E. Ibarra, Carlos Primo C. David, and Pamela Louise M. Tolentino
Hydrol. Earth Syst. Sci., 25, 2805–2820, https://doi.org/10.5194/hess-25-2805-2021,https://doi.org/10.5194/hess-25-2805-2021, 2021
Short summary
Hydrology and water resources management in ancient India
Pushpendra Kumar Singh, Pankaj Dey, Sharad Kumar Jain, and Pradeep P. Mujumdar
Hydrol. Earth Syst. Sci., 24, 4691–4707, https://doi.org/10.5194/hess-24-4691-2020,https://doi.org/10.5194/hess-24-4691-2020, 2020
Short summary

Cited articles

Adler, R. F., Kidd, C., Petty, G., Morissey, M., and Goodman, H. M.: Intercomparison of global precipitation products: The third precipitation intercomparison project (PIP-3), B. Am. Meteorol. Soc., 82, 1377–1396, 2001.
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., 116, D02115, https://doi.org/10.1029/2010JD014741, 2011.
Akinremi, O. O., McGinn, S. M., and Cutforth, H. W.: Precipitation trends on the Canadian prairies, J. Climate, 12, 2996–3003, 1999.
Albergel, C., Dorigo, W., Reichle, R. H., Balsamo, G., de Rosnay, P., Muñoz Sabater, J. M., Isaksen, L., de Jeu, R., and Wagner, W.: Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing, J. Hydrometeorol., 14, 1259–1277, 2013.
Alijanian, M., Rakhshandehroo, G. R., Mishra, A. K., and Dehghani, M.: Evaluation of satellite rainfall climatology using CMORPH, PERSIANN-CDR, PERSIANN, TRMM, MSWEP over Iran, Int. J. Climatol., 37, 4896–4914, 2017.
Download
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.