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

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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.
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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.