Articles | Volume 28, issue 14
https://doi.org/10.5194/hess-28-3099-2024
https://doi.org/10.5194/hess-28-3099-2024
Research article
 | 
17 Jul 2024
Research article |  | 17 Jul 2024

Global-scale evaluation of precipitation datasets for hydrological modelling

Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby

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Cited articles

Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., and Hegewisch, K. C.: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015, Sci. Data, 5, 170191, https://doi.org/10.1038/sdata.2017.191, 2018. 
Acharya, S. C., Nathan, R., Wang, Q. J., Su, C.-H., and Eizenberg, N.: An evaluation of daily precipitation from a regional atmospheric reanalysis over Australia, Hydrol. Earth Syst. Sci., 23, 3387–3403, https://doi.org/10.5194/hess-23-3387-2019, 2019. 
Ahmed, K., Shahid, S., Wang, X., Nawaz, N., and Khan, N.: Evaluation of Gridded Precipitation Datasets over Arid Regions of Pakistan, Water, 11, 210, https://doi.org/10.3390/w11020210, 2019. 
Alazzy, A. A., Lü, H., Chen, R., Ali, A. B., Zhu, Y., and Su, J.: Evaluation of Satellite Precipitation Products and Their Potential Influence on Hydrological Modeling over the Ganzi River Basin of the Tibetan Plateau, Adv. Meteorol., 2017, e3695285, https://doi.org/10.1155/2017/3695285, 2017. 
AL-Falahi, A. H., Saddique, N., Spank, U., Gebrechorkos, S. H., and Bernhofer, C.: Evaluation the Performance of Several Gridded Precipitation Products over the Highland Region of Yemen for Water Resources Management, Remote Sens., 12, 2984, https://doi.org/10.3390/rs12182984, 2020. 
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Short summary
This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
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