Abstract
The Rwenzori Mountains, in southwest Uganda, are prone to precipitation-related hazards such as flash floods and landslides. These natural hazards highly impact the lives and livelihoods of the people living in the region. However, our understanding of the precipitation patterns and their impact on related hazardous events and/or agricultural productivity is hampered by a dearth of in situ precipitation observations. Here, we propose an evaluation of gridded precipitation products as potential candidates filling this hiatus. We evaluate three state-of-the-art gridded products, the ERA5 reanalysis, IMERG satellite observations, and a simulation from the convection-permitting climate model (CPM), COSMO-CLM, for their ability to represent precipitation totals, timing, and precipitation probability density function. The evaluation is performed against observations from 11 gauge stations that provide at least 2.5 years of hourly and half-hourly data, recorded between 2011 and 2016. Results indicate a poor performance of ERA5 with a persistent wet bias, mostly for stations in the rain shadow of the mountains. IMERG gives the best representation of the precipitation totals as indicated by bias score comparisons. The CPM outperforms both ERA5 and IMERG in representing the probability density function, while both IMERG and the CPM have a good skill in capturing precipitation seasonal and diurnal cycles. The better performance of CPM is attributable to its higher resolution. This study highlights the potential of using IMERG and CPM precipitation estimates for hydrological and impact modeling over the Rwenzori Mountains, preferring IMERG for precipitation totals and CPM for precipitation extremes.
| Original language | English |
|---|---|
| Pages (from-to) | 747-768 |
| Number of pages | 22 |
| Journal | Journal of Hydrometeorology |
| Volume | 23 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 20 May 2022 |
Bibliographical note
Funding Information:Acknowledgments. This work is adapted from Faluku’s master’s degree thesis, which was fully funded by VLIR-UOS. The gauge observations were provided by AfReSlide and the Eagles projects, for which the authors thank Professor Matthieu Kervyn and Dr. Elise Monsieurs. The authors also thank the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Aeronautics and Space Administration (NASA) for providing the ERA5 reanalysis and IMERG satellite data, respectively. The resources and services used in this work were provided by the Flemish Supercomputer Center (VSC), funded by the Research Foundation}Flanders (FWO) and the Flemish Government. COSMO-CLM integrations were financed by the KU Leuven C1 project “Climate extremes in the Lake Victoria region: The role of urban-and lake-induced dynamics” and were performed on high performance computing facilities of the VSC. The authors are grateful to the CLM community for all their efforts in developing COSMO-CLM and making its code available.
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© 2022 American Meteorological Society.
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