Verification of satellite and model products against a dense rain gauge network for a severe flooding event in Kumasi, Ghana

Agyekum, J., Amekudzi, L. K., Stein, T. ORCID: https://orcid.org/0000-0002-9215-5397, Aryee, J. N. A., Atiah, W. A., Adefisan, E. A. and Danuor, S. K. (2023) Verification of satellite and model products against a dense rain gauge network for a severe flooding event in Kumasi, Ghana. Meteorological Applications, 30 (5). e2150. ISSN 1350-4827 doi: 10.1002/met.2150

Abstract/Summary

Floods as a result of severe storms cause significant impacts on lives and properties. Therefore, timely and accurate forecasts of the storms will reduce the associated risks. In this study, we look at the characteristics of a storm on 28 June, 2018 in Kumasi from a rain gauge network and satellite data, and reanalysis data. The storm claimed at least 8 lives and displaced 293 people in Kumasi, Ghana. The ability of satellite and reanalysis data to capture the temporal variations of the storm was assessed using a high temporal resolution (accumulation per minute) rain gauge data. We employed the observation data from the Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa (DACCIWA) rain gauges to assess the storm's onset, duration, and cessation. Subsequently, the performance of the ERA5 reanalysis and Global Precipitation Measurement (GPM) satellite precipitation estimates in capturing the rainfall is assessed. Both GPM and the ERA5 had difficulty reproducing the hourly pattern of the rain. However, the GPM produced variability that is similar to the observed. Generally, the region of maximum rainfall was located in the southern parts of the study domain in ERA5, while GPM placed it in the northern parts. The study contributes a verification measure to improve weather forecasting in Ghana as part of the objectives of the GCRF African Science for Weather Information and Forecasting Techniques (SWIFT) project.

Item Type	Article
URI	https://reading-pure-test.eprints-hosting.org/id/eprint/113555
Identification Number/DOI	10.1002/met.2150
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology Central Services
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