A comprehensive assessment of satellite precipitation products over a semi-arid region: focus on extreme events

Wiam Salih (), Terence Epule Epule, Mahdi EL Khalki El, Hamza Ouatiki, Salah Erraki, Soumia Achli and Abdelghani Chehbouni
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Wiam Salih: Mohammed VI Polytechnic University
Terence Epule Epule: Mohammed VI Polytechnic University
Mahdi EL Khalki El: Mohammed VI Polytechnic University
Hamza Ouatiki: Mohammed VI Polytechnic University
Salah Erraki: Mohammed VI Polytechnic University
Soumia Achli: Mohammed VI Polytechnic University
Abdelghani Chehbouni: Mohammed VI Polytechnic University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 3, No 37, 3037-3065

Abstract: Abstract Global warming has increased the frequency and intensity of extreme weather events worldwide. Arid and semi-arid regions, such as the Tensift basin in Morocco, have experienced severe water shortages as a result. The unavailability of quality data limits our understanding of the occurrence of extreme events and their associated impacts. This study assesses the accuracy of eight satellite, reanalysis, and merged precipitation products (SRMP): PERSIANN, PERSIANN CDR, IMERG, ARC2, RFE2, CHIRPS, ERA5, and MSWEP, in estimating extreme precipitation in the Tensift basin. The datasets were assessed against observed data from fourteen weather stations for the period 2001–2016 at daily, monthly, seasonal, and annual time scales. Volumetric and categorical metrics were used for analysis, along with evaluation of extreme precipitation indices (EPI) and drought characterization. The ability of SRMP to characterize meteorological drought using Standardized Precipitation Index (SPI) was also examined. A complementary analysis is carried out by comparing all the SRMPs to reproduce the precipitation of November 2014 event. Cumulative Distribution Function (CDF) mapping bias correction method was employed to enhance the performance of the SRMP, with particular focus on improving the extreme events. Results showed that PERSIANN CDR, IMERG, MSWEP, and ERA5 exhibit the highest accuracy, performing relatively well at monthly and annual time scales (correlation > 0.7, Rbias

Keywords: Precipitation; Satellite products; Extreme events; Bias correction; Tensift basin; Morocco (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-023-06317-y

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