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

Author

Listed:
  • Wiam Salih

    (Mohammed VI Polytechnic University)

  • Terence Epule Epule

    (Mohammed VI Polytechnic University
    Université du Québec en Abitibi-Témiscamingue)

  • EL Mahdi EL Khalki

    (Mohammed VI Polytechnic University)

  • Hamza Ouatiki

    (Mohammed VI Polytechnic University)

  • Salah Erraki

    (Mohammed VI Polytechnic University
    Cadi Ayyad University)

  • Soumia Achli

    (Mohammed VI Polytechnic University)

  • Abdelghani Chehbouni

    (Mohammed VI Polytechnic University
    Mohammed VI Polytechnic University)

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

Suggested Citation

  • Wiam Salih & Terence Epule Epule & EL Mahdi EL Khalki & Hamza Ouatiki & Salah Erraki & Soumia Achli & Abdelghani Chehbouni, 2024. "A comprehensive assessment of satellite precipitation products over a semi-arid region: focus on extreme events," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(3), pages 3037-3065, February.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:3:d:10.1007_s11069-023-06317-y
    DOI: 10.1007/s11069-023-06317-y
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    References listed on IDEAS

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    1. A. N. Pettitt, 1979. "A Non‐Parametric Approach to the Change‐Point Problem," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(2), pages 126-135, June.
    2. Xuebin Zhang & Lisa Alexander & Gabriele C. Hegerl & Philip Jones & Albert Klein Tank & Thomas C. Peterson & Blair Trewin & Francis W. Zwiers, 2011. "Indices for monitoring changes in extremes based on daily temperature and precipitation data," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 2(6), pages 851-870, November.
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    1. Mohammad Sadegh Keikhosravi-Kiany & Robert C. Balling, 2025. "Utility of satellite precipitation products for drought monitoring (case study: southwestern regions in Iran)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(6), pages 6467-6497, April.

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