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Trends and Interannual Variability of Extreme Rainfall Indices over Cameroon

Author

Listed:
  • Derbetini A. Vondou

    (Laboratory for Environmental Modelling and Atmospheric Physics, Department of Physics, University of Yaounde 1, Yaounde P.O. Box 812, Cameroon)

  • Guy Merlin Guenang

    (Laboratory for Environmental Modelling and Atmospheric Physics, Department of Physics, University of Yaounde 1, Yaounde P.O. Box 812, Cameroon
    L2MPS, Department of Physics, Faculty of Science, University of Dschang, Dschang P.O. Box 96, Cameroon)

  • Tchotchou Lucie Angennes Djiotang

    (Laboratory for Environmental Modelling and Atmospheric Physics, Department of Physics, University of Yaounde 1, Yaounde P.O. Box 812, Cameroon)

  • Pierre Honore Kamsu-Tamo

    (Laboratory for Environmental Modelling and Atmospheric Physics, Department of Physics, University of Yaounde 1, Yaounde P.O. Box 812, Cameroon)

Abstract

Central African citizens are highly vulnerable to extreme hydroclimatic events due to excess precipitation or to dry spells. This study makes use of CHIRPS precipitation data gridded at 0.05° × 0.05° resolution and extended from 1981 to 2019 to analyze spatial variabilities and trends of six extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) over Cameroon. They are the number of wet days (RR1), the simple daily intensity index (SDII), the annual total precipitation from days greater than the 95th percentile (R95ptot), the maximum number of consecutive wet days (CWD), the maximum number of consecutive dry days (CDD), the number of very heavy rainfall (RR20). The standard precipitation index (SPI) time series were also examined in the five agro-climatic regions of the domain. The pattern of annual precipitation was first checked over the entire domain. We obtain a well-known pattern showing a decreased precipitation northward with the highest values around the Atlantic Ocean coast. The analysis shows that all indices represent patterns approximately similar to that of annual rainfall except CDD where the spatial south-north gradient is reversed. RR20 shows the lowest spatial variability. Trend study of RR1 indicates negative values south of the domain and predominated positive values in the northern part, where CDD, on the contrary, shows a decreased trend. The highest trends are observed in the northernmost area for CWD and around the coast for SDII and R95ptot. SPI time series indicate an alternative dry and wet period and the years between 1990 and 2000 witnessed more annual wet conditions. Such a study is very important in this domain where variabilities of climatic components are very high due to climate change impact and diversified relief. The results can serve as a reference for agricultural activity, hydropower management, civil engineering, planning of economic activities and can contribute to the understanding of the climate system in Cameroon.

Suggested Citation

  • Derbetini A. Vondou & Guy Merlin Guenang & Tchotchou Lucie Angennes Djiotang & Pierre Honore Kamsu-Tamo, 2021. "Trends and Interannual Variability of Extreme Rainfall Indices over Cameroon," Sustainability, MDPI, vol. 13(12), pages 1-12, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6803-:d:576057
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    References listed on IDEAS

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    1. Thierry C. Fotso-Nguemo & Ismaïla Diallo & Moussa Diakhaté & Derbetini A. Vondou & Mamadou L. Mbaye & Andreas Haensler & Amadou T. Gaye & Clément Tchawoua, 2019. "Projected changes in the seasonal cycle of extreme rainfall events from CORDEX simulations over Central Africa," Climatic Change, Springer, vol. 155(3), pages 339-357, August.
    2. Michela Biasutti, 2019. "Rainfall trends in the African Sahel: Characteristics, processes, and causes," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 10(4), July.
    3. P. Moudi Igri & Roméo S. Tanessong & D. A. Vondou & Jagabandhu Panda & Adamou Garba & F. Kamga Mkankam & A. Kamga, 2018. "Assessing the performance of WRF model in predicting high-impact weather conditions over Central and Western Africa: an ensemble-based approach," 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. 93(3), pages 1565-1587, September.
    4. 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.
    5. Ibrahim Njouenwet & Derbetini Appolinaire Vondou & Elisabeth Fita Dassou & Brian Odhiambo Ayugi & Robert Nouayou, 2021. "Assessment of agricultural drought during crop-growing season in the Sudano–Sahelian region of Cameroon," 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. 106(1), pages 561-577, March.
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    1. Fanta F. Jabbi & Yu’e Li & Tianyi Zhang & Wang Bin & Waseem Hassan & You Songcai, 2021. "Impacts of Temperature Trends and SPEI on Yields of Major Cereal Crops in the Gambia," Sustainability, MDPI, vol. 13(22), pages 1-19, November.

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