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Projections of Drought Characteristics Based on the CNRM-CM6 Model over Africa

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  • Isaac Kwesi Nooni

    (Binjiang College, Nanjing University of Information Science and Technology, Wuxi 214105, China
    School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
    Wuxi Institute of Technology, Nanjing University of Information Science & Technology, Wuxi 214105, China)

  • Daniel Fiifi Tawia Hagan

    (School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Waheed Ullah

    (School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Jiao Lu

    (School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Shijie Li

    (School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Nana Agyemang Prempeh

    (Department of Geographical Sciences, School of Geosciences, University of Energy and Natural Resources, Sunyani P.O. Box 214, Ghana)

  • Gnim Tchalim Gnitou

    (Binjiang College, Nanjing University of Information Science and Technology, Wuxi 214105, China)

  • Kenny Thiam Choy Lim Kam Sian

    (Binjiang College, Nanjing University of Information Science and Technology, Wuxi 214105, China
    Wuxi Institute of Technology, Nanjing University of Information Science & Technology, Wuxi 214105, China)

Abstract

In a warming climate, drought events are projected to increase in many regions across the world, which would have detrimental impacts on water resources for agriculture activity and human life. Thus, projecting drought changes, especially the frequency of future drought events, is very important for the African continent. This study investigates the future changes in drought events based on the France Centre National de Recherches Météorologiques (CNRM-CM6) model in the Coupled Model Intercomparison Project phase six (CMIP6) datasets for four shared socio-economic pathways (SSP): SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5; and three time slices: near future (2020–2039), mid-century (2050–2069), and end-of-century (2080–2099), relative to a historical baseline period (1995–2014). The interannual variability and trends of the self-calibrating Palmer Drought Severity Index (scPDSI) based on the Penman–Monteith methods for measuring potential evapotranspiration (PET) are used to estimate future droughts. The temporal analysis shows that the drought frequency, intensity, and affected area will increase throughout the 21st century. Among the scenarios, SSP3-7.0 and SSP5-8.5 project a larger upward trend in drought characteristics than SSP1-2.6 and SSP2-4.5. The spatial pattern shows drought frequency decreases in humid regions and increases in non-humid regions across Africa. For all SSP scenarios, the projected wetting trend per decade ranges from 0.05 to 0.25, while the drying trend per decade ranges from −0.05 to 0.25. A regional trend analysis revealed key differences in spatial pattern, with varied trend projections of wetter and drier conditions in humid and non-humid regions under all SSP scenarios. Drier conditions are expected to intensify in Southern Africa under all SSP scenarios but are projected to be more intense under either SSP3-7.0 and SSP5-8.5. In general, the projected wetter trends in humid areas may favor agricultural production and ecological conservation, and drier trends in non-humid regions may call for the possible adoption of tailor-made drought adaptation strategies and development programmes to minimize impacts.

Suggested Citation

  • Isaac Kwesi Nooni & Daniel Fiifi Tawia Hagan & Waheed Ullah & Jiao Lu & Shijie Li & Nana Agyemang Prempeh & Gnim Tchalim Gnitou & Kenny Thiam Choy Lim Kam Sian, 2022. "Projections of Drought Characteristics Based on the CNRM-CM6 Model over Africa," Agriculture, MDPI, vol. 12(4), pages 1-19, March.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:4:p:495-:d:784397
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    Keywords

    CNRM-CM6; PET; climate change; IPCC-AR6; SSP scenarios;
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