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<p>Changes in rainfall and temperature influence community livelihoods by affecting agriculture, water availability, health, and overall economic stability. This study investigates the spatial patterns of observed seasonal mean rainfall and temperatures for the period 1983–2021 and the projected seasonal changes in temperatures and rainfall over Rwanda using CORDEX-CORE multi-model ensemble simulations under the RCP2.6 and the RCP8.5 scenarios for 2026–2060 and 2066–2100 periods relative to 1986–2020. For observational period, the analysis reveals a heterogeneous spatial distribution of rainfall across all seasons, with higher rainfall in the northern and southwestern highlands and lower amounts in the eastern lowlands. Maximum temperatures are generally higher in the eastern and southwestern lowlands, while minimum temperatures are lowest in the northern and western highlands. Significant reductions in rainfall are projected for MAM ([-1, 49, 59] mm) and JJA ([-62, 12] mm), while a significant increase is projected for SOND ([173, 234] mm) under both scenarios. A significant increase in Tx under RCP2.6 is expected for JF (0.38&#xa0;°C) and for SOND (0.35&#xa0;°C) during 2026–2066. Under RCP8.5, Tx is projected to increase for both periods during JF ([1.02, 3.20] °C), MAM ([0.94, 3.02] °C), and SOND ([0.86, 2.68] °C). For JJA, Tx is anticipated to increase under both emission scenarios for both periods ([1.87, 4.54] °C). Minimum temperature is projected to statistically increase across all seasons under both emission scenarios and periods, with a higher magnitude under RCP8.5 than RCP2.6. Tn is projected to increase for JF ([1.84, 5.16] °C), MAM ([1.99, 4.96] °C), JJA ([1.28, 5.12] °C), and SOND ([2.35, 4.82] °C). These expected changes suggest significant impacts for water resources, agriculture, ecosystem management, and energy, highlighting the need for adaptation strategies to enhance climate resilience in Rwanda’s key socio-economic sectors.</p>

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Projected change in precipitation and temperatures under a changing climate in Rwanda

  • 期刊论文

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  • 发表日期：

    2026年1月27日

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  • Ndakize Joseph Sebaziga

摘要

Changes in rainfall and temperature influence community livelihoods by affecting agriculture, water availability, health, and overall economic stability. This study investigates the spatial patterns of observed seasonal mean rainfall and temperatures for the period 1983–2021 and the projected seasonal changes in temperatures and rainfall over Rwanda using CORDEX-CORE multi-model ensemble simulations under the RCP2.6 and the RCP8.5 scenarios for 2026–2060 and 2066–2100 periods relative to 1986–2020. For observational period, the analysis reveals a heterogeneous spatial distribution of rainfall across all seasons, with higher rainfall in the northern and southwestern highlands and lower amounts in the eastern lowlands. Maximum temperatures are generally higher in the eastern and southwestern lowlands, while minimum temperatures are lowest in the northern and western highlands. Significant reductions in rainfall are projected for MAM ([-1, 49, 59] mm) and JJA ([-62, 12] mm), while a significant increase is projected for SOND ([173, 234] mm) under both scenarios. A significant increase in Tx under RCP2.6 is expected for JF (0.38 °C) and for SOND (0.35 °C) during 2026–2066. Under RCP8.5, Tx is projected to increase for both periods during JF ([1.02, 3.20] °C), MAM ([0.94, 3.02] °C), and SOND ([0.86, 2.68] °C). For JJA, Tx is anticipated to increase under both emission scenarios for both periods ([1.87, 4.54] °C). Minimum temperature is projected to statistically increase across all seasons under both emission scenarios and periods, with a higher magnitude under RCP8.5 than RCP2.6. Tn is projected to increase for JF ([1.84, 5.16] °C), MAM ([1.99, 4.96] °C), JJA ([1.28, 5.12] °C), and SOND ([2.35, 4.82] °C). These expected changes suggest significant impacts for water resources, agriculture, ecosystem management, and energy, highlighting the need for adaptation strategies to enhance climate resilience in Rwanda’s key socio-economic sectors.