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  High-resolution climate projection data for climate risk assessments in Rwanda

Meteo Rwanda, Potsdam Institute for Climate Impact Research (2026): High-resolution climate projection data for climate risk assessments in Rwanda, (Scientific report), Kigali, Rwanda, 29 p.
https://doi.org/10.48485/pik.2026.21

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HiClAPReportRevisedFinal03072026_3.pdf (???ENUM_CONTENTCATEGORY_publisher-version???), 8???ViewItemMedium_lblFileSizeMB???
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HiClAPReportRevisedFinal03072026_3.pdf
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 ???ViewItemFull_lblCreators???:
Meteo Rwanda, ???ENUM_CREATORROLE_AUTHOR???
Potsdam Institute for Climate Impact Research, ???ENUM_CREATORROLE_AUTHOR???
Undorf, Sabine1, ???ENUM_CREATORROLE_CONTRIBUTOR???                 
Iyakaremye, Vedaste2, ???ENUM_CREATORROLE_CONTRIBUTOR???
von Loeben, Sophie Charlotte1, ???ENUM_CREATORROLE_CONTRIBUTOR???           
Kazora, Jonah2, ???ENUM_CREATORROLE_CONTRIBUTOR???
Maniraguha, Fidele2, ???ENUM_CREATORROLE_CONTRIBUTOR???
Musanganire, Alphonsine2, ???ENUM_CREATORROLE_CONTRIBUTOR???
Gleixner, Stephanie1, ???ENUM_CREATORROLE_CONTRIBUTOR???           
Menz, Christoph1, ???ENUM_CREATORROLE_CONTRIBUTOR???                 
Erl, Maria1, ???ENUM_CREATORROLE_CONTRIBUTOR???           
Gornott, Christoph1, ???ENUM_CREATORROLE_CONTRIBUTOR???                 
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1Potsdam Institute for Climate Impact Research, ou_persistent13              
2Meteo Rwanda, ou_persistent22              

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 ???ViewItemFull_lblAbstract???: Rwanda's steep elevation and complex terrain create strong local climatic contrasts that the coarse-resolution global climate models used in most existing studies cannot capture, limiting their value for adaptation planning. This report addresses that gap by applying a topographically informed, mechanistic downscaling method (CHELSA) to bias-corrected CMIP6 model data from nine global climate models, producing climate projections at 1km resolution for Rwanda under three SSP scenarios (SSP1-2.6, SSP3-7.0, SSP5-8.5) across three future periods (2030, 2055, 2080). All scenarios show substantial warming, with temperature extremes increasing faster than means and warming patterns spatially homogeneous across the country. Total annual precipitation is projected to increase, particularly in the September–January season, with a significant rise in heavy-precipitation days under medium- and high-emissions scenarios. Precipitation changes show much greater spatial variability than temperature. Meteorological drought trends remain statistically inconclusive, and comparisons with national observations suggest the models likely underestimate absolute drought risk. The report demonstrates how high-resolution data can inform localized climate risk assessments and recommends extending this approach to sectoral impact studies.

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???ViewItemFull_lblLanguages???: eng - English
 ???ViewItemFull_lblDates???: 2026-07-162026-07-16
 ???ViewItemFull_lblPublicationStatus???: ???ViewItem_lblPublicationState_published-in-print???
 ???ViewItemFull_lblPages???: 29
 ???ViewItemFull_lblPublishingInfo???: Kigali, Rwanda
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_DOI???: 10.48485/pik.2026.21
???ENUM_IDENTIFIERTYPE_PIKDOMAIN???: RD2 - Climate Resilience
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD2 - Climate Resilience
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???ViewItemFull_lblSourceTitle???: Scientific report
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