This study enhances wind energy resource assessment under climate change by applying a robust bias correction framework to NEX-GDDP-CMIP6 projections for ten wind farm stations across Africa at 150-m hub heights. We assessed wind speed, wind power density, variability, and capacity factor under SSP2-4.5 and SSP5-8.5 scenarios for 2041–2070 and 2071–2100. Model performance shows regional disparities, with higher accuracy in East and Southern Africa (correlations 0.86–0.96) than in North and West Africa (correlations 0.63–0.73). Baseline analysis highlights North Africa's Sahara-Sahel and East Africa's highlands as high-potential regions (6–8 m/s, 100–300 W/m2), while Central and West Africa exhibit lower resources (1–3 m/s, <50 W/m2). Weibull-based bias correction reduces errors to near-zero (±0.017 m/s), achieving correlations above 0.7 and up to 70 % reduction in root mean square error (RMSE), with East African stations showing the greatest error reduction. Future projections indicate significant regional and seasonal variability. East African coastal stations (Lamu, Zanzibar) and selected West African sites project capacity factor increases over 30 % and wind power density gains of 80–90 % under SSP5-8.5, while North African stations face minimal or negative changes. Seasonal trends show West Africa's winter gains (+23.5 % wind speed, +90 % power density) contrasted by autumn declines, and North Africa's summer improvements offset by winter reductions. Wind speed variability decreases at some stations, aiding grid stability, but increases at others, requiring advanced forecasting. Exceptional winter capacity factor gains (>100 %) highlight East and West African potential. This study provides guidance for wind farm site selection, supporting Africa's renewable energy transition.
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