Coupled climate–land-use interactions modulate projected heatwave intensification across Africa

Africa faces intensifying heatwave hazards with far-reaching impacts on health, agriculture, and economic stability. Here, we assess changes in heatwave attributes, including duration, frequency, timing, and intensity, across nine African regions using 10 global numerical climate model simulations, with a multivariate bias-correction method applied to the model output. Under a high-end emissions scenario (SSP585), an upper limit projection, Western South Africa is projected to experience more than a 12-fold increase in heatwave duration and frequency. We apply Shapley Additive Explanations, an explainable artificial intelligence technique, to quantify how environmental drivers shape these changes, revealing strong regional contrasts arising from interactions among temperature, humidity, and land-surface modification. Temperature and humidity together account for more than 35% of projected increases in several regions, amplified by cropland and pasture expansion. A moderate mitigation scenario (SSP370) substantially reduces heatwave occurrence in West Africa, offering actionable guidance for land management and early-warning systems. Nonlinear climate and land-use interactions drive historical and future heatwave intensification across Africa, especially in Western South Africa, based on multivariate bias-correction and explainable AI applied to CMIP6 future projections.

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Publication Details

Journal
Communications Earth & Environment
Published
2026-01-07
DOI
https://doi.org/10.1038/s43247-025-03110-6
Citations
2
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
73.25
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article

Coupled climate–land-use interactions modulate projected heatwave intensification across Africa

Thierry N. Taguela, Oluwafemi E. Adeyeri, Christopher E. Ndehedehe, Sodiq Abayomi AJADİ et al.
2 citations
Communications Earth & Environment
Climate variability and models
73.25
article

Coupled climate–land-use interactions modulate projected heatwave intensification across Africa

Thierry N. Taguela, Oluwafemi E. Adeyeri, Christopher E. Ndehedehe, Sodiq Abayomi AJADİ, Tobi Eniolu Morakinyo, Kazeem A. Ishola, Akintomide A. Akinsanola, Kayode Ayegbusi, Bibian Ekot, Akinleye H. Folorunsho
article en
2 citations

Abstract

Africa faces intensifying heatwave hazards with far-reaching impacts on health, agriculture, and economic stability. Here, we assess changes in heatwave attributes, including duration, frequency, timing, and intensity, across nine African regions using 10 global numerical climate model simulations, with a multivariate bias-correction method applied to the model output. Under a high-end emissions scenario (SSP585), an upper limit projection, Western South Africa is projected to experience more than a 12-fold increase in heatwave duration and frequency. We apply Shapley Additive Explanations, an explainable artificial intelligence technique, to quantify how environmental drivers shape these changes, revealing strong regional contrasts arising from interactions among temperature, humidity, and land-surface modification. Temperature and humidity together account for more than 35% of projected increases in several regions, amplified by cropland and pasture expansion. A moderate mitigation scenario (SSP370) substantially reduces heatwave occurrence in West Africa, offering actionable guidance for land management and early-warning systems. Nonlinear climate and land-use interactions drive historical and future heatwave intensification across Africa, especially in Western South Africa, based on multivariate bias-correction and explainable AI applied to CMIP6 future projections.

Communications Earth & EnvironmentVol. 7(1)
Griffith University (AU), Australian National University (AU), National University of Ireland, Maynooth (IE), Baylor University (US), Central European University (AT), University of Illinois Chicago (US), Nigerian Meteorological Agency (NG), Texas A&M University (US)
Climate action
Openalex Percentile: Top 0%
Climate variability and models
73.25
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