Amplification of compound hot-dry extremes and associated population exposure over East Africa

Brian Odhiambo Ayugi, Charles Onyutha, Kenny Thiam Choy Lim Kam Sian, Huanhuan Zhu, Hassen Babousmail and Eun-Sung Chung ()
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Brian Odhiambo Ayugi: Seoul National University of Science and Technology
Charles Onyutha: Kyambogo University
Kenny Thiam Choy Lim Kam Sian: Wuxi University
Huanhuan Zhu: Wuxi University
Hassen Babousmail: Wuxi University
Eun-Sung Chung: Seoul National University of Science and Technology

Climatic Change, 2024, vol. 177, issue 9, No 13, 23 pages

Abstract: Abstract Quantifying the vulnerability of population to multi-faceted climate change impacts on human well-being remains an urgent task. Recently, weather and climate extremes have evolved into bivariate events that heighten climate risks in unexpected ways. To investigate the potential impacts of climate extremes, this study analyzes the frequency, magnitude, and severity of observed and future compound hot-dry extremes (CHDEs) over East Africa. The CHDE events were computed from the observed precipitation and maximum temperature data of the Climatic Research Unit gridded Timeseries version five (CRU TS4.05) and outputs of climate models of Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, this study quantifies the population exposure to CHDE events based on future population density datasets under two Shared Socioeconomic Pathways (SSPs). Using the 75th/90th and 25th/10th percentile of precipitation and temperature as threshold to define severe and moderate events, the results show that the East African region experienced multiple moderate and severe CHDE events during the last twenty years. Based on a weighted multi-model ensemble, projections indicate that under the SSP5-8.5 scenario, the frequency of moderate CHDE will double, and severe CHDE will be 1.6 times that of baseline (i.e., an increase of 60%). Strong evidence of an upward trajectory is noted after 2080 for both moderate and severe CHDE. Southern parts of Tanzania and northeastern Kenya are likely to be the most affected, with all models agreeing (signal-to-noise ratio, SNR > 1), indicating a likely higher magnitude of change during the mid- and far-future. Consequentially, population exposure to these impacts is projected to increase by up to 60% for moderate and severe CHDEs in parts of southern Tanzania. Attribution analysis highlights that climate change is the primary driver of CHDE exposure under the two emission pathways. The current study underscores the urgent need to reduce CO2 emissions to prevent exceeding global warming thresholds and to develop regional adaptation measures.

Keywords: Compound extremes; Climate change; CMIP6 GCMs; CRU; Precipitation; Maximum temperature (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10584-024-03802-6

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