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Internally driven variability of the Angola Low is the main source of uncertainty for the future changes in southern African precipitation

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Monerie, P.-A. orcid id iconORCID: https://orcid.org/0000-0002-5304-9559, Dieppois, B., Pohl, B. and Crétat, J. (2024) Internally driven variability of the Angola Low is the main source of uncertainty for the future changes in southern African precipitation. JGR Atmospheres, 129 (15). e2024JD041255. ISSN 2169-8996 doi: 10.1029/2024JD041255

Abstract/Summary

Variations in southern African precipitation have a major impact on local communities, increasing climate-related risks and affecting water and food security, as well as natural ecosystems. However, future changes in southern African precipitation are uncertain, with climate models showing a wide range of responses from near-term projections (2020-2040) to the end of the 21st century (2080-2100). Here, we assess the uncertainty in southern African precipitation change using five Ocean-Atmosphere General Circulation single model initial-condition large ensembles (30 to 50 ensemble members) and four emissions scenarios. We show that the main source of uncertainty in 21st Century projections of southern African precipitation is the internal climate variability. In addition, we find that differences between ensemble members in simulating future changes in the location of the Angola Low explain a large proportion (~60%) of the uncertainty in precipitation change. Together, the internal variations in the large-scale circulation over the Pacific Ocean and the Angola Low explain ~64% of the uncertainty in southern African precipitation change. We suggest that a better understanding of the future evolutions of the southern African precipitation may be achieved by understanding better the model’s ability to simulate the Angola Low and its effects on precipitation.

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/117481
Item Type Article
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher American Geophysical Union
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