Extreme event attribution using km-scale simulations reveals the pronounced role of climate change in the Durban floods
Abstract The Durban floods of 11–12 April 2022 is the worst flood disaster in South Africa’s history and raised questions about the role of climate change in the event. Meso-scale dynamics, involving processes that cannot be resolved at the spatial resolutions of current global climate models, playe...
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Communications Earth & Environment |
| Online Access: | https://doi.org/10.1038/s43247-025-02460-5 |
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| Summary: | Abstract The Durban floods of 11–12 April 2022 is the worst flood disaster in South Africa’s history and raised questions about the role of climate change in the event. Meso-scale dynamics, involving processes that cannot be resolved at the spatial resolutions of current global climate models, played an important role in the heavy falls of rain. Here we report on the development of a convection-permitting conditional extreme event attribution modelling system, well-suited to explore the role of climate change in meso- and convective-scale extreme weather events. The African-based attribution system makes use of a computationally-efficient variable-resolution atmospheric model and runs on a local high-performance computer in South Africa. Similar systems can potentially be rolled out across the Global South (and North). The system relies on a km-scale perturbed-physics ensemble to describe the simulation/structural uncertainty associated with an extreme weather event in an anthropogenically-warmed world, compared to counterfactual cooler worlds where the effects of anthropogenic forcing are (partially) removed. Simulations reveal a pronounced role of climate change in the Durban floods. Average rainfall in the Durban region is simulated to have been at least 40% higher during the two days of the flood, relative to rainfall in a counterfactual cooler world. |
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| ISSN: | 2662-4435 |