Heatwave attribution based on reliable operational weather forecasts

Nicholas J. Leach (), Christopher D. Roberts, Matthias Aengenheyster, Daniel Heathcote, Dann M. Mitchell, Vikki Thompson, Tim Palmer, Antje Weisheimer and Myles R. Allen
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Nicholas J. Leach: University of Oxford
Christopher D. Roberts: European Centre for Medium-Range Weather Forecasts
Matthias Aengenheyster: University of Oxford
Daniel Heathcote: University of Oxford
Dann M. Mitchell: University of Bristol
Vikki Thompson: University of Bristol
Tim Palmer: University of Oxford
Antje Weisheimer: University of Oxford
Myles R. Allen: University of Oxford

Nature Communications, 2024, vol. 15, issue 1, 1-11

Abstract: Abstract The 2021 Pacific Northwest heatwave was so extreme as to challenge conventional statistical and climate-model-based approaches to extreme weather attribution. However, state-of-the-art operational weather prediction systems are demonstrably able to simulate the detailed physics of the heatwave. Here, we leverage these systems to show that human influence on the climate made this event at least 8 [2–50] times more likely. At the current rate of global warming, the likelihood of such an event is doubling every 20 [10–50] years. Given the multi-decade lower-bound return-time implied by the length of the historical record, this rate of change in likelihood is highly relevant for decision makers. Further, forecast-based attribution can synthesise the conditional event-specific storyline and unconditional event-class probabilistic approaches to attribution. If developed as a routine service in forecasting centres, it could provide reliable estimates of human influence on extreme weather risk, which is critical to supporting effective adaptation planning.

Date: 2024
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DOI: 10.1038/s41467-024-48280-7

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