Windows of opportunity for predicting seasonal climate extremes highlighted by the Pakistan floods of 2022

Nick Dunstone (), Doug M. Smith, Steven C. Hardiman, Paul Davies, Sarah Ineson, Shipra Jain, Chris Kent, Gill Martin and Adam A. Scaife
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Nick Dunstone: Met Office Hadley Centre
Doug M. Smith: Met Office Hadley Centre
Steven C. Hardiman: Met Office Hadley Centre
Paul Davies: Met Office Hadley Centre
Sarah Ineson: Met Office Hadley Centre
Shipra Jain: Centre for Climate Research Singapore (CCRS)
Chris Kent: Met Office Hadley Centre
Gill Martin: Met Office Hadley Centre
Adam A. Scaife: Met Office Hadley Centre

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: Abstract Skilful predictions of near-term climate extremes are key to a resilient society. However, standard methods of analysing seasonal forecasts are not optimised to identify the rarer and most impactful extremes. For example, standard tercile probability maps, used in real-time regional climate outlooks, failed to convey the extreme magnitude of summer 2022 Pakistan rainfall that was, in fact, widely predicted by seasonal forecasts. Here we argue that, in this case, a strong summer La Niña provided a window of opportunity to issue a much more confident forecast for extreme rainfall than average skill estimates would suggest. We explore ways of building forecast confidence via a physical understanding of dynamical mechanisms, perturbation experiments to isolate extreme drivers, and simple empirical relationships. We highlight the need for more detailed routine monitoring of forecasts, with improved tools, to identify regional climate extremes and hence utilise windows of opportunity to issue trustworthy and actionable early warnings.

Date: 2023
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DOI: 10.1038/s41467-023-42377-1

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