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

Earth Sciences

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

N. Dunstone, D. M. Smith, et al.

This groundbreaking research conducted by Nick Dunstone, Doug M. Smith, Steven C. Hardiman, Paul Davies, Sarah Ineson, Shipra Jain, Chris Kent, Gill Martin, and Adam A. Scaife reveals how current forecasting methods fall short in predicting rare and impactful climate extremes. Learn how they propose enhancing forecast confidence for extreme rainfall events, such as the 2022 Pakistan floods, to better prepare society for future climate challenges.

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Playback language: English
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. The 2022 Pakistan floods, an extreme event, were widely predicted by seasonal forecasts, yet standard tercile probability maps failed to convey the magnitude. This paper argues that a strong summer La Niña created a window of opportunity for a much more confident extreme rainfall forecast than average skill estimates suggest. The authors explore methods for building forecast confidence, including physical understanding of dynamical mechanisms, perturbation experiments, and empirical relationships. They emphasize the need for improved tools and routine monitoring of forecasts to identify regional climate extremes and utilize these windows of opportunity for trustworthy early warnings.
Publisher
Nature Communications
Published On
Oct 17, 2023
Authors
Nick Dunstone, Doug M. Smith, Steven C. Hardiman, Paul Davies, Sarah Ineson, Shipra Jain, Chris Kent, Gill Martin, Adam A. Scaife
Tags
climate extremes
seasonal forecasts
La Niña
extreme rainfall
Pakistan floods
forecast confidence
early warnings
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