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

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 Nina 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.

Automated summary

Skilful predictions of near-term climate extremes are crucial for a resilient society. However, current methods of analysing seasonal forecasts are not effective in identifying rare and impactful extremes. This article argues that a strong summer La Nina provided an opportunity to issue a more confident forecast for extreme rainfall. The authors emphasize the need for improved tools and routine monitoring of forecasts to identify and issue trustworthy early warnings for regional climate extremes.