Simulating the West Pacific heatwave of 2021 with analog importance sampling

Flavio Pons (1) , Pascal Yiou (1) , Aglaé Jézéquel (2) , Gabriele Messori (3)

1 LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette]
2 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)
3 Uppsala Universitet [Uppsala]

During the summer of 2021, the North American Pacific Northwest was affected by an extreme heatwave that broke previous temperature records by several degrees and lasted almost two months after the initial peak. The event caused severe impacts on human life and ecosystems, and was associated with the superposition of concurrent extreme drivers, whose effects were amplified by climate change. We evaluate whether this record-breaking heatwave could be foreseen prior to its observation, and how climate change affects North American Pacific Northwest worst-case heatwave scenarios. To this purpose, we use a stochastic weather generator with empirical importance sampling. The generator simulates temperature sequences with realistic statistical properties using circulation analogues, chosen with an importance sampling based on the daily maximum temperature over the region that recorded the most extreme impacts. We show how some of the large-scale drivers of the event can be obtained form the circulation analogues, even if such information is not directly given to the stochastic weather generator.

Mots clés: extreme events; North American heatwave; stochastic weather generator; climate change

Domaines: Sciences de l'environnement

Flavio Pons, Pascal Yiou, Aglaé Jézéquel, Gabriele Messori. Simulating the West Pacific heatwave of 2021 with analog importance sampling. 2023. ⟨hal-03982838v1⟩