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compound Climate Extremes in North America and Europe: from dynamics to predictability

Periodic Reporting for period 1 - CENAE (compound Climate Extremes in North America and Europe: from dynamics to predictability)

Okres sprawozdawczy: 2021-03-01 do 2022-08-31

Extreme climate events in a changing climate are one of the most challenging problems facing society. Indeed, the World Climate Research Programme and the European Commission have both stressed the need to further our knowledge of current and future climate extremes. The EU-funded CENÆ project will shed light on how different climate extremes (cold spells, heavy rains and strong winds) interact and co-occur, leading to larger socioeconomic impacts than the sum of their individual components. The project will also focus on the predictability aspect of these extremes. The multivariate nature and inherent rarity of co-occurring extremes poses a formidable challenge to current analysis techniques, requiring a combination of different disciplines to attain the project's goals.
The project thus far has been chiefly focussing identifying the physical processes leading to co-occurring climate extremes in North America and Europe, computing co-occurrence statistics of the extremes and, more recently, looking at statistical, data-driven models for predictability of the extremes being studied. Project members have presented their results as scientific publications, at scientific meetings, at events open to the general public, in schools and in the media.
Several knowledge gaps hinder our understanding of co-occurring climate extremes. First of all, we lack a detailed understanding of the drivers and characteristics of the cold spell, heavy rain and strong wind extremes studied in CENÆ. The literature investigating present-day European wet and windy extremes has mostly addressed the two separately. The co-occurrence of extremes on both sides of the North Atlantic has received even less attention. Second, some analysis approaches which have been developed in applied mathematics to study extremes in complex systems have yet to the applied to the study of co-occurring climate extremes. We are also yet to leverage machine learning for studying the predictability of co-occurring extremes. Finally, little is known about how climate change may affect the occurrence and predictability of co-occurring extremes.
CENÆ will address these four knowledge gaps. The results thus far have focussed on the first point, and we are starting to touch the second and third points. By the end of the project we expect to have made progress on all four of these knowledge gaps, leading to a step-change in our understanding of the drivers and predictability of co-occurring climate extremes, including how climate change may affect these two aspects.

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