DYnamical drivers, predictability and trends of compound CLimate EXtremes ("DYCLEX")

Beskrivning

Compound climate extremes arise from interactions between multiple hazards and can produce amplified socioeconomic impacts. Understanding their drivers, predictability and long-term trends is therefore critical for assessing climate risks. However, these events are inherently multivariate and rare, posing significant challenges for current scientific approaches.

DYCLEX addresses these challenges by advancing a combined physical and statistical framework to analyse how large-scale atmospheric circulation influences compound extremes. The project focuses on the co-occurrence of temperature, precipitation and wind extremes across mid-latitudes, both locally and across regions.

Building on recent advances in atmospheric dynamics, dynamical systems theory, statistical analysis and machine learning, DYCLEX will develop methods to detect, quantify and interpret compound extremes and their links to circulation patterns. This enables the identification of new pathways for predictability and improved understanding of long-term trends. The resulting framework is designed to be flexible and applicable across a wide range of multivariate extremes in the Earth system.

The project aligns with international and European priorities on climate risk and adaptation, including the World Climate Research Programme and the EU strategy on climate adaptation, and contributes to advancing interdisciplinary approaches to climate extremes.