Research Group Climate Extremes
Weather and climate extremes and their physical and socioeconomic impacts challenge society and sciences in many ways. With increasing global warming many weather and climate extremes will become more frequent and intense. The Climate Extremes group in the Research Unit for Sustainability and Climate Risks at the University of Hamburg is doing research on a variety of aspects related to understanding and modeling weather and climate extremes as well as their impacts and associated risks.
We use large ensembles of regional and global climate models as well as simulations from high-resolution (km-scale) climate models and dedicated climate prediction simulations to analyze the occurrence, predictability, and distribution of weather and climate extremes. Such extremes include extreme temperatures and precipitation, heatwaves and cold spells, droughts, and storms. We evaluate the performance of the models under current climate conditions using observational and reanalysis datasets, and we study changes in weather and climate extremes in different future climate scenarios. Our data analysis techniques include indices for extreme events, extreme value statistics as well as spatial and multi-variate statistics (including compound events).
We are involved in many projects that investigate the impacts and risks of weather and climate extremes on society, for instance related to heat and cold extremes impacting human health, physical risk for the financial sector, extreme precipitation and temperatures affecting urban areas or climate extremes affecting forestry and agriculture. To explore these impacts, we employ physically based and statistical impact models. Furthermore, we study the socioeconomic consequences of weather and climate extremes using econometric and macro-economic model approaches. Our work is also contributing to a better understanding of weather and climate extremes in the context of multi-hazard and systemic risks and how they interact with the sustainable development goals. We aim on improving approaches to analyze and model extreme events in coupled human-environment systems.