Regional Risk of Convective Extreme Weather Events: User-oriented Concepts for Trend Assessment and Adaptation


Extreme convective events such as severe storms, hail or heavy precipitation endanger both human life and considerable amounts of material assets. For Germany alone, the  MunichRe reports damages of 1 to 2 Billion € each year. Despite this there are gaps in the understanding of economic and climatological risk, especially lacking are estimations for the the risk of a changing climate in the near future up to 2030.

Sectors of the economy that are directly influenced by weather, such as insurances, air traffic, and water management but also weather services itself developing their own storm warnings, have a pressing need for regional risk assessments and methods to predict extreme convective events. The adjustment of structure and building standards to trends for extreme weather is also of great importance to the economy. Of the possible benefiters of this project the Munich Airport and the Munich Re have been exemplarily chosen.

In close cooperation with these users, RegioExAKT looks into the hydro-meteorological and insurance relevant extreme events caused by regional climate change, keeping the time dependent development of the vulnerability in mind. This enables insurances and construction companies to adapt to the changing climate conditions.

Other then meteorological models (global and regional climate, weather forecasts) and socio-economic approaches, highly developed remote sensing and in situ observation methods are used to answer the questions. The informing of other potential users, the DWD, the public and the decision makers will ensure the dissemination and realization of the project.


FUB specific contribution:


The core task of the Freie Universität Berlin in this project is to estimate the probability of occurrence and intensity of potential extreme events in relation to current conditions and anthropogenic climate change.  The possibility of using the newly developed energy index (DSI) to predict extreme events will be looked into based on the data of observed extreme events and the large scale meteorological situation at the time of occurrence. To do so, typical pre-event conditions and specific weather situations are extracted from the observed data and statistically linked to the intensity and frequency of the events. The results are then applied to climate simulations. With the aid of the DSI as a local indicator for extreme events and their  pre-event conditions, a prediction algorithm shall be developed to improve the forecast quality of meteorological extreme events for southern Germany.



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