Modul E - VESPA (Variability of Extremes, its causes and Predictability on decadal time scales in ensembles of climate simulations)
Decadal predictions of extreme events are of major relevance for users such as the (re-) insurance industry, energy producing companies and politics. Whereas seasonal forecasts are too short to be usable in long term planning of the users, centennial scenarios of climate change are often beyond the temporal range they are interested in. Decadal predictions of extremes would be a suitable basis for the development of adaptation strategies, even if these predictions are not deterministic but probabilistic.
VESPA aims to address the decadal forecast of the risk of extremes within MiKlip. The underlying methodological idea is that the probability of occurrence of extreme weather and climate events varies with relevant large scale conditions which are physically connected to the generation of the events. Understanding the processes influencing these relevant parts of climate variability and their role for the occurrence of extremes is thus contributing to an improved estimation of predictability of the events. In VESPA, special emphasis is laid on mid-latitude weather events like cyclones, winter storms, floods, thunderstorms and hail storms. A project target is to improve our knowledge and understanding of the decadal variability of frequency, intensity, and spatial distribution of extreme events, and the processes shaping these characteristics of extreme events occurrence.
Research line 1 (RL1) considers these processes starting from large scale features such as AMO, AMM and NAO. Part 1a aims to improve the decadal prediction practices through attribution of climate variability with respect to the Atlantic multidecadal oscillation (AMO). The focus of part 1b is on the detection and attribution of AMO- and PDO-related decadal-scale variability in tropical West and subtropical Northwest African precipitation. This will include decadal changes in the probability of extreme droughts and rainfall. The objective of part 1c is the variability of transport mechanisms of predictability from the tropics to extra tropics. In research line 2 (RL2) the project is completed by the assessment of effects on extremes by regional downscaling and the estimation of probabilistic information from post processing ensemble based information. It considers different downscaling techniques and spatial scales, focusing on the DSI (Dynamic state index) as a measure for local scale convective extreme event occurrence.
The knowledge and methodological approaches gained in VESPA will be incorporated into the MiKlip system, contributing to specialized features for the decadal prediction of extremes.