The project Long-term Variability and serial Clustering of Severe Thunderstorms in a changing climate (VarCluST) ) is a sub-project of the BMBF joint project ClimXtreme (Climate Change and Extreme Events). ClimXtreme is a 3-year project funded by the German Ministry of Education and Research (BMBF). Within the Module A Physics and Processes, the overall aims are to achieving a comprehensive view of meteorological extremes in Europe under climate change with a focus on the period from the 20th and 21st century. In particular, the project focusses on an improved assessment of extreme weather events in Central Europe in a changing climate. The assessment comprises changes in frequency, severity, spatial distribution and duration of past and future storms, high precipitation events, summer dry/hot periods and convective hazards. The aim is to understand and quantify the relevant causal mechanisms, and to validate these mechanisms in climate models in order to reduce uncertainty in future projections.
VarCluST aims to link severe convective storms (SCS) across Europe to large-scale atmospheric processes and to examine their contribution on the annual variability of SCS in past and future periods. Furthermore, it will be investigated how observed clusters of SCS on scales of days to weeks (denoted to as serial clustering) will be affected by large-scale mechanism. Knowledge on these mechanisms is still insufficient, but a prerequisite for estimating robust statements about long-term changes and trends in the SCS frequency.
Because SCS are not recorded comprehensively over longer periods, an event set will be developed for mesoscale sub-regions across Europe based on overshooting cloud top (OT) detections from satellite, frequently used as proxy for SCS. A relation has to be established between the OT events and an appropriate combination of meteorological parameters from reanalysis data, referred to as severe convective storm index (SCSI). This index is then applied to an ensemble of high-resolution climate models to estimate the long-term variability of convective predisposition. Subsequently, low-frequency variability modes of the climate system (e.g., teleconnection patterns) will be identified that are most decisive for the annual or multi-annual variability of convective activity. Additionally, specific weather regimes that are responsible for an accumulation of SCSI affecting the same sub-region on time scales of several days to weeks (serial clustering) will be assessed statistically. Finally, by using an ensemble of climate models in combination with the SCSI, it shall be quantified how the probability and persistency of SCSI- and SCS-related large-scale mechanisms on both time scales will change in the future.