CE:LLO

Abstract:
Compound events (CEs) are major extreme events that result from the joint occurrence of underlying contributing events. Typical examples are drought in conjunction with a heatwave, and a storm surge coinciding with heavy precipitation causing river flooding. To fully describe the dependence structure of CEs and to correctly assess their severity, multivariate statistical models are required. To understand the physical processes underlying the structure of CEs, the inclusion of physical predictors is necessary. These also provide insight into the temporal variability of CEs and their dependence structure. So far, no multivariate statistical models including predictors to describe CEs have been formulated. In the CE:LLO project, we will build upon the experience from its predecessor PLEIADES. Based on pair copula constructions, we will develop a multivariate statistical model with predictors to describe the structure of CEs and their temporal variability. The model will be applicable to a wide class of CEs. In CE:LLO we will apply the model to the drought and flood examples mentioned above. For CEs in the observational record we will analyse the severity, their variability and underlying physical mechanisms. The representation of CEs by dynamically downscaled global climate models will be evaluated, and potential future changes in CEs will be analysed.