Blocking events are an important cause of extreme weather, especially long-lasting blocking events that trap weather systems in place. The duration of blocking events is, however, underestimated in climate models. Explainable Artificial Intelligence are a class of data analysis methods that can help identify physical causes of prolonged blocking events and diagnose model deficiencies. We...
Multistability is a frequent feature in the climate system and leads to key challenges for our ability to predict how the system will respond to transient perturbations of the dynamics. As a particular example, the stably stratified atmospheric boundary layer is known to exhibit distinct flow regimes that are believed to be metastable. Numerical weather prediction and climate models encounter...
We present a spatial Bayesian hierarchical model for postprocessing surface maximum wind gusts in COSMO-REA6. Our approach uses a non-stationary extreme value distribution (GEV) at the top level, with parameters that vary based on linear regressions of predictor variables from the COSMO-REA6 reanalysis. To capture spatial patterns in surface extreme wind gust behavior, the regression...
