Probabilistic forecasting and comparative model assessment, with focus on extreme events

Probabilistic forecasts allow to quantify the prediction uncertainty and are essential for informed decision making. We investigate how to evaluate probabilistic forecasts with an emphasis on extreme events, and how to make and evaluate forecasts based on simulation output in Bayesian forecasting models. Further, we propose new models and estimation approaches for statistical post-processing of ensemble forecasts in numerical weather prediction.