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Description:
Over the last two decades the paradigm in hydrometeorological forecasting has shifted from deterministic to probabilistic. Weather prediction and hydrological models are run increasingly as ensemble forecasting systems, which provide a finite sample of forecast scenarios. Ensemble forecasts are often biased and lack calibration. Different statistical methods to correct for bias and miscalibration are developed and applied to real-world problems within the framework of this thesis.