Effects of Model Resolution and Statistical Postprocessing on Shelter Temperature

Shelter temperature and wind forecasts from numerical weather prediction models are subject to large sys-tematic errors. Kalman filtering and model output statistics (MOS) are commonly used postprocessing methods,but how effective are they in comparison with steadily increasing resolution of the forecast model? Observationsfrom over 1100 stations in central Europe are used to compare the different postprocessing methods and theinfluence of model resolution in complex and simple terrain, respectively. A 1-yr period with hourly, or at least3-hourly, data is used to achieve statistically meaningful results. Furthermore, the importance of real-timeobservations as MOS predictors and the effects of daily training of the MOS equations are studied.