Spatially adaptive post-processing of ensemble forecasts for temperature - Scheuerer, Michael; Büermann, Luca (Journal of the Royal Statistical Society. Series C, Applied statistics, 2014)
We propose a statistical post-processing method that yields locally calibrated probabilistic forecasts of temperature, based on the output of an ensemble prediction system. It represents the mean of the predictive distributions as a sum of short-term averages of local temperatures and ensemble prediction system driven terms. For the spatial interpolation of temperature averages and local forecast uncertainty parameters we use an intrinsic Gaussian random-field model with a location-dependent nugget effect that accounts for small-scale variability. Applied to the COSMO-DE ensemble, our method yields locally calibrated and sharp probabilistic forecasts and compares favourably with other approaches.