Empirical statistical downscaling with EPISODES in Austria

EPISODES is an empirical statistical downscaling (ESD) method, which has been initiated and developed by the German Weather Service (DWD). Having resulted in good evaluation scores for Germany, the methodology it is also set-up and adapted for Austria at ZAMG and, hence, for an alpine territory with complex topography.

ESD methods are sparing regarding computational costs compared to dynamical downscaling models. Due to this advantage ESD can be applied in a short time frame and in a demand-based manner. It enables, e.g., processing ensembles of downscaled climate projections, which can be assessed either as stand-alone data set or to enhance ensembles based on dynamical methods. This helps improve the robustness of climatological statements for the purpose of climate impact research.

Preconditions for achieving high-quality results by EPISODES are long-term, temporally consistent observation data sets and a best possible realistic reproduction of relevant large-scale weather conditions by the GCMs. Given these requirements, EPISODES produces high-quality multivariate and spatially/temporally consistent synthetic time series on regular grids or station locations. The output is provided for daily time steps and, at maximum, for the resolution of underlying observation data.

The EPISODES method consists on mainly two steps: At first stage, univariate time series are produced on a coarse grid based on the analogue method and linear regression. It means that coarse scale atmospheric conditions of each single day as described by the GCM projections are assigned to a selection of at most similar daily weather situations of the observed past. From this selection new values are determined by linear regression for each day.

The second stage of the EPISODES method works like a weather generator. Short-term anomalies based on first stage results, on the one hand, and on observations, on the other hand, are matched selecting the most similar day for all used meteorological parameters and coarse grid points at the same time. Together with the high-resolution climatological background of observations and the climatological shift as described by GCM projections the short-term variability are combined to synthetic daily values for each target grid point. This approach provides the desired characteristics of the downscaled climate projections such as multivariability and spatio-temporal consistency.

Recent EPISODES evaluation results for daily precipitation and daily mean temperature are presented for the Austrian federal territory. Performance of the EPISODES ensemble will also be discussed in relation to existing ensembles based on dynamical methods which have already been widely used in climate impact studies in Austria: EURO-CORDEX and ÖKS15.