Downscaling and Evaluation of Seasonal Climate Data for the European Power Sector

Atmosphere

Barbara Früh¹  Jennifer Ostermöller¹  Kristina Fröhlich¹  Frank Kreienkamp²  Philip Lorenz² 

[1] Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany;Deutscher Wetterdienst, Güterfelder Damm 87-91, 14532 Stahnsdorf, Germany;

关键词: seasonal forecasts;    statistical downscaling;    Clim2Power;    renewable energy;    climate service;   

DOI  :  10.3390/atmos12030304

来源: DOAJ

【 摘 要 】

Within the Clim2Power project, two case studies focus on seasonal variations of the hydropower production in the river basins of the Danube (Germany/Austria) and the Douro (Portugal). To deliver spatially highly resolved climate data as an input for the hydrological models, the forecasts of the German Climate Forecast System (GCFS2.0) need to be downscaled. The statistical-empirical method EPISODES is used in this approach. It is adapted to the seasonal data, which consists of ensemble hindcasts and forecasts. Beside this, the two case study regions need specific configurations of the statistical model, providing appropriate predictors for the meteorological variables. This paper describes the technical details of the adaptation of the EPISODES method for the needs of Clim2Power. We analyse the hindcast skill of the downscaled hindcasts of all four seasons for the two variables near-surface (2 m) temperature and precipitation, and conclude that on the average the skill is conserved compared to the global model. This means that the seasonal information is available at a higher spatial resolution without losing skill. Furthermore, the output of the statistical downscaling is nearly bias-free, which is, beside the higher spatial resolution, an added value for the climate service.

【 授权许可】

Unknown