DOI for Scientific and Technical Data
Seasonal Climate Predictions for Germany (EPISODES) version 2022.01
Seasonal Climate Predictions (GCFS2.1) downscaled over Germany using the empirical-statistical downscaling method DWD-EPISODES version 2022
Hoff, Amelie; Pasternack, Alexander; Wehring, Sabrina; Fröhlich, Kristina; Lorenz, Philip; Paxian, Andreas; Kreienkamp, Frank; Früh, Barbara
Seasonal Climate Predictions for Germany (EPISODES) version 2022.01
https://doi.org/10.5676/DWD/SEASONAL-EPI-DE_V2022.01
Hoff, Amelie; Pasternack, Alexander; Wehring, Sabrina; Fröhlich, Kristina; Lorenz, Philip; Paxian, Andreas; Kreienkamp, Frank; Früh, Barbara
Deutscher Wetterdienst (DWD, http://www.dwd.de/EN/)
Hoff, Amelie; Pasternack, Alexander; Wehring, Sabrina; Fröhlich, Kristina; Lorenz, Philip; Paxian, Andreas; Kreienkamp, Frank; Früh, Barbara
The seasonal climate predictions for Germany are performed with the German Climate Forecast System GCFS2.1 and downscaled over Germany using the empirical-statistical downscaling method DWD-EPISODES version 2022. The seasonal climate predictions for Germany are available on a Germany-wide grid of about 5 km x 5 km (regular 0.075° x 0.05° grid). The following variables are included in the data set and are aggregated on a daily timescale: air temperature 2 m (daily mean: tas, daily maximum: tasmax, daily minimum: tasmin), precipitation (pr), relative humidity 2 m (hurs), global radiation (rsds), sea level pressure (psl), and wind speed 10 m (sfcWind).
The German Climate Forecast System is described by: Fröhlich, K., Dobrynin, M., Isensee, K. et al. (2021). The german climate forecast system: GCFS. Journal of Advances in Modeling Earth Systems, 13. DOI: 10.1029/2020MS002101. https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020MS002101.
The empirical-statistical downscaling method EPISODES is described by: Kreienkamp, F., Paxian, A., Früh, B. et al. (2019). Evaluation of the empirical-statistical downscaling method EPISODES. Clim Dyn, 52, 991-1026. DOI: 10.1007/s00382-018-4276-2. https://link.springer.com/article/10.1007/s00382-018-4276-2. Kreienkamp, F., Lorenz, P., Geiger, T. (2020). Statistically Downscaled CMIP6 Projections Show Stronger Warming for Germany. Atmosphere 11, 1245. DOI: 10.3390/atmos11111245. https://www.mdpi.com/2073-4433/11/11/1245. The latest EPISODES version 2022 contains minor bug fixes and technical updates for climate predictions.
To establish a statistical transfer function between regional and large scales, observations and reanalysis data are required. (For more details please have a look at the publications). The empirical-statistical downscaling method EPISODES version 2022 uses the regional-scale observation data set HYRAS for Germany (https://www.dwd.de/DE/leistungen/hyras/hyras.html) and the data set Testreferenzjahre TRY v1.0 for Germany (https://www.dwd.de/TRY). The data set HYRAS covers the time period 1951 to 2015 with following versions of variables: HYRAS-TAS v4.0 (for tas), HYRAS-TMAX v4.0 (for tasmax), HYRAS-TMIN v4.0 (for tasmin), HYRAS-PRE v3.0 (for pr), HYRAS-HURS v4.0 (for hurs). The data set TRY cover the time period 1995 to 2012 with following variables: sea level pressure (for psl), global radiation (for rsds) and wind speed (for sfcWind). For the analysis of the large-scale circulation the pressure level fields of temperature, geopotential and humidity from the NCEP/NCAR reanalysis for the period from 1948 to the present are used (https://www.psl.noaa.gov/data/gridded/data.ncep.reanalysis.html).
Climate predictions should only be used considering the respective climate prediction skills and the recommended time aggregations. If daily data are used for subsequent modelling the respective output should be aggregated following the recommended time aggregations. Please note that climate prediction skill generally increases if aggregated over time and space, and that the data only partly consider urban heat island effects. Please find figures of the climate prediction skills on a regular grid with 0.3° x 0.2° for Germany and further background information on climate predictions (e.g. on the recommended time aggregations) on https://www.dwd.de/climatepredictions.
V2022.01
September 2022 to present
Daily
Monthly
DE-0075x005 (Germany on a regular 0.075° x 0.05° grid, approx. 5 km x 5 km)
NetCDF4
approx. 7 MB per netcdf file
The Deutscher Wetterdienst (DWD) is the producer of the data. The General Terms and Conditions of Business and Delivery apply for services provided by DWD
http://www.dwd.de/EN/service/terms/terms.html
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