DECADAL-EPI-DE v2022.01

10.5676/DWD/DECADAL-EPI-DE_V2022.01

Decadal Climate Predictions for Germany (EPISODES) version 2022.01 Decadal Climate Predictions (MPI-ESM-LR) downscaled over Germany using the empirical-statistical downscaling method DWD-EPISODES version 2022 Hoff, Amelie; Pasternack, Alexander; Wehring, Sabrina; Pankatz, Klaus; Lorenz, Philip; Paxian, Andreas; Kreienkamp, Frank; Früh, Barbara
Decadal Climate Predictions for Germany (EPISODES) version 2022.01 https://doi.org/10.5676/DWD/DECADAL-EPI-DE_V2022.01
Hoff, Amelie; Pasternack, Alexander; Wehring, Sabrina; Pankatz, Klaus; Lorenz, Philip; Paxian, Andreas; Kreienkamp, Frank; Früh, Barbara
Deutscher Wetterdienst (DWD, http://www.dwd.de/EN/Home/home_node.html) 2023 The decadal climate predictions for Germany are performed with the Max-Planck-Institute Earth System Model with Low-Resolution (MPI-ESM-LR) and downscaled over Germany using the empirical-statistical downscaling method DWD-EPISODES version 2022. The decadal 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 reanalysis COSMO-REA6 for Europe (https://reanalysis.meteo.uni-bonn.de/?COSMO-REA6). The data set HYRAS covers the time period 1951 to 2020 with following versions of variables: HYRAS-TAS v5.0 (for tas), HYRAS-TMAX v5.0 (for tasmax), HYRAS-TMIN v5.0 (for tasmin), HYRAS-PRE v5.0 (for pr), HYRAS-HURS v5.0 (for hurs). The data of COSMO-REA6 cover the time period 1995 to August 2019 with following variables: mean sea level pressure (for psl), global radiation (for rsds), 10m 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. Please consider that the daily data on this ESGF node are not recalibrated and might differ from the statistically postprocessed (recalibrated) yearly decadal prediction data on the website cited above. V2022.01 2023 to present Daily Yearly DE-0075x005 (Germany on a regular 0.075° x 0.05° grid, approx. 5 km x 5 km) NetCDF4
approx. 120 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 https://www.dwd.de/EN/service/terms/terms.html Zentrales Klimabüro
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