ALBERT

Description: Das GERICS hat für alle 401 deutschen Landkreise, Kreise, Regionalkreise und kreisfreien Städte einen Klimaausblick veröffentlicht. https://www.gerics.de/products_and_publications/fact_sheets/landkreise/index.php.de Jeder Bericht fasst die Ergebnisse für Klimakenngrößen wie z.B. Temperatur, Hitzetage, Trockentage oder Starkregentage auf wenigen Seiten zusammen. Die Ergebnisse zeigen die projizierten Entwicklungen der Klimakenngrößen im Verlauf des 21. Jahrhunderts für ein Szenario mit viel Klimaschutz, ein Szenario mit mäßigem Klimaschutz und ein Szenario ohne wirksamen Klimaschutz. Datengrundlage sind 85 EURO-CORDEX-Simulationen, sowie der HYRAS-Datensatz des Deutschen Wetterdienstes. GERICS has published a climate report for each of the 401 German districts. https://www.gerics.de/products_and_publications/fact_sheets/landkreise/index.php.de Each report summarizes a selection of climate indices like temperature, hot days, dry days or days with heavy precipitation on a few pages. The results show the future development of these indices in the 21st century for three scenarios with strong, medium and weak climate protection, respectively. The data originates from 85 EURO-CORDEX simulations with regional climate models, and the HYRAS dataset of the German Weather Service.

Description: Model runs over Europe were conducted within the ESM project (www.esm-project.net/) for the Frontier Simulations supporting the water and matter fluxes from the European landmass to receiving water bodies (Baltic Sea, Atlantic Ocean and the Mediterranean Sea). Daily discharge from the mesoscale Hydrologic Model (mHM; Samaniego et al., 2010; Kumar et al., 2013; Code version: git.ufz.de/mhm/mhm git version: 35b5cb1) operated at the spatial resolution of 1/16deg for the simulation period from 1.1.1960-31.12.2019 across the European domain (Longitude -11 to 41 Latitude 35 to 72). Model runs were conducted within the ESM project (www.esm-project.net/) for the Frontier Simulations supporting the water and matter fluxes from the European landmass to receiving water bodies (Baltic Sea, Atlantic Ocean and Mediterranian Sea). Special consideration was given to the coastal cells by filtering out those (bordering) grid cells that do not have 100% landmass (i.e., cells with a significant proportion of water bodies/sea/ocean coverage). Meteorological forcing data are based on the E-OBS v21e (daily precipitation, temperature, Hofstra et al. 2009), potential evapotranspiration is based on the Hargreaves-Samani method. Soil characteristics are obtained from the global SoilGrids database (Hengtl et al. 2014; the land cover is derived from the Globcover_V2 (http://due.esrin.esa.int/page_globcover.php); geomorphological features are based on the GMTED2010 (Danielson et al., 2011). Model parameterization was constrained using the observed discharge time series from the GRDC stations (https://portal.grdc.bafg.de/), satisfying the following three conditions: gauge LAT〉48degN, area〉 5000km2, area 〈170000km2. Multi-basin calibration and validation were employed to check the consistency of model simulations following Rakovec et al., 2016 and Samaniego et al. 2019, as follows. Calibration objective function using KGE, DDS algorithm with 500 iterations, to account for uncertainty in the calibration process and the basin selections, 50 random initial conditions were randomly drawn sub-set of basins (N=6basins). The best parameter set in the cross-validations across 1201 basins was selected for the final run (ID: 542). A static 2D file of flow direction over Europe at the routing resolution 1/16deg. Internal upscaling to 1/16deg from the higher resolution (1/512deg) done within mHM (Code version: mesoscale Hydrologic Model (git.ufz.de/mhm/mhm git version: 35b5cb1). Special consideration was given to the coastal cells by filtering out those (bordering) grid cells that do not have 100% landmass (i.e., cells with a significant proportion of water bodies/sea/ocean coverage). Flow direction network (lat,lon) and routed runoff (time,lat,lon) at 1/16deg are provided as separate datasets.

Description: The data contains the emission variation simulations which build the lookup-tables for TransClim. Eleven emission regions are defined: Germany, Western Europe, Northern Europe, Eastern Europe, Southern Europe, China, India, Southeast Asia, Japan/South Korea, North America and South America. In each of these emission regions, the road traffic emissions of nitrogen oxide (NOx), volatile organic compounds (VOC) and carbon monooxide (CO) are varied and the resulting climate response is calculated with the global chemistry climate model EMAC.

Description: In order to explore the sensitivity of the climate impact of volcanic eruptions to eruption season and latitude, we simulate volcanic eruptions at different latitudes and in different seasons with the Max Planck Institute Earth System Model (MPI-ESM). We use the same configuration of the MPI-ESM model as used for the historical simulation of CMIP6. An initial run is performed firstly (PINArst). Then we perform 23 and 10 control runs without any volcanic eruption (PINAref and PINAwRef). Two groups of three different latitudinal volcanic eruptions in boreal summer and winter are simulated. We perform 10-member simulations for each eruption case. 9 Tg of total sulfur injection magnitude is prescribed. The eruption latitudes are set to be 0° for the equatorial eruptions (PINAeq and PINAwEQ) and 30° N and 30° S for the northern and southern hemispheric eruptions (PINAnh, PINAwNH, PINAsh and PINAwNH), respectively. For the summer eruptions, the date is set to be the same as the 1991 Pinatubo eruption on June 15, 1991; for the winter eruptions, the date is set to be December 15, 1991.

Description: The experiment includes the source code, compile and run scripts for ICON-ESM-V1.0 in the configuration “Ruby-0”, the initialization data for ICON-ESM-V1 in the configuration “Ruby-0”, and scripts, libraries, and input data used to produce figures.

Description: Regional climate simulations with the COSMO-CLM V. 5.0-CLM6 + TERRA_URB V. 2.0 model by KULeuven. Dynamical downscaling on the CORDEX EUR-11 domain and HRes domain over Belgium at convection-permitting scale. Model name: COSMO-CLM V. 5.0-CLM6 + TERRA_URB V. 2.0 Important reference: Wouters et al. 2016: https://dx.doi.org/10.5194/gmd-9-3027-2016 Resolution: RCM: 12.5km; LAM: 2.8 km Nr. vertical levels: 40 Time step (s): 80 (12.5 km); 20 (2.8 km) Important scheme: TERRA_URB Focal time series / severity index: Precipitation, UHI Host GCM: ERA-Interim / EC-EARTH Non-hydrostatic: yes

Description: Regional climate simulations with the MAR V 3.9 model by University of Liège. Dynamical downscaling on the CORDEX EUR-11 domain and HRes domain over Belgium at convection-permitting scale. Model name: MAR V. 3.9 Important reference: Wyard et al. 2017: https://dx.doi.org/10.1002/joc.4879 Resolution: RCM: 50 km and 12.5 km; LAM: 5 km Nr. vertical levels: 30 Time step (s): Important scheme: Snow variables Focal time series / severity index: Snowfall events and snowmelt events inducing floods Host GCM: ERA-Interim / various Non-hydrostatic: no

Description: Regional climate simulations with the ALARO-0 model by the Royal Meteorological Institute of Belgium and Ghent University (RMIB-UGent). Dynamical downscaling on the CORDEX EUR-11 domain and HRes domain over Belgium at convection-permitting scale. Model name: ALARO-0 Important reference: Giot et al. 2016: https://dx.doi.org/10.5194/gmd-9-1143-2016 Resolution: RCM: 50 km and 12.5 km; LAM: 4 km Nr. vertical levels: 46 Time step (s): 900 (50 km); 300 (12.5 km); 180 (4 km) Important scheme: 3MT Focal time series / severity index: (Sub-)hourly precipitation Host GCM: ERA-Interim / ARPEGE Non-hydrostatic: no

Description: MPI-ESM1-2-LR’s CMIP6 CovidMIP baseline simulations are based on simulations forced with CO2 emissions allowing interactive carbon cycle. The baseline simulations (ssp245-cov-baseline, publish here) is a reference to the CovidMIP simulations (ssp245-covid, ssp245-cov-fossil, ssp245-cov-strgreen, and ssp245-cov-modgreen, published under CMIP6 CovidMIP) to investigate the effects of COVID-19 induced emission reductions on global carbon cycle, climate change and feedbacks. As presented in Jones et al. (2021), the radiative and climate responses of MPI-ESM1-2-LR are within the range of multi-model simulation results. have 10 ensemble members of the simulation named from r1i1p1f99 to r10i1p1f99. Here f99 is used in the file name *r*i1p1f99* of all CovidMIP simulations because of the updated aerosol forcing (Fiedler et al. 2021). Fiedler, S.; Wyser, K.; Rogelj, J. & van Noije, T. (2021): Radiative effects of reduced aerosol emissions during the COVID-19 pandemic and the future recovery, Atmospheric Research, 264, 105866, https://doi.org/10.1016/j.atmosres.2021.105866 Jones, C. D., Hickman, J. E., Rumbold, S. T., Walton, J., Lamboll, R. D., Skeie, R. B., ... & Ziehn, T. (2021). The climate response to emissions reductions due to COVID‐19: Initial results from CovidMIP. Geophysical research letters, 48(8), e2020GL091883.

Description: The data contains the code of TransClim: written in Python 2.

Description: The LUCAS LUC future dataset consists of annual land use and land cover maps from 2016 to 2100. It is based on land cover data from the LANDMATE PFT dataset for the year 2015. The LANDMATE PFT consists of 16 plant functional types and non-vegetated classes that were converted from the ESA-CCI LC land cover data according to the method of Reinhart et al. (2021). The land use change information from the Land-Use Harmonization Data Set version 2 (LUH2 v2.1f, Hurtt et al. 2020) were imposed using the land use translator developed by Hoffmann et al. (2021). The projected land use change information was derived for different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) combinations used in the framework of the 6th phase of Coupled Modelling Intercomparison Project (CMIP6). For each year, a map is provided that contains 16 fields. Each field holds the fraction the respective plant functional types and non-vegetated classes in the total grid cell (0-1). The LUCAS LUC dataset was constructed within the HICSS project LANDMATE and the WCRP flagship pilot study LUCAS to meet the requirements of downscaling experiments within EURO-CORDEX. Plant functional types and non-vegetated classes: 1 - Tropical broadleaf evergreen trees 2 - Tropical deciduous trees 3 - Temperate broadleaf evergreen trees 4 - Temperate deciduous trees 5 - Evergreen coniferous trees 6 - Deciduous coniferous trees 7 - Coniferous shrubs 8 - Deciduous shrubs 9 - C3 grass 10 - C4 grass 11 - Tundra 12 - Swamp 13 - Non-irrigated crops 14 - Irrigated crops 15 - Urban 16 - Bare

Description: The LANDMATE PFT dataset provides a land cover map for Europe for the year 2015 in 0.1° (~10km) and 0.018° (~2km) resolution. The dataset is based on land cover data of the ESA Climate Change Initiative (ESA-CCI, native resolution: 300m) which is translated into 16 plant functional types (PFTs) and non-vegetated classes employing the cross-walking procedure introduced by Reinhart et al. (2021). The translation is done under consideration of the Holdridge Life Zones (HLZs), a system, that classifies land areas based on bioclimatic properties. Through the HLZs, regional distinction of the individual PFT distribution can be achieved. The land cover information is given as fractions per grid cell where each fraction represents the area covered by the respective land cover within each grid cell (0-1). The dataset is available in two different horizontal resolutions, 0.1° (~10km) and 0.018° (~2km), whereby the land cover information is resampled using a fractional approach to achieve the desired resolution. The LANDMATE PFT dataset was carefully developed and designed to meet the present and future requirements of regional climate models and is therefore recommended to be used for regional climate modeling over the European Continent. The LANDMATE PFT dataset (0.1° resolution) serves as basemap for the historical and future land use and land cover dataset LUCAS LUC developed by Hoffmann et al. (2021).

Description: The LUCAS LUC historical dataset consists of annual land use and land cover maps from 1950 to 2015. It is based on land cover data from the LANDMATE PFT dataset that was generated from ESA-CCI LC data. The ESA-CCI LC land cover classes are converted into 16 plant functional types and non-vegetated classes employing the method of Reinhart et al. (2021). The land use change information from the Land-Use Harmonization Data Set version 2 (LUH2 v2h, Hurtt et al. 2020) were imposed using the land use translator developed by Hoffmann et al. (2021). For each year, a map is provided that contains 16 fields. Each field holds the fraction the respective plant functional types and non-vegetated classes in the total grid cell (0-1). The LUCAS LUC dataset was constructed within the HICSS project LANDMATE and the WCRP flagship pilot study LUCAS to meet the requirements of downscaling experiments within EURO-CORDEX. Plant functional types and non-vegetated classes: 1 - Tropical broadleaf evergreen trees 2 - Tropical deciduous trees 3 - Temperate broadleaf evergreen trees 4 - Temperate deciduous trees 5 - Evergreen coniferous trees 6 - Deciduous coniferous trees 7 - Coniferous shrubs 8 - Deciduous shrubs 9 - C3 grass 10 - C4 grass 11 - Tundra 12 - Swamp 13 - Non-irrigated crops 14 - Irrigated crops 15 - Urban 16 - Bare

Description: Source code of the Max Planck Institute atmospheric general circulation model (ECHAM6) adopted to the project PalMod for the concurrent execution of radiative transfer on HPC-systems.

Description: Ensemble of MPI-ESM1-2-HR CMIP6 historical simulations with low-pass filtered solar and ozone variability (i.e., using a 33-years running-mean). The simulations are performed within the BMBF project "Solar contribution to climate change on decadal to centennial timescales" (SOLCHECK) of the "Role of the middle atmosphere in climate" (ROMIC II: https://romic2.iap-kborn.de/en/romic/strategy). The experimental setup is identical to the MPI-ESM1-2-HR historical CMIP6 simulations except for the solar and ozone variability.