For the latest version of this description please visit https://www.tu.berlin/klima/forschung/regionalklimatologie/mitteleuropa/cer-v2 The Central Europe Refined analysis version 2 (CER v2) The Central Europe Refined analysis version 2 (CER) is an atmospheric data set based on the original CER v1 which was generated within the frameworks of the DFG-funded research unit "Urban Climate and Heat Stress in mid-latitude cities in view of climate change (UCaHS)" and the DFG-funded research project "Heat waves in Berlin, Germany - Urban climate modifications" . The current version (CER v2) covers the period 2000 - 2021 and provides gridded two-dimensional fields of a multitude of atmospheric variables. The setup of the original CER v1 was based on a sensitivity study concerning planetary boundary layer schemes and urban canopy models by Jänicke et al. (2017). This setup was adapted using the Kain-Fritsch cumulus and the Thompson microphysics scheme. Description The CER v2 data set is generated by dynamical downscaling using the Weather Research and Forecasting model (WRF) version 4.3.3. This version uses ERA5 reanalysis forcing data provided by ECMWF. The domain setup for the original CER v1 (Figure 1) consisted of two-way nested domains with 30 km, 10 km and 2 km grid spacing. These domains broadly cover Europe, Germany and the Berlin-Brandenburg area, respectively.CER v2 uses the 10 km and 2 km domain. Results for the CER v2 are currently only available for the 2 km domain. The simulation strategy is cascaded two-way nesting with daily re-initialization, adopted from the High Asia Refined analysis (HAR, Maussion et al., 2011, 2014). Each run starts at 12:00 UTC and contains 36 h, with the first 12 h as spin-up time. This strategy avoids the model from deviating too far from the forcing data and provides computational flexibility since daily runs are totally independent of each other and can be computed in parallel and in any sequence. Similar to HAR and HAR v2, the output of the simulations is post-processed into product-files: one single file per variable and per year at various temporal aggregation levels. A selection of variables is displayed in the table below. The data is currently available for the years 1990-2022. Time Span: 1980 - 2022 Spatial Resolution: 30 km (only CER v1), 10 km (only CER v1), 2 km Temporal Resolution: hourly (h), daily (d), monthly (m), yearly (y) Data Format: compressed NetCDF 4 Pressure Levels (hPa): 1000, 975, 925, 900, 850, 800, 700, 650, 600, 550, 500, 450, 400, 350, 300, 250, 200, 150, 100, 75 List of Selected Variables Variable Name Variable Description Type Unit albedo Albedo 2d - canwat canopy water 2d kg m-2 col_qliquid total column liquid water mixing ratio 2d kg kg-1 col_qsolid total column solid water mixing ratio 2d kg kg-1 col_qvapor total column vapor water mixing ratio 2d kg kg-1 emiss surface emissivity 2d - et Evapotranspiration 2d mm h-1 graupel grid scale graupel 2d mm h-1 grdflx Ground Heat Flux 2d W m-2 hail grid scale hail (stepwise) 2d mm h-1 hfx Upward Heat Flux at the Surface 2d W m-2 intliquidflux column integrated absolute liquid water flux 2d kg m-1 s-1 intsolidflux column integrated absolute solid water flux 2d kg m-1 s-1 intvaporflux column integrated absolute vapor water flux 2d kg m-1 s-1 lh Latent Heat Flux at the Surface 2d W m-2 lwdown Downward Long Wave Flux at Ground Surface 2d W m-2 lwup Upward Long Wave Flux at Ground Surface 2d W m-2 netrad Net Radiation at Ground Surface 2d W m-2 pblh PBL Height 2d m prcp Total Precipitation 2d mm h-1 prcp_c cumulus precipitation (stepwise) 2d mm h-1 prcp_fr frozen precipitation (stepwise) 2d mm h-1 prcp_nc grid scale precipitation (stepwise) 2d mm h-1 psfc SFC Pressure 2d Pa q2 Water Vapor Mixing Ratio at 2 m 2d kg kg-1 qfx upward moisture flux at the surface 2d km m-2 s-1 scld total column clouds 2d - scldfra Surface cloud fraction computed in a 50km radius FOV 2d - sfroff surface runoff 2d mm slp Sea Level Pressure 2d hPa snow snow water equivalent 2d kg m-2 snowfall Grid Scale Snow and Ice 2d mm h-1 snowh physical snow depth 2d mean sst Sea Surface Temperature 2d K swdown Downward Short Wave Flux at Ground Surface 2d W m-2 swup Upward Short Wave Flux at Ground Surface 2d W m-2 t2 Temperature at 2 m 2d K t2eta 2 m temperature (extrapolated from the first two eta-levels) 2d K t2pbl 2 m temperature (linear fit from pbl eta-levels) 2d K tsk Surface Skin Temperature 2d K u10 u at 10m 2d m s-1 u_intliquidflux column integrated zonal liquid water flux 2d kg -1 s-1 u_intsolidflux column integrated zonal solid water flux 2d kg -1 s-1 u_intvaporflux column integrated zonal water vapor flux 2d kg -1 s-1 udroff underground runoff 2d mm ust u* in similarity theory 2d m s-1 v_intliquidflux column integrated meridional liquid water flux 2d kg m-1 s-1 v_intsolidflux column integrated meridional solid water flux 2d kg m-1 s-1 v_intvaporflux column integrated meridional water vapor flux 2d kg m-1 s-1 v10 v at 10m 2d m s-1 w_intliquidflux column integrated vertical liquid water flux 2d kg m-1 s-1 w_intsolidflux column integrated vertical solid water flux 2d kg m-1 s-1 w_intvaporflux column integrated vertical water vapor flux 2d kg m-1 s-1 ws10 10 m Wind Speed 2d m s-1 3d Variables geopotential Full Model Geopotential on Mass Points 3d_press m2 s-2 qliquid Liquid Water Mixing Ratio 3d_press kg kg-1 qsolid Solid Water Mixing Ratio 3d_press kg kg-1 qvapor Water Vapor Mixing Ratio 3d_press kg kg-1 theta Potential Temperature (theta) 3d_press K u x-wind component 3d_press m s-1 uliquidflux zonal liquid water flux 3d_press kg m-2 s-1 usolidflux zonal solid water flux 3d_press kg m-2 s-1 uvaporflux zonal water vapor flux 3d_press kg m-2 s-1 v y-wind component 3d_press m s-1 vliquidflux meridional liquid water flux 3d_press kg m-2 s-1 vsolidflux meridional solid water flux 3d_press kg m-2 s-1 vvaporflux meridional water vapor flux 3d_press kg m-2 s-1 w z-wind component 3d_press m s-1 wliquidflux vertical liquid water flux 3d_press kg m-2 s-1 wsolidflux vertical solid water flux 3d_press kg m-2 s-1 wvaporflux vertical water vapor flux 3d_press kg m-2 s-1 ws horizontal wind speed on mass grid points 3d_press m s-1 cldfra cloud fraction 3d_press - pressure full model pressure 3d_press hpa 3d Soil variables smois soil moisture 3d_soil m3 m-3 sh2o soil liquid water 3d_soil m3 m-3 smcrel relative soil moisture 3d_soil - tslb soil temperature 3d_soil K Static Variables hgt Terrain Height static m lu_index Land Use Category static - cosalpha Local cosine of map rotation static - sinalpha Local sine of map rotation static - lai Leaf area index static area/area e Coriolis cosine latitude term static s-1 f Coriolis sine latitude term static s-1 isltyp Dominant soil category static - ivgtyp Dominant vegetation category static - vegfra Vegetation fraction static - landmask Land mask (1 for land, 0 for water) static - mapfac_m Map scale factor on mass grid static - mapfac_mx map scale factor on mass grid, x direction static - mapfac_my map scale factor on mass grid, y direction static - Data Access Please refer to Jaenicke et al. (2017) and provide a link to this webpage when using CER v1 data. Publications Jaenicke, B., Meier, F., Fenner, D., Fehrenbach, U., Holtmann, A., Scherer, D. (2017): Urban-rural differences in near-surface air temperature as resolved by the Central Europe Refined analysis (CER): sensitivity to planetary boundary layer schemes and urban canopy models. Int. J. Climatol. 37 (4), 2063-2079. DOI: 10.1002/joc.4835.