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The Central Europe Refined analysis version 2 (CER v2)

The Central Europe Refined analysis version 2 (CER v2) 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.

Important message (2023/02/03):

  • For the CER v2 the global attribute "TITLE" was corrected from "Central Europe Refined analysis - CER V1 - d10km" to "Central Europe Refined analysis - CER V2 - d02km" in all files. Please note that the order of the global attributes has changed as a result. The attribute "TITLE" is now in last place.

  • We apologize for any inconvenience caused.

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 this version 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 2000-2021.

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Model domains
Figure 1: WRF domain setup (rectangles) and terrain height in the 30 km domain for CER v1.

Time Span: 2000 - 2021
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
afwa_cape Convective available potential energy 2d J kg-1
afwa_cin Convective inhibition 2d J kg-1
afwa_pwat Precipitable water 2d kg m-2
afwa_zlfc Level of free convection 2d m
albedo Albedo 2d -
et Evapotranspiration 2d mm h-1
grdflx Ground Heat Flux 2d W m-2
hfx Upward Heat Flux at the Surface 2d W m-2
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
psfc SFC Pressure 2d Pa
q2 Water Vapor Mixing Ratio at 2 m 2d kg kg-1
scld total column clouds 2d -
slp Sea Level Pressure 2d hPa
snowfall Grid Scale Snow and Ice 2d mm h-1
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
swddif Diffuse Downward Short Wave Flux at Ground Surface 2d W m-2
swddir Direct Downward Short Wave Flux at Ground Surface 2d W m-2
t2 Temperature at 2 m 2d K
tsk Surface Skin Temperature 2d K
u10 u at 10m 2d m s-1
v10 v at 10m 2d m s-1
ws10 10 m Wind Speed 2d m s-1
3d Variables (Only CER v1)
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
v y-wind component 3d_press m s-1
w z-wind component 3d_press m s-1
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 -

Examples (CER v1)



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Mean wind speed at 10 m in January 2014
Fig. 2: Mean wind speed at 10 m in January 2014, 30 km Domain

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Total precipitation in January 2014
Fig. 3: Total precipitation in January 2014, 30 km Domain


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Mean Air Temperature at 2 m JJA 2010
Fig. 4: Mean Air Temperature at 2 m JJA 2010,
10 km Domain


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Mean Precipitation JJA 2010
Fig. 5: Mean Precipitation JJA 2010,
10 km Domain


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Mean Air Temperature at 2 m 2006
Fig. 6: Mean Air Temperature at 2 m 2006,
2 km Domain


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Mean Air Temperature at 2 m 2010
Fig. 7: Mean Air Temperature at 2 m 2010,
2 km Domain

Data Access


Please refer to Jänicke et al. (2017) and provide a link to this webpage when using CER v1 data.

CER data can be accessed here: CER download page (webdav)


nach oben

Fachgebietsleiter:

Prof. Dr. Dieter Scherer

Lead and contact Regional climatology:

Dr. Marco Otto

Publications

Jänicke, 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. Link