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The Central Europe Refined analysis version 1 (CER v1)

The Central Europe Refined analysis version 1 (CER v1) is an atmospheric data set 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 CER covers the period March 2001 - May 2019 and provides gridded two- and three-dimensional fields of a multitude of atmospheric variables for three domains. The setup of the CER is based on a sensitivity study concerning planetary boundary layer schemes and urban canopy models by Jänicke et al. (2017).

Description

The CER data set is generated by dynamical downscaling using the Weather Research and Forecasting model (WRF) version 3.7.1. As forcing data, ERA-Interim reanalysis data provided by ECMWF is used. The domain setup (Figure 1) consists of two-way nested domains with 30 km, 10 km and 2 km grid spacing. The domains broadly cover Europe, Germany and the Berlin-Brandenburg area, respectively. Results for all three domains are provided. 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 Currently available from March 2001 to December 2016.

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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: 2001 - 2019
Spatial Resolution: 30 km, 10 km, 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 Specific Humidity at 2m 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
geopotential Full Model Geopotential on Mass Points 3d_press m2 s-2
qliquid Liquid Water Mixing Ratio 3d_press kg kg-
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



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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 (ftp server)


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