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 DFGfunded research unit
"Urban Climate and Heat Stress in midlatitude cities in view of climate change (UCaHS)"
and the DFGfunded research project
"Heat waves in Berlin, Germany  Urban climate modifications". The CER covers the period March 2001  May 2019 and provides gridded two
and threedimensional 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, ERAInterim reanalysis data
provided by ECMWF is used.
The domain setup (Figure 1) consists of twoway nested domains with 30 km, 10 km and 2 km grid spacing.
The domains broadly cover Europe, Germany and the BerlinBrandenburg area, respectively. Results for all three domains are provided.
The simulation strategy is cascaded twoway nesting with daily reinitialization, 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 spinup 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 postprocessed into productfiles:
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.
Figure 1: WRF domain setup (rectangles) and terrain height in the 30 km domain for CER v1.
© Chair of Climatology

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 kg1 
afwa_cin 
Convective inhibition  2d 
J kg1 
afwa_pwat 
Precipitable water 
2d 
kg m2 
afwa_zlfc 
Level of free convection 
2d 
m 
albedo 
Albedo 
2d 
 
et 
Evapotranspiration  2d 
mm h1 
grdflx 
Ground Heat Flux  2d 
W m2 
hfx 
Upward Heat Flux at the Surface  2d 
W m2 
lh 
Latent Heat Flux at the Surface  2d 
W m2 
lwdown 
Downward Long Wave Flux at Ground Surface  2d 
W m2 
lwup 
Upward Long Wave Flux at Ground Surface  2d 
W m2 
netrad 
Net Radiation at Ground Surface  2d 
W m2 
pblh 
PBL Height  2d 
m 
prcp 
Total Precipitation
 2d 
mm h1 
psfc 
SFC Pressure  2d 
Pa 
q2 
Specific Humidity at 2m  2d 
kg kg1 
scld 
total column clouds  2d 
 
slp 
Sea Level Pressure  2d 
hPa 
snowfall 
Grid Scale Snow and Ice  2d 
mm h1 
sst 
Sea Surface Temperature  2d 
K 
swdown 
Downward Short Wave Flux at Ground Surface  2d 
W m2 
swup 
Upward Short Wave Flux at Ground Surface  2d 
W m2 
swddif 
Diffuse Downward Short Wave Flux at Ground Surface  2d 
W m2 
swddir 
Direct Downward Short Wave Flux at Ground Surface  2d 
W m2 
t2 
Temperature at 2 m  2d 
K 
tsk 
Surface Skin Temperature  2d 
K 
u10 
u at 10m  2d 
m s1 
v10 
v at 10m  2d 
m s1 
ws10 
10 m Wind Speed  2d 
m s1 
3d Variables




geopotential 
Full Model Geopotential on Mass Points  3d_press 
m2 s2 
qliquid 
Liquid Water Mixing Ratio  3d_press 
kg kg 
qsolid 
Solid Water Mixing Ratio  3d_press 
kg kg1 
qvapor 
Water Vapor Mixing Ratio  3d_press 
kg kg1 
theta 
Potential Temperature (theta)  3d_press 
K 
u 
xwind component  3d_press 
m s1 
v 
ywind component  3d_press 
m s1 
w 
zwind component  3d_press 
m s1 
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 
s1 
f 
Coriolis sine latitude term  static 
s1 
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
Fig. 2: Mean wind speed at 10 m in January 2014, 30 km Domain
© Chair of Climatology

Fig. 3: Total precipitation in January 2014, 30 km Domain
© Chair of Climatology

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

Fig. 5: Mean Precipitation JJA 2010, 10 km Domain
© Chair of Climatology

Fig. 6: Mean Air Temperature at 2 m 2006, 2 km Domain
© Chair of Climatology

Fig. 7: Mean Air Temperature at 2 m 2010, 2 km Domain
© Chair of Climatology

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)
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