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
rovided 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 May 2019.
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 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
|
< tr>
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
Fig. 2: Mean wind speed at 10 m in January 2014, 30 km Domain
© Chair of Climatology
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Fig. 3: Total precipitation in January 2014, 30 km Domain
© Chair of Climatology
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Fig. 4: Mean Air Temperature at 2 m JJA 2010,
10 km Domain
© Chair of Climatology
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Fig. 5: Mean Precipitation JJA 2010,
10 km Domain
© Chair of Climatology
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Fig. 6: Mean Air Temperature at 2 m 2006,
2 km Domain
© Chair of Climatology
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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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