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.
Figure 1: WRF domain setup (rectangles) and terrain height in the 30 km domain for CER v1.
© Chair of Climatology
|
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)
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 (webdav)
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