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 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 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

Water Vapor Mixing Ratio at 2 m

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 kg1

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 (webdav)
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