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 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	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
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

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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