T. Spangehl et al.: Intercomparing the quality of recent reanalyses for offshore wind farm planning 
ı 11 
satellite imaginary, research aircraft measurements and nu- 
merical model simulations that the wakes from large wind 
farms can be several tens of kilometres in length under sta- 
ble atmospheric stratification (Platis et al., 2018). Wakes of 
more than 100km length are seen for very large wind farms 
in large eddy simulations (Maas and Raasch, 2022) under 
certain meteorological conditions. 
Moreover, high-resolution climate model simulations em- 
ploying a wind farm parameterization that considers the wind 
turbines as a sink of kinetic energy (KE) and source of turbu- 
lent kinetic energy (TKE) at rotor height indicate a distinct 
effect of offshore wind farms on power generation down- 
stream of wind farms as well as on the near-surface wind 
field and climate (Akhtar et al., 2021, 2022). 
In the present study the quality of recent regional reanaly- 
ses for offshore wind farm planning in Germany’s EEZ of the 
North Sea is assessed and compared to the quality of simula- 
tions without data assimilation by using in-situ observations 
[rom FINO and satellite-based data products as observational 
reference. 
The structure of the manuscript is as follows. Section 2 
ıntroduces the reanalysis, simulation and observational data. 
In addition, the statistical methods used for evaluation are 
oriefly discussed. Results are presented in Sect. 3 focusing 
on interannual to multi-annual variability of wind speed, fre- 
quency distribution of wind speed and wind direction, and as- 
sessment of extreme wind speeds during wind storm CHRIS- 
TIAN at near-turbine hub height using FINO1 measurements 
as reference. Wind storm CHRISTIAN, 27-29 October 2013, 
led to severe damage in Western and Central Europe. Fur- 
thermore, the spatial variability of near-surface wind speed 
using different satellite-based data products as reference is 
assessed. Section 4 provides discussion of results and con- 
clusions. 
from 26 September to 12 December 2012. The model do- 
main is adjusted to match the EURO-CORDEX region. The 
configuration used incorporates a horizontal resolution of 
6km with a non-hydrostatic model formulation. In the ver- 
tical the terrain following hybrid coordinate system con- 
sists of 40 main levels with 10 levels in the lowest 1000 m. 
The top level is located at 22 700m (— 40 hPa). The nu- 
merical core of the model is integrated with a time step of 
50s. For data assimilation COSMO-REA6 employs a New- 
tonian relaxation scheme (nudging) to combine prognostic 
model variables with observations. Observations of wind, 
temperature, humidity, geopotential and station pressure are 
assimilated stemming from radiosondes, SYNOP stations, 
ships, buoys or aircrafts. No satellite data is assimilated by 
COSMO-REAG6. In addition, an external analysis scheme is 
used for (i) snow depth, (ii) sea surface temperature and sea 
ice and (iii) soil moisture. The soil moisture scheme uses 
2m temperature observations for the derivation of optimized 
soil moisture fields. It should be noted that the assimilation 
of non-conventional observations such as satellite data (ra- 
diances) is not always possible by the nudging technique, 
as the observations have to be available in the model space 
rather than the observation space (Bollmeyer et al., 2015). 
Data from the global reanalysis ERA-Interim (6-hourly data) 
serves as boundary for COSMO-REA6. More details on the 
configuration and results of the regional reanalysis system 
are specified by Bollmeyer et al. (2015). Data of COSMO- 
REAG6 is publicly available as part of DWD’s open data 
(https://opendata.dwd.de/climate_environment/REA, last ac- 
cess: 6 November 2023). An overview of evaluation studies 
and application examples with a focus on renewable energy 
is illustrated by Kaspar et al. (2020). 
2.1.2 COSMO-REA2 
2 Data and methodology 
COSMO-REA?2 is a convective-scale reanalysis nested into 
COSMO-REA6. The model domain constitutes a slightly en- 
larged version of COSMO-DE thereby covering Germany 
and adjacent areas. COSMO model version 5.00.2 is used. 
The horizontal resolution is about 2km. There are 50 verti- 
cal levels with the model top at 22 km. In addition to the con- 
tinuous nudging of conventional observations a latent heat 
nudging scheme is used. A detailed description of COSMO- 
REA2 is given by Wahl et al. (2017). 
In this section the used regional and global reanalyses, the 
simulations without data assimilation, the in-situ observa- 
tions, and satellite-based data products are described. More- 
over, the methods used to process (time series manipulation, 
regridding) and statistically analyse (histogram, shape pa- 
rameters, box-plot) the data are briefly explained. 
2.1 Reanalyses 
21.1 COSMO-REA6 
2.1.3 COSMO-REAG6 Generation 2 (COSMO-R6G2) 
In order to extend the COSMO-based reanalysis and to pro- 
vide regional reanalysis data with short delay from real 
time DWD is currently producing a successor of COSMO- 
REA6 (COSMO-REA6 Generation 2, hereafter referred to 
as COSMO-R6G2) using ERAS5 as boundary conditions and 
a newer model version (Kaspar et al., 2020). Hourly data 
from ERA5 is used as lateral boundaries. Moreover, the 
benefit of incorporating ERAST to generate near real-time 
The regional reanalysiıs COSMO-REA6 was developed 
within the Hans-Ertel-Centre for Weather Research (Kas- 
par et al., 2020). COSMO-REA6 is based on DWD’s for- 
mer operational NWP model COSMO. The model is well 
documented and has intensively been used by the meteo- 
rological community. The regional reanalysis is based on 
COSMO model version 4.25 which was operational at DWD 
attos://doi.org/10.5194/asr-20-109-2 u2- 
Adv. Sei. Res., 20, 109-128. 2023