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3.7 Cloud Cover 
Clouds are the visible aggregates of water droplets and/or ice crystals in the atmos 
phere. The cloud cover is the portion of the sky that is attributed to clouds. It is tradi 
tionally measured in octa of sky covered or tenth (WMO 2012). According to the 
amount, height, thickness, layering and types of clouds have an important influence 
on the heat and radiation budget of the atmosphere. There are, however, still large 
gaps in understanding the interactions. The knowledge of the cloud cover alone is not 
sufficient to describe the processes. 
Comparing 
meteorological 
fields of the 
Ensembles 
regional climate 
models with ERA- 
40-data over the 
North Sea 
The annual cycle of the cloud cover shows in the ERA-40 data a flat minimum from 
May to August (see Fig. 3.7.13). All four North Sea boxes show the same annual cy 
cle. Within the large uncertainty there is no difference between the southern and the 
northern North Sea. RCMs even exceed the large temporal variations of cloud cover 
in the ERA-40 data. Less variability compared to ERA-40 occurs in all analysed sea 
sons (annual average, January, July) only in METNO-HIRHAM (Figs. 3.7.8, 3.7.10 
and 3.7.12). The largest variability compared to ERA-40 is found in DMI-HIRHAM 
(Figs. 3.7.8, 3.7.12). 
The annual cycle in the RCMs varies in time and amplitude compared to ERA-40 (see 
Fig. 3.7.13). A completely different annual cycle with a maximum in April and a min 
imum in October is simulated by HADRM3Q3. Both of the HIRHAM variants (DMI 
and KNMI) display weak summer maxima in cloud cover over the northern areas. 
Other models show more or less constant differences with both signs compared to 
ERA-40 the entire year (see Fig. 3.7.14). 
Basically the same separation of the RCMs in the simulations as for global radiation 
exists for cloud cover (see Tab. 2 and 3) Models in which overestimation of global 
radiation was detected underestimated cloud cover. However, this relationship does 
not hold for all models, SMHIRCA for example underestimates global radiation but 
also underestimates cloud cover in most months of the year. 
Table 3: List of RCMs that underestimate cloud cover respectively overestimate cloud cover. 
RCM-name 
Overestimator 
Underestimator 
CAIRCA3 
CNRM-RM 
DMI-HIRHAM 
HADRM3Q0 
EHTZ-CLM 
HADRM3Q3 
ICTP-RegCM3 
HADRM3Q16 
METNO-HIRHAM 
KNMI-RACM03 
MPIOM 
SMHIRCA