## 3 Results
### Validation against ECA&D Ground Measurements  
In order to validate the performance of the two satellite data records, TCC data from ECA&D were used as ground truth. For every station the TCC values of the corresponding grid cell from CLARA-A2 and ISCCP-H were analyzed for their common period (1984-2012). TCC time-series for each station were created for both CLARA-A2 and ISCCP-H and were compared to the corresponding ECA&D ones. The overall comparison between CLARA-A2, ISCCP-H, and ECA&D is presented in Figure 4. TCC data from all the corresponding grid cells of CLARA-A2 and ISCCP-H were analyzed against all the ECA&D stations. Both satellite data records perform fairly well against the ground measurements. Figure 3: (**a**) Time series of the mean annual TCC and (**b**) average seasonal variation of TCC from ISCCP-H and CLARA-A2 over the domain shown in Figure 2 for their common period (1984–2012). However, CLARA-A2 is overall better correlated to ECA&D ground measurements in comparison to ISCCP-H, having a correlation coefficient of 0.90 versus 0.84, respectively. Satellite measurements from both data records mainly overestimate ground measurements from ECA&D. CLARA-A2 is slightly less biased against ECA&D (2.08%) with respect to the bias value of ISCCP-H (5.15%). CLARA-A2 shows only a minor overestimation and only for a few TCC values, whereas ISCCP-H appears to overestimate TCC, particularly for low TCC values, resulting in a slope value of 0.62 compared to 0.93 for CLARA-A2. An overestimation of satellite-based TCC with respect to ground measurements has frequently been found before on a global basis since there is a slight tendency for surface observations to give less TCC in comparison to satellites, which may be caused by an effect of the viewing angle of the geostationary satellites or the fact that satellites may detect cirrus that are not observed from the surface [17; 26; 30; 54]. However, underestimations of satellite cloud cover with respect to surface-based observations have also been reported by [PERSON] et al. [16] who attributed them to different observational geometries and to characteristics in the satellite algorithm or, in particular, for higher latitudes (i.e., the Arctic) by [PERSON] et al. [55], which seems to be in accordance with the negative bias values computed in this study for the northern stations (i.e., Scandinavia and the UK). Furthermore, [PERSON] et al. (2018) compared satellite retrieved cloud cover to ground measurements for the Arabian Peninsula and found similar results. They reported both CLARA-A2 and ISCCP-D2 overestimating TCC compared to ground measurements, with the TCC values of CLARA being closer to the ground observations and better correlated than ISCCP-D2 [56]. The computed correlation coefficients for the comparison between the satellite data and ECA&D are shown in Figure 5. Both CLARA-A2 and ISCCP-H compare fairly well to ECA&D, having correlation coefficients larger than 0.7 for most cases and larger than 0.8 for a considerable number of stations. However, CLARA-A2 appears to have quite higher correlation coefficient values, which are greater than 0.8 or 0.9 for the majority of the stations, but even more so primarily over central and northern Europe and secondarily over the UK. It should be noted that over these areas, the correlation coefficient values between ISCCP-H and ECA&D drop to 0.5, whereas the correlation coefficients computed for CLARA-A2, remain higher than 0.7. Furthermore, with increasing latitude there is an obvious decrease in the correlation between both comparisons (CLARA-A2-ECA&D and ISCCP-H-ECA&D), where the correlation coefficient drops to values less than 0.7 (over Scandinavia and the UK). This can be attributed to the stronger TCC covariability between satellite data and ECA&D in southern than northern stations combined with a smaller TCC seasonality in northern stations (Figure S4).