## 3 Results
### Validation against ECA&D Ground Measurements
This finding is just based on the 22 stations used in the present study and could  
Figure 4: Scatter density plots of monthly mean TCC (%) of (**a**) CLARA-A2 and (**b**) ISCCP-H against all selected ECA&D stations. be further validated using a larger number of stations. The different behavior between higher and lower latitudes could be attributed to differences in the seasonal variation for Northern and Southern regions. A smaller seasonal variation over high latitudes could lead to lower correlations. Considering areas of lower latitude, besides the overall better performance of the satellite data in comparison to northern regions, correlation values between ISCCP-H and ECA&D are considerably high and much closer to those of the CLARA-A2 and ECA&D comparison. Moreover, the overall better performance of CLARA-A2 can be clearly confirmed by the higher linear regression slope values for each station (Figure 6). It is evident that CLARA-A2 has slope values close to 1 (0.9-1.0), whereas the corresponding slope values for ISCCP-H indicate stronger deviations, being smaller than 0.7 or larger than 1.3 for most stations. Biases for the two comparisons were computed from the overall mean TCC value of each station and corresponding grid cell (Figure 7). For grid cells and stations located in higher latitudes (Scandinavia and the Northern UK) biases acquire negative values (greater than \(-3.0\%\)), showing a tendency of underestimation (blue circles) of the satellite TCC data in comparison to the ground-based observations from ECA&D. In lower latitudes (i.e., Iberian Peninsula, Greece etc. ), there is widespread overestimation (red circles) of both CLARA-A2 and ISCCP-H to the ECA&D measurements of TCC (biases mainly greater than 6.0%). [PERSON] et al. (2016), while studying TCC over the Mediterranean, also found that surface observations show a slight tendency to lower mean values of TCC compared to ISCCP-D and CLARA-A1, especially over land areas [17]. A similar overestimation of satellite MODIS TCC against ECA&D has been also reported over the Mediterranean taking place mainly in winter [25]. On the other hand, the magnitude of the biases decreases with increasing  
Figure 5: Correlation coefficients between (**a**) CLARA-A2 and ECA&D and (**b**) ISCCP-H and ECA&D TCC values. Correlation coefficient values are given for each one of the 22 selected stations and are increasing with increasing circle size. latitude especially for ISCCP-H. This could be attributed to the shift from geostationary to polar orbiting satellite measurements, above 55\({}^{\circ}\)N, in the ISCCP-H data set. It is also apparent that ISCCP-H is significantly more biased to ECA&D in comparison to CLARA-A2. For CLARA-A2 biases range from \(-3.0\%\) to \(+6.0\%\) for the majority of cases with the exception of a few stations. ISCCP-H biases are greater than \(+6.0\%\) for more stations and for some stations even greater than \(+12.0\%\). The conclusions derived from Figures 5-7, i.e., the better performance of CLARA-A2 than ISCCP-H TCC data, is also confirmed by the results for another two statistical parameters, namely the Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), shown in Table 4. In 16/22 stations for MAE and 14/22 stations for RMSE CLARA-A2 performs better. By averaging over the 22 selected ECA&D stations and the corresponding grid cells, we created a mean of the station-based TCC and an average of the corresponding grid cells of CLARA-A2 and ISCCP-H, in order to evaluate the overall inter-annual long-term and seasonal variability of the biases between CLARA-A2, ISCCP-H and ECA&D (Figure 8). In this way, better insight is given into the year-to-year and season-to-season patterns of differences between the satellite and surface TCC datasets. As expected, ISCCP-H and CLARA-A2 show a positive bias for most of their common period; however, ISCCP-H is constantly more biased than CLARA-A2 with respect to ECA&D.