## 3 Results
### Validation against ECA&D Ground Measurements
\begin{table}
\begin{tabular}{c c c c c} \hline
**ECA\&D Station** & \multicolumn{2}{c}{**MAE**} & \multicolumn{2}{c}{**RMSE**} \\ \cline{2-5}  & **CLARA-A2–ECA\& ISCCP-H–ECA\&D & **CLARA-A2–ECA\& ISCCP-H–ECA\&D** \\ \hline _Trans_ & 7.0 & 6.2 & 9.0 & 7.8 \\ _Oslo-Blindern_ & 7.2 & 5.8 & 9.3 & 7.6 \\ _Stockholm_ & 6.2 & 6.2 & 8.2 & 8.0 \\ _Eskallemair_ & 4.3 & 4.7 & 6.4 & 6.2 \\ _Groningen_ & 6.7 & 10.4 & 8.8 & 12.4 \\ _De Blit_ & 4.7 & 7.8 & 6.4 & 9.7 \\ _Hentrova_ & 7.2 & 6.5 & 9.5 & 8.5 \\ _Wien_ & 4.8 & 9.2 & 6.6 & 10.8 \\ _Minchen-Botannischer Carten_ & 6.6 & 9.2 & 8.6 & 11.1 \\ _Gence-Observatoire_ & 4.2 & 8.3 & 6.2 & 10.2 \\ _Laguno_ & 5.7 & 10.4 & 8.0 & 12.5 \\ _Zagreb-Gric_ & 4.6 & 6.8 & 6.2 & 8.7 \\ _Belgrade_ & 8.7 & 10.2 & 10.8 & 11.9 \\ _A Cornu_ & 5.9 & 7.1 & 8.0 & 8.7 \\ _Bilbo-Aeropuerto_ & 7.7 & 7.2 & 10.4 & 9.6 \\ _Zarugoza-Aeropuerto_ & 5.9 & 8.6 & 7.8 & 9.8 \\ _Barcelona-Aeropuerto_ & 5.7 & 9.1 & 7.5 & 10.8 \\ _Madrid-Barajas_ & 9.7 & 9.7 & 11.8 & 11.2 \\ _Corti_ & 8.5 & 13.1 & 11.4 & 15.3 \\ _Athens-Hellinikun_ & 7.0 & 16.7 & 12.6 & 18.7 \\ _Sevilla-San Pablo_ & 8.1 & 8.4 & 10.5 & 10.2 \\ _Heralion_ & 6.8 & 11.7 & 9.2 & 14.8 \\ \hline \end{tabular}
\end{table} 
Table 4: Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), both in percent cloud cover, for the comparison between CLARA-A2 and ISCCP-H against ECA&D stations. Figure 8: (**a**) Mean annual TCC and (**b**) seasonal variation of TCC averaged over all ECA&D stations and the average of the corresponding grid cells of ISCCP-H and CLARA-A2 for their common period (1984-2012). Vertical bars denote the year-to-year variability of monthly TCC values. (**c**) Seasonal variation of the bias of CLARA-A2 and ISCCP-H with respect to ECA&D. A final remark about the sensitivity of the measurements to specific cloud types should be made. The cloud detection sensitivity of CLARA-A2 has been assessed through extensive comparisons against Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud products for the period between October 2006 and December 2015. The results, Figure 6, in [PERSON] and [PERSON] 2018 [PERSON] (2018) show that the probability of cloud detection drastically decreases below 70% for optically thin clouds (cloud optical thickness--COT--smaller than 1). For a probability of detection larger than 50% the COT values must be larger than 0.225. On the other hand, to our knowledge, no similar reported limit of ISCCP-H COT values is available in the literature, but it is expected that the ISCCP-H retrieval algorithm has a similar reduced sensitivity to optically thin clouds. Indeed, night-time ISCCP retrieval depends only on the IR, so thin high clouds could be at least partially missed. It should be noted that CLARA-A2 and ISCCP-H determine cloud top in different ways. ISCCP-H uses the nnHIRS T/q profiles and/or detectability limits in order to determine cloud top. In CLARA-A2 no HIRS information is used. The cloud top height retrieval for semi-transparent clouds is done using the difference between the 11- and 12-micron channels. Another type of clouds posing challenges to the satellite retrievals are broken, sub-pixel clouds, the sensitivity to which may differ between the datasets. Ground-based measurements can also suffer from limited sensitivity to certain cloud types. In particular, some types of ceilometers are not able to detect thin high clouds. These varying sensitivities of the different observing systems discussed in this study provide additional potential reasons why the observed cloud fractions, as shown, for example, in Figure 8b, do not line up.