## 3 Results
### Climatologies and Differences of CLARA-A2 and ISCCP-H

Table 3: \(Cont.\)The observed differences may, to some extent, be related to the switch of preferred ISCCP-H input data source at 55\({}^{\circ}\)N. South of this latitude, geostationary imager measurements are used, which are taken with a relatively large viewing zenith angle (VZA). For example, at 45\({}^{\circ}\)N the geostationary VZA over Europe is around 52-58 degrees depending on the longitude, while the average VZA for AVHRR is estimated to be around 32 degrees. The differences in VZA between the two TCC datasets are shown in Figure S3 (Supplement) where the mean VZAs of the two datasets over Europe (30\({}^{\circ}\)-70\({}^{\circ}\)N) are plotted. There is an obvious changing pattern of differences at 55\({}^{\circ}\)N. South of this latitude, the ISCCP-H (MSG based) VZAs are larger than the CLARA-A2 (AVHRR based) VZAs, while north of it the VZAs of the two datasets coincide since AVHRR is used in both of them. As an example, at 45\({}^{\circ}\)N, the geostationary VZA over Europe is around 52-58 degrees depending on the longitude, while the average VZA for AVHRR is estimated to be around 32 degrees. [PERSON] et al. (2010) in [51] demonstrated a strong increase in MODIS Collection 5 cloud fraction with VZA. Their Figure 5 yields a difference in cloud fraction of about 8% between VZAs of 55 and 32 degrees. Although  
Figure 2: Average TCC for the 29-year period 1984-2012 over Europe based on **(a)** CLARA-A2 and (b) ISCCP-H, and (c) difference (in absolute terms) between ISCCP-H and CLARA-A2 TCC. this value should only be considered as a very rough estimate, it suggests that the differences between CLARA-A2 and ISCCP-H TCC south of 55\({}^{\circ}\)N can at least partly be attributed to the different viewing geometries of the employed satellite instruments. Indeed, global difference plots between ISCCP-H and CLARA-A2 (see Supplementary Figure S2) show signs of discontinuities at 55\({}^{\circ}\)N and 55\({}^{\circ}\)S, especially over ocean. These discontinuities are also evident in the results of [PERSON] and [PERSON] (2018) [50] who inter-compared and evaluated four satellite cloud data sets, including CLARA-A2 and ISCCP-H, on a global scale. Over land, which covers most of our study area, retrieval differences related to surface heterogeneity, surface temperature, snow cover, or other factors may be present and obscure the discontinuity described above. The north-south gradient apparent in the differences between CLARA-A2 and ISCCP-H TCC datasets may also be attributed to the different number of polar orbiting satellites and AVHRR instruments used in the two analyses (see Table 2). CLARA-A2 uses all available instruments. On the other hand, while ISCCP uses both morning and afternoon polar orbiters as availability simultaneously, it does not use more than 1 afternoon (or 1 morning) at a time for the gridded products. In fact, ISCCP uses one operational NOAA satellite/AVHRR instrument, usually the satellite with the equator crossing time closest to the original intended orbit. The inter-annual and seasonal variability of total cloudiness over the whole study region as estimated from CLARA-A2 and ISCCP-H is shown in Figure 3a,b, respectively. The time series of the annual mean TCC values averaged over Europe (Figure 3a) show a fairly good agreement between CLARA-A2 and ISCCP-H. Both satellite-derived data records exhibit a comparable year-to-year pattern for their common period 1984-2012. Nevertheless, ISCCP-H shows systematically higher TCC values during the whole period in comparison to CLARA-A2, with an average annual difference of 3.4%. The largest (reaching or exceeding 5%) differences (higher ISCCP-H values) are found in the 1980s. Similarly, higher ISCCP-D2 TCC data compared to PATMOS-x in the 1980s has been reported in the past and was regarded as an artifact due to systematically larger satellite zenith angles in some regions for the geostationary satellites contributing to the ISCCP dataset [22; 52; 53].