## 3 Results  
### SSR Data Evaluation  
To gain confidence in the monthly solar radiation patterns and the corresponding radiative effects calculated by our radiative transfer system, our SSR simulations (SBDART) are validated against monthly SSR observations from three ground stations with quality-assured long time series [27], and satellite-based observations from CM SAF SARAH-2.1 and CERES EBAF edition 4.1 for the 16 locations investigated here. As shown in Figure 2(a), SSR is underestimated in our simulations by \(-7.5\%\) (\(-14.5\,\text{W}/\text{m}^{2}\)) compared to the ground-based observations, with a very good correlation (regression line slope and Pearson's correlation coefficient R of -1). The high R values mentioned here show, to a great extent, that our SSR simulations capture the seasonal cycle of SSR well [92]. To gain a better insight into the quality of our simulations, relative to the ground-based observations, we also compare the deseasonalized values (Figure 2(b)). The correlation is again very good, with R being 0.78, similarly to other studies comparing deseasonalized SSR data [92; 93]. Apartfrom the normalized mean bias (NMB) and the mean bias (MB) referenced here, other metrics, i.e., regression line, mean absolute bias (MAB), and root mean square error (RMSE), are given in Figure 3. A negative bias appears in the comparison against the CM SAF and CERES data (\(-9.1\%\) and \(-7.2\%\)) as well, again with a very good correlation (Figure 3c-f) for both the original and the deseasonalized timeseries. Figure 3: Scatterplot of monthly mean SSR data produced in this work based on SBDART and (**a**) ground-based SSR observations from Thessaloniki, Athens, and HCMR; (**c**) CM SAF SARAH-2.1 SSR data from all the 16 locations that are studied here; and (**d**) CERES EBAF edition 4.1 SSR data from all the 16 locations that are studied here. The grey open circles represent the collocation points, the solid line is the regression line and the dashed line is the 1:1 line. The regression line (slope and offset with the corresponding \(\pm 1\sigma\)) and the correlation coefficient R, the MB, MAB, NMB, RMSE and the number of collocation points are also given on the plots. The (**b**,**d**,**f**) plots are the same as the (**a**,**c**,**e**) plots, respectively, but for deseasonalized timeseries. The ability of our system to simulate the monthly SSR values is similar to that of other systems (e.g., [PERSON] et al. [21]), which are based on a monthly mean daily SZA and dalylength. [PERSON] et al. [21] simulations underestimated the SSR by \(-5.3\%\) compared to the monthly observations from the Global Energy Balance Archive (GEBA) for the Mediterranean Basin, with a regression line slope of 0.95 and R of 0.95. Specifically for the station of Thessaloniki, our SSR simulations agree with the ground-based observations better than theirs (NMB of \(-6.5\%\) vs. \(-10.2\%\)) (Figure S1 in the electronic supplement of this paper). An NMB of \(-10.2\%\) compared to the daily instantaneous ground-based SSR observations from HCMR was shown in another study that focused on the radiative effect of aerosols [86]. These results were obtained using a different version of the radiative transfer model used by [PERSON] et al. [21], with aerosol input data from MODIS/Aqua. Our SSR simulations over HCMR exhibit better agreement with the ground-based observations (NMB of \(-6\%\) with a very good correlation) (see Figure S1). However, it has to be noted that our simulations are monthly and do not refer to instantaneous SSR values. The evaluation of our SSR simulations against ground-based observations, and against the CM SAF SARAH-2.1 and CERES EBAF edition 4.1 satellite-based products for each of the 16 locations of interest, is shown in Figures S2, S4 and S5, respectively. The evaluation of the CM SAF and CERES data against the ground-based observations is shown in Figure S3.