## 4 Conclusions  
Reanalysis datasets have the advantage of providing global coverage and long-term data for various climate parameters, including SSR. Yet, the reanalysis data assimilation can lead to errors in SSR and its interannual variation and trends and, hence, in uncertainties in studies making use of them. Therefore, before applying reanalysis SSR products in climate studies, it is necessary to validate them against available reference ground measurements. A detailed and thorough evaluation and verification of MERRA-2 reanalysis SSR for the 40-year period 1980-2019 has been performed here against ground measurements and satellite estimates at scales ranging from global, to regional and down to local (station-level). In particular, this study deals, for the first time to our knowledge, with the detailed evaluation of MERRA-2 SSR and their changes (\(\Delta\)(SSR) or GDB) over the period 1980-2019 using high-quality surface measurements from 1099 GEBA and 70 BSRN stations. The performed analysis enabled to derive some useful conclusions, which are summarized as follows. * The MERRA-2 SSR fluxes correlate very well with the ground truth measurements, with R values equal to 0.95 and 0.97 for the comparison with GEBA and BSRN stations, respectively. The corresponding R values for the comparison of deseasonalized SSR anomalies, which are free of the seasonal cycle and give more meaningful results, are still satisfactory and equal to 0.61 and 0.62. On an individual station-level, the estimated R values range from \(-\)0.25 to 0.92, the lowest values occurring in tropical and sub-tropical regions, probably due to uncertainties in the Reanalysis cloudiness. * 2 SSR compared to GEBA and BSRN measurements, the mean bias being equal to 24.25 and 10.31 W/m\({}^{2}\) or 15.3 and 5.9%, respectively. The ranges of variability of the biases in terms of absolute and relative percent values for individual stations are \(-\)64.24-141.07 W/m\({}^{2}\) or \(-\)20.3-103.9% for GEBA and \(-\)36.32-54.97 W/m\({}^{2}\) or \(-\)15.8-35% for BSRN stations. However, MERRA-2 underestimates SSR at low latitudes and polar regions. The general overestimation leads to the conclusion that the atmosphere of MERRA-2 is too transparent. The computed average RMSE is equal to 36.07 W/m\({}^{2}\) (equivalent to 22.8%) for the comparison of MERRA-2 with GEBA, while the corresponding values for BSRN are equal to 26.12 W/m\({}^{2}\) or 15.1%. The RMSE values are high in the tropics and the highest in Southern China. * The assessment of the performance of MERRA-2 SSR with GEBA on a seasonal basis has shown that in both hemispheres the performance is worse during the cold period of the year, when the computed hemispherical mean values of percent bias and RMSE are the highest (17.9 and 30.9%, respectively) and those of R are the lowest (0.52). * The time-series of the average SSR anomalies of GEBA and BSRN stations and the corresponding MERRA-2 pixels show that MERRA-2 show larger anomalies, positive before 2000 and negative in the post 2000 years, which can affect the computed trends of SSR, namely GDB, of MERRA-2 and stations. Indeed, the MERRA-2 SSR trends show a stronger dimming and a weaker brightening than the stations' trends. * Comparing the sign of GDB for each station (232 GEBA and 22 BSRN) and MERRA-2 pixels where the stations are located, an agreement is found for 63.4% of matched MERRA-2 and GEBA pairs (for the period 1980-2017), with the corresponding number being equal to 50% for the matched MERRA-2 and BSRN pairs (for the period 1992-2020). A very good agreement between the Reanalysis and stations in terms of signs of GDB is found for Europe and India, opposite to a strong disagreement in Japan. * The estimated MERRA-2 SSR changes (GDB) during the 40-year period 01/1980-12/2019, reveal a statistically significant brightening in Europe, Central Africa, Mongolia, Mexico, parts of the tropical oceans, Brazil and Argentina.