Surface solar radiation (SSR) and energy balance are closely related to the Earth’s climate, water cycle, atmospheric conditions, and thus the human habitat, and accurate tracking of the energy cycle is essential. However, a certain degree of uncertainty still exists in current studies of long-term SSR changes due to the lack of a state-of-the-art benchmark observational dataset. To understand this issue, we present a systematic comparison of SSR from in-situ observations, the Fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), and the The Coupled Model Intercomparison Project—Phase 6 (CMIP6) in this paper. Our results show that: (1) The reverse interpolated station SSR series based on the ERA5 and the CMIP6 multi-models ensemble (MME) reflects the observed SSR values at the local/station scale to a certain degree. Although the underestimation/overestimation varies slightly in different regions/stations, the overall Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) are about 15% and 21%, respectively of the observations. (2) Both the ERA5 SSR and the CMIP6 MME roughly reflect the seasonal variability and the spatial distributions of the SSR’s climatological means (1971–2000) from gridded in-situ observations. (3) The SSR from the ERA5 is more consistent with observations than the CMIP6 MME in the temporal variations, long-term trend, and the uncertainties at global and continental scales. The latter has insignificant fluctuations in interannual variability, consistent with the trend in-situ observations only from 1950 to 1990, but fails the significant test (at 5% level) after that except for some regions. Therefore, developing a higher quality global long-term SSR benchmark climatic dataset with more complete coverage is still of great significance for optimizing surface energy balance estimates and studies of the impact of human activities on climate change.
Further reading:
Jiao, B., Li, Q., Sun, W. et al. Uncertainties in the global and continental surface solar radiation variations: inter-comparison of in-situ observations, reanalyses, and model simulations. Clim Dyn (2022). https://doi.org/10.1007/s00382-022-06222-3