Benchmark of estimated solar irradiance data at high latitude locations

• Six solar irradiance data products are benchmarked against a ground station network. • Geostationary, satellite-based estimates yield higher accuracy than reanalysis. • Challenges of estimating solar irradiance at high latitudes is highlighted. • Snow and high latitudes pose challenges for satellite-based estimates. Estimated solar irradiances from CAMS, PVGIS SARAH-2, Solargis, Meteonorm, PVGIS ERA5, and NASA POWER are benchmarked against measurements conducted at 34 ground stations in Norway at latitudes between 58 and 76°N. We find that the data products that mainly rely on high-resolution, geostationary satellite images, i.e., CAMS, PVGIS SARAH-2, and Solargis, have higher accuracy with lower relative Mean Absolute Error (rMAE) and relative Mean Bias Error. By dividing the stations in distinct categories, such as above 65°N, snow-affected and horizon-shaded, challenges with irradiance estimation that are common in Norway and at high latitudes in general are highlighted and discussed. The accuracy of the data products is dependent on latitude, and by excluding stations above 65°N, the median rMAE of the different data products improves 3.2 – 9.4 % abs compared to the median rMAE when including all stations, depending on data product. Similarly, by excluding snow-affected stations, the median rMAE improves 1.9 – 8.1 % abs , depending on data product. The improvement in rMAE by excluding snow-affected stations is partially related to the difficulty of separating snow on the ground from cloud cover in satellite images. This difficulty is illustrated by concrete examples of irradiance time series from clear sky days when the ground is covered in snow. Although the performance of the data products is dependent on the categorization of stations, i.e., latitude, snow conditions, and local topography, the relative performance between the products is maintained regardless of sub-division.