Improvement of Hourly Surface Solar Irradiance Estimation Using MSG Rapid Scanning Service

Abstract

The purpose of this work is to explore the effect of temporal sampling on the accuracy of the hourly mean Surface Solar Irradiance (SSI) estimation. An upgraded version of the Advanced Model for the Estimation of Surface Solar Irradiance from Satellite (AMESIS), exploiting data from the Meteosat Second Generation Rapid Scanning Service (MSG-RSS), has been used to evaluate the SSI. The assessment of the new version of AMESIS has been carried out against data from two pyranometers located in Southern (Tito) and Northern (Ispra) Italy at an altitude of 760 m and 220 m, respectively. The statistical analysis of the comparison between hourly mean SSI estimates based on temporal sampling every five minutes shows a quantitative improvement compared to those based on 15-minute sampling. In particular, for the whole dataset in Tito, the correlation increases from 0.979 to 0.998, the Root Mean Square Error (RMSE) decreases from 45.16 W/m2 to 13.19 W/m2 and the Mean Bias Error (MBE) is reduced from −0.67 W/m2 to −0.02 W/m2. For the whole dataset in Ispra, the correlation increases from 0.995 to 0.998, the RMSE decreases from 24.85 W/m2 to 15.59 W/m2, whereas the MBE increases from 3.84 W/m2 to 4.58 W/m2. This preliminary assessment shows that higher temporal sampling can improve SSI monitoring over areas featuring frequent and rapid solar irradiance variation.

Keywords

• AMESIS
• Rapid Scanning Service (RSS)
• MSG
• SEVIRI
• Surface Solar Irradiance