Improved estimation of global solar radiation over rugged terrains by the disaggregation of Satellite Applications Facility on Land Surface Analysis data (LSA SAF)
Improved estimation of global solar radiation over rugged terrains by the disaggregation of Satellite Applications Facility on Land Surface Analysis data (LSA SAF)
Anno Pubblicazione  
2020 Pubblicazione ISI  

Autori: Fibbi L., Maselli F. e Pieri M.

Rivista: Meteorologial Application 2020; 27:e1940 

DOIhttps://doi.org/10.1002/met.1940

 

Abstract

Abstract: This paper presents a new method to predict global solar radiation over irregular terrain, named Estimation of global solar RADiation (ERAD). The method is based on the disaggregation of Satellite Applications Facility on Land Surface Analysis (LSA SAF) data using a digital elevation model and is applied in Italy with a time step of 1?min and a spatial resolution of 200?m. A quantitative assessment of ERAD is performed in comparison with three other standard methods (Mountain Microclimate Simulation Model [MTCLIM], LSA SAF and Copernicus Atmosphere Monitoring Service [CAMS]) using measurements taken in 43 stations located in Italy or in the surrounding countries, in the years 2005?2016. Such assessment concerns the irradiance incoming on a horizontal surface, which is measured by ground radiation sensors and is summarized by means of four accuracy statistics (i.e. mean absolute error [MAE], root mean square error [RMSE], coefficient of determination [R2] and mean bias error [MBE]). Overall, the average daily global solar radiation estimates obtained by ERAD have RMSE and R2 about 25?W·m?2 and 0.943, respectively. These statistics are similar to those of LSA SAF and better than those of CAMS and, above all, MTCLIM. The bias analysis by elevation ranges shows a slight ERAD overestimation over plains and hills and a slight underestimation over mountains. An additional qualitative assessment shows how the ERAD radiation estimates are more spatially detailed than those of the other methods and are redistributed on inclined surfaces consistently with expectations.