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This paper presents an improved model for global sunshine duration estimation.The methodology incorporates geostationary satellite images by including snow cover information,sun and satellite angles and a trend correction factor for seasons,for the determination of cloud cover index.The effectiveness of the proposed methodology has been tested using Meteosat geostationary satellite images in the visible band with a temporal resolution of 1 h and spatial resolution of 2.5 km×2.5 km,for the Brue Catchment in the southwest of England.Validation results show a significant improvement in the estimation of global sunshine duration by the proposed method as compared to its predecessor(R 2 is improved from 0.68 to 0.83,root mean squared error(RMSE) from 2.37 h/d to 1.19 h/d and the mean biased error(MBE) from 0.21 h/d to 0.08 h/d).Further studies are needed to test this method in other parts of the world with different climate and geographical conditions.
This paper presents an improved model for global sunshine duration estimation. The methodology incorporates geostationary satellite images by including snow cover information, sun and satellite angles and a trend correction factor for seasons, for the determination of cloud cover index. The effectiveness of the proposed methodology has been tested using Meteosat geostationary satellite images in the visible band with a temporal resolution of 1 h and spatial resolution of 2.5 km × 2.5 km for the Brue Catchment in the southwest of England. Valuation results show a significant improvement in the estimation of global sunshine duration by the proposed method as compared to its predecessor (R2 is improved from 0.68 to 0.83, root mean squared error (RMSE) from 2.37 h / d to 1.19 h / d and the mean biased error (MBE) from 0.21 h / d to 0.08 h / d). Further studies are needed to test this method in other parts of the world with different climate and geographical conditions.