Optimizing the Heliosat-II Method for Surface Solar Irradiation Estimation with GOES Images

Abstract : The Heliosat-II method was developed to process Meteosat satellite images in order to assess the solar irradiation at surface. It is modified for its use with GOES satellite images in order to estimate the solar irradiation over French Guiana. Modifications include a change in the calibration formula, in the calculation of the cloud albedo, and in the values of the Linke turbidity factor. These modifications allow the improvement of the performances of the Heliosat-II model in Intertropical zones in French Guiana. The outcomes were compared to coincident measurements of hourly irradiation performed by ground stations. The results show that the use of the maximum apparent albedo as the cloud albedo (ρcmax), along with a fixed value of the Linke turbidity factor produces the best results; the bias was less than 23.61 Wh/m2 (5% of the mean value of the measurements) overall, and the RMSE was less than 109.39 W/m2 (24%) overall when using hourly values. In the case of daily means, the RMSE drops to less than 10.08 W/m2 (10%) overall, whereas the overall bias remains unchanged, as expected. The model performs better in clear skies than in cloudy skies. The results suggest that the Linke turbidity factor used in the Heliosat-II method does not reproduce well the attenuation of the solar radiation in French Guiana. The results were compared to those obtained from Heliosat II method and Meteosat images (HelioClim-3 database) and we found a better accuracy for GOES satellite data, which exhibits smaller viewing angle. The use of the Heliosat II method with GOES images allows assessment of the SSI with a good accuracy and high temporal and spatial resolutions.
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Contributor : Laurent Linguet <>
Submitted on : Wednesday, April 20, 2016 - 12:06:44 AM
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Laurent Linguet, Albarelo Tommy, Isabelle Marie-Joseph, Antoine Primerose, Frédérique Seyler, et al.. Optimizing the Heliosat-II Method for Surface Solar Irradiation Estimation with GOES Images. Canadian Journal of Remote Sensing, Canadian Aeronautics, 2015, 41 (2), pp.86-100. ⟨10.1080/07038992.2015.1040876⟩. ⟨meteo-01304576⟩



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