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Article

Updated GOES-13 Heliosat-2 Method for Global Horizontal Irradiation in the Americas

ESPACE-DEV, Univ Guyane & Univ Réunion & Univ Montpellier & IRD & Univ Antilles, 97300 Cayennez, France
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Remote Sens. 2022, 14(1), 224; https://doi.org/10.3390/rs14010224
Submission received: 26 October 2021 / Revised: 6 December 2021 / Accepted: 7 December 2021 / Published: 4 January 2022

Abstract

Increasing the utilization of renewable energy is at the center of most sustainability policies. Solar energy is the most abundant resource of this type on Earth, and optimizing its use requires the optimal estimation of surface solar irradiation. Heliosat-2 is one of the most popular methods of global horizontal irradiation (GHI) estimation. Originally developed for the Meteosat satellite, Heliosat-2 has been modified in previous work to deal with GOES-13 data and named here GOES_H2. This model has been validated through the computation of indicators and irradiation maps for the Guiana Shield. This article proposes an improved version of GOES_H2, which has been combined with a radiative transfer parameterization (RTP) and the McClear clear-sky model (MC). This new version, hereafter designated RTP_MC_GOES_H2, was tested on eight stations from the Baseline Surface Radiation Network, located in North and South America, and covered by GOES-13. RTP_MC_GOES_H2 improves the hourly GHI estimates independently of the type of sky. This improvement is independent of the climate, no matter the station, the RTP_MC_GOES_H2 gives better results of MBE and RMSE than the original GOES_H2 method. Indeed, the MBE and RMSE values, respectively, change from 11.93% to 2.42% and 23.24% to 18.24% for North America and from 4.35% to 1.79% and 19.97% to 17.37 for South America. Moreover, the flexibility of the method may allow to improve results in the presence of snow cover and rainy/variable weather. Furthermore, RTP_MC_GOES_H2 results outperform or equalize those of other operational models.
Keywords: global horizontal irradiation; Heliosat-2; GOES-13; McClear; radiative transfer parameter global horizontal irradiation; Heliosat-2; GOES-13; McClear; radiative transfer parameter

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MDPI and ACS Style

Bechet, J.; Albarelo, T.; Macaire, J.; Salloum, M.; Zermani, S.; Primerose, A.; Linguet, L. Updated GOES-13 Heliosat-2 Method for Global Horizontal Irradiation in the Americas. Remote Sens. 2022, 14, 224. https://doi.org/10.3390/rs14010224

AMA Style

Bechet J, Albarelo T, Macaire J, Salloum M, Zermani S, Primerose A, Linguet L. Updated GOES-13 Heliosat-2 Method for Global Horizontal Irradiation in the Americas. Remote Sensing. 2022; 14(1):224. https://doi.org/10.3390/rs14010224

Chicago/Turabian Style

Bechet, Jessica, Tommy Albarelo, Jérémy Macaire, Maha Salloum, Sara Zermani, Antoine Primerose, and Laurent Linguet. 2022. "Updated GOES-13 Heliosat-2 Method for Global Horizontal Irradiation in the Americas" Remote Sensing 14, no. 1: 224. https://doi.org/10.3390/rs14010224

APA Style

Bechet, J., Albarelo, T., Macaire, J., Salloum, M., Zermani, S., Primerose, A., & Linguet, L. (2022). Updated GOES-13 Heliosat-2 Method for Global Horizontal Irradiation in the Americas. Remote Sensing, 14(1), 224. https://doi.org/10.3390/rs14010224

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