@Article{JesusCebaCoelPorf:2023:EvClIm,
               author = "Jesus, Hallan Souza de and Ceballos, Juan Carlos and Coelho, 
                         Simone Marilene Sievert da Costa and Porfirio, A. C. S.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and FUNCEME",
                title = "Evaluation of cloud-type impact on performance of the GL model 
                         version 1.2 for estimation of solar irradiance",
              journal = "International Journal of Remote Sensing",
                 year = "2023",
               volume = "44",
               number = "20",
                pages = "6501--6522",
             keywords = "Surface solar irradiance, GL model, geostationary satellite, cloud 
                         classification.",
             abstract = "This work evaluates the quality of the satellite-based GLobal 
                         radiation model version 1.2 (GL1.2) estimates for four cloud 
                         classes. The GL1.2 calculates the global solar irradiance at 
                         ground level using images from a single visible band channel (VIS) 
                         of the Geostationary Operational Environmental Satellite GOES 
                         (GOES-East). The model \́s performance was assessed by 
                         comparing hourly mean GL1.2 values with ground- based hourly 
                         measurements from the Brazilian National Institute of Meteorology 
                         (INMET, 354 automatic weather stations), for the entire year 2017. 
                         A satellite-based cloud classifier was adopted to discriminate the 
                         datasets according to prevailing cloud conditions (cumulus, 
                         stratus, cirrus and multilayer), but the clear sky behaviour was 
                         presented. The results were analysed for the five Brazilian 
                         regions. In the first analysis, we selected days with a 
                         predominance for five stations. It was found that the diurnal 
                         cycle was well reproduced. Then the regional investigation for the 
                         cloud types reveals that the best results are found for the Center 
                         West region over multilayer cloud (mean bias error, MBEannual = -2 
                         ± 91 Wm\−2 and root mean squared error, RMSE = 91 
                         Wm\−2), while the worst ones are in the North over cumulus 
                         fields (MBEannual = 101.5 ± 136.4 Wm\−2). When considering 
                         all cloud types, the MBEannual is lower than 5 Wm\−2 for 
                         the Northeast, Southeast and South regions, but it reaches 101 
                         Wm\−2 in the North. It is noteworthy that winter has the 
                         highest MBE in all classes analysed in the North, as well as 
                         cirrus situations in other regions. Although the inhomogeneities 
                         of cumulus and the semitransparent cirrus clouds tend to propagate 
                         errors to the model, the quality of GL1.2 data has a high degree 
                         of agreement with the observations. Improvements including an 
                         updated monthly minimum reflectance (Rmin) and water vapour column 
                         (H2Ovapour), and a better spatial resolution of the Advanced 
                         Baseline Imager (ABI) of GOES-16 (ABI/GOES-16) VIS imagery will 
                         allow refinement, especially for cumulus clouds.",
                  doi = "10.1080/01431161.2023.2270111",
                  url = "http://dx.doi.org/10.1080/01431161.2023.2270111",
                 issn = "0143-1161",
                label = "self-archiving-INPE-MCTIC-GOV-BR",
             language = "pt",
           targetfile = "Evaluation of cloud-type impact on performance of the GL model 
                         version 1.2 for estimation of solar irradiance.pdf",
        urlaccessdate = "11 maio 2024"
}