@Article{AzevedoOlivArav:2021:EvAbSs,
               author = "Azevedo, Mayna Helena and Oliveira, Nat{\'a}lia Rudorff and 
                         Arav{\'e}quia, Jos{\'e} Ant{\^o}nio",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Evaluation of the abi/goes-16 sst product in the tropical and 
                         southwestern atlantic ocean",
              journal = "Remote Sensing",
                 year = "2021",
               volume = "13",
               number = "2",
                pages = "e192",
                month = "jan.",
             keywords = "SST, ABI/GOES-16, South Atlantic Ocean.",
             abstract = "Sea surface temperature (SST) is an essential climate variable 
                         used for ocean and weather monitoring and forecasting. The NOAAs 
                         next generation geostationary satellite GOES-16 was declared 
                         operational at the east position (75\◦W) in December 2017, 
                         carrying onboard an Advanced Baseline Imager (ABI). The 
                         hyperspectral ABI sensor now allows SST estimates every 1015 min 
                         at both day and nighttime, with advanced options for cloud 
                         screening and water vapor correction. In the present work, we 
                         compare the first operational ABI SST product (OSI SAF, 2018) with 
                         an in situ match-up database (MDB) across the Tropical and 
                         Southwestern Atlantic Ocean, off the Brazilian coast, throughout 
                         the year of 2018. The MDB was obtained from two long-term 
                         programs, i.e., PIRATA moored buoys (FOLTZ et al., 2016) and 
                         PNBoia moored and drifting buoys (MARINHA DO BRASIL, 2017). 
                         Separate comparisons were made for each data set, analyzing the 
                         uncertainties according to the program (i.e., buoy type and 
                         region), satellite SST quality level and influence of diurnal 
                         heating. We also compare the ABI product with the OSTIA analysis 
                         L4 SST (DONLON et al., 2012) to increment our analyses on the 
                         spatio-temporal biases within the study region. The results show 
                         that the OSI SAF ABI SST L3C has a mean bias (0.1 \◦C) and 
                         error (RMSE, 0.5 \◦C) within the GHRSST standards, with an 
                         exception being coastal waters off the southeast Brazilian coast 
                         (RMSE, 0.65 \◦C), which are subjected to sharp thermal 
                         fronts. The highest biases are for regions/seasons subjected to 
                         persistent cloud coverage and high water-vapor content, i.e., the 
                         Intertropical and South Atlantic Convergence Zones, as well as 
                         highly dynamic frontal zones, i.e., the Brazil Malvinas Confluence 
                         Zone, the Subtropical Front and coastal waters. The ABI SST 
                         product is suitable for operational use, and applications should 
                         explore more deeply the new set of information provided.",
                  doi = "10.3390/rs13020192",
                  url = "http://dx.doi.org/10.3390/rs13020192",
                 issn = "2072-4292",
             language = "en",
           targetfile = "azevedo_evaluation.pdf",
        urlaccessdate = "28 abr. 2024"
}