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@MastersThesis{Azevedo:2020:AvTeSu,
               author = "Azevedo, Mayna Helena",
                title = "Avalia{\c{c}}{\~a}o da temperatura da superf{\'{\i}}cie do mar 
                         estimada pelo sensor ABI/GOES-16, no oceano Atl{\^a}ntico 
                         Tropical e Sudoeste",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2020",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2020-03-20",
             keywords = "TSM, temperatura da superf{\'{\i}}cie do mar, GOES-16, OSTIA, 
                         NOAA Geo-Polar-Blended, SST, sea surface temperature.",
             abstract = "No final de 2016 foi lan{\c{c}}ado o primeiro sat{\'e}lite da 
                         nova gera{\c{c}}{\~a}o de sat{\'e}lites geoestacion{\'a}rios 
                         da NOAA (GOES-16), com um sensor Advanced Baseline Imager (ABI) 
                         capaz de estimar a temperatura da superf{\'{\i}}cie do mar (TSM) 
                         a cada 15 min ao longo de todo ciclo diurno. H{\'a} uma 
                         expectativa de que este novo produto possa gerar novas 
                         informa{\c{c}}{\~o}es sobre o ciclo diurno da TSM, processos de 
                         mesoescala e intera{\c{c}}{\~o}es oceano-atmosfera, bem como ter 
                         um uso potencial na assimila{\c{c}}{\~a}o de dados em modelos 
                         oce{\^a}nico acoplados {\`a} modelos num{\'e}ricos de 
                         previs{\~a}o do tempo. No entanto, antes de seu uso operacional 
                         {\'e} preciso averiguar a qualidade deste produto comparado a 
                         dados in situ e outros produtos padr{\~o}es de TSM. Desta forma o 
                         presente trabalho apresenta uma avalia{\c{c}}{\~a}o da TSM 
                         ABI/GOES-16 no Atl{\^a}ntico Tropical e Sudoeste, ao largo da 
                         costa Brasileira at{\'e} 20oO. Observa{\c{c}}{\~o}es in situ de 
                         programas brasileiros em conjunto com outros pa{\'{\i}}ses 
                         (PIRATA e PNBoia) s{\~a}o usadas para comparar a TSM gerada pelo 
                         ABI-GOES-16 (TSMsub-pele) com dados de TSM in situ (TSMbalde). 
                         Numa segunda etapa a TSM ABI (L3) {\'e} comparada com dois 
                         produtos globais L4 (TSMfnd) OSTIA e Geo Polar Blended. Por fim, 
                         s{\~a}o feitas algumas an{\'a}lises comparativas da 
                         representatividade dos processos de mesoescala pelo produto ABI 
                         (L3) e global (L4), em um estudo de caso. Como resultado, 
                         compara{\c{c}}{\~o}es entre o algoritmo e a TSM in situ 
                         exp{\~o}em vi{\'e}s positivo para as m{\'e}dias hor{\'a}rias 
                         do per{\'{\i}}odo diurno (PNBoia fixa e deriva) revelando a 
                         maior discrep{\^a}ncia entre a TSM sub-pele (de sat{\'e}lite) e 
                         TSM in situ com a estratifica{\c{c}}{\~a}o termal diurna. 
                         Vi{\'e}s m{\'e}dio ficou abaixo de 0,1 oC e o EMQ e erro 
                         absoluto igual ou menor que 0,5 oC, para quase todos os casos, que 
                         {\'e} o recomendado pelo GHRSST. Na compara{\c{c}}{\~a}o entre 
                         a TSM ABI-GOES-16 L3 com produtos L4 verificou-se que o produto de 
                         estudo TSM ABI-GOES-16 pode fornecer benef{\'{\i}}cios 
                         significativo no fornecimento de TSM para o Brasil, com maiores 
                         erros encontrados nas regi{\~o}es de maior gradiente horizontal e 
                         mais din{\^a}micas i.e., regi{\~a}o costeira, Conflu{\^e}ncia 
                         Brasil-Malvinas e extremo sul do Atl{\^a}ntico Sul. Melhorias 
                         precisam ser feitas em regi{\~o}es mais complexas, mas para 
                         processos de larga escala a TSM ABI L3 OSTIA possui bom 
                         desempenho. ABSTRACT: At the end of 2016, the first satellite of 
                         the new generation of NOAA geostationary satellites (GOES-16) was 
                         launched, with an Advanced Baseline Imager (ABI) sensor capable of 
                         estimating the sea surface temperature (SST) every 15 minutes 
                         throughout the daytime cycle. There is an expectation that this 
                         new product can generate new information about the SST diurnal 
                         cycle, mesoscale processes and ocean-atmosphere interactions, as 
                         well as having a potential use in the assimilation of data in 
                         oceanic models coupled with numerical weather forecasting models. 
                         However, before its operational use, it is necessary to check the 
                         quality of this product compared to in situ data and other 
                         standard SST products. In this way, this work presents an 
                         evaluation of SST ABI/GOES-16 in the Tropical and Southwest 
                         Atlantic, off the Brazilian coast up to 20oW. In situ observations 
                         of Brazilian programs in conjunction with other countries (PIRATA 
                         and PNBoia) are used to compare the SST generated by ABI-GOES-16 
                         (SSTsubskin) with SST in situ data (SSTbucket). In a second step, 
                         SST ABI (L3) is compared with two global L4 products (SSTfnd) 
                         OSTIA and Geo Polar Blended. Finally, some comparative analyzes of 
                         the representativeness of the mesoscale processes by the ABI (L3) 
                         and global (L4) products are made, in a case study. As a result, 
                         comparisons between the algorithm and the in situ SST expose a 
                         positive bias for the hourly averages of the daytime period (fixed 
                         and drifting bouys PNBoia) revealing the largest discrepancy 
                         between the sub-skin (satellite) SST and the in situ SST with 
                         daytime thermal stratification. Mean bias was below 0.1 oC and the 
                         RMSE and absolute error equal to or less than 0.5 oC, for almost 
                         all cases, which is recommended by the GHRSST. When comparing the 
                         SST ABI-GOES-16 L3 with L4 products, it was found that the study 
                         product SST ABI-GOES-16 can provide significant benefits in the 
                         supply of SST, with greater errors found in regions with a higher 
                         horizontal gradient and dynamic, i.e, coastal region, 
                         Brazil-Malvinas Confluence Zone and Southern Atlantic. 
                         Improvements need to be made in more complex regions, but for 
                         large-scale processes the SST ABI L3 OSTIA performs well.",
            committee = "Coelho, Simone Marilene Sievert da Costa (presidente) and 
                         Arav{\'e}quia, Jos{\'e} Antonio (orientador) and Oliveira, 
                         Nat{\'a}lia Rudorff (orientadora) and Pezzi, Luciano Ponzi and 
                         Assireu, Arcilan Trevenzoli",
         englishtitle = "Evaluation of the sea surface temperature estimated by the 
                         ABI/GOES-16, in the Tropical Atlantic ocean and Southwest",
             language = "pt",
                pages = "117",
                  ibi = "8JMKD3MGP3W34R/428TQ8P",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34R/428TQ8P",
           targetfile = "publicacao_FA provisoria.pdf",
        urlaccessdate = "05 mar. 2021"
}


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