@InProceedings{FinottiSouzCasa:2019:AnCoSa,
               author = "Finotti, Elis{\^a}ngela and Souza, Ronald Buss de and Casagrande, 
                         Fernanda",
          affiliation = "{Universidade Federal do Rio Grande do Sul (UFRGS)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "An{\'a}lise da concentra{\c{c}}{\~a}o sazonal do gelo marinho 
                         ant{\'a}rtico atrav{\'e}s de dados de sensoriamento remoto e do 
                         modelo BESM-AO",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "835--838",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Sensoriamento Remoto de Microondas Passivo, Gelo Marinho 
                         Ant{\'a}rtico, Modelo BESM-OA e Oceano Austral, Passive Microwave 
                         Remote Sensing, Antarctic Sea Ice, BESM-OA Model and Southern 
                         Ocean.",
             abstract = "O gelo marinho {\'e} um componente importante e complexo do 
                         sistema terrestre e {\'e} respons{\'a}vel pela 
                         regula{\c{c}}{\~a}o dos fluxos e das trocas de energia entre o 
                         oceano e a atmosfera. A din{\^a}mica da concentra{\c{c}}{\~a}o 
                         do gelo marinho (sea ice concentration - SIC) influencia o clima e 
                         tamb{\'e}m interage, na escala sin{\'o}tica com a 
                         circula{\c{c}}{\~a}o atmosf{\'e}rica e oce{\^a}nica. Este 
                         trabalho tem como objetivo avaliar a capacidade do modelo BESM-OA 
                         de representar a variabilidade sazonal da SIC. Para isso, 
                         utilizamos dados de sensoriamento remoto e do modelo BESM-OA para 
                         o per{\'{\i}}odo entre 1980 e 2005 para o Oceano Austral. 
                         Conclui-se que, para o experimento hist{\'o}rico do BESM-OA, o 
                         modelo superestima significativamente a SIC (diferen{\c{c}}as 
                         positivas) no per{\'{\i}}odo em que ocorrem os m{\'a}ximos 
                         valores dessa vari{\'a}vel. Para o per{\'{\i}}odo de 
                         m{\'{\i}}nimo SIC, as diferen{\c{c}}as entre os dados de 
                         sensoriamento remoto e do modelo s{\~a}o pequenas e negativas. A 
                         an{\'a}lise preliminar realizada nesse estudo {\'e} extremamente 
                         importante para avaliar o desempenho de modelos clim{\'a}ticos e 
                         possibilitar melhorias na modelagem e previs{\~a}o 
                         clim{\'a}tica. ABSTRACT: The sea ice is an important and complex 
                         component of the earth system and is responsible for regulating 
                         the fluxes and energy changes between the ocean and the 
                         atmosphere. The dynamics of the sea ice concentration (SIC) 
                         influences the climate and also interacts in the synoptic scale 
                         with the atmospheric and oceanic circulation. This work aims to 
                         evaluate the capacity of the BESM-OA model to represent the 
                         seasonal variability of the SIC. For this, we used remote sensing 
                         and BESM-OA data for period between 1980 and 2005 for the Southern 
                         Ocean. We concluded that, for the historical experiment of the 
                         BESM-OA, the model significantly overestimated the SIC (positive 
                         differences) in the period in which the maximum values of this 
                         variable occur. For the SIC's minimum period, the differences 
                         between the remote sensing and the model are small and 
                         negative.The preliminary analysis mede in this study is extremely 
                         important to evaluate the performance of climatic models and to 
                         allow for an improvement in the climatic modeling and forecast.",
  conference-location = "Santos",
      conference-year = "14-17 abril 2019",
                 isbn = "978-85-17-00097-3",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3U4334P",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U4334P",
           targetfile = "97608.pdf",
                 type = "Meteorologia e climatologia",
        urlaccessdate = "28 abr. 2024"
}