@InProceedings{LimaPezzPenn:2017:InInAs,
               author = "Lima, Leonardo Nascimento and Pezzi, Luciano Ponzi and Penny, 
                         Stephen Gregory",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Uma investiga{\c{c}}{\~a}o das incertezas associadas {\`a} 
                         modelagem num{\'e}rica dos oceanos atrav{\'e}s de experimentos 
                         de previs{\~a}o e assimila{\c{c}}{\~a}o de dados por conjuntos 
                         no Atl{\^a}ntico Sudoeste",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6233--6240",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Numerical ocean models incorporate errors originating from 
                         different sources (e.g. atmospheric forcing, physics 
                         parameterizations, boundary conditions, bathymetry, numerical 
                         error). Data assimilation provides an important tool for 
                         correcting the numerical representation generated by the ocean 
                         model itself. In this study, ensemble experiments were performed 
                         by using the Regional Ocean Modeling System (ROMS) in the 
                         Southwest Atlantic Ocean (55ºS 5ºS; 70ºW 20ºW), with the aim to 
                         investigate uncertainties in the ocean state that derived from 
                         perturbations in atmospheric forcing and ocean bathymetry. 
                         Ensemble experiments that incorporated different atmospheric 
                         perturbations exhibited the main qualitative differences between 
                         the members during the first months of integration. The wind 
                         component perturbations dominated and provoked the greatest impact 
                         in the ocean ensemble spread as compared with other atmospheric 
                         variables. Even though as a terrain-following vertical coordinate 
                         model, ROMS proved to be more sensitive to perturbations in 
                         bathymetry, particularly in shallow waters. Next, the Local 
                         Ensemble Transform Kalman Filter (LETKF) was applied to ROMS to 
                         examine the impact of observed temperature and salinity (TS) 
                         profiles on a regional ocean analysis. The assimilation of TS 
                         profiles improved the thermohaline representation. For example, 
                         the area-averaged root mean square deviation of temperature was 
                         2.30ºC for the free model run and was reduced to 0.95°C for the 
                         LETKF analyses. The next step will be to assimilate the Sea 
                         Surface Temperature (SST) and Absolute Dynamic Topography (ADT) 
                         observation data to provide further constraints on the ocean 
                         mesoscale in the study region.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59347",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMCGU",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMCGU",
           targetfile = "59347.pdf",
                 type = "Oceanografia",
        urlaccessdate = "27 abr. 2024"
}