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@InProceedings{GherardiMoraKrug:2015:DeMoPr,
               author = "Gherardi, Douglas Francisco Marcolino and Moraes, Luiz Eduardo de 
                         Souza and Krug, Lilian Anne",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Desenvolvimento de um modelo previs{\~a}o do branqueamento de 
                         corais em escala global",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2333--2340",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Global coral bleaching episodes as those reported in 1982-83 and 
                         1997-98, showed significant intra-regional differences in 
                         intensity. These bleaching events are generally associated to 
                         climatic forcing, namely thermal anomalies triggered by El Niņo 
                         events. Evidences show that regional scale environmental 
                         variability is one important component that determine the severity 
                         of coral bleaching outbrakes. The combined use of remote sensing 
                         and model reanalysis data with probabilistic graphical models 
                         forms the basis of a process oriented model used to predict 
                         bleaching intensity. This model scheme was first applied to 
                         back-predict bleaching intensity in seven reef sites across Bahia 
                         state coast in Brazil. There is now an ongoning research 
                         inicitative aimed at testing the robustness of this approach in 
                         two areas within the Caribbean region, using bleaching data from 
                         the Reefbase Project. Area 1 encopassing Yucat{\'a}n and Belize, 
                         and Area 2 including Florida, Bahamas, Cuba, Jamaica, Haiti, 
                         Dominican Republic and Puerto Rico. We have achieved a predictive 
                         rate for bleaching of up to 88% with a clear dependence of the 
                         five-day accumulated sea surface temperature (SST) and a secondary 
                         influence of the wind regime. Area 1 of the Caribbean showed a 
                         clear bleaching dependence on the five-day maximum SST, surface 
                         salinity and the El Niņo Multivariate Index (MEI). Area 2 showed 
                         that bleaching is conditionally dependent on the zonal surface 
                         current and wind fields and with MEI. These results give a good 
                         indication that the increase in the conditional dependencies, 
                         compared to the Bahia experiment will contribute to more robust 
                         predictions and acceptable prediction rates.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "474",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM49SQ",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3JM49SQ",
           targetfile = "p0474.pdf",
                 type = "Sistemas marinhos costeiros",
        urlaccessdate = "02 dez. 2020"
}


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