@Article{TanajuraSaMiLiBeXi:2014:GeDePr,
               author = "Tanajura, Clemente Augusto Souza and Santana, Alex Novaes and 
                         Mignac, Davi and Lima, Leonardo Nascimento and Belyaev, Konstantin 
                         Pavlovich and Xie, Ji-ping",
          affiliation = "{} and {} and {} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "The REMO ocean data assimilation system into HYCOM (RODAS_H): 
                         general description and preliminary results",
              journal = "Atmospheric and Oceanic Science Letters",
                 year = "2014",
               volume = "7",
               number = "5",
                pages = "464--470",
             keywords = "ocean data assimilation, Ensemble Optimal Interpolation, observing 
                         system experiment, HYCOM, Atlantic Ocean.",
             abstract = "The first version of the Brazilian Oceanographic Modeling and 
                         Observation Network (REMO) ocean data assimilation system into the 
                         Hybrid Coordinate Ocean Model (HYCOM) (RODAS_H) has recently been 
                         constructed for research and operational purposes. The system is 
                         based on a multivariate Ensemble Optimal Interpolation (EnOI) 
                         scheme and considers the high frequency variability of the model 
                         error co-variance matrix. The EnOI can assimilate sea surface 
                         temperature (SST), satellite along-track and gridded sea level 
                         anomalies (SLA), and vertical profiles of temperature (T) and 
                         salinity (S) from Argo. The first observing system experiment was 
                         carried out over the Atlantic Ocean (78°S50°N, 100°W20°E) with 
                         HYCOM forced with atmospheric reanalysis from 1 January to 30 June 
                         2010. Five integrations were performed, including the control run 
                         without assimilation. In the other four, different observations 
                         were assimilated: SST only (A_SST); Argo T-S profiles only 
                         (A_Argo); along-track SLA only (A_SLA); and all data employed in 
                         the previous runs (A_All). The A_SST, A_Argo, and A_SLA runs were 
                         very effective in improving the representation of the assimilated 
                         variables, but they had relatively little impact on the variables 
                         that were not assimilated. In particular, only the assimilation of 
                         S was able to reduce the deviation of S with respect to 
                         observations. Overall, the A_All run produced a good analysis by 
                         reducing the deviation of SST, T, and S with respect to the 
                         control run by 39%, 18%, and 30%, respectively, and by increasing 
                         the correlation of SLA by 81%.",
                  doi = "10.3878/j.issn.1674-2834.14.0011",
                  url = "http://dx.doi.org/10.3878/j.issn.1674-2834.14.0011",
                 issn = "1674-2834",
                label = "lattes: 7758920363746942 4 TanajuraSaMiLiBeXi:2014:GeDePr",
             language = "en",
           targetfile = "The REMO Ocean Data Assimilation System into HYCOM 
                         %28RODAS_H%29%3A General Description and Preliminary Results.pdf",
                  url = "http://159.226.119.58/aosl/article/2014/1674-2834-7-5-464.html",
        urlaccessdate = "01 maio 2024"
}