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@Article{AravéquiaSzFeKaKuKo:2011:EvStAs,
               author = "Arav{\'e}quia, Jos{\'e} Antonio and Szunyogh, Istvan and Fertig, 
                         Elana J. and Kalnay, Eugenia and Kuhl, David and Kostelich, Eric 
                         J.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and Texas A\&M 
                         University, College Station, Texas and John Hopkins University, 
                         Baltimore, Maryland and University of Maryland, College Park, 
                         College Park, Maryland and Naval Research Laboratory, Washington, 
                         D.C. and Arizona State University, Tempe, Arizona",
                title = "Evaluation of a Strategy for the Assimilation of Satellite 
                         Radiance Observations with the Local Ensemble Transform Kalman 
                         Filter",
              journal = "Monthly Weather Review",
                 year = "2011",
               volume = "139",
               number = "6",
                pages = "1932--1951",
                month = "June",
             keywords = "assimila{\c{c}}{\~a}o de dados, dados de sat{\'e}lite, 
                         AIRS/AMSU, Filtro de Kalman.",
             abstract = "This paper evaluates a strategy for the assimilation of satellite 
                         radiance observations with the local ensemble transform Kalman 
                         filter (LETKF) data assimilation scheme. The assimilation strategy 
                         includes a mechanism to select the radiance observations that are 
                         assimilated at a given grid point and an ensemblebased observation 
                         bias-correction technique. Numerical experiments are carried out 
                         with a reduced (T62L28) resolution version of the model component 
                         of the National Centers for Environmental Prediction (NCEP) Global 
                         Forecast System (GFS). The observations used for the evaluation of 
                         the assimilation strategy are AMSU-A level 1B brightness 
                         temperature data from the Earth Observing System (EOS) Aqua 
                         spacecraft. The assimilation of these observations, in addition to 
                         all operationally assimilated nonradiance observations, leads to a 
                         statistically significant improvement of both the temperature and 
                         wind analysis in the Southern Hemisphere. This result suggests 
                         that the LETKF, combinedwith the proposed data assimilation 
                         strategy for the assimilation of satellite radiance observations, 
                         can efficiently extract information from radiance observations.",
                  doi = "10.1175/2010MWR3515.1",
                  url = "http://dx.doi.org/10.1175/2010MWR3515.1",
                 issn = "0027-0644",
                label = "lattes: 4485209823374151 1 Arav{\'e}quiaSzFeKaKuKo:2011:EvStAs",
             language = "en",
           targetfile = "Aravequia_Evaluation of a Strategy.pdf",
        urlaccessdate = "18 jan. 2021"
}


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