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@Article{CamposSapuLimaFerr:2018:SeNuWe,
               author = "Campos, Thamiris Luisa de Oliveira Brand{\~a}o and Sapucci, Luiz 
                         Fernando and Lima, Wagner and Ferreira, Douglas Silva",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and Climatempo and 
                         {Instituto Tecnol{\'o}gico Vale (ITV)}",
                title = "Sensitivity of numerical weather prediction to the choice of 
                         variable for atmospheric moisture analysis into the Brazilian 
                         global model data assimilation system",
              journal = "Atmosphere",
                 year = "2018",
               volume = "9",
               number = "4",
                pages = "e123",
                month = "Mar.",
             keywords = ": atmospheric water vapor, numerical weather prediction, 
                         variational data assimilation, moisture control variable, 
                         pseudo-relative humidity, normalized relative humidity.",
             abstract = "Due to the high spatial and temporal variability of atmospheric 
                         water vapor associated with the deficient methodologies used in 
                         its quantification and the imperfect physics parameterizations 
                         incorporated in the models, there are significant uncertainties in 
                         characterizing the moisture field. The process responsible for 
                         incorporating the information provided by observation into the 
                         numerical weather prediction is denominated data assimilation. The 
                         best result in atmospheric moisture depend on the correct choice 
                         of the moisture control variable. Normalized relative humidity and 
                         pseudo-relative humidity are the variables usually used by the 
                         main weather prediction centers. The objective of this study is to 
                         assess the sensibility of the Center for Weather Forecast and 
                         Climate Studies to choose moisture control variable in the data 
                         assimilation scheme. Experiments using these variables are carried 
                         out. The results show that the pseudo-relative humidity improves 
                         the variables that depend on temperature values but damage the 
                         moisture field. The opposite results show when the simulation used 
                         the normalized relative humidity. These experiments suggest that 
                         the pseudo-relative humidity should be used in the cyclical 
                         process of data assimilation and the normalized relative humidity 
                         should be used in non-cyclic process (e.g., nowcasting application 
                         in high resolution).",
                  doi = "10.3390/atmos9040123",
                  url = "http://dx.doi.org/10.3390/atmos9040123",
                 issn = "2073-4433",
             language = "en",
           targetfile = "campos_sensitivity.pdf",
        urlaccessdate = "24 nov. 2020"
}


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