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@InProceedings{NascimentoHerdSouzAnge:2010:EvPrOv,
               author = "Nascimento, M G do and Herdies, Dirceu Luis and Souza, Diego 
                         Oliveira de and Angelis, Carlos Frederico",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Evaluation of precipitation over South America in the reanalysis 
                         MERRA",
            booktitle = "Abstracts...",
                 year = "2010",
         organization = "The Meeting of the Americas.",
            publisher = "AGU",
             keywords = "hydrological cycles, budgets, precipitation, climatology, data 
                         assimilation.",
             abstract = "The reanalysis data are an essential tool in the study of weather 
                         and climate variability in the past 15 years. The reanalysis are 
                         nothing more than a merger of a large amount of observational data 
                         with data from numerical modeling. One of the key utilities in a 
                         reanalysis is that the output generated from the model physics 
                         provides data not easily observed, but is consistent with the 
                         analyzed observed data. Knowing that precipitation is one of the 
                         critical components of the balance of moisture and energy, and 
                         that this variable on reanalysis data is highly correlated with 
                         the model physical parameterizations, this work attempts to 
                         quantify the uncertainty of rainfall data between the MERRA 
                         reanalysis and data of precipitation obtained from the GPCP and 
                         TRMM for the period 1999 to 2008. For a better understanding of 
                         the observed data, TRMM and GPCP data were compared, where make 
                         clear a large spatial correlation (0.93) between these two 
                         datasets, with major differences in the tropical region, where 
                         TRMM data have higher values on the Amazon river mouth, equatorial 
                         Pacific Ocean and the Caribbean. On the whole South America this 
                         analisys showed an average error of -0.33 mm/day, showing that the 
                         values observed by TRMM are higher than GPCP. Analysis of the 
                         MERRA data for the entire period showed a good spatial correlation 
                         between the reanalysis data and TRMM (0.77) and GPCP (0.78). It 
                         was also noted that the MERRA data tend to overestimate the values 
                         of precipitation over much of the equatorial region, mainly on the 
                         tropical Atlantic Ocean, and to underestimate the values of 
                         precipitation over southern Brazil. When analyzed seasonally it 
                         was found that the MERRA data had lower spatial correlation in the 
                         seasons that show more convective activity, mainly in summer (0.75 
                         TRMM and GPCP 0.76) and spring (0.72 TRMM and GPCP 0.73). In all 
                         seasons, especially in spring and summer, it was observed that the 
                         MERRA data have difficulties in representing the values of 
                         precipitation over southern Brazil and the La Plata Basin 
                         (underestimating the values) and over the region of tropical 
                         Atlantic Ocean (overestimating the values). More detailed studies 
                         should be conducted to better estimate the errors presented in 
                         this work, but the results make clear that the use of MERRA data 
                         for the southern and northern South America deserve more 
                         attention.",
  conference-location = "Foz do Igua{\c{c}}u, BR",
      conference-year = "8-12 aug 2010",
             language = "en",
        urlaccessdate = "24 jan. 2021"
}


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