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@Article{CalvettiBNISGHG:2017:QuPrEs,
               author = "Calvetti, Leonardo and Beneti, Cesar and Neundorf, R{\'e}verton 
                         Lu{\'{\i}}s Antunes and Inouye, Rafael Toshio and Santos, Tiago 
                         Noronha dos and Gomes, Ana Maria and Herdies, Dirceu Luis and 
                         Gon{\c{c}}alves, Luis Gustavo Gon{\c{c}}alves de",
          affiliation = "{Universidade Federal de Pelotas} and SIMEPAR and SIMEPAR and 
                         SIMEPAR and SIMEPAR and {Universidade Estadual Paulista (UNESP)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Quantitative precipitation estimation integrated by poisson's 
                         equation using radar mosaic, satellite, and rain gauge network",
              journal = "Journal of Hydrologic Engineering",
                 year = "2017",
               volume = "22",
               number = "5",
                pages = "E5016003",
             abstract = "High-resolution quantitative precipitation estimation (QPE) from 
                         radar and satellite combined with rain gauges is one of the most 
                         important guides for hydrological forecasts. Whereas rain gauges 
                         provide accurate measurement at a point, remote sensing helps to 
                         retrieve the spatial pattern. An algorithm, named Siprec, has been 
                         used to blend rain gauges, radar mosaic data, and satellite 
                         Eumetsat/MPE estimates by using Poissons equation over two basins 
                         in Brazil. The results indicated that Siprec decreased the root 
                         mean square error (RMSE) when compared to radar and satellite 
                         estimates as well as improved the correlation. Most of the errors 
                         were related to precipitation above 
                         10\ \ mm\ h\−110\ \ mm\ h\−1, 
                         due to large spatial variability, typical of deep convection. The 
                         solution of Poissons equation acts directly on the data received 
                         at a certain time, converging the amplitude to the rain gauge 
                         values and keeping the spatial distribution of the radar or 
                         satellite measurement without a priori adjustments. This is an 
                         important advantage in an operational environment because it does 
                         not require frequent processing to update the weights like other 
                         schemes.",
                  doi = "10.1061/(ASCE)HE.1943-5584.0001432",
                  url = "http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0001432",
                 issn = "1084-0699",
                label = "lattes: 6072354470541631 8 CalvettiBNISGHG:2016:QuPrEs",
             language = "en",
           targetfile = "Siprec_poisson_JHE_Calvetti_etal_2016.pdf",
                  url = "http://ascelibrary.org/doi/ref/10.1061/%28ASCE%29HE.1943-5584.0001432",
        urlaccessdate = "04 dez. 2020"
}


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