@Article{PereiraFoVVRGCSLGOZCADA:2019:StToIn,
               author = "Pereira Filho, Augusto Jos{\'e} and Vemado, Felipe and Vemado, 
                         Guilherme and Reis, F{\'a}bio Augusto Gomes Vieira and Giordano, 
                         Lucila do Carmo and Cerri, Rodrigo Irineu and Santos, Cl{\'a}udia 
                         Cristina dos and Lopes, Eymar Silva Sampaio and Gramani, Marcelo 
                         Fisher and Ogura, Agostinho Tadashi and Zaine, Jos{\'e} Eduardo 
                         and Cerri, Leandro Eugenio da Silva and Augusto Filho, Oswaldo and 
                         D'Affonseca, Fernando Mazo and Amaral, Cl{\'a}udio dos Santos",
          affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {Universidade de 
                         S{\~a}o Paulo (USP)} and {Universidade de S{\~a}o Paulo (USP)} 
                         and {Universidade Estadual Paulista (UNESP)} and {Universidade 
                         Estadual Paulista (UNESP)} and {Universidade Estadual Paulista 
                         (UNESP)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto de Pesquisas Tecnol{\'o}gicas (IPT)} and {Instituto de 
                         Pesquisas Tecnol{\'o}gicas (IPT)} and {Universidade Estadual 
                         Paulista (UNESP)} and {Universidade Estadual Paulista (UNESP)} and 
                         {Universidade de S{\~a}o Paulo (USP)} and {Eberhard Karls 
                         Universit{\"a}t T{\"u}bingen} and {Petrobras Research and 
                         Development Center}",
                title = "A step towards integrating CMORPH precipitation estimation with 
                         rain gauge measurements",
              journal = "Advances in Meteorology",
                 year = "2019",
               volume = "2018",
                pages = "2095304",
             abstract = "Accurate daily rainfall estimation is required in several 
                         applications such as in hydrology, hydrometeorology, water 
                         resources management, geomorphology, civil protection, and 
                         agriculture, among others. CMORPH daily rainfall estimations were 
                         integrated with rain gauge measurements in Brazil between 2000 and 
                         2015, in order to reduce daily rainfall estimation errors by means 
                         of the statistical objective analysis scheme (SOAS). Early 
                         comparisons indicated high discrepancies between daily rain gauge 
                         rainfall measurements and respective CMORPH areal rainfall 
                         accumulation estimates that tended to be reduced with accumulation 
                         time span (e.g., yearly accumulation). Current results show CMORPH 
                         systematically underestimates daily rainfall accumulation along 
                         the coastal areas. The normalized error variance (NEXERVA) is 
                         higher in sparsely gauged areas at Brazilian North and 
                         Central-West regions. Monthly areal rainfall averages and standard 
                         deviation were obtained for eleven Brazilian watersheds. While an 
                         overall negative tendency (3 mm·h \−1 ) was estimated, the 
                         Amazon watershed presented a long-term positive tendency. Monthly 
                         areal mean precipitation and respective spatial standard deviation 
                         closely follow a power-law relationship for data-rich watersheds, 
                         i.e., with denser rain gauge networks. Daily SOAS rainfall 
                         accumulation was also used to calculate the spatial distribution 
                         of frequencies of 3-day rainfall episodes greater than 100 mm. 
                         Frequencies greater than 3% were identified downwind of the 
                         Peruvian Andes, the Bolivian Amazon Basin, and the La Plata Basin, 
                         as well as along the Brazilian coast, where landslides are 
                         recurrently triggered by precipitation.",
                  doi = "10.1155/2018/2095304",
                  url = "http://dx.doi.org/10.1155/2018/2095304",
                 issn = "1687-9309",
             language = "en",
           targetfile = "2095304.pdf",
        urlaccessdate = "28 abr. 2024"
}