@Article{RampazoPicoCava:2019:CoDaMe,
               author = "Rampazo, Nuria Aparecida Miatto and Picoli, Michelle Cristina 
                         Ara{\'u}jo and Cavaliero, Carla Kazue Nakao",
          affiliation = "{Universidade Estadual de Campinas (UNICAMP)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Compara{\c{c}}{\~a}o entre dados meteorol{\'o}gicos 
                         provenientes de sensoriamento remoto (modelados e de 
                         sat{\'e}lites) e de esta{\c{c}}{\~o}es de superf{\'{\i}}cie",
              journal = "Revista Brasileira de Geografia F{\'{\i}}sica",
                 year = "2019",
               volume = "12",
               number = "2",
                pages = "412--426",
             keywords = "CERES, CM SAF, GLDAS, PERSIANN, ECMWF.",
             abstract = "Dados meteorol{\'o}gicos obtidos por sensoriamento remoto 
                         s{\~a}o uma alternativa para suprir a escassez de 
                         informa{\c{c}}{\~o}es provindas de esta{\c{c}}{\~o}es 
                         meteorol{\'o}gicas convencionais e autom{\'a}ticas. O objetivo 
                         deste trabalho consistiu em comparar dados meteorol{\'o}gicos 
                         derivados de sat{\'e}lites (CERES, GLDAS, CM SAF) e modelos 
                         (PERSIANN, ECMWF) com dados observados em 31 esta{\c{c}}{\~o}es 
                         meteorol{\'o}gicas (INMET) do estado de S{\~a}o Paulo, no 
                         per{\'{\i}}odo de janeiro de 2015 a junho de 2016. Para 
                         verificar a efici{\^e}ncia dos dados oriundos de modelos e 
                         sat{\'e}lites em rela{\c{c}}{\~a}o aos dados de 
                         esta{\c{c}}{\~o}es meteorol{\'o}gicas, foram calculados o teste 
                         de normalidade de Shapiro-Wilk, coeficiente de 
                         correla{\c{c}}{\~a}o de Spearman, Erro M{\'e}dio (mean error, 
                         ME), Erro M{\'e}dio Absoluto (mean absolute error, MAE) e 
                         {\'{\I}}ndice de Concord{\^a}ncia de Willmott modificado (d1). 
                         De modo geral, os resultados obtidos atrav{\'e}s dos testes 
                         estat{\'{\i}}sticos indicaram que as estimativas fornecidas 
                         pelos produtos ou dados de modelos analisados s{\~a}o 
                         alternativas adequadas para aplica{\c{c}}{\~a}o em estudos 
                         clim{\'a}ticos, com exce{\c{c}}{\~a}o do dado de umidade 
                         relativa, que n{\~a}o apresentou boa exatid{\~a}o em 
                         rela{\c{c}}{\~a}o aos dados de esta{\c{c}}{\~a}o 
                         meteorol{\'o}gica. ABSTRACT: Meteorological data obtained by 
                         remote sensing are an alternative to supply the gap of information 
                         proceeded from conventional and automatic weather stations. The 
                         aim of this study was to compare meteorological data derived from 
                         satellites (CERES, GLDAS, CM SAF) and models (PERSIANN, ECMWF) 
                         with observed data in 31 weather stations (INMET) of the state of 
                         S{\~a}o Paulo, during the period January 2015 to June 2016. The 
                         efficiency of the data from models and satellites in relation to 
                         weather stations data was evaluated by the following tests: 
                         Shapiro-Wilk normality test, Spearmans correlation, mean error 
                         (ME), mean absolute error (MAE) and modified Willmott index of 
                         agreement (d1). In general, the results obtained through the 
                         statistical tests indicated that the estimates provided by the 
                         analyzed products or data from models are suitable alternatives 
                         for application in climatic studies, with the exception of the 
                         relative humidity data, which did not show good accuracy in 
                         relation to weather station data.",
                 issn = "1984-2295",
             language = "en",
           targetfile = "236588-142598-1-PB.pdf",
        urlaccessdate = "26 abr. 2024"
}