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@Article{RozanteRaSiFeAlSi:2020:TeVa,
               author = "Rozante, Jos{\'e} Roberto and Ramirez Gutierrez, Enver and Silva 
                         Dias, Pedro Leite da and Fernandes, Alex de Almeida and Alvim, 
                         D{\'e}bora Souza and Silva, Vin{\'{\i}}cius Matoso",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade de 
                         S{\~a}o Paulo (USP)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade Federal do ABC (UFABC)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Development of an index for frost prediction: technique and 
                         validation",
              journal = "Meteorological Applications",
                 year = "2020",
               volume = "27",
               number = "1",
                pages = "e1807",
                month = "Jan.",
             keywords = "frost index, frost prediction, temperature.",
             abstract = "An index for frost prediction is proposed and calibrated against 
                         observations. It takes into account: (1) the main meteorological 
                         variables that favour or oppose to frost; (2) weights attributed 
                         to these variables; and (3) means and standard deviations of these 
                         variables, only for cases in which frost occurs, as defined by 
                         observation of temperatures that are <= 6 degrees C. The 
                         meteorological variables used for the frost index IG (from the 
                         Portuguese, indice de Geada) are numerically predicted by a 
                         regional weather forecast model. An outcome of the calibration 
                         processes results is that temperature has the largest 
                         contribution, followed by pressure and winds, while the other 
                         variables were adjusted to obey the restriction that the sum of 
                         weights are equal to 1. After index calibration and threshold 
                         determination, the method was applied for the 2017 winter season, 
                         and a case study for May 2018 was also considered. In order to 
                         verify whether the new index can satisfactorily contribute to the 
                         weather forecasting, the results using the IG were compared with 
                         the temperature outputs of the numerical regional model. It was 
                         found that for three selected areas, and for all the forecasted 
                         hours, the IG produces better results than the model's direct 
                         temperature forecasts. Thus, it was concluded that the use of the 
                         IG in an operational environment potentially provides considerable 
                         improvement in the predictive skill of frost events.",
                  doi = "10.1002/met.1807",
                  url = "http://dx.doi.org/10.1002/met.1807",
                 issn = "1350-4827",
                label = "self-archiving-INPE-MCTIC-GOV-BR",
             language = "en",
           targetfile = "rozante_development.pdf",
        urlaccessdate = "14 abr. 2021"
}


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