@Article{MoretoRolEstVanCho:2020:SuDeSu,
               author = "Moreto, Victor B. and Rolim, Glauco de S. and Esteves, Jo{\~a}o 
                         T. and Vanuytrecht, Eline and Chou, Sin Chan",
          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 
                         {Flemish Institute for Technological Research (VITO)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Sugarcane decision-making support using Eta Model precipitation 
                         forecasts",
              journal = "Meteorology and Atmospheric Physics",
                 year = "2020",
               volume = "132",
               number = "3",
                pages = "1--2",
                 note = "{Setores de Atividade: Pesquisa e desenvolvimento 
                         cient{\'{\i}}fico.}",
             keywords = "Avaliacao de Previsao, erro de previs{\~a}o, Modelo Eta.",
             abstract = "Agricultural activity is largely infuenced by climatic conditions. 
                         Rainfall is essential for crop production, and precipitation 
                         events also interfere with soil preparation, planting, application 
                         of pesticides and harvesting. Weather forecast models are tools to 
                         facilitate decision making for agricultural activities, hence high 
                         accuracy is desired. Farmers often criticize the accuracy of 
                         weather forecasts, which sometimes fail to predict precipitation 
                         events, leading to yield loss and environmental harm. In this 
                         study, precipitation forecasts of the Eta Model were evaluated for 
                         28 of Brazils most productive sugarcane areas, considering a grid 
                         of 15×15 km. Using a combination of diferent indicators of 
                         forecast success, observed and forecasted daily precipitation data 
                         were compared for consecutive days of all 10-day periods in a 
                         course of 6 years (20052010). Skill scores and performance 
                         diagrams based on the indicators were used to evaluate the 
                         goodness and robustness of the model forecasts. The Eta Model 
                         forecasts showed overall accuracies ranging between 55 and 71% for 
                         the Atlantic forest biomes (located North-West and South-East of 
                         S{\~a}o Paulo) and the Cerrado biomes (located in the Goi{\'a}s 
                         State and in the Center-North S{\~a}o Paulo State), respectively. 
                         The forecasts were most reliable for up to 4 days, showing an 
                         accuracy of 60%. Forecasts for periods of more than 4 days had an 
                         average accuracy of 4050%. The probability of detecting rainfall 
                         correctly was the strongest characteristic of Eta Model, with more 
                         than 70% hits.",
                  doi = "10.1007/s00703-020-00738-1",
                  url = "http://dx.doi.org/10.1007/s00703-020-00738-1",
                 issn = "0177-7971",
                label = "lattes: 4336175279058172 5 MoretoRolEstVanCha:2020:SuDeSu",
             language = "en",
           targetfile = "moreto_sugarcane.pdf",
        urlaccessdate = "09 maio 2024"
}