@Article{MoretoRolEstVanCho:2021: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 = "2021",
               volume = "133",
               number = "2",
                pages = "181--191",
                month = "Apr.",
             abstract = "Agricultural activity is largely influenced 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 different 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",
             language = "en",
           targetfile = "moreto-sugarcane.pdf",
        urlaccessdate = "09 maio 2024"
}