Sugarcane decision-making support using Eta Model precipitation forecasts

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Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorFlemish Institute for Technological Research (VITO)-
Autor(es): dc.contributorKU Leuven-
Autor(es): dc.contributorAv. dos Astronautas-
Autor(es): dc.creatorMoreto, Victor B.-
Autor(es): dc.creatorRolim, Glauco de S.-
Autor(es): dc.creatorEsteves, João T.-
Autor(es): dc.creatorVanuytrecht, Eline-
Autor(es): dc.creatorChou, Sin Chan-
Data de aceite: dc.date.accessioned2022-08-04T22:08:38Z-
Data de disponibilização: dc.date.available2022-08-04T22:08:38Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2021-04-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/s00703-020-00738-1-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/221470-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/221470-
Descrição: dc.descriptionAgricultural 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 Brazil’s 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 (2005–2010). 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 São Paulo) and the Cerrado biomes (located in the Goiás State and in the Center-North São 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 40–50%. The probability of detecting rainfall correctly was the strongest characteristic of Eta Model, with more than 70% hits.-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionDepartment of Mathematical Sciences Faculty of Agricultural and Veterinarian Sciences University of São Paulo State, Prof. Paulo Donato Castellane-
Descrição: dc.descriptionFlemish Institute for Technological Research (VITO), Boeretang 200-
Descrição: dc.descriptionDepartment of Earth and Environmental Sciences KU Leuven, Celestijnenlaan 200E-
Descrição: dc.descriptionCenter for Weather Forecasts and Climate Studies National Institute for Space Research Av. dos Astronautas-
Formato: dc.format181-191-
Idioma: dc.languageen-
Relação: dc.relationMeteorology and Atmospheric Physics-
???dc.source???: dc.sourceScopus-
Título: dc.titleSugarcane decision-making support using Eta Model precipitation forecasts-
Tipo de arquivo: dc.typelivro digital-
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