O Using Xgboost models dor daily rainfall prediction
- Rafael Grecco Sanches University of São Paulo https://orcid.org/0000-0003-2471-5070
- Dr. School of Computer Science, Federal University of Uberlandia (UFU), Minas Gerais, Brazil https://orcid.org/0000-0002-8176-8040
- Dr. Department of Environmental Sciences (DCAM), Federal University of São Carlos (UFSCar), São Carlos, Brazil https://orcid.org/0000-0001-8218-6803
- Dr. Environmental Engineering Department, Federal University of Rondônia (UNIR), Rondônia, Brazil https://orcid.org/0000-0001-6794-6026
- Dr. aSão Carlos School of Engineering, University of São Paulo (USP), São Paulo, Brazil https://orcid.org/0000-0002-3952-8238
- Dr. Department of Environmental Sciences (DCAM), Federal University of São Carlos (UFSCar), São Carlos, Brazil https://orcid.org/0000-0001-5419-323X
- O Faculty of Civil Engineering, Federal University of Uberlandia (UFU), Minas Gerais, Brazil
Abstract
Machine learning models for predicting daily precipitation have gained traction in recent years. Understanding the benefits of using this technology in different regions is a relevant research topic. For this reason, this study aims to evaluate daily precipitation estimated forecasts from climate data between 1983 and 2019 in Itirapina, São Paulo, Brazil. We used a novel machine learning algorithm, XGBoost (eXtreme Gradient Boosting), to create several daily precipitation prediction models. Two tasks were modeled: the occurrence of daily precipitation (classification) and the amount of daily precipitation (regression). The results revealed that the occurrence of daily precipitation could be predicted with an accuracy of around 90%. Additionally, models were developed to predict the amount of daily precipitation with error rates of around 3mm. We observed that precipitation in the study area is directly associated with solar radiation, and estimated forecasts of precipitation and the corresponding months are characteristic of the tropical climate.
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Author Biographies
Possui graduação em Matemática pela Universidade Federal de São Carlos (2005), mestrado em Engenharia Elétrica pela Universidade Estadual de Campinas (2009) e doutorado em Engenharia Elétrica pela Universidade Estadual de Campinas (2013). Durante seu doutorado, passou seis meses como pesquisador visitante no CyQL (Laboratório de Quantificação de Segurança Cibernética) da Universidade de Maryland, EUA.
Atualmente é professor adjunto da Faculdade de Computação (FACOM) da Universidade Federal de Uberlândia (UFU).
Bachelor's degree in Geography from the Federal University of Alfenas-MG (UNIFAL-MG). Master's and PhD in Environmental Engineering Sciences from the University of São Paulo (USP). Post-doctorate in progress at the Department of Environmental Sciences (DCAm) of the Federal University of São Carlos (UFSCar). I conduct research in the areas of Climatology and Geotechnologies applied to the environment. I have experience as a teacher in the area of Geography education at elementary and high school levels.
Adjunct Professor in the Department of Environmental Engineering at the Federal University of Rondônia - Ji-Paraná Campus, promoting quality public education and popularization of science. Coordinator of the Laboratory of Geomatics and Statistics (LABGET - UNIR) and leader of the Environmental Engineering Research Group (GPEA-UNIR). I am a data scientist who transforms multi-sensor remote sensing products (optical and radar) and census data into spatial information to respond to complex environmental problems related to climate science, forest fragmentation, water resources, and public health. Post-Doctorate at San Diego State University - USA (2023). Post-Doctorate in Natural Resources - UFMS (2020). PhD in Environmental Engineering Sciences - EESC/USP (2017) with a sandwich period at the University of Michigan - USA. Master in Agricultural Sciences (2014), Environmental Sanitarian (2011) and Environmental Manager (2013) from IFGoiano - Campus Rio Verde. Mastery of Google Earth Engine, R and Python for spatial data analysis.
He holds a bachelor's and a degree in Geography from UTPR. He holds a master's degree in Science from USP (2014), with a study on Urban Climate in the city of São Carlos-SP. He holds a PhD in Science from USP (2018), whose research focused on the performance of atmospheric systems and the rainfall distribution of the state of Goiás and the Federal District. He was a collaborating professor in the Postgraduate Program in Environmental Engineering Sciences at the University of São Paulo, offering two courses: [SEA5916] Introduction to the Dynamic Study of Climate Generalities and Specificities and [SEA5862] Climatology Applied to the Environment; he is an advisor for academic master's degrees in the research line Climatology Applied to the Environment. He taught courses related to geosciences at the State University of Goiás and at the Barretos Educational Foundation, in undergraduate and graduate courses. Scientific advisor and visiting researcher at the National Laboratory for Sustainable Living and Communities of the Faculty of Architecture of the Autonomous University of Chiapas (UNACH - Mexico). He is a member of the Brazilian Association of Climatology (ABClima), serving as Director-Secretary (2018-2021) and of the Deliberative Council (2023-2025; 2021-2023; 2016-2018 and 2014-2016). Member of the research group Readings and Analysis in Hydrography, Climatology and Cartography (UFRN/CNPq) and of the Locality Study Group (USP/CNPq). He has teaching and professional experience in the area of Geosciences, with interests in the themes of Geography, Climatology, Atmospheric circulation of South America, Comfort and Technology of the built environment, Engineering Geology and Environmental Geotechnics. Reviewer for national and international scientific journals.
He is an associate professor at the Department of Environmental Sciences (DCAm) and a permanent professor at the Postgraduate Program in Environmental Sciences at the Federal University of São Carlos (UFSCar), where he has worked since 2013. He has a degree in Geography from the Federal University of Santa Maria (2006), a master's degree (2008) and a doctorate (2012) in Space Geophysics (concentration in Atmospheric Sciences) from the National Institute for Space Research (INPE). He was a postdoctoral fellow at the atmospheric electricity group (ELAT) at INPE until early 2013. He was a visiting researcher at INRAE (Institut national de recherche pour l'agriculture, l'alimentation et l'environnement), Antony, France, between 2019 and 2020. He works mainly in the area of atmospheric sciences and GIS, with an emphasis on topics such as: climatology and hydrology, storm formation, hydrological modeling, remote sensing and geoprocessing.
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