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Analysis of possible changes in climatic extremes over São Paulo State due to climate change

Grant number: 19/14430-3
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): October 01, 2019
Effective date (End): November 30, 2020
Field of knowledge:Physical Sciences and Mathematics - Geosciences - Meteorology
Principal researcher:Marta Pereira Llopart
Grantee:Renan Muinos Parrode de Godoy
Home Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil


The main anthropogenic influences on the climate are the greenhouse gas (GHG) emissions in the atmosphere mainly through the burning of fossil fuels, causing an increase in the air temperature in the lower troposphere. Today, societies are focused on improving living standards and economic growth, which depend directly on non-renewable energy consumption, and the question arises as to where adaptation policies will be needed in the context of climate change. Brazil. One of the consequences of global warming is the change in the intensity and frequency of extreme weather events, such as hot and cold waves, and floods and droughts, which can greatly affect natural ecosystems and diverse sectors of society. the question arises that is extremely relevant to decision makers: which regions are most vulnerable to extreme events of precipitation and air temperature under climate change? Therefore, the main objective of this research project is to evaluate climatic extremes related to air temperature (heat waves) and precipitation (dry and rainy extremes) for the present climate (1975-2005) and future (2070-2100) in the State of São Paulo through regional climate projections that are part of the CORDEX REgCM hyper-MAtrix experiment (CREMA) and consider the GHG emissions scenario RCP 8.5. The main differential of this project is the use of several regional climate projections, which allows to better analyze the signal of change from climatic extremes to the future climate in relation to the uncertainties associated to the model. This study is expected to provide relevant contributions to impact and adaptation issues due to climate change.

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