| Grant number: | 24/05084-2 |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| Start date: | May 01, 2024 |
| End date: | June 30, 2025 |
| Field of knowledge: | Physical Sciences and Mathematics - Geosciences - Meteorology |
| Agreement: | CNPq - INCTs |
| Principal Investigator: | Paulo Nobre |
| Grantee: | Priscila da Silva Tavares |
| Host Institution: | Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia e Inovação (Brasil). São José dos Campos , SP, Brazil |
| Associated research grant: | 14/50848-9 - INCT 2014: INCT for Climate Change, AP.PFPMCG.TEM |
Abstract Climate change can occur due to changes in greenhouse gas (GHG) emissions at a global level and due to changes in land use or land cover that are at a local level. Therefore, to simulate the impacts on climate due to changes in land use, it is necessary to use a climate model with high spatial resolution. In this project, the Eta Model is used, as it has been developed toward a model of the Earth system that can be applied on multiple spatial scales (Gomes et al. 2023). Maps of different land uses or cover in Southeast Brazil will be constructed. One of the scenarios to be applied is the growth of urban areas, while another is the restoration of the Atlantic Forest (Mata Atlântica). The maps will be prepared for input into the Eta model. Continuous simulations will be developed for at least 30 years at high resolution, 5 km x 5 km, in the region. The model´s ability to reproduce the current climate will be assessed. Climate change projections will be generated according to different SSP (Shared Socioeconomic Pathways) emission scenarios and different land use change scenarios for at least the beginning and middle of the 21st century. The impacts on climate due to different scenarios constructed at high spatial resolution will be analyzed. In addition to analyzing changes in the climate variables, changes in the frequency and intensity of severe weather events will also be analyzed. Climate variables will be prepared for input in several themes. For example, for biodiversity, projections will be prepared for input into ecology models to analyze species at risk of extinction. Health indicators such as heat waves, heat indices, apparent thermal temperatures, extreme temperatures, and dryness events will be estimated to support studies of the impacts on the health sector. Furthermore, climate variables will be prepared for application in hydrology models and for conducting studies related to renewable energy. This project can contribute to the construction of several impact indicators to support adaptation studies in different socioeconomic sectors in Southeast Brazil and, in particular, in the state of Sao Paulo. The constructed dataset will be made available through an open repository, such as the CNPq LattesData. | |
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