Oliveira, Cristiano Prestrelo deSilva, Maria Leidinice da2022-08-172022-08-172022-06-24SILVA, Maria Leidinice da. Avaliação do impacto das mudanças climáticas na América do Sul Tropical usando downscaling dinâmico: histórico e futuro. 2022. 196f. Tese (Doutorado em Ciências Climáticas) - Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Natal, 2022.https://repositorio.ufrn.br/handle/123456789/49183Several studies have pointed out South America (SA) as one of the continental regions with the highest degree of vulnerability to climate change. Therefore, regionalized simulations with the Regional Climate Modeling system version 4.7 (RegCM4.7) coupled with the Community Land Model version 4.5 (CLM4.5) under the low (RCP2.6) and high (RCP8.5) emissions scenarios that interact with the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (AR5-IPCC) were carried out in tropical SA (TSA). The aim is to evaluate the Added Value (AV) of the regional modeling through dynamic downscaling during the historical period (1986–2005), as well as to analyze the regional aspects projected by the model in reporting the climate change in the far future (2080–2099). In view of this, this research consisted of three main steps: i) initially, the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method – among other analyzes – was used to evaluate and rank the General Circulation Models (GCM) that are part of the Coupled Model Intercomparison Project Phase 5 (CMIP5) when reproducing surface variables over TSA subregions; ii) in addition to demonstrating a selection methodology that avoids less realistic input models, after selecting the GCM, dynamic downscaling was performed on the TSA domain and, consequently, the validation of the simulations; iii) finally, the climatic extremes were evaluated. The climate over the domain of interest was characterized based on the variables of precipitation and near-surface air temperature. The mean climate of the historical period was compared with the monthly dataset of the Climate Research Unit version ts4.02 (CRU). In turn, the Climate Prediction Center (CPC) daily dataset was used to validate climate extremes. The results of the TOPSIS method point to the GCMs BNU-ESM, CSIROACESS1.0, HadGEM-ES, INMCM4, NorESM-ME and MME, as one of the best to represent precipitation and temperature over TSA sub-regions. Taking into account the computational limitations, only HadGEM-ES was selected to direct RegCM4.7 and generate the necessary climate simulations and projections for the following stages of this study. Regarding dynamic downscaling, RegCM4.7 presents AV in the spatial representation of precipitation and temperature over the Northeast region of Brazil and part of the Andes Mountains, mainly in winter. However, it does not adequately represent the precipitation over the Amazon Basin, especially in summer. The mean climate projections indicate the more refined simulation of RegCM4.7 significantly improves the spatial patterns projected from the coarser resolution simulation of HadGEM2-ES and even modifies the precipitation signal in some cases, e.g., in autumn. Regarding temperature, both models project an increase with greater magnitude for RCP8.5. With respect to climate extremes, RegCM4.7 projects more significant changes in precipitation and temperature indices than the conduction HadGEM2-ES, indicating greater sensitivity to changes in extremes. Although some differences and biases still persist, properly configured RegCM4.7 is a viable tool for climate studies.Acesso AbertoClimatologiaCMIP5RegCM4.7Mudanças climáticasEventos extremosdoctoralThesisCNPQ::CIENCIAS EXATAS E DA TERRA