Oliveira, Cristiano Prestrelo deMedeiros, Felipe Jeferson de2024-11-182024-11-182024-08-28MEDEIROS, Felipe Jeferson de. Extremos climáticos de precipitação e suas projeções sobre o Brasil utilizando as gerações de modelos do CMIP. Orientador: Dr. Cristiano Prestrelo de Oliveira. 2024. 146f. Tese (Doutorado em Ciências Climáticas) - Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Natal, 2024.https://repositorio.ufrn.br/handle/123456789/60654The occurrence of extreme climate events usually causes numerous economic and social losses, especially in vulnerable and low adaptive capacity areas, such as Brazil. In this context, the main goal of this study is to investigate the pattern and trends of the extreme precipitation climate events and their future changes during the 21st century using projections from the Coupled Model Intercomparison Project (CMIP). Within this scope, several General Circulation Models (GCMs) from different generations of CMIP have been used. With the daily data from these models, extreme weather conditions were calculated, such as the number of dry and heavy rainfall days, and several extreme precipitation climate indices suggested by the Expert Team on Climate Change Detection and Indices (ETCCDI) for the historical period (1981-2005) and their projections until the end of the 21st century considering different emissions scenarios. Statistical metrics such as Mean Bias Error (MBE), Percent Bias (PBIAS), RMSE-observations standard deviation ratio (RSR), refined index of agreement (dr ) and Pearson correlation coefficient (CORR). Furthermore, the comprehensive model rank (Mr rank) was applied to analyze whether the evolution of the CMIP models provided an improvement in the simulation of extreme climate events. The results indicated that the number of dry days are project to increase over the entire NEB territory, especially during DJF and MAM and more pronounce in the east coast, with projections that these conditions will be more severe under the SSP5-8.5 scenario. The number of dry days may increase up to 15%. For heavy rainfall days, although the results indicate that the number of days with heavy precipitation will be more frequent in the future (the increase can exceed 140%), the analysis show that under the low (SSP2-4.5) or intermediate (SSP3-7.0) forcing scenarios the HRD tends to be higher than in the most pessimistic scenario (SSP5-8.5). Regarding the performance of extreme climate indices, results reveal that CDD are the most challenging precipitation index to be simulated, while the best ones were PRCPTOT and R20mm. The model performance shows that CMIP3 has the best skill for Northeast Brazil, CMIP5 for Center-West, and CMIP6 for North, Southeast and South regions. Thus, at least for Brazil, the evolution of the ESMs from CMIP did not reflect a substantial improvement in the representation of precipitation climate extremes over all Brazilian regions. In addition, all the models across CMIP generations have difficulty in simulating the observed trends. This indicate that improvements are still needed in CMIP models. Despite the relative low performance in the historical climate, the climate projections indicate a consensus signal among most of precipitation climate extremes and CMIP generations, which increase its reliability. Overall, the extreme precipitation events are projected to be more severe, frequent, and long-lasting in all Brazilian regions, with the more pronounce changes expected in heavy rainfall and severe droughts in the central northern portion of Brazil and in the southern sector.Acesso AbertoClimatologiaÍndices climáticosEventos extremosMudanças climáticasIPCCdoctoralThesisCNPQ::CIENCIAS EXATAS E DA TERRA