Analyses and climate forecasts indicate significant changes in climate elements, particularly the global mean temperature, and variations in rainfall patterns, which can have profound effects on ecosystems and agriculture. This study aims to assess the impacts of climate change on the Brazilian territory using the Köppen-Geiger (1936) climate classification. Climate data were analyzed at 4,942 locations, encompassing municipalities in Brazil from 1989 to 2019. These data were obtained from the NASA/POWER platform and complemented with monthly temperature and rainfall projections from the BCC-CSM1-1 model, part of the CMIP5 (Coupled Model Intercomparison Project Phase 5), under four emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) for the periods 2041-2060 and 2061-2080. The findings reveal a temperature increase across all scenarios, with RCP 8.5 indicating the most significant rise, reaching 4.30 and 5.42 °C for the periods 2041-2060 and 2061-2080, respectively. Additionally, the least rainy month of the year exhibits precipitation values exceeding 60 mm, leading to the dominance of the tropical climate typology “A” in 82.94% of the current climate assessment. In contrast, under climate change scenarios, reductions in areas with typical temperate climate “C” and expansions in arid climate “B” and tropical climate classes were observed compared to the present climate pattern. Notably, the BSh class has a prevalence of 6.09% and 8.16% for the periods 2041-2060 and 2061-2080, respectively. The observed climate changes signal potential challenges for the preservation of species in Brazil, as higher temperatures may hinder their adaptability to drier and warmer conditions. As a result, careful measures and strategies are needed to address the implications of these changes in the coming decades.

Know the precision of potential evapotranspiration models in different agronomic and climatic conditions is useful for irrigated agriculture. Therefore, we aimed to compare 18 methods of estimation of ETP with the Penman-Monteith (FAO-56) method, at different time scales for the State of Mato Grosso do Sul. Time series of climatic data were used on a daily scale between 1983 and 2018 from 22 locations in the state of Mato Grosso do Sul. ETP estimation models tested were: Benevidez-Lopez, Blaney-Criddle, Camargo, Hamon, Hargreaves, Hargreaves-Samani, Jensen-Haise, Jobson, Kharrufa, Linacre, Makkink, Penman, Priestley-Taylor, Radiation, Romanenko, Tanner-Pelton, Thornthwaite, and Turc. These models were compared with Penman-Monteith in daily, weekly, and monthly scales. The comparison between the ETP estimation models and the Penman-Monteith model was performed by the statistical indices: accuracy (MAPE) and precision (R²aj). Estimation methods showed differences in efficiency over time scales. The best performances of the models were on the daily scale. For daily scale, methods of Priestley-Taylor, Hargreaves, Hamon, and Makkink present the best values of accuracy and precision for the State of Mato Grosso do Sul. In the weekly scale, the most accurate methods are Hamon and Makkink, while for monthly scale the best methods are Makkink and Priestley-Taylor.