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This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007–2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov–Smirnov test, the corrected Akaike criterion AICc, the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28–32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes. [ABSTRACT FROM AUTHOR]

Studies of the anticipated consequences of climate change suggest that among all economic sectors, agriculture would be the most affected. In Brazil, this issue is particularly relevant, since the agricultural sector and its related activities account for a significant share of the country's GDP and employment. Using a fixed effects panel model and data from 1990 through 2012, this paper empirically analyzes the vulnerability of agriculture to climate variables in Brazil's ten main agricultural states and the possible resulting loss of agricultural value in the face of future climate change. Our work is differentiated from prior studies in that it employs state level annual data series, which allows the aggregation of a great deal of relevant current information to the analysis. The results indicate that climate variables have a significant impact on most of these states' agricultural production, especially air temperature, whose effects showed higher estimated magnitude than those from rainfall. Considering the estimated elasticities and climatic projections, the most severe damage to agriculture is expected in Espírito Santo, Minas Gerais, and Rio Grande do Sul. [ABSTRACT FROM AUTHOR]