摘要：Extreme weather events can have severe consequences for the population and the environment. Therefore, in this study a temporal trend of annual temperatures was built with a time series from 1950 to 2010 for Mexicali, Mexico, and estimates of 5- to 100-year return periods are provided by modeling of summer maximum and winter minimum temperatures. A non-parametric Kendall’s tau test and the Sen’s slope estimator were used to compute trends. The generalized extreme value (GEV) distribution was applied to the approximation of block maxima and the generalized Pareto distribution (GPD) to values over a predetermined threshold. Due to the non-stationary characteristic of the series of temperature values, the temporal trend was included as a covariable in the location parameter and substantial improvements were observed, particularly with the extreme minimum temperature, compared to that obtained with the GEV with no covariable and with the GPD. A positive and significant statistically trend in both summer maximum temperature and winter minimum temperature was found. By the end of 21st century the extreme maximum temperature could be 2 to 3 ºC higher than current, and the winter could be less severe, as the probabilistic model suggests increases of 7 to 9 ºC in the extreme minimum temperature with respect to the base period. The foreseeable consequences on Mexicali city are discussed.
其他摘要：Extreme weather events can have severe consequences for the population and the environment. Therefore, in this study a temporal trend of annual temperatures was built with a time series from 1950 to 2010 for Mexicali, Mexico, and estimates of 5- to 100-year return periods are provided by modeling of summer maximum and winter minimum temperatures. A non-parametric Kendall’s tau test and the Sen’s slope estimator were used to compute trends. The generalized extreme value (GEV) distribution was applied to the approximation of block maxima and the generalized Pareto distribution (GPD) to values over a predetermined threshold. Due to the non-stationary characteristic of the series of temperature values, the temporal trend was included as a covariable in the location parameter and substantial improvements were observed, particularly with the extreme minimum temperature, compared to that obtained with the GEV with no covariable and with the GPD. A positive and significant statistically trend in both summer maximum temperature and winter minimum temperature was found. By the end of 21st century the extreme maximum temperature could be 2 to 3 ºC higher than current, and the winter could be less severe, as the probabilistic model suggests increases of 7 to 9 ºC in the extreme minimum temperature with respect to the base period. The foreseeable consequences on Mexicali city are discussed.
关键词：Generalized extreme value distribution;generalized Pareto distribution;maximum temperature;minimum temperature;Mexicali, Mexico;Generalized extreme value distribution;generalized Pareto distribution;maximum temperature;minimum temperature;Mexicali, Mexico
其他关键词：Generalized extreme value distribution; generalized Pareto distribution; maximum temperature; minimum temperature; Mexicali; Mexico
