Trends in temperature extremes in selected growing cities of Mexico under a non-stationary climate

Abstract

Mexico is vulnerable to extreme climatic events; however, their impact is not uniform in all the country. This study presents an analysis of extreme temperatures in 12 Mexican cities, modeled under the assumption of a non-stationary climate. Temporal trends were estimated from an available climatological base of maximum and minimum temperatures with the non-parametric tests of Mann-Kendall and Sen’s slope method, and a generalized extreme value (GEV) distribution was used to model both temperatures. A likelihood ratio test and Akaike and Bayesian information criteria were used to evaluate the optimal model choice with incorporation of a covariate. Using the best model, return levels and confidence intervals for future scenarios were estimated. A trend towards urban warming was detected from both the non-parametric tests and the GEV distribution, although with heterogeneous behavior. In the series of the maximum temperatures, half of the cities analyzed were non-stationary, and of those, the city of Guadalajara, located in the center-west of the country had a negative trend. The trend for minimum temperatures was more uniform, as 90% of the cities were non-stationary with a positive trend, and only 10%, in an urban area to the east of the metropolitan area of the Valley of Mexico (Milpa Alta) and a coastal city of the Gulf of Mexico (Veracruz), showed stationary series. It is therefore concluded that return periods of thermal extremes estimated in a changing climate temporarily showed a significant variation, so statistical modeling must consider this behavior due to its importance for risk assessments and adaptation purposes.