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Long-term temperature records are essential for detecting sustained warming and assessing associated changes in heatwave occurrence and characteristics. We examined two contrasting environmental settings in northeastern Mexico: the densely urbanized and topographically complex area of Monterrey and the open, low-relief landscape influenced by the El Cuchillo Reservoir. Using 1971–2023 station records, we estimated Tmax, Tmean, and Tmin trends with autocorrelation-adjusted Mann–Kendall tests and Sen slopes, examined multi-year periodicity and summer heatwaves, and evaluated ENSO influences. Seasonal temperature patterns and long-term changes differed between sites. El Cuchillo had warmer summer daytime conditions, whereas Monterrey was warmer in winter, particularly at night. Monterrey warmed across all seasons and temperature variables, with the strongest change in summer Tmax. Warming at El Cuchillo was more selective and was most pronounced in winter Tmin. No recurring multi-year temperature cycles were detected, and the predictive influence of ENSO in Monterrey was limited to autumn Tmin and winter Tmax and Tmean. These contrasting trajectories were interpreted as site-specific changes rather than as a measure of urban heat-island intensity. Summer heatwaves also evolved differently at the two sites. In Monterrey, they became more frequent, longer, and more intense and produced greater cumulative heat across all three temperature definitions. At El Cuchillo, no measurable increase was found in event frequency or total heatwave days, and changes were limited mainly to the persistence and intensity of Tmean-defined events. No recurring multi-year cycles were detected, and ENSO did not consistently explain or predict heatwave variability in Monterrey. Overall, the results demonstrate that heatwave evolution within northeastern Mexico is spatially heterogeneous and sensitive to the temperature variable considered. As climate warming intensifies, accounting for local differences in daytime and nighttime heat dynamics will be essential for designing urban adaptation strategies that reduce heat exposure and improve thermal well-being.
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Heredia et al. (2026) studied this question.
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