Climate change exhibits substantial variability across both space and time, requiring mitigation and adaptation strategies that effectively address challenges at global and local scales. Accurately capturing this variability is essential for assessing climate impacts, attributing underlying causes, and formulating effective policies. This study introduces simple yet robust quantitative methods to detect local warming, distinguish among different types of warming, and compare warming trends across contiguous U.S. states using the concept of warming dominance. In contrast to traditional approaches that focus solely on average temperatures, our analysis rigorously and systematically examines the entire distribution of daily temperatures for the contiguous United States from 1950 to 2021. The results reveal that, while 44% of states show no statistically significant warming based on average temperature trends, a much larger proportion—84%—exhibit warming when assessing various quantiles of the distribution. Statistical significance is evaluated using HAC-robust t -tests at the 5% significance level (95% confidence), ensuring that detected warming reflects genuine shifts rather than random variability. These findings underscore the substantial heterogeneity in warming patterns: some states, such as those located in the so-called “Warming Hole,” display no evidence of warming at any quantile; others experience more pronounced warming in either the lower or upper tails of the temperature distribution; and a few states show consistent warming across all quantiles. The study concludes by identifying which states exhibit warming dominance over others and which appear comparatively less affected. These insights are particularly important in the United States, where climate policy is formulated and implemented at both federal and state levels.
Rivas et al. (Wed,) studied this question.