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Regional heterogeneity and warming dominance in the United States

Author

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  • María Dolores Gadea Rivas
  • Jesús Gonzalo

Abstract

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.

Suggested Citation

  • María Dolores Gadea Rivas & Jesús Gonzalo, 2026. "Regional heterogeneity and warming dominance in the United States," PLOS Climate, Public Library of Science, vol. 5(2), pages 1-27, February.
  • Handle: RePEc:plo:pclm00:0000808
    DOI: 10.1371/journal.pclm.0000808
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    References listed on IDEAS

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    1. Kamiar Mohaddes & Ryan N C Ng & M Hashem Pesaran & Mehdi Raissi & Jui-Chung Yang, 2023. "Climate change and economic activity: evidence from US states," Oxford Open Economics, Oxford University Press, vol. 2, pages 28-46.
    2. Lin Ye & Nancy Grimm, 2013. "Modelling potential impacts of climate change on water and nitrate export from a mid-sized, semiarid watershed in the US Southwest," Climatic Change, Springer, vol. 120(1), pages 419-431, September.
    3. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2020. "Trends in distributional characteristics: Existence of global warming," Journal of Econometrics, Elsevier, vol. 214(1), pages 153-174.
    4. José-Luis Cruz & Esteban Rossi-Hansberg, 2024. "The Economic Geography of Global Warming," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(2), pages 899-939.
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    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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