Fig 1.
Climate areas in the U.S. (NCEI, Karl and Koss, 1984).
Base layer: U.S. Census Bureau, Cartographic Boundary Files — States (public domain). Source: https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html.
Fig 2.
Climate areas in the U.S. (National Climate Assessment, 2023, Fifth Report).
Source: Adapted from the Fifth U.S. National Climate Assessment (2023). Public-domain material (U.S. Government Work). No permission required. URL: https://nca2023.globalchange.gov/regions.
Fig 3.
Evolution of the mean temperature across contiguous U.S. states (1950–2021).
Source: Own elaboration from PRISM state-level temperature series (see Sect 2 for data description). Figure generated with MATLAB (R2024b). Each panel shows the annual mean temperature (°C) for one U.S. state, illustrating both the long-term upward trend and the regional heterogeneity of warming.
Fig 4.
Trend slopes of representative distributional characteristics across U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Figure generated with MATLAB (R2024b). The panels show the estimated linear trend coefficients for the mean, the interquartile range (IQR), the lower tail (q05), and the upper tail (q95) of the temperature distribution across U.S. states.
Fig 5.
T-statistics for trend tests of representative distributional characteristics.
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Figure generated with MATLAB (R2024b). Red horizontal lines mark the 5% two-sided critical values ().
Fig 6.
State rankings by HAC-based t-statistics of mean temperature warming across U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Map generated with MATLAB (R2024b, Mapping Toolbox); no additional permissions required beyond software citation. Colours represent the HAC-based t-statistic of the linear trend in mean temperature for each state. Cooler (bluer) shades indicate weaker or statistically insignificant warming signals (lower t-statistics), whereas warmer (green to yellow) shades indicate stronger statistical evidence of warming (higher t-statistics). Negative values, where present, correspond to cooling trends.
Fig 7.
State rankings by HAC-based t-statistics of lower-tail (q05) temperature warming across U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Map generated with MATLAB (R2024b, Mapping Toolbox); no additional permissions required beyond software citation. Colours represent the HAC-based t-statistic of the linear trend in the 5th percentile (q05) of the temperature distribution for each state. Cooler (bluer) shades indicate weaker or statistically insignificant warming in the lower tail (lower t-statistics), whereas warmer (green to yellow) shades indicate stronger statistical evidence of lower-tail warming (higher t-statistics). Negative values, where present, correspond to cooling trends in the lower tail.
Fig 8.
State rankings by HAC-based t-statistics of upper-tail (q95) temperature warming across U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Map generated with MATLAB (R2024b, Mapping Toolbox); no additional permissions required beyond software citation. Colours represent the HAC-based t-statistic of the linear trend in the 95th percentile (q95) of the temperature distribution for each state. Cooler (bluer) shades indicate weaker or statistically insignificant warming in the upper tail (lower t-statistics), whereas warmer (green to yellow) shades indicate stronger statistical evidence of upper-tail warming (higher t-statistics). Negative values, where present, correspond to cooling trends in the upper tail.
Fig 9.
Test of warming existence across U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Map generated with MATLAB (R2024b, Mapping Toolbox); no additional permissions required beyond software citation. States coded as 0 correspond to cases in which the joint trend test fails to reject the null hypothesis of no warming (type W0), while states coded as 1 indicate warming detected in at least one part of the temperature distribution (types W1–W3).
Fig 10.
Warming typology across U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Map generated with MATLAB (R2024b, Mapping Toolbox); no additional permissions required beyond software citation. States are classified into four categories (W0–W3) according to the estimated warming pattern, distinguishing mean warming, dispersion changes, and tail-specific effects.
Fig 11.
Synthetic warming dominance index across U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Map generated with MATLAB (R2024b, Mapping Toolbox); no additional permissions required beyond software citation. Colours represent the synthetic Warming Dominance Index (), which summarizes the relative strength of warming signals across the full set of distributional measures. Positive values indicate stronger and more pervasive warming dominance.
Fig 12.
Warming dominance between U.S. states based on mean temperatures (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Figure heatmap generated with MATLAB (R2024b) using pairwise HAC-based trend tests. Each cell shows the t-statistic for the dominance of the state in the row over the state in the column. Positive (negative) values indicate that the row (column) state exhibits stronger mean-temperature warming.
Fig 13.
Warming dominance between U.S. states based on lower-tail (q05) temperatures (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Figure heatmap generated with MATLAB (R2024b) using pairwise HAC-based trend tests. Each cell shows the t-statistic for the dominance of the state in the row over the state in the column. Positive (negative) values indicate that the row (column) state exhibits stronger warming at the lower tail of the temperature distribution.
Fig 14.
Warming dominance between U.S. states based on upper-tail (q95) temperatures (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Figure generated with MATLAB (R2024b) using pairwise HAC-based trend tests. Each cell shows the t-statistic for the dominance of the state in the row over the state in the column. Positive (negative) values indicate that the row (column) state exhibits stronger warming at the upper tail of the temperature distribution.
Table 1.
Results of pareto warming dominance tests (1950-2021).
Fig 15.
Warming dominance indicators (WDI) by U.S. states and temperature quantiles.
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Figure generated with MATLAB (R2024b) from the spreadsheet WD_USA.xlsx. Each cell shows the synthetic WDI for a given state and quantile (mean, q05–q95). Colours represent the magnitude of warming dominance, with green (red) shades indicating negative (positive) values. States are sorted alphabetically to enhance comparability.
Fig 16.
Consistency of warming dominance across temperature quantiles for U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Figure generated with MATLAB (R2024b) using pairwise HAC-based trend tests. The upper panel shows, for states with positive mean warming dominance, the number of temperature quantiles (q05–q95) that also exhibit positive dominance. The lower panel shows, for states with negative mean dominance, the number of quantiles that also display negative dominance. Red bars indicate dominant states, and blue bars indicate dominated states.
Fig 17.
Synthetic pareto warming dominance (SPWD) across U.S. states (1950–2021).
Sources: Own elaboration from PRISM state-level temperature series (see Sect 2). Map generated with MATLAB (R2024b, Mapping Toolbox); no additional permissions required beyond software citation. The figure shows the classification of states according to the Synthetic Pareto Warming Dominance indicator (SPWD): states in dark blue satisfy Pareto warming dominance, while those in light blue do not. The SPWD provides a summary measure of whether warming dominance holds jointly across all distributional dimensions.