Research ArticleATMOSPHERIC SCIENCE

Population dynamics modify urban residents’ exposure to extreme temperatures across the United States

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Science Advances  18 Dec 2019:
Vol. 5, no. 12, eaay3452
DOI: 10.1126/sciadv.aay3452
  • Fig. 1 Population dynamics–induced changes in residents’ exposure temperature (Tpop− Tarea) during simulated extreme events.

    (A) In normal winter days and (C) during the 2014 cold wave. (B) In normal summer days and (D) during the three simulated heat waves in 2006, 2011, and 2012. Each circle represents a metropolitan area affected by the extreme event, and its size is proportional to the magnitude of exposure temperature averaged over the entire metropolitan area without population dynamics (Tarea). The magnitude of changes for individual cities is referred to table S2.

  • Fig. 2 Temperature, population, and grid number distributions as a function of urban land use intensity.

    Each gray bar stands for the percentage of grids within a 5% urban land use intensity interval to the total number of grids within the studied metropolitan area (right-side axis). Orange and green lines denote the ratios of population within grids of different urban land use intensities to the total population of the metropolitan area (right-side axis) at day and night. Shaded areas around the daily average temperature profiles (blue and red lines) stand for the 25% and 75% quantiles over grids within a 5% urban land use intensity interval (left-side axis).

  • Fig. 3 Temperature anomalies over studied metropolitan areas during simulated extreme events.

    Solid (dashed) lines indicate the linear relationship is statistically significant at 0.05 (0.1) level.

  • Fig. 4 The relations between population dynamics–induced changes in exposure temperature under extreme events and cities’ temperature and population spatial variabilities.

    (A) Relations between the coefficient of spatial variation for daily average temperature over individual cities and the effect of population dynamics. (B) Relations between the effect of population dynamics and the spatial correlation coefficient of daily average temperature and population. The linear regression is performed for cities under the humid warm temperate climate with one standard deviation confidence band. Solid lines indicate the linear relation is statistically significant at 0.05 level.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/5/12/eaay3452/DC1

    Fig. S1. Anomalies in residents’ exposure temperatures during simulated heat and cold waves across CONUS.

    Fig. S2. Map of studied domains around selected metropolitan areas across CONUS.

    Fig. S3. Spatial variability of WRF-simulated mean air temperature during studied extreme events in four example metropolitan areas.

    Fig. S4. Relations between the impact of population dynamics on temperature exposure during extreme events and the studied city boundaries.

    Fig. S5. Population dynamics–induced changes in exposure temperature under different climate zones for normal days and extreme events.

    Fig. S6. Relations between the effect of population dynamics under extreme events and cities’ temperature and population spatial variabilities.

    Table S1. Population and climate information of the studied metropolitan areas.

    Table S2. Tarea and Tpop (°C) estimates in normal days and under extreme events during the simulation periods.

    Table S3. Summary of the number of extreme event days during the simulation periods.

    Table S4. Summary of mean absolute errors of 2-m air temperature during four simulated extreme events.

  • Supplementary Materials

    This PDF file includes:

    • Fig. S1. Anomalies in residents’ exposure temperatures during simulated heat and cold waves across CONUS.
    • Fig. S2. Map of studied domains around selected metropolitan areas across CONUS.
    • Fig. S3. Spatial variability of WRF-simulated mean air temperature during studied extreme events in four example metropolitan areas.
    • Fig. S4. Relations between the impact of population dynamics on temperature exposure during extreme events and the studied city boundaries.
    • Fig. S5. Population dynamics–induced changes in exposure temperature under different climate zones for normal days and extreme events.
    • Fig. S6. Relations between the effect of population dynamics under extreme events and cities’ temperature and population spatial variabilities.
    • Table S1. Population and climate information of the studied metropolitan areas.
    • Table S2. Tarea and Tpop (°C) estimates in normal days and under extreme events during the simulation periods.
    • Table S3. Summary of the number of extreme event days during the simulation periods.
    • Table S4. Summary of mean absolute errors of 2-m air temperature during four simulated extreme events.

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