Urban Heat Island Effects in U.S. Summer Surface Temperature Data, 1895–2023

Abstract A novel method is described for quantifying average urban heat island (UHI) warming since 1895 in the contiguous United States (CONUS) summer air temperature data. The method quantifies the sensitivity of the Global Historical Climatology Network (GHCN) station raw temperature to station-centered population density (PD). Specifically, closely spaced station pair differences in monthly raw (nonhomogenized) T AVG (the average of daily maximum and minimum temperature) and PD are sorted by station pair average PD into six PD classes, and linear regression estimates of the temperature sensitivity to population density change dT AVG /dPD are made for each class for historical periods ranging from 1 to 21 years in length. Every one of the resulting six sensitivity relationships in each of the 22 historical periods from 1880 to 2020 is found to be positive, and their magnitudes allow the construction of station-average urban heat island temperature T UHI curves as a function of population density. When applied to the history of population changes at each CONUS station location (1895–2023) and grouped into four categories of station population density, the resulting T UHI warming trends range from 8% of observed T AVG warming for the most rural category of stations to about 65% of observed warming for suburban and urban categories. Across all stations, the UHI warming amounts to 22% of the observed raw GHCN warming trend (+0.016° vs + 0.072°C decade −1 ). The method provides an independent way to quantify station-average UHI warming over time.