Strong UHI Temperature Biases Confirmed in USA

WUWT readers may recall that NOAA did an experiment at Oak Ridge National Laboratory that vindicated my findings about the effects of local urbanization on surface temperature measurements.

The urban heat island (UHI) effect is strongly affected by urban-scale changes to local land surfaces. Basically, the more asphalt, concrete, buildings, etc. that exist near a thermometer, the more the overnight low temperature is biased upwards due to heat storage.

Climate monitoring thermometers are therefore biased upwards. This new UHI database further vindicates my findings in 2015 released at the AGU Fall Meeting. – Anthony


New Surface Urban Heat Island Database for the United States

A new study published in the ISPRS Journal of Photogrammetry and Remote Sensing presents clear-sky surface UHI (SUHI) intensities for 497 urbanized areas in the United States by combining remotely-sensed data products with multiple US census-defined urban areas.

The SUHI intensity is the difference in surface temperature between the built-up and non-built up pixels of an urbanized area.

The study reported that the daytime summer SUHI was 1.91 °C higher and the daytime winter SUHI was 0.87 °C higher.

The study also reports that the SUHI intensity is lower in census tracts with higher median income and higher proportion of white people. Unfortunately, the study didn’t report on how the UHI effect changes with time.

h/t to Friends of Science

The paper: https://www.sciencedirect.com/science/article/abs/pii/S0924271620302082#!

Abstract
The urban heat island (UHI) effect is strongly modulated by urban-scale changes to the aerodynamic, thermal, and radiative properties of the Earth’s land surfaces. Interest in this phenomenon, both from the climatological and public health perspectives, has led to hundreds of UHI studies, mostly conducted on a city-by-city basis. These studies, however, do not provide a complete picture of the UHI for administrative units using a consistent methodology. To address this gap, we characterize clear-sky surface UHI (SUHI) intensities for all urbanized areas in the United States using a modified Simplified Urban-Extent (SUE) approach by combining a fusion of remotely-sensed data products with multiple US census-defined administrative urban delineations. We find the highest daytime SUHI intensities during summer (1.91 ± 0.97 °C) for 418 of the 497 urbanized areas, while the winter daytime SUHI intensity (0.87 ± 0.45 °C) is the lowest in 439 cases.

Since urban vegetation has been frequently cited as an effective way to mitigate UHI, we use NDVI, a satellite-derived proxy for live green vegetation, and US census tract delineations to characterize how vegetation density modulates inter-urban, intra-urban, and inter-seasonal variability in SUHI intensity. In addition, we also explore how elevation and distance from the coast confound SUHI estimates. To further quantify the uncertainties in our estimates, we analyze and discuss some limitations of these satellite-derived products across climate zones, particularly issues with using remotely sensed radiometric temperature and vegetation indices as proxies for urban heat and vegetation cover. We demonstrate an application of this spatially explicit dataset, showing that for the majority of the urbanized areas, SUHI intensity is lower in census tracts with higher median income and higher proportion of white people. Our analysis also suggests that poor and non-white urban residents may suffer the possible adverse effects of summer SUHI without reaping the potential benefits (e.g., warmer temperatures) during winter, though establishing this result requires future research using more comprehensive heat stress metrics. This study develops new methodological advancements to characterize SUHI and its intra-urban variability at levels of aggregation consistent with sources of other socioeconomic information, which can be relevant in future inter-disciplinary research and as a possible screening tool for policy-making.

The dataset developed in this study is visualized at: https://datadrivenlab.users.earthengine.app/view/usuhiapp

CONTINUE READING –>

 

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