Cited by 8Urban Heat Island MitigationSoil Moisture and Remote SensingLand Use and Ecosystem Services

Ground-truth of a 1-km downscaled NLDAS air temperature product using the New York City Community Air Survey

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Eliezer, Heather, Johnson, Sarah, Crosson, William L., Al-Hamdan, Mohammad Z., Insaf, Tabassum Z.·2019·Journal of Applied Remote Sensing

Abstract

Ground-truthing results are presented for a new 1-km air temperature product downscaled for New York City (NYC) from ∼12 km North American Land Data Assimilation System (NLDAS) air temperature data using 1 km moderate resolution imaging spectroradiometer surface temperature data. The downscaled product was compared against a unique highly spatially resolved ground-level ambient air temperature dataset collected through the New York City Community Air Survey (NYCCAS), a neighborhood level air pollution and temperature monitoring network, for the years 2009 and 2010. This work focuses on the spatial variation in daily minimum temperatures within the five counties that comprise NYC (∼784 km2). Overall, the downscaled daily minimum temperature was well correlated with ground station data, with NYCCAS minimum temperatures being slightly higher. Minimum temperature R2 values were 0.9 and 0.92, and mean absolute errors were 0.69°C and 0.86°C for years 2009 and 2010, respectively. The smallest differences between NYCCAS and the downscaled data were seen at lower temperatures, in less densely urbanized areas, and in areas with higher vegetative cover, suggesting systematic bias in the downscaled data related to land-use. The 1-km dataset discerned neighborhood level temperature differences in high-density urban situations with heterogeneous land cover.

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  • An earlier study of NYC found that the non-Hispanic Black population in a 100-year floodplain (relative to what is expected based on population size) was nearly 60% higher in Manhattan, 40% higher in the Bronx, and nearly 100% higher in Queens, whereas the non-Hispanic White population was approximately 100% higher in the Bronx and 40% higher in Brooklyn.

    “An earlier study of NYC found that the non-Hispanic Black population in a 100-year floodplain (relative to what is expected based on population size) was nearly 60% higher in Manhattan, 40% higher in the Bronx, and nearly 100% higher in Queens, whereas the non-Hispanic White population was approximately 100% higher in the Bronx and 40% higher in Brooklyn.”

    From NPCC4: Advancing climate justice in climate adaptation strategies for New York City (2024) · cites this paper as [146]

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  1. U. S. A. 109(37), E2415-E2423 (2012). · DOI
  2. J. K. Vanos, L. S. Kalkstein, and T. J. Sanford, "Detecting synoptic warming trends across the US Midwest and implications to human health and heat-related mortality," Int. J. Climatol. 35, 85-96 (2015). · DOI

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Authors
Eliezer, H., Johnson, S., Crosson, W. L., Al-Hamdan, M. Z., & Insaf, T. Z.
Affiliations
  • New York City Department of Health and Mental Hygiene (US)
  • Marshall Space Flight Center (US)
  • Universities Space Research Association, NASA Marshall Space Flight Ctr.
  • New York State Department of Health (US)
Venue
Journal of Applied Remote Sensing
Published
2019-05-13
Volume
13
Issue
02
Pages
1-14
ISSN
1931-3195 (ISSN-L)
OpenAlex
W2946711169
Cited by
8
References
35
Citations by year
2025: 1 · 2024: 2 · 2023: 1 · 2021: 3 · 2020: 1
FWCI
0.42
Type
journal article
Language
en
Open access
Locations
Journal of Applied Remote Sensing (publishedVersion, cc-by)
Funders
NASA Research Opportunities in Space an Earth Sciences (2013-NNX15AN77G)
Topics
  • Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
  • Physical Sciences › Environmental Science › Environmental Engineering › Soil Moisture and Remote Sensing
  • Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
Keywords
air temperature, NLDAS, downscaling, ground truth, MODIS land surface temperature, daily minimum temperature, urban heat, vegetation cover, urban heterogeneity

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