The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States

Newman, Andrew J.; Kalb, Christina; Chakraborty, T. C.; Fitch, Amy; Darrow, Lyndsey A.; Warren, Joshua L.; Strickland, Matthew J.; Holmes, Heather A.; Monaghan, Andrew J.; Chang, Howard H.

doi:10.1038/s41597-024-04086-2

Title: The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States

Journal Article · 03 December 2024 · Scientific Data

DOI: https://doi.org/10.1038/s41597-024-04086-2 · OSTI ID:2481598

^[1]; Kalb, Christina ^[1];

^[2]; Fitch, Amy ^[3]; Darrow, Lyndsey A. ^[3];

^[4]; Strickland, Matthew J. ^[3]; Holmes, Heather A. ^[5]; Monaghan, Andrew J. ^[6]; Chang, Howard H. ^[7]

National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
Yale Univ., New Haven, CT (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Univ. of Nevada, Reno, NV (United States)
Yale Univ., New Haven, CT (United States)
Univ. of Utah, Salt Lake City, UT (United States)
Univ. of Colorado, Boulder, CO (United States)
Emory Univ., Atlanta, GA (United States)

Many current gridded surface meteorological datasets are inadequate for quantifying near surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. We also synthesize in situ meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981-2018 over the CONUS. Daily maximum, minimum, and mean values for a variety of temperature estimates, humidity, and surface energy budget terms, among others, are included. This High-resolution Urban Meteorology for Impacts Dataset (HUMID) will be useful for studies examining spatial variability of near surface meteorology and the impacts of urban heat islands across many disciplines including epidemiology, ecology, and climatology.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Science (SC); National Science Foundation (NSF); National Institutes of Health (NIH)

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 2481598

Report Number(s):: PNNL-SA--196690

Journal Information:: Scientific Data, Journal Name: Scientific Data Journal Issue: 1 Vol. 11; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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