The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the conterminous United States
<p><span style="-webkit-text-stroke-width:0px;background-color:rgb(255, 255, 255);color:rgb(34, 34, 34);display:inline !important;float:none;font-family:-apple-system, "system-ui", "Segoe UI", Roboto, Oxygen-Sans, Ubuntu, Cantarell, "Helvetica Neue", sans-serif;font-size:18px;font-style:normal;font-variant-caps:normal;font-variant-ligatures:normal;font-weight:400;letter-spacing:normal;orphans:2;text-align:start;text-decoration-color:initial;text-decoration-style:initial;text-decoration-thickness:initial;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;">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 </span><em><i style="-webkit-text-stroke-width:0px;background-color:rgb(255, 255, 255);box-sizing:inherit;color:rgb(34, 34, 34);font-family:-apple-system, "system-ui", "Segoe UI", Roboto, Oxygen-Sans, Ubuntu, Cantarell, "Helvetica Neue", sans-serif;font-size:18px;font-variant-caps:normal;font-variant-ligatures:normal;font-weight:400;letter-spacing:normal;orphans:2;text-align:start;text-decoration-color:initial;text-decoration-style:initial;text-decoration-thickness:initial;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;">in situ</i></em><span style="-webkit-text-stroke-width:0px;background-color:rgb(255, 255, 255);color:rgb(34, 34, 34);display:inline !important;float:none;font-family:-apple-system, "system-ui", "Segoe UI", Roboto, Oxygen-Sans, Ubuntu, Cantarell, "Helvetica Neue", sans-serif;font-size:18px;font-style:normal;font-variant-caps:normal;font-variant-ligatures:normal;font-weight:400;letter-spacing:normal;orphans:2;text-align:start;text-decoration-color:initial;text-decoration-style:initial;text-decoration-thickness:initial;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;"> meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981–2018 over the CONUS at daily temporal resolution. 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.</span></p>
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https://n2t.net/ark:/85065/d76q22j0
eng
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publication
2016-01-01T00:00:00Z
publication
2024-12-01T00:00:00Z
<span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</span>
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OpenSky Support
UCAR/NCAR - Library
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Boulder
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name: homepage
pointOfContact
2025-07-10T19:56:12.651269