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  "description": "Vapor pressure deficit (VPD) is a critical variable in assessing drought conditions and evaluating plant water stress. Gridded products of global and regional VPD are not freely available from satellite remote sensing, model reanalysis, or ground observation datasets. We present two versions of the first gridded VPD product for the Continental US and parts of Northern Mexico and Southern Canada (CONUS+) at a 1 km spatial resolution and daily time step. We derived VPD from Daymet maximum daily temperature and average daily vapor pressure and scale the estimates based on (1) climate determined by the K\u00f6ppen-Geiger classifications and (2) land cover determined by the International Geosphere-Biosphere Programme. Ground-based VPD data from 253 AmeriFlux sites representing different climate and land cover classifications were used to improve the Daymet-derived VPD estimates for every pixel in the CONUS+ grid to produce the final datasets. We evaluated the Daymet-derived VPD against  independent observations and reanalysis data. The CONUS+ VPD datasets will aid in investigating disturbances including drought and wildfire, and informing land management strategies.",
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        "name": "Wake Forest University"
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      "name": "Corak, Nicholas K."
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        "name": "Wake Forest University"
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      "name": "Lowman, Lauren E.L."
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  "dateCreated": "2024-09-25 19:59:46.082328+00:00",
  "keywords": [
    "land-atmosphere interactions",
    "land management",
    "drought",
    "vapor pressure deficit (VPD)",
    "wildfire risk"
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  "datePublished": "2025-01-10 19:04:59.179198+00:00",
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  "dateModified": "2025-02-12 17:16:44.416035+00:00",
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      "identifier": "2228047",
      "funder": {
        "type": "Organization",
        "url": "https://ror.org/021nxhr62",
        "address": null,
        "name": "U.S. National Science Foundation"
      },
      "name": "ORE-CZ: Integrating Vegetation Phenology to Understand the Sensitivity of Dynamic Water Storage to Drought Using Remote Sensing Data and Hydrology Modeling"
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  "citation": [
    "Corak, N. K., L. E. Lowman (2025). Land cover and climate informed vapor pressure deficit datasets derived from Daymet, HydroShare, https://doi.org/10.4211/hs.de74b0a457c74deca09f9a41afa03c8f"
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