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<p>This study introduces the <b>W</b>estern U.S. <b>Hi</b>gh-resolution <b>L</b>ong-term <b>D</b>ataset for <b>H</b>ydro<b>M</b>eteorology (WHiLD-HM), a 4-km, 74-year spatiotemporally continuous daily dataset spanning 1952–2025 for the western United States (WUS). WHiLD-HM is generated by driving the Noah-MP version 5.0 land surface model with observed precipitation, surface air temperature, downward shortwave radiation, and specific humidity, along with dynamically downscaled reanalysis-based surface air pressure, downward longwave radiation, and wind speed. The dataset encompasses key hydrometeorological variables, including surface energy and water fluxes. Cross-comparisons with observational datasets demonstrate the high temporal and spatial accuracy of WHiLD-HM. Case studies illustrate WHiLD-HM’s ability to capture long-term drying trends in WUS, as well as extreme drought and pluvial conditions. By extending coverage beyond the satellite era, WHiLD-HM enables high-resolution analyses of daily to multidecadal hydroclimatic variability and trends, as well as extremes, providing crucial insights for water resources and food security management and ecohydrological monitoring.</p>

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A 4-km long-term (1952–2025) daily hydrometeorological dataset for the western United States

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月25日

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  • Gavin D. Madakumbura,
  • Ronnie Abolafia-Rosenzweig,
  • Cenlin He,
  • Jacob Jones,
  • Qian He,
  • Menaka Revel,
  • Bowen Wang,
  • A. Park Williams

摘要

This study introduces the Western U.S. High-resolution Long-term Dataset for HydroMeteorology (WHiLD-HM), a 4-km, 74-year spatiotemporally continuous daily dataset spanning 1952–2025 for the western United States (WUS). WHiLD-HM is generated by driving the Noah-MP version 5.0 land surface model with observed precipitation, surface air temperature, downward shortwave radiation, and specific humidity, along with dynamically downscaled reanalysis-based surface air pressure, downward longwave radiation, and wind speed. The dataset encompasses key hydrometeorological variables, including surface energy and water fluxes. Cross-comparisons with observational datasets demonstrate the high temporal and spatial accuracy of WHiLD-HM. Case studies illustrate WHiLD-HM’s ability to capture long-term drying trends in WUS, as well as extreme drought and pluvial conditions. By extending coverage beyond the satellite era, WHiLD-HM enables high-resolution analyses of daily to multidecadal hydroclimatic variability and trends, as well as extremes, providing crucial insights for water resources and food security management and ecohydrological monitoring.