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    <responseDate>2026-10-14T14:21:15Z</responseDate>
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    <identifier>10.57760/sciencedb.23752</identifier>
    <datestamp>2026-06-16T16:15:31Z</datestamp>
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  <dc:date>2026-06-16</dc:date>
  <dc:title>A 1 km Hourly High-Resolution 3D Wind Field Dataset over the Yangtze River Delta during June-August 2021-2023</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.23752</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The 3D wind field dataset was generated through dynamic downscaling using the Weather Research and Forecasting (WRF) model, driven by ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The simulation incorporates multi-source observational nudging, optimized physical parameterization schemes, and high-resolution land use updates to enhance the accuracy of local atmospheric processes.&amp;nbsp;This dataset includes four variables: 10-meter zonal wind (U10m), 10-meter meridional wind (V10m), zonal wind profile (U), and meridional wind profile (V).&amp;nbsp;The vertical wind profiles are provided&amp;nbsp;on 32 ERA5-standard pressure levels from 1000 hPa to 10 hPa. All data are stored in NetCDF format with lossless compression enabled. Key variables are encoded using scale_factor and add_offset attributes, following the relation: real_value = scale_factor &amp;times; packed_value + add_offset. The dataset complies with CF conventions and can be automatically decoded by standard tools such as xarray, NCL, and CDO, without manual intervention.</dc:description>
  <dc:subject>Dynamical downscaling; Multi-source observation nudging; High-resolution land use; Yangtze River Delta; Three-dimension wind field</dc:subject>
  <dc:creator>Zhengyan Zhang</dc:creator>
  <dc:creator>Yan-An Liu</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.5194/essd-18-1683-2026</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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