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    <identifier>10.57760/sciencedb.011iz</identifier>
    <datestamp>2026-09-11T09:41:19Z</datestamp>
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  <dc:date>2026-09-11</dc:date>
  <dc:title>MSE-Stack Downscaled 1-km Monthly XCO₂ Dataset over the Mongolian Plateau, 2017&amp;ndash;2020</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.011iz</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset provides continuous monthly XCO₂ fields at a spatial resolution of 1 km over the Mongolian Plateau for 2017&amp;ndash;2020. The dataset was generated using a three-layer stacked ensemble learning framework (MSE-Stack), which integrates OCO-2 XCO₂ retrievals with multi-source meteorological, ecological, topographic, and anthropogenic variables.The dataset is designed to characterize the spatial, seasonal, and interannual variability of atmospheric XCO₂ over the Mongolian Plateau and to support regional carbon-cycle and environmental studies. It provides high-resolution and spatially continuous XCO₂ estimates, helping to address the spatial and temporal discontinuities associated with sparse satellite observations.The dataset was generated as part of the study &amp;ldquo;A three-layer stacked ensemble learning method for high-resolution XCO₂ downscaling using OCO-2 and multi-source data.&amp;rdquo;</dc:description>
  <dc:subject>OCO-2; ERA5;  MODIS</dc:subject>
  <dc:creator>Wei Wei</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/publicdomain/zero/1.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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