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    <responseDate>2026-10-14T18:08:13Z</responseDate>
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    <identifier>10.57760/sciencedb.35790</identifier>
    <datestamp>2026-01-22T17:44:13Z</datestamp>
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  <dc:date>2026-01-22</dc:date>
  <dc:title>&amp;quot;Mismatches between satellite-based vegetation greenness and primary productivity in response to the 2022/23 megadrought in Southwest China&amp;quot;</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.35790</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The &amp;ldquo;.bin&amp;rdquo; files represent the original data employed in this analysis. The data can be accessed by Python or NCL. The files of &amp;quot;gogpp.bin&amp;quot;, &amp;quot;gosif.bin&amp;quot;, &amp;quot;inter.FluxMGPP.toGOGPP.bin&amp;quot;, &amp;quot;inter.modis.NIRv.toGOGPP.bin&amp;quot;, &amp;quot;inter.modisevi.toGOGPP.bin&amp;quot;, &amp;quot;inter.modislai.toGOGPP.bin&amp;quot;, &amp;quot;inter.modisndvi.toGOGPP.bin&amp;quot; are vegetation metrics data. And &amp;quot;mask.ERAland_climtogogpp.bin&amp;quot;, &amp;quot;ssrd.ssr.era5.bin&amp;quot;, &amp;quot;vpd.tcc.ssrd.era5.bin&amp;quot; are hydrothermal variables.&amp;nbsp;</dc:description>
  <dc:subject>Drought; Vegetation; GPP; Greenness; Hydrothermal variables</dc:subject>
  <dc:creator>Xu Xue</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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