December 14, 2022 Dataset Open Access

Fan, Kai; Dhammapala, Ranil; Harrington, Kyle; Lamb, Brian; Lee, Yun Ha

DataCite XML Export

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  <identifier identifierType="DOI">10.14278/rodare.2029</identifier>
  <creators>
    <creator>
      <creatorName>Fan, Kai</creatorName>
      <givenName>Kai</givenName>
      <familyName>Fan</familyName>
    </creator>
    <creator>
      <creatorName>Dhammapala, Ranil</creatorName>
      <givenName>Ranil</givenName>
      <familyName>Dhammapala</familyName>
    </creator>
    <creator>
      <creatorName>Harrington, Kyle</creatorName>
      <givenName>Kyle</givenName>
      <familyName>Harrington</familyName>
    </creator>
    <creator>
      <creatorName>Lamb, Brian</creatorName>
      <givenName>Brian</givenName>
      <familyName>Lamb</familyName>
    </creator>
    <creator>
      <creatorName>Lee, Yun Ha</creatorName>
      <givenName>Yun Ha</givenName>
      <familyName>Lee</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7478-2672</nameIdentifier>
    </creator>
  </creators>
  <titles>
    <title>Training data of a machine learning modeling framework for the air quality forecasts in the Pacific Northwest, USA.</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2022</publicationYear>
  <dates>
    <date dateType="Issued">2022-12-14</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/2029</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-35834</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-35780</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsReferencedBy">10.3389/fdata.2023.1124148</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.2028</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;These files are the training data of a machine learning modeling framework&amp;nbsp;for the air quality forecasts in the Pacific Northwest (PNW), USA.&lt;/p&gt;

&lt;p&gt;O3.zip contains the AQS observations data of O3.&lt;/p&gt;

&lt;p&gt;PM_FRM.zip contains the AQS data of PM2.5 using&amp;nbsp;federal reference methods (FRM).&lt;/p&gt;

&lt;p&gt;PM_nFRM.zip&amp;nbsp;contains the AQS data of PM2.5 using&amp;nbsp;&amp;ldquo;FRM-like&amp;rdquo;&amp;nbsp;methods.&lt;/p&gt;

&lt;p&gt;WRF_pkl.zip contains the archived WRF data for the AQS sites in the PNW.&lt;/p&gt;</description>
  </descriptions>
</resource>