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CASCCAD: Cumulus And Stratocumulus Cloudsat-CAlipso Dataset

Cesana, Grégory

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  <identifier identifierType="DOI">10.5281/zenodo.2667637</identifier>
      <creatorName>Cesana, Grégory</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-8899-0509</nameIdentifier>
      <affiliation>Columbia University, NASA-GISS</affiliation>
    <title>CASCCAD: Cumulus And Stratocumulus Cloudsat-CAlipso Dataset</title>
    <subject>cloud, stratocumulus, cumulus, CALIPSO, CloudSat, profiles, maps, lidar, radar</subject>
    <date dateType="Issued">2019-05-05</date>
  <resourceType resourceTypeGeneral="Dataset"/>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.2667636</relatedIdentifier>
    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;In these two&amp;nbsp;datasets, we document spatial distributions and profiles of stratocumulus (Sc) and cumulus (Cu) clouds on a global scale.&lt;/p&gt;

&lt;p&gt;To this end, we design an original discrimination algorithm (DA) that distinguishes Sc and Cu based on three observable cloud-properties: cloud top height (CTH), horizontal cloud fraction (HCF) and vertical cloud fraction variability (VCF). These simple criteria are sufficient to characterize the distinctive shape of Cu, which have a limited horizontal extent and highly variable CTH as opposed to Sc, which cover larger areas and have a small and stable geometrical thickness. The DA is utilized on instantaneous profiles of active-sensor Cloud-Aerosols Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), specifically the&amp;nbsp;General Circulation Model - Oriented CALIPSO Cloud Product (CALIPSO-GOCCP), and&amp;nbsp;CloudSat-CALIPSO combined observations.&lt;/p&gt;

&lt;p&gt;By documenting the geographical distribution of Sc and Cu clouds, these datasets make it possible to evaluate the shallow convection (Cu type) and boundary layer (Sc type) clouds in state-of-the art climate models, which are typically generated by distinct parametrizations.&lt;/p&gt;</description>
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