Spatial characterization of the meltwater field from icebergs in the Weddell Sea.
Identifieur interne : 000052 ( PubMed/Corpus ); précédent : 000051; suivant : 000053Spatial characterization of the meltwater field from icebergs in the Weddell Sea.
Auteurs : John J. Helly ; Ronald S. Kaufmann ; Maria Vernet ; Gordon R. StephensonSource :
- Proceedings of the National Academy of Sciences of the United States of America [ 1091-6490 ] ; 2011.
English descriptors
- KwdEn :
- MESH :
- geographic : Antarctic Regions.
- methods : Data Collection, Informatics, Information Dissemination, Remote Sensing Technology.
- trends : Informatics.
- Ecosystem, Freezing, Geographic Information Systems, Geography, Ice Cover, Oceans and Seas, Salinity, Temperature.
Abstract
We describe the results from a spatial cyberinfrastructure developed to characterize the meltwater field around individual icebergs and integrate the results with regional- and global-scale data. During the course of the cyberinfrastructure development, it became clear that we were also building an integrated sampling planning capability across multidisciplinary teams that provided greater agility in allocating expedition resources resulting in new scientific insights. The cyberinfrastructure-enabled method is a complement to the conventional methods of hydrographic sampling in which the ship provides a static platform on a station-by-station basis. We adapted a sea-floor mapping method to more rapidly characterize the sea surface geophysically and biologically. By jointly analyzing the multisource, continuously sampled biological, chemical, and physical parameters, using Global Positioning System time as the data fusion key, this surface-mapping method enables us to examine the relationship between the meltwater field of the iceberg to the larger-scale marine ecosystem of the Southern Ocean. Through geospatial data fusion, we are able to combine very fine-scale maps of dynamic processes with more synoptic but lower-resolution data from satellite systems. Our results illustrate the importance of spatial cyberinfrastructure in the overall scientific enterprise and identify key interfaces and sources of error that require improved controls for the development of future Earth observing systems as we move into an era of peta- and exascale, data-intensive computing.
DOI: 10.1073/pnas.0909306108
PubMed: 21444769
Links to Exploration step
pubmed:21444769Le document en format XML
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Stephenson</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2011">2011</date><idno type="doi">10.1073/pnas.0909306108</idno><idno type="RBID">pubmed:21444769</idno><idno type="pmid">21444769</idno><idno type="wicri:Area/PubMed/Corpus">000052</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Spatial characterization of the meltwater field from icebergs in the Weddell Sea.</title><author><name sortKey="Helly, John J" sort="Helly, John J" uniqKey="Helly J" first="John J" last="Helly">John J. Helly</name><affiliation><nlm:affiliation>San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Kaufmann, Ronald S" sort="Kaufmann, Ronald S" uniqKey="Kaufmann R" first="Ronald S" last="Kaufmann">Ronald S. Kaufmann</name></author><author><name sortKey="Vernet, Maria" sort="Vernet, Maria" uniqKey="Vernet M" first="Maria" last="Vernet">Maria Vernet</name></author><author><name sortKey="Stephenson, Gordon R" sort="Stephenson, Gordon R" uniqKey="Stephenson G" first="Gordon R" last="Stephenson">Gordon R. Stephenson</name></author></analytic><series><title level="j">Proceedings of the National Academy of Sciences of the United States of America</title><idno type="eISSN">1091-6490</idno><imprint><date when="2011" type="published">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Antarctic Regions</term><term>Data Collection (methods)</term><term>Ecosystem</term><term>Freezing</term><term>Geographic Information Systems</term><term>Geography</term><term>Ice Cover</term><term>Informatics (methods)</term><term>Informatics (trends)</term><term>Information Dissemination (methods)</term><term>Oceans and Seas</term><term>Remote Sensing Technology (methods)</term><term>Salinity</term><term>Temperature</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Antarctic Regions</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Data Collection</term><term>Informatics</term><term>Information Dissemination</term><term>Remote Sensing Technology</term></keywords><keywords scheme="MESH" qualifier="trends" xml:lang="en"><term>Informatics</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Ecosystem</term><term>Freezing</term><term>Geographic Information Systems</term><term>Geography</term><term>Ice Cover</term><term>Oceans and Seas</term><term>Salinity</term><term>Temperature</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We describe the results from a spatial cyberinfrastructure developed to characterize the meltwater field around individual icebergs and integrate the results with regional- and global-scale data. During the course of the cyberinfrastructure development, it became clear that we were also building an integrated sampling planning capability across multidisciplinary teams that provided greater agility in allocating expedition resources resulting in new scientific insights. The cyberinfrastructure-enabled method is a complement to the conventional methods of hydrographic sampling in which the ship provides a static platform on a station-by-station basis. We adapted a sea-floor mapping method to more rapidly characterize the sea surface geophysically and biologically. By jointly analyzing the multisource, continuously sampled biological, chemical, and physical parameters, using Global Positioning System time as the data fusion key, this surface-mapping method enables us to examine the relationship between the meltwater field of the iceberg to the larger-scale marine ecosystem of the Southern Ocean. Through geospatial data fusion, we are able to combine very fine-scale maps of dynamic processes with more synoptic but lower-resolution data from satellite systems. Our results illustrate the importance of spatial cyberinfrastructure in the overall scientific enterprise and identify key interfaces and sources of error that require improved controls for the development of future Earth observing systems as we move into an era of peta- and exascale, data-intensive computing.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">21444769</PMID><DateCreated><Year>2011</Year><Month>04</Month><Day>06</Day></DateCreated><DateCompleted><Year>2011</Year><Month>07</Month><Day>01</Day></DateCompleted><DateRevised><Year>2015</Year><Month>02</Month><Day>04</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1091-6490</ISSN><JournalIssue CitedMedium="Internet"><Volume>108</Volume><Issue>14</Issue><PubDate><Year>2011</Year><Month>Apr</Month><Day>5</Day></PubDate></JournalIssue><Title>Proceedings of the National Academy of Sciences of the United States of America</Title><ISOAbbreviation>Proc. Natl. Acad. Sci. U.S.A.</ISOAbbreviation></Journal><ArticleTitle>Spatial characterization of the meltwater field from icebergs in the Weddell Sea.</ArticleTitle><Pagination><MedlinePgn>5492-7</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1073/pnas.0909306108</ELocationID><Abstract><AbstractText>We describe the results from a spatial cyberinfrastructure developed to characterize the meltwater field around individual icebergs and integrate the results with regional- and global-scale data. During the course of the cyberinfrastructure development, it became clear that we were also building an integrated sampling planning capability across multidisciplinary teams that provided greater agility in allocating expedition resources resulting in new scientific insights. The cyberinfrastructure-enabled method is a complement to the conventional methods of hydrographic sampling in which the ship provides a static platform on a station-by-station basis. We adapted a sea-floor mapping method to more rapidly characterize the sea surface geophysically and biologically. By jointly analyzing the multisource, continuously sampled biological, chemical, and physical parameters, using Global Positioning System time as the data fusion key, this surface-mapping method enables us to examine the relationship between the meltwater field of the iceberg to the larger-scale marine ecosystem of the Southern Ocean. Through geospatial data fusion, we are able to combine very fine-scale maps of dynamic processes with more synoptic but lower-resolution data from satellite systems. Our results illustrate the importance of spatial cyberinfrastructure in the overall scientific enterprise and identify key interfaces and sources of error that require improved controls for the development of future Earth observing systems as we move into an era of peta- and exascale, data-intensive computing.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Helly</LastName><ForeName>John J</ForeName><Initials>JJ</Initials><AffiliationInfo><Affiliation>San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kaufmann</LastName><ForeName>Ronald S</ForeName><Initials>RS</Initials></Author><Author ValidYN="Y"><LastName>Vernet</LastName><ForeName>Maria</ForeName><Initials>M</Initials></Author><Author ValidYN="Y"><LastName>Stephenson</LastName><ForeName>Gordon R</ForeName><Initials>GR</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2011</Year><Month>03</Month><Day>28</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Proc Natl Acad Sci U S A</MedlineTA><NlmUniqueID>7505876</NlmUniqueID><ISSNLinking>0027-8424</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2011 Apr 5;108(14):5488-91</RefSource><PMID Version="1">21467227</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Science. 2007 Jul 27;317(5837):478-82</RefSource><PMID Version="1">17588896</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="N" Type="Geographic" UI="D000864">Antarctic Regions</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003625">Data Collection</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D017753">Ecosystem</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D005615">Freezing</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D040362">Geographic Information Systems</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D005843">Geography</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D046448">Ice Cover</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D048088">Informatics</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName><QualifierName MajorTopicYN="N" UI="Q000639">trends</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D033181">Information Dissemination</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D009792">Oceans and Seas</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D058998">Remote Sensing Technology</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D054712">Salinity</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D013696">Temperature</DescriptorName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC3078385</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="aheadofprint"><Year>2011</Year><Month>3</Month><Day>28</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2011</Year><Month>3</Month><Day>30</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2011</Year><Month>3</Month><Day>30</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2011</Year><Month>7</Month><Day>2</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pii">0909306108</ArticleId><ArticleId IdType="doi">10.1073/pnas.0909306108</ArticleId><ArticleId IdType="pubmed">21444769</ArticleId><ArticleId IdType="pmc">PMC3078385</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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