Realization of Dynamically Adaptive Weather Analysis and Forecasting in LEAD: Four Years Down the Road
Identifieur interne : 000122 ( Istex/Corpus ); précédent : 000121; suivant : 000123Realization of Dynamically Adaptive Weather Analysis and Forecasting in LEAD: Four Years Down the Road
Auteurs : Lavanya Ramakrishnan ; Yogesh Simmhan ; Beth PlaleSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: Linked Environments for Atmospheric Discovery (LEAD) is a large-scale cyberinfrastructure effort in support of mesoscale meteorology. One of the primary goals of the infrastructure is support for real-time dynamic, adaptive response to severe weather. In this paper we revisit the conception of dynamic adaptivity as appeared in our 2005 DDDAS workshop paper, and discuss changes since the original conceptualization, and lessons learned in working with a complex service oriented architecture in support of data driven science.
Url:
DOI: 10.1007/978-3-540-72584-8_147
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One of the primary goals of the infrastructure is support for real-time dynamic, adaptive response to severe weather. In this paper we revisit the conception of dynamic adaptivity as appeared in our 2005 DDDAS workshop paper, and discuss changes since the original conceptualization, and lessons learned in working with a complex service oriented architecture in support of data driven science.</Para></Abstract><KeywordGroup Language="En"><Heading>Keywords</Heading><Keyword>Weather Analysis and Forecasting</Keyword></KeywordGroup></ChapterHeader><NoBody></NoBody></Chapter></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Realization of Dynamically Adaptive Weather Analysis and Forecasting in LEAD: Four Years Down the Road</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Realization of Dynamically Adaptive Weather Analysis and Forecasting in LEAD: Four Years Down the Road</title></titleInfo><name type="personal"><namePart type="given">Lavanya</namePart><namePart type="family">Ramakrishnan</namePart><affiliation>School of Informatics, Indiana University, Bloomington, IN 47045</affiliation><affiliation>E-mail: laramakr@cs.indiana.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Yogesh</namePart><namePart type="family">Simmhan</namePart><affiliation>School of Informatics, Indiana University, Bloomington, IN 47045</affiliation><affiliation>E-mail: ysimmhan@cs.indiana.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Beth</namePart><namePart type="family">Plale</namePart><affiliation>School of Informatics, Indiana University, Bloomington, IN 47045</affiliation><affiliation>E-mail: plale@cs.indiana.edu</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2007</dateIssued><copyrightDate encoding="w3cdtf">2007</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: Linked Environments for Atmospheric Discovery (LEAD) is a large-scale cyberinfrastructure effort in support of mesoscale meteorology. One of the primary goals of the infrastructure is support for real-time dynamic, adaptive response to severe weather. In this paper we revisit the conception of dynamic adaptivity as appeared in our 2005 DDDAS workshop paper, and discuss changes since the original conceptualization, and lessons learned in working with a complex service oriented architecture in support of data driven science.</abstract><relatedItem type="host"><titleInfo><title>Computational Science – ICCS 2007</title><subTitle>7th International Conference, Beijing, China, May 27 - 30, 2007, Proceedings, Part I</subTitle></titleInfo><name type="personal"><namePart type="given">Yong</namePart><namePart type="family">Shi</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Geert</namePart><namePart type="given">Dick</namePart><namePart type="family">van Albada</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jack</namePart><namePart type="family">Dongarra</namePart><role><roleTerm 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2007</recordOrigin></recordInfo></mods></metadata><enrichments><json:item><type>multicat</type><uri>https://api.istex.fr/document/9B953067259EB39BEEC1BE685375E59649F2C142/enrichments/multicat</uri></json:item><istex:refBibTEI uri="https://api.istex.fr/document/9B953067259EB39BEEC1BE685375E59649F2C142/enrichments/refBib"><teiHeader></teiHeader><text><front></front><body></body><back><listBibl><biblStruct xml:id="b0"><analytic><title level="a" type="main">Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD</title><author><persName><forename type="first">B</forename><surname>Plale</surname></persName></author><author><persName><forename type="first">D</forename><surname>Gannon</surname></persName></author><author><persName><forename type="first">D</forename><surname>Reed</surname></persName></author><author><persName><forename type="first">S</forename><surname>Graves</surname></persName></author><author><persName><forename 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