Content in the Context of 4D-Var Data Assimilation. II: Application to Global Ozone Assimilation

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dc.contributor.authorSingh, Kumareshen
dc.contributor.authorJardak, Mohameden
dc.contributor.authorSandu, Adrianen
dc.contributor.authorBowman, Kevinen
dc.contributor.authorLee, Meemongen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:36:48Zen
dc.date.available2013-06-19T14:36:48Zen
dc.date.issued2011-11-01en
dc.description.abstractData assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. Not all observations used in data assimilation are equally valuable. The ability to characterize the usefulness of different data points is important for analyzing the effectiveness of the assimilation system, for data pruning, and for the design of future sensor systems. In the companion paper [Sandu et al.(2011)] we derived an ensemble-based computational procedure to estimate the information content of various observations in the context of 4D-Var. Here we apply this methodology to quantify two information metrics (the signal and degrees of freedom for signal) for satellite observations used in a global chemical data assimilation problem with the GEOS-Chem chemical transport model. The assimilation of a subset of data points characterized by the highest information content, gives analyses that are comparable in quality with the one obtained using the entire data set.en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00001173/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00001173/01/information_content_tes.pdfen
dc.identifier.trnumberTR-11-24en
dc.identifier.urihttp://hdl.handle.net/10919/19460en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.relation.ispartofComputer Science Technical Reportsen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectNumerical analysisen
dc.titleContent in the Context of 4D-Var Data Assimilation. II: Application to Global Ozone Assimilationen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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