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dc.contributor.authorGaver, Donald Paul
dc.contributor.authorJacobs, Patricia A.
dc.date1991-09
dc.date.accessioned2013-03-07T21:53:46Z
dc.date.available2013-03-07T21:53:46Z
dc.date.issued1991-09
dc.identifier.urihttp://hdl.handle.net/10945/30088
dc.description.abstractEstimation of mean square prediction error of wind components is required in the optimal interpolation (OI) process in numerical prediction of atmospheric variables. Statistical models with log-linear scale parameters which include covariates are described for the prediction error. Data from February and April of 1991 are used to fit the model parameters and to study the predictive ability of the models. This preliminary investigation indicates that observational and first guess wind components can be helpful in predicting mean square prediction error for wind componentsen_US
dc.description.sponsorshipNaval Oceanographic and Atmospheric Research Laboratory, Monterey, CAen_US
dc.description.urihttp://archive.org/details/preliminaryresul00gave
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.subject.lcshWINDen_US
dc.titlePreliminary results from the analysis of wind component erroren_US
dc.typeTechnical Reporten_US
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentOperations Research
dc.contributor.departmentNaval Oceanographic and Atmospheric Research Laboratory
dc.subject.authorGaussian model with log-linear scale parameter; maximum likelihood; Newton's methoden_US
dc.description.funderNaval Oceanographic and Atmospheric Research Laboratory, Monterey, Californiaen_US
dc.description.recognitionNAen_US
dc.identifier.oclcNA
dc.identifier.npsreportNPS-OR-91-029


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