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dc.contributor.authorGaver, Donald Paul
dc.contributor.authorJacobs, Patricia A.
dc.date1992-11
dc.date.accessioned2013-03-07T21:53:47Z
dc.date.available2013-03-07T21:53:47Z
dc.date.issued1992-11
dc.identifier.urihttp://hdl.handle.net/10945/30090
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 April and July 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 components. The predictions using observational winds appear to be better at the 850 mb level. The predictions using first guess winds appear to be better at the 250 mb levelen_US
dc.description.sponsorshipNaval Research Laboratory-Westen_US
dc.description.urihttp://archive.org/details/preliminaryresul93003gave
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.lcshWIND.en_US
dc.titlePreliminary results from the anlysis of wind component error: July dataen_US
dc.typeTechnical Reporten_US
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentOperations Research
dc.subject.authorGaussian model with log-linear scale parameter; maximum likelihood; Newton's methoden_US
dc.description.funderNaval Research Laboratory-Westen_US
dc.description.recognitionNAen_US
dc.identifier.oclcNA
dc.identifier.npsreportNPS-OR-93-003


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