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dc.contributor.advisorRenard, R.J.
dc.contributor.authorKarl, Michael L.
dc.dateJune 1984
dc.date.accessioned2012-11-19T23:50:01Z
dc.date.available2012-11-19T23:50:01Z
dc.date.issued1984-06
dc.identifier.urihttp://hdl.handle.net/10945/19336
dc.description.abstractThis report describes the development and application of a program to forecast important air/ocean parameters using the method (s) of model output statistics. The focus of this operationally oriented study is to forecast atmospheric marine horizontal visibility using a discrete analysis of observed visibility and the Navy's Operational Global Atmospheric Prediction System (NOGAPS) model output parameters. Three strategies (two based on maximum-probability and one based on natural-regression) are compared to two multiple linear regression methods. The primary data set is from a North Atlantic Ocean area bounded approximately by the North American coast from Norfolk, Va. to St. Johns, Newfoundland, and then eastward to about 37.5°W. Both the dependent and independent data were derived from the same basic set. New or unfamiliar concepts, in addition to the primary methodology, include the statistical division of the North Atlantic Ocean into physically homogeneous areas, two new threshold models for the application of linear regression equations, linear regression based upon a 'decision-tree' concept, functional dependence of predictors and class errors. Results show that the methodology proposed by Preisendorfer does out perform multiple linear regression.
dc.description.urihttp://archive.org/details/experimentsinfor1094519336
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. Copyright protection is not available for this work in the United States.
dc.subject.lcshMeteorologyen_US
dc.titleExperiments in forecasting atmospheric marine horizontal visibility using model output statistics with conditional probabilities of discretized parameters.en_US
dc.typeThesisen_US
dc.contributor.secondreaderPreisendorfer, Rudolph W.
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentMeteorology
dc.subject.authormodel output statisticsen_US
dc.subject.authorvisibilityen_US
dc.subject.authorNorth Pacific Ocean visibilityen_US
dc.subject.authorNorth Atlantic Ocean visibilityen_US
dc.subject.authormarine visibilityen_US
dc.subject.authorvisibility forecastingen_US
dc.subject.authordiscretizationen_US
dc.subject.authorconditional probabilitiesen_US
dc.subject.authorcategorical forecastingen_US
dc.subject.authorocean areasen_US
dc.subject.authorhomogeneous ocean areasen_US
dc.subject.authorthresholdsen_US
dc.subject.authorlinear regressionen_US
dc.subject.authornatural regressionen_US
dc.subject.authormaximum probabilityen_US
dc.description.serviceLieutenant Commander, United States Navy
etd.thesisdegree.nameM.S. in Meteorology and Oceanographyen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineMeteorology;Oceanographyen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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