Experiments in Forecasting Atmospheric Marine Horizontal Visibility Using Model Output Statistics with Conditional Probabilities of Discretized Parameters.

This thesis 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 v...

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Bibliographic Details
Main Author: Karl,M L
Other Authors: NAVAL POSTGRADUATE SCHOOL MONTEREY CA
Format: Text
Language:English
Published: 1984
Subjects:
Meteorology
*WEATHER FORECASTING
MATHEMATICAL MODELS
COMPUTERIZED SIMULATION
THESES
MATHEMATICAL PREDICTION
VISIBILITY
NAVAL OPERATIONS
HORIZONTAL ORIENTATION
LINEAR REGRESSION ANALYSIS
OCEAN ENVIRONMENTS
NORTH ATLANTIC OCEAN
NOGAPS computer program
Newfoundland
North Atlantic
Online Access:http://www.dtic.mil/docs/citations/ADA147574
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA147574
Description
Summary:This thesis 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 laser regression methods. The primary data set is from a North Atlantic Ocean are bounded approximately by the North American coast from Norfolk, Va. to St. Johns, Newfoundland, and then eastward to about 37.5 deg W. Both the dependent and independent data were derived from the same basic set. New or unfamiliar concepts, in addition to the primary method, 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 method proposed by Preisendorfer out performs multiple linear regression.

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