Publication:
An evaluation of discretized conditional probability and linear regression threshold techniques in model output statistics forecasting of visibility over the North Atlantic Ocean

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Authors
Diunizio, Mark
Subjects
Model output statistics
Visibility
North Atlantic Ocean visibility
Marine horizontal visibility
Discretization
Conditional probability
Physically homogeneous ocean areas
Minimum probable error threshold models
Weather forecasting
Maximum-likelihood-of-detection threshold models
Linear regression
Natural regression
Maximum probability
Advisors
Renard, Robert J.
Date of Issue
1984-09
Date
September 1984
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
This report describes the application and evaluation of four primary statistical models in the forecasting of horizontal marine visibility over selected physically homogeneous area of the North Atlantic Ocean. The main focus of this study is to propose an optimal model output statistics (MOS) approach to operationally forecast visibility at the 00-hour model initialization time and the 24-hour and 48-hour model forecast projections. The technique utilized involves the manipulation of observed visibility and Navy Operational Global Atmospheric Prediction System (NOGAPS) model output parameters. The models employ the statistical methodologies of maximum conditional probability, natural regression and minimum probable error linear regression threshold techniques. Additionally, an evaluation of the 1983 predictive arrays/equations using 1984 NOGAPS data fields and a maximum-likelihood-of-detection threshold model were accomplished. Results show that two statistical approaches, namely a maximum conditional probability strategy utilizing linear regression equation predictors and the minimum probable error threshold models, produce the best results achieved in this study.
Type
Thesis
Description
Series/Report No
Department
Meteorology
Other Units
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This 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.
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