Preliminary results from the anlysis of wind component error: July data
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Authors
Gaver, Donald Paul
Jacobs, Patricia A.
Subjects
Gaussian model with log-linear scale parameter; maximum likelihood; Newton's method
Advisors
Date of Issue
1992-11
Date
1992-11
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
Estimation 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 level
Type
Technical Report
Description
Series/Report No
Department
Operations Research
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
NPS-OR-93-003
Sponsors
Naval Research Laboratory-West
Funding
Naval Research Laboratory-West
Format
Citation
Distribution Statement
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.