A comparison of predictors for first-guess wind speed errors
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Author
Contributions
- Jacobs, Patricia A. - Contributor
- Naval Postgraduate School (U.S.). Dept. of Operations Research - Contributor
Publication
1993 - Available from National Technical Information Service, Monterey, Calif, California
Language
English
Word Count
8,250 words, Guess
Page Count
33 pages
Identifiers
- Internet Archivecomparisonofpred00gave
- Open LibraryOL25510344M
Alternate Titles
- NPS-OR-93-020.
Description
Numerical meteorological models are used to assist in the prediction of weather. Each run of a numerical model produces forecasts of meteorological variables which are used as preliminary predictions of the future values of these variables. These initial predictions are referred to as first-guess values. Estimation of the mean-square first-guess error is required in the optimal interpolation process in the numerical prediction of atmospheric variables. Several predictors for the mean-square error of the first-guess wind speeds are studied. The results suggest that prediction using observed covariates tend to be better than those using first-guess covariates. However, observed covariates are not always available. Predictions using first-guess covariates are better at the 250 mb level than the 850 or 500 mb levels. Of those first-guess covariates studied, first-guess wind speed appears to be the best. Gaussian model with log-linear scale parameter, Nonparametric models, Prediction of mean square errors, First-guess errors in meteorological models, Generalized linear regression.
Subjects
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