A comparison of predictors for first-guess wind speed errors
By: Donald P. Gaver, Patricia A. Jacobs
Contributors: Jacobs, Patricia A.; Naval Postgraduate School (U.S.). Dept. of Operations Research
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1993
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Number of pages: 33
Subjects: MATHEMATICAL MODELS; MATHEMATICAL PREDICTION; WIND  VELOCITY
Other 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.
Notes: Title from cover.

"NPS-OR-93-020."

"December 1993."

AD A276 460.

Includes bibliographical references (p. 9 )

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