Ensemble forecasting techniques in medium-range forecasting
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Authors
Warren, Steven W.
Subjects
Ensemble models
Regression technique
Forecast divergence
Systematic error
Regression technique
Forecast divergence
Systematic error
Advisors
Nuss, Wendell A.
Date of Issue
1993-03
Date
March 1993
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
A continuing trend in numerical weather prediction (NWP) is the desire for reduced model forecast error. Developments in NWP such as advanced computing power and improved model physics and analysis methods have been successful in lowering error but are potentially limited The regression method of ensemble forecasting is used to further reduce mean forecast error when compared to individual model forecast performances. A statistical regression scheme is utilized to achieve an optimum combination fitting of the National Meteorological Center, the European Centre for Medium-Range Weather Forecasts, and the U.S. Navy Fleet Numerical Oceanography Center forecast models. The performance of the regression model is evaluated for 72-h and 108-h prediction cycles through statistical and subjective comparisons with the individual models and an equally weighted ensemble model at the surface and at 500 hPa. The regression model is shown to produce gains through the reduction of systematic error present in the individual model forecasts...
Type
Thesis
Description
Series/Report No
Department
Meteorology
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
111 p.
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.