An Analysis of the Error Characteristics of Atlantic Tropical Cyclone Track Prediction Models

Using 140 track forecasts between 1976-1985, the error characteristics of the National Hurricane Center's tropical cyclone track prediction models are assessed with special emphasis on the Moveable Fine Mesh (MFM) model. The results indicate that beyond the 12-hour forecast, the MFM has the low...

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Bibliographic Details
Main Author: Kroll, James T.
Other Authors: AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH
Format: Text
Language:English
Published: 1988
Subjects:
Meteorology
*TROPICAL CYCLONES
*ATMOSPHERE MODELS
TRACKING
THESES
WEATHER FORECASTING
MESH
WEIGHTING FUNCTIONS
MATHEMATICAL PREDICTION
ERROR ANALYSIS
LINEAR REGRESSION ANALYSIS
NORTH ATLANTIC OCEAN
CONFIDENCE LEVEL
MOTION
WIND
PATHS
MFM(MOVABLE FINE MESH)
North Atlantic
Online Access:http://www.dtic.mil/docs/citations/ADA197146
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA197146
Description
Summary:Using 140 track forecasts between 1976-1985, the error characteristics of the National Hurricane Center's tropical cyclone track prediction models are assessed with special emphasis on the Moveable Fine Mesh (MFM) model. The results indicate that beyond the 12-hour forecast, the MFM has the lowest mean forecast error of the NHC models. The forecast error component, relative to storm motion, are also analyzed. The MFM displayed the smallest mean across-track error, which is a measure of the accuracy of the path of movement. A consensus style track forecast known as the Combined Confidence Weighted Forecast (CCWF) scheme is tested using the track prediction output from NHC models. The CCWF provides improved track forecasts at 12 and 24 hours relative to the individual track prediction models. The CCWF scheme, on average, is also more accurate than the official forecast disseminated by NHC. An attempt is made to develop linear regression models, using independent variables which describe storm characteristics and the large-scale wind field,l to predict the magnitude of the NHC track prediction model forecast errors. Finally, a spectral barotropic model is used to identify the effects that sparse data and initial position errors have upon track forecast errors. Various scales of motion are removed from the initial wind field to test the effect of sparse data. Theses.

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