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Bibliography: l. 146-148

Empirical Orthogonal Function (EOF) analysis is used to describe the synoptic forcing features of selected northwestern Pacific Ocean tropical cyclones from 1967 to 1976. EOF analysis is applied to the geopotential field at 850, 700 and 500mb on a 120 point grid with 5 degree latitude and longitude spacing that is centered on the storm. The 120 EOF coefficients (for each level) are computed for a sample of 454 cases in the history file. The coefficient vectors are truncated to the first 10 coefficients, based on the Monte Carlo selection criteria of Preisendorfer and Barnett. These coefficients describe about 85% of the variance in the fields. The synoptic forcing represented by the EOF coefficients is then used as a predictor in a regression analysis track forecast scheme, along with past storm movement and intensity during the past 36 hours. The EOF-based regression equations are verified over an independent sample of 50 storms, and the position errors compared to the official Joint Typhoon Warning Center (JTWC) forecast errors. The EOF-based regression equations give, on the average, a 17% reduction in error when compared to the official forecast issued by JTWC. Over the independent sample, the 500mb equations performed better than the equations of the other two levels

Empirical Orthogonal Function (EOF) analysis is used to describe the synoptic forcing features of selected northwestern Pacific Ocean tropical cyclones from 1967 to 1976. EOF analysis is applied to the geopotential field at 850, 700 and 500mb on a 120 point grid with 5 degree latitude and longitude spacing that is centered on the storm. The 120 EOF coefficients (for each level) are computed for a sample of 454 cases in the history file. The coefficient vectors are truncated to the first 10 coefficients, based on the Monte Carlo selection criteria of Preisendorfer and Barnett. These coefficients describe about 85% of the variance in the fields. The synoptic forcing represented by the EOF coefficients is then used as a predictor in a regression analysis track forecast scheme, along with past storm movement and intensity during the past 36 hours. The EOF-based regression equations are verified over an independent sample of 50 storms, and the position errors compared to the official Joint Typhoon Warning Center (JTWC) forecast errors. The EOF-based regression equations give, on the average, a 17% reduction in error when compared to the official forecast issued by JTWC. Over the independent sample, the 500mb equations performed better than the equations of the other two levels.