Citation

Chen P, Yu H, Chan JCL. Acta Meterol. Sin. 2011; 25(5): 611-624.

Copyright

(Copyright © 2011, Chinese Meteorological Society, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s13351-011-0506-9

PMID

unavailable

Abstract

A western North Pacific tropical cyclone (TC) intensity prediction scheme (WIPS) is developed based on TC samples from 1996 to 2002 using the stepwise regression technique, with the western North Pacific divided into three sub-regions: the region near the coast of East China (ECR), the South China Sea region (SCR), and the far oceanic region (FOR). Only the TCs with maximum sustained surface wind speed greater than 17.2 m s−1 are used in the scheme. Potential predictors include the climatology and persistence factors, synoptic environmental conditions, potential intensity of a TC and proximity of a TC to land. Variances explained by the selected predictors suggest that the potential intensity of a TC and the proximity of a TC to land are significant in almost all the forecast equations. Other important predictors include vertical wind shear in ECR, 500-hPa geopotential height anomaly at the TC center, zonal component of TC translation speed in SCR, intensity change of TC 12 or 24 h prior to initial time, and the longitude of TC center in FOR.

Independent tests are carried out for TCs in 4 yr (2004-2007), with mean absolute errors of the maximum surface wind being 3.0, 5.0, 6.5, 7.3, 7.6, and 7.9 m s−1 for 12- to 72-h predictions at 12-h intervals, respectively. Positive skills are obtained at all leading time levels as compared to the climatology and persistence prediction scheme, and the large skill scores (near or over 20%) after 36 h imply that WIPS performs especially better at longer leading times. Furthermore, it is found that the amendment in TC track prediction and real-time model analysis can significantly improve the performance of WIPS in the SCR and ECR. Future improvements will focus on applying the scheme for weakening TCs and those near the coastal regions.