The Analysis of Tropical Cyclone Tracks in the Western North Pacific through Data Mining. Part II: Tropical Cyclone Landfall
Publication in refereed journal


Times Cited
Web of Science14WOS source URL (as at 07/07/2020) Click here for the latest count
Altmetrics Information
.

Other information
AbstractThis is the second paper of a two-part series of papers on the analysis of tropical cyclone (TC) tracks in the western North Pacific Ocean. In this paper, TC landfalls in the South China Sea and western North Pacific basins are investigated through the data-mining approach. On the basis of historical TC archives, the C4.5 algorithm, a classic tree algorithm for classification, has been employed to quantitatively discover rules governing TC landfall. A classification tree, with 14 leaf nodes, has been built. The path from the root node to each leaf node forms a rule. Fourteen rules governing TC landfall across the Chinese coast have been unraveled with respect to the selected attributes having potential influence on TC landfall. The rules are derived by the attributes and splitting values. From the classification tree, split values, such as 27 degrees N latitude, 130 degrees E longitude, 141 degrees E in the west extension index, and 0.289 in the monsoon index have been shown to be useful for TC forecasting. The rules have been justified from the perspective of meteorology and knowledge of TC movement and recurvature (e.g., deep-layer mean winds and large-scale circulation). The research findings are also consistent with existing results concerning TC movement and landfall. Both the unraveled rules and the associated splitting values can provide useful references for the prediction of TC landfall over China.
All Author(s) ListZhang W, Leung Y, Chan JCL
Journal nameJournal of Applied Meteorology and Climatology
Year2013
Month6
Day1
Volume Number52
Issue Number6
PublisherAMER METEOROLOGICAL SOC
Pages1417 - 1432
ISSN1558-8432
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesMeteorology & Atmospheric Sciences; METEOROLOGY & ATMOSPHERIC SCIENCES

Last updated on 2020-08-07 at 04:27