Open AccessDiscriminating Developing versus Nondeveloping Tropical Disturbances in the Western North Pacific through Decision Tree Analysis
Author(s) -
Wei Zhang,
Bo Fu,
Melinda S. Peng,
Tim Li
Publication year - 2015
Publication title -
weather and forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.393
H-Index - 106
eISSN - 1520-0434
pISSN - 0882-8156
DOI - 10.1175/waf-d-14-00023.1
Subject(s) - tropical cyclone , anomaly (physics) , climatology , precipitation , decision tree , environmental science , hindcast , meteorology , geology , computer science , geography , data mining , physics , condensed matter physics
This study investigates the classification of developing and nondeveloping tropical disturbances in the western North Pacific (WNP) through the C4.5 algorithm. A decision tree is built based on this algorithm and can be used as a tool to predict future tropical cyclone (TC) genesis events. The results show that the maximum 800-hPa relative vorticity, SST, precipitation rate, divergence averaged between 1000- and 500-hPa levels, and 300-hPa air temperature anomaly are the five most important variables for separating the developing and nondeveloping tropical disturbances. This algorithm also unravels the thresholds of the five variables (i.e., 4.2 × 10−5 s−1 for maximum 800-hPa relative vorticity, 28.2°C for SST, 0.1 mm h−1 for precipitation rate, −0.7 × 10−6 s−1 for vertically averaged convergence, and 0.5°C for 300-hPa air temperature anomaly). Six rules are derived from the decision tree. The classification accuracy of this decision tree is 81.7% for the 2004–10 cases. The hindcast accuracy for the 2011–13 dataset is 84.6%.