Discriminating Developing versus Nondeveloping Tropical Disturbances in the Western North Pacific through Decision Tree Analysis
Discriminating Developing versus Nondeveloping Tropical Disturbances in the Western North Pacific through Decision Tree Analysis
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DOI：
10.1175/waf-d-14-00023.1
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发表时间：
2015-04
影响因子：
2.9
通讯作者：
Wei Zhang;B. Fu;M. Peng;Tim Li
中科院分区：
文献类型：
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作者：
Wei Zhang;B. Fu;M. Peng;Tim Li
摘要本研究通过C4.5算法研究了西北太平洋（WNP）正在发生和未发生的热带扰动的分类。基于该算法构建的决策树可用作预测未来热带气旋 (TC) 成因事件的工具。结果表明，800 hPa最大相对涡度、海温、降水率、1000和500 hPa平均辐散以及300 hPa气温距平是区分热带扰动发展和非发展的五个最重要的变量。该算法还揭示了五个变量的阈值（即，最大800 hPa相对涡度为4.2 × 10−5 s−1，海温为28.2°C，降水率为0.1 mm h−1，垂直平均收敛为−0.7 × 10−6 s−1，300 hPa气温异常为0.5°C）。从决策树中导出了六个规则。对于 2004-10 年的案例，该决策树的分类准确率为 81.7%。后报准确度...
AbstractThis 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 t...