Relationship between Early-Stage Features and Lifetime Maximum Intensity of Tropical Cyclones over the Western North Pacific

• Main Authors: Ren Lu, Xiaodong Tang
• Format: Article
• Language: English
• Published: MDPI AG 2021-06-01
• Series: Atmosphere
• Subjects: tropical cyclone; lifetime maximum intensity; machine learning; AdaBoost; decision tree; composite analysis
• Online Access: https://www.mdpi.com/2073-4433/12/7/815

The relationship between early-stage features and lifetime maximum intensity (LMI) of tropical cyclones (TCs) over the Western North Pacific (WNP) was investigated by ensemble machine learning methods and composite analysis in this study. By selecting key features of TCs’ vortex attributes and environmental conditions, a two-step AdaBoost model demonstrated accuracy of about 75% in distinguishing weak and strong TCs at genesis and a coefficient of determination (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></semantics></math></inline-formula>) of 0.30 for LMI estimation from the early stage of strong TCs, suggesting an underlying relationship between LMI and early-stage features. The composite analysis reveals that TCs with higher LMI are characterized by lower latitude embedded in a continuous band of high low-troposphere vorticity, more compact circulation at both the upper and lower levels of the troposphere, stronger circulation at the mid-troposphere, a higher outflow layer with stronger convection, a more symmetrical structure of high-level moisture distribution, a slower translation speed, and a greater intensification rate around genesis. Specifically, TCs with greater “tightness” at genesis may have a better chance of strengthening to major TCs (LMI ≥ 96 kt), since it represents a combination of the inner and outer-core wind structure related to TCs’ rapid intensification and eyewall replacement cycle.