Typhoon Tracks Regulated by Feedbacks of Fine-Scale Clouds to Environment
Haoran Zhao, Shaoqing Zhang, Yang Gao, Lixin Wu, Yihan Cao, Wenju Cai, Bin Wang, L. Ruby Leung, Zebin Lu, Zhong Zhong, Xiaolin Yu, Mingkui Li, Chenyu Zhu
公開日: 2025/9/30
Abstract
Accurate tropical cyclone (TC) track prediction is crucial for mitigating the catastrophic impacts of TCs on human life and the environment. Despite decades of research on tropical cyclone (TC) track prediction, large errors known as track forecast busts (TFBs) occur frequently, and their causes remain poorly understood. Here, we examine a few dozens of TCs using a unique TC downscaling strategy that can quantitatively assess the sensitivity of TC track on the strength of feedbacks of fine-scale clouds to environment. We show that as TFBs have a weaker environmental steering that favors scattering cumulonimbus clouds, capturing asymmetric distribution of planetary vorticity advection induced by such fine-scale clouds corrects TFBs by 60 percent. Our clear identification of such important TC track predictability source promises continuous improvement of TC track prediction as finer-scale TC clouds and their interactions with environment are better resolved as model larger-scale behaviors have improved.