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Remote Sensing
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5 December 2025

Predictability of Landfalling Typhoon Tracks in East China Based on Ensemble Sensitivity Analysis

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1
Shanghai Typhoon Institute, China Meteorological Administration, Shanghai 200030, China
2
Nanjing Innovation Institute for Atmospheric Sciences, Chinese Academy of Meteorological Sciences–Jiangsu Meteorological Service, Nanjing 210041, China
3
Key Laboratory of Transportation Meteorology of CMA/Jiangsu Key Laboratory of Severe Storm Disaster Risk, Nanjing 210041, China
*
Author to whom correspondence should be addressed.
Remote Sens.2025, 17(24), 3944;https://doi.org/10.3390/rs17243944 
(registering DOI)
This article belongs to the Special Issue Multi-Source Atmospheric Remote Sensing: Enabling High-Precision Meteorological Monitoring and Forecasting

Abstract

Accurate typhoon track forecasting is vital for disaster mitigation in East China, a region frequently impacted by landfalling typhoons. Despite advances in numerical weather prediction, uncertainties remain high, especially within 48 h of landfall, due to complex interactions among tropical cyclones, the subtropical high, and mesoscale systems. This study applies Ensemble-based Sensitivity Analysis (ESA) within a high-resolution regional ensemble prediction system (Shanghai Weather And Risk Model System-Ensemble Prediction System, SWARMS-EN) to investigate forecast uncertainties of three representative typhoons—Gaemi, Bebinca, and Kong-rey—that made landfall in East China in 2024. Our results reveal consistent sensitivity patterns across diverse large-scale environments, particularly around the western flank of the subtropical high and in proximity to nearby low-pressure systems. Track uncertainty was closely tied to fluctuations in the steering flow, notably its zonal component. Moreover, binary typhoon interactions emerged as key drivers of forecast divergence. ESA effectively identified sensitive regions where small initial perturbations exert significant downstream influence on typhoon tracks. This study demonstrates the operational value of ESA for diagnosing forecast error sources and guiding targeted observations. By linking forecast uncertainty to physical mechanisms, this research enhances our understanding of typhoon predictability and supports the development of more adaptive and accurate regional forecasting systems.

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