Decoding Typhoon Wind Patterns: Variational Retrieval and Multifractal Insights

Typhoon wind dynamics are inherently nonlinear, exhibiting complex interactions between large-scale trajectory shifts and small-scale variability. This study employs variational retrieval techniques and multifractal analysis to investigate altitude-specific wind field patterns and their connections to trajectory and intensity changes. Using radar observations and numerical model data, high-resolution 3D wind fields were constructed to explore the structural and statistical characteristics of wind components (U, V) across different altitudes and typhoon trajectories.

Our analysis focuses on two distinct trajectory types: northward-moving typhoons (e.g., Nakri, Lingling, Bavi) and northeastward-moving typhoons (e.g., Chaba, Kong-Rey). Results indicate that northward trajectories exhibit crescent-shaped wind patterns dominated by northerly wind components, while northeastward trajectories show circular wind structures. Notably, multifractal analysis revealed abrupt decreases in the multifractal parameter α for northerly winds at 1–2 km altitude during trajectory transitions, suggesting nonlinear structural reorganization within the typhoon system. For example, during Typhoon Chaba (2016) and Typhoon Kong-Rey (2018), α values for northerly winds dropped sharply by 1.5–2.2 units, coinciding with significant directional shifts and rapid changes in typhoon directions.

In addition to wind field analysis, we quantified variability in rainfall fields using radar reflectivity and rainfall intensity data. Northeastward-moving typhoons demonstrated broader and more intense rainfall bands, with higher vertical reflectivity profiles up to 8 km altitude, compared to the narrower and more localized patterns observed in northward-moving cases. This suggests a strong coupling between wind field variability and rainfall distribution, driven by nonlinear interactions.

By integrating multifractal techniques with variational retrieval methods, this study bridges small-scale turbulence with large-scale trajectory dynamics, offering new insights into the inherent complexity of typhoon systems. These findings contribute to the development of advanced prediction systems, enabling more accurate trajectory and intensity forecasts. Such approaches could significantly mitigate the impacts of typhoons on the Korean Peninsula and beyond.

 

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No.RS-2024-00460019)