Wind Distribution in the Eye of Tropical Cyclone Revealed by a Novel Atmospheric Motion Vector Derivation

Observations of wind distribution in the eye of tropical cyclones (TCs) are still limited. Aircraft reconnaissance has revealed the dynamics in the eye of TC. However, aircraft observation usually takes ~1 hour to horizontally cover the inner-core region, and steady-state conditions are often assumed due to the lengthy observation periods. Airborne radar also cannot observe the wind in the eye due to the lack of precipitation particles. Geostationary meteorological satellites (GMSs) provide uninterrupted observations of TCs throughout their lifecycle. If atmospheric motion vectors (AMVs) could be derived using consecutive images, it allows us to estimate dense wind distribution in the eye.

Third-generation GMSs such as Himawari-8, which began operating in 2015, have significantly improved the spatiotemporal and wavelength resolution compared to their predecessors. For instance, Himawari-8/9 have twice the spatial resolution of its predecessor, with 0.5 km for a visible channel and 2 km for infrared channels at nadir. In particular, the rapid-scan observations for TCs are made every 2.5 min covering an entire TC area.

In a recent study, Horinouchi et al. (2023; hereinafter, H23) investigated low-level AMVs obtained in the eye of Typhoon Haishen (2020) using research-based special observations with Himawari-8, which were conducted every 30 sec. They identified both stationary and transient asymmetric features in the eye that were associated with an algebraically growing wavenumber-1 disturbance (Nolan & Montgomery 2000). These features were found to be important in the angular momentum transport towards the storm center, which resulted in an acceleration of the rotation in the eye. They suggested that the wavenumber-1 disturbance might be one of the major processes that redistribute potential vorticity in the eye to increase rotation near the center.

H23 employed template matching method with cross-correlation to derive AMVs. To demonstrate the effect of the high-frequency imaging, they also conducted an experiment in which the time interval was deliberately increased and showed that the number of obtained AMVs decreases as the observation frequency decreases, suggesting the need for elaborated methods to estimate wind distribution.

In this study, a novel TC-specific cloud tracking method is developed by extending the method of H23 by considering the characteristics of TCs. Initially, we create image sequences that are rotated with respect to time in the direction opposite to the rotation in the eye to offset the eye rotation. For each image sequence, the cloud tracking method of H23 is performed with a narrow template matching search range. The AMVs that pass a quality control are used as candidate estimates for each spatiotemporal grid point. The candidate AMV with the highest cross-correlation coefficient is selected as tentative estimate at each grid point. The candidate AMVs that have large differences from spatiotemporal median wind field obtained from tentative estimates are rejected. The tentative estimates are then re-selected based on remaining candidates. This process is repeated iteratively, using the median wind field obtained from updated tentative estimates to reject candidate estimates, until the differences become small enough. The final tentative estimates are used as the final AMVs.

By employing this method, we obtained AMVs with high spatiotemporal resolution for Typhoons Haishen (2020), Nanmadol (2022), and Lan (2017). An example of the AMVs obtained from 2.5-min interval images of Typhoon Lan is shown in attached figure. The AMVs obtained from 2.5-min interval images are compared with those from 30-sec interval images for Typhoons Haishen and Nanmadol. As a comparison with the in-situ observations, the AMVs obtained from the 2.5-min images are found to be in good agreement with the dropsonde observations in Typhoons Nanmadol and Lan.

As asymmetric motions in the obtained AMVs in the eye, transient azimuthal wavenumber-1 features are identified in all three TCs. These features are consistent with the algebraically growing wavenumber-1 disturbances as shown by H23. In the eye of Lan, the angular velocity increased by approximately 1.5 times within 1-hour period. This short-term acceleration in angular velocity is consistent with the findings of Kossin & Eastin (2001) who observed a similar acceleration in the eye using aircraft flight-level data. In an unforced idealized barotropic simulation, the eyewall vorticity ring breaks down and forms mesovortices due to the barotropic instability around the eyewall (Schubert et al. 1999; Kossin and Schubert 2001). They explained the cause of the acceleration in the eye as the mesovortices transporting angular momentum inward and pushing out the relatively weaker vorticity in the eye. To further understand this phenomenon, a visualization of low-level vorticity in the eye and angular momentum budget analysis are conducted. The results suggest that angular momentum transport associated with mesovortices may have played an important role in the increase of tangential wind and the homogenization of angular velocity in the eye of Lan.

The results presented in this study highlight the significant potential of utilizing operational rapid-scan observations from latest GMSs to study the dynamics of TCs. Future work is expected to involve statistical studies applying the developed method to a larger number of TC cases. Additionally, the combination of Doppler radar observations to analyze the wind field over the eyewall and low-level AMVs over the eye shows potential for revealing new insights into the low-level inner-core dynamics of TCs.