Wind distribution in the eye of tropical cyclone revealed by a novel atmospheric motion vector derivation
概要
Observations of wind distribution in the eye of tropical cyclones (TCs) are still limited. In this study, a method to derive atmospheric motion vectors (AMVs) for TCs is developed, where selection from multiple local rotation speeds is made by considering continuity among neighboring grid points. The method is applied to 2.5‐min interval image sequences of three TCs, Lan (2017), Haishen (2020), and Nanmadol (2022), observed by the Himawari‐8 satellite. The results are compared with AMVs derived from research‐based 30‐s Himawari‐8 special observations conducted for Haishen and Nanmadol, as well as with in‐situ dropsonde observations conducted for Lan and Nanmadol. In these storms, the AMVs obtained from the 2.5‐min interval images in the eye are found to be in good agreement with the dropsonde observations. Examinations of AMVs in the eye reveal transient azimuthal wavenumber‐1 features in all three TCs. These features are consistent with algebraically growing wavenumber‐1 disturbances, which transport angular momentum inward and accelerate the eye rotation. In the case of Lan, the angular velocity in the eye increased by approximately 1.5 times within 1 hr. This short‐term increase is further examined. Visualization of low‐level vorticity in the eye and angular momentum budget analysis suggest that angular momentum transport associated with mesovortices played an important role in the increase of tangential wind and the homogenization of angular velocity in the eye of Lan.
引用
Tsukada, T., T. Horinouchi, and S. Tsujino, 2024: Wind distribution in the eye of tropical cyclone revealed by a novel atmospheric motion vector derivation. Journal of Geophysical Research: Atmospheres, 129, e2023JD040585. https://doi.org/10.1029/2023JD040585.
公開データ
本研究で得られた台風中心の主観解析結果、導出された大気追跡風、比較に用いられたドロップゾンデデータは次のリポジトリにて公開しています:
https://doi.org/10.5281/zenodo.10798896
ライセンス
上記データは Creative Commons Attribution 4.0 International に準拠しています。公開ソフトウェア
本研究で開発された openTCAMV
のソースコードは次のリポジトリにて公開しています:
https://github.com/tsukada-cs/openTCAMV
openTCAMV
では、雲追跡部分に pyVTTrac
ライブラリを用います。pyVTTrac
は VTTrac.jl
をPythonでラップしたものです。pyVTTrac
とVTTrac.jl
のソースコードは次のリポジトリにて公開しています:
- pyVTTrac: https://github.com/tsukada-cs/pyVTTrac
- VTTrac.jl: https://github.com/tsukada-cs/VTTrac.jl