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A numerical study of the Tornado-like vortex event over Oahu, Hawaii, on 8 June 2003
A numerical study of the Tornado-like vortex event over Oahu, Hawaii, on 8 June 2003
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A numerical study of the Tornado-like vortex event over Oahu, Hawaii, on 8 June 2003
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A numerical study of the Tornado-like vortex event over Oahu, Hawaii, on 8 June 2003
A numerical study of the Tornado-like vortex event over Oahu, Hawaii, on 8 June 2003

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A numerical study of the Tornado-like vortex event over Oahu, Hawaii, on 8 June 2003
A numerical study of the Tornado-like vortex event over Oahu, Hawaii, on 8 June 2003
Journal Article

A numerical study of the Tornado-like vortex event over Oahu, Hawaii, on 8 June 2003

2025
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Overview
In this study, we revisit a heavy rainfall event over central Oahu in June 2003, during which a rare weak tornado occurred. We used a numerical model to analyze the meteorological conditions that led to the formation of the tornado. Previous studies on this event have analyzed convection initiation over the semiarid region using a numerical model with 1.5-km grids. By contrast, we used an ultra-high-resolution model to simulate the formation and movement of the tornado-like vortex. An appropriate grid size of 40 m, coupled with the large-eddy simulation method, successfully reproduced the weak vortex event. This simulation facilitated a detailed analysis of the vortex’s initialization and downstream movement, demonstrating the model’s effectiveness despite minor discrepancies in the tornado’s exact location. Our results indicated that the tornado event was influenced by the interactions among Oahu’s local land and sea breeze, thermally induced convective systems, and topography. A weak vortex formed near the ground due to downdrafts from the land-sea breeze and convective systems. Subsequently, through the coupling effect of the upper and lower layers, the incoming convective system exerted a suction effect that enhanced the upper-level downdrafts. This process allowed the tornado vortex to connect from the top to the bottom. Our findings may significantly improve numerical weather prediction, thereby assisting forecasters in accurately predicting similar weather events across tropical islands.