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Peer-Reviewed Research

Ocean wave buoy network in extreme tropical cyclones detects the saturation of air-sea momentum transfer

This paper was written by T. Shimura, N. Mori, and T. Miyashita.

Abstract

Tropical cyclone is one of the most destructive natural phenomena, causing tremendous disasters worldwide. The maximum intensity of tropical cyclones is determined by momentum and heat transfer at the air-sea interface. Momentum transfer corresponds to the momentum loss of tropical cyclones and, consequently, to the underlying ocean’s momentum gain. Air-side observations of wind profiles (top-down approach) and ocean-side observations of ocean subsurface currents (bottom-up approach) showed a slowdown of momentum transfer under high tropical cyclone wind speeds. Although the intensity of tropical cyclones and related disasters are directly related to momentum transfer at high wind speeds, there is still disagreement regarding the slowdown owing to lack of data. Here, we showed momentum transfer in a high-wind-speed region by observing ocean waves directly at the air-sea interface (middle-up-down approach). Although ocean wave observations are highly spatially limited, we deployed a fleet of newly developed drifting ocean wave buoys covering the active area of tropical cyclones in the Western North Pacific. The buoys fleet captured extreme waves near the eye of the strongest category 5 tropical cyclone, showing clear saturation of momentum transfer beyond surface wind speeds of 25 m/s. Our ocean waves (air-sea interface) results fill in the missing link of quantitative momentum transfer slowdown under extreme wind speeds from both the air and ocean sides. This finding advances not only tropical cyclone modeling but also ocean waves, ocean circulation, and storm surge modeling.

Ocean wave buoy network in extreme tropical cyclones detects the saturation of air-sea momentum transfer

August 4, 2023

Explore groundbreaking research on tropical cyclone intensity & momentum transfer, by Shimura, Mori & Miyashita. Essential for advanced climate modeling.

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