Exploring the Green Tide Transport Mechanisms and Evaluating Leeway Coefficient Estimation via Moderate-Resolution Geostationary Images

Author:

Ji Menghao1ORCID,Dou Xin1,Zhao Chengyi1,Zhu Jianting2ORCID

Affiliation:

1. School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China

2. Department of Civil and Architectural Engineering and Construction Management, University of Wyoming, Laramie, WY 82071, USA

Abstract

The recurring occurrence of green tides as an ecological disaster has been reported annually in the Yellow Sea. While remote sensing technology effectively tracks the scale, extent, and duration of green tide outbreaks, there is limited research on the underlying driving mechanisms of green tide drift transport and the determination of the leeway coefficient. This study investigates the green tide transport mechanism and evaluates the feasibility of estimating the leeway coefficient by analyzing green tide drift velocities obtained from Geostationary Ocean Color Imager-II (GOCI-II) images using the maximum cross-correlation (MCC) technique and leeway method across various time intervals alongside ocean current and wind speed data. The results reveal the following: (1) Significant spatial variations in green tide movement, with a distinct boundary at 34°40′N. (2) Short-term green tide transport is primarily influenced by tidal forces, while wind and ocean currents, especially the combined Ekman and geostrophic current component, predominantly govern net transport. (3) Compared to 1, 3, and 7 h intervals, estimating the leeway coefficient with a 25 h interval is feasible for moderate-resolution geostationary images, yielding values consistent with previous studies. This study offers new insights into exploring the transport mechanisms of green tides through remote sensing-driven velocity.

Funder

key project of National Natural Science Foundation, China

the Innovative and Entrepreneurial Talent Program of Jiangsu Province, China

Publisher

MDPI AG

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