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Deriving Coastal Sea Surface Current by Integrating a Tide Model and Hourly Ocean Color Satellite Data

  • Songyu Chen
  • , Fang Shen*
  • , Renhu Li
  • , Yuan Zhang
  • , Zhaoxin Li
  • *此作品的通讯作者
  • East China Normal University

科研成果: 期刊稿件文章同行评审

摘要

Sea surface currents (SSCs) play a pivotal role in material transport, energy exchange, and ecosystem dynamics in coastal marine environments. While traditional methods to obtain wide-range SSCs, such as satellite altimetry, often struggle with limited performance in coastal regions due to waveform contamination, deriving SSCs from sequential ocean color data using maximum cross-correlation (MCC) has emerged as a promising approach. In this study, we proposed a novel SSC estimation method, called tide-restricted maximum cross-correlation (TRMCC), and implemented it on hourly ocean color data obtained from the Geostationary Ocean Color Imager II (GOCI-II) and the global tide model FES2014 to derive SSCs in coastal seas and turbid estuaries. Cross-comparison over three years with buoy data, high-frequency radar, and numerical model products shows that TRMCC is capable of obtaining high-resolution SSCs with good accuracy in coastal and estuarine areas. Both large-scale ocean circulation patterns in seas and fine-scale surface current structures in estuaries can be effectively captured. The deriving accuracy, especially in coastal and estuarine areas, can be significantly improved by integrating tidal current data into the MCC workflow, and the influence of invalid data can be minimized by using a flexible reference window size and normalized cross-correlation in the Fourier domain technique. Seasonal SSC structure in the Bohai Sea and diurnal SSC variation in the Yangtze River Estuary were depicted via the satellite method, for the first time. Our study highlights the vast potential of TRMCC to improve the understanding of current dynamics in complex coastal regions.

源语言英语
文章编号874
期刊Remote Sensing
17
5
DOI
出版状态已出版 - 3月 2025

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 14 - 水下生物
    可持续发展目标 14 水下生物

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