The impact of the mesoscale ocean variability on the estimation of tidal harmonic constants based on satellite altimeter data in the south china sea

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Abstract

The estimation accuracy of tidal harmonic constants is of great significance to maritime traffic and port construction. However, due to the long sampling period of satellite altimeters, tidal signals alias the mesoscale ocean frequencies. As a result, the harmonic analysis is affected by mesoscale environmental noise. In this study, the influence of the mesoscale ocean variability (MOV) on the estimation of tidal harmonic constants was quantified by analyzing 25 years of altimeter data from the Topex/Poseidon (T/P) and Jason satellites in the South China Sea (SCS). The results indicated that the absolute amplitude differences (AADs) of the eight major tidal constituents before and after the mesoscale variability correction (MVC) were generally within 10 mm, and most were within 6 mm. For the relative impact, M2, O1, and K1 were not obviously affected by the MOV because of their large amplitudes, and the AADs generally accounted for less than ±10% of the am-plitudes. As a tidal constituent with amplitude less than 2 cm in the SCS, the amplitude of K2 was significantly affected by the MOV, with the ratios of the AADs to its own amplitudes ranging from −64.79% to 95.99% in space. In terms of phase, the K2 tide was most affected by the MOV: 63% of the data points before and after correction were over ±5°, and the maximum and minimum values were 86.46° and −176.27°, respectively. The absolute phase differences of other tidal constituents before and after the MVC were generally concentrated within ±5°. The impact of the MOV on the evolution of tidal amplitudes in the SCS was also explored. It was found that the MOV can cause pseudo-rapid temporal variations of tidal amplitudes in some regions of the SCS.

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Yu, Q., Pan, H., Gao, Y., & Lv, X. (2021). The impact of the mesoscale ocean variability on the estimation of tidal harmonic constants based on satellite altimeter data in the south china sea. Remote Sensing, 13(14). https://doi.org/10.3390/rs13142736

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