Observation and propagation velocity study of internal solitary waves in the northern South China Sea based on the FY-4B geostationary meteorological satellite
This study uses the data of the China's new generation geostationary-orbit meteorological satellite FY-4B to observe the internal solitary wave(ISW)and study the propagation speed of ISW in the northern South China Sea(NSCS).Firstly,the observable ISW region of the FY-4B satellite was discussed by using ARGI data of 500 m resolution,and the NSCS was confirmed as the research area.Then,the MTI method(Multitemporal Image Compar-ison method)was used to calculate the propagation velocity of ISWs in NSCS using GHI data of 250 m resolution,and the average propagation velocity of ISW in NSCS is about 1.78 m/s.The average velocity in the eastern deep sea was 3.02 m/s,and it decreased to 1.90 m/s after westward transmission near Dongsha Islands.After the division of Dongsha Islands,the velocity of ISW in the south was faster than the north,with 2.08 m/s and 1.54 m/s,respect-ively.Finally,the velocity decreases to 0.42 m/s after westward to the nearshore region,then dissipates.Compared with the results of the MTI method and theoretical propagation velocity calculated by the eKdV(extended Korteweg-de Vries)equation in the two-layer mode,and the correlation coefficient between them reached 0.89.Prove the feasibility of using the eKdV theoretical equation to invert the propagation velocity of ISW in the NSCS.Finally,the results of calculating the propagation velocity of ISW by combining measured data with remote sens-ing images were compared with the results of MTI method.The correlation between the two reached 0.93.This art-icle verifies the high temporal resolution characteristics of geostationary-orbit optical remote sensing data,which have significant advantages in calculating the propagation speed of ISW.It has certain significance for research work such as inversion of ISW parameters in the NSCS.
ISWsFY-4B geostationary meteorological satelliteMTIeKdV equationnorthern South China Sea
万方数据
维普
