Sieving nonlinear internal waves through path prediction

Nonlinear internal waves (NLIWs) have been studied as unusual phenomena in the ocean for several decades. As the quality, quantity and variety of satellite images have increased, NLIWs have been found as a ubiquitous phenomenon over the continental shelf. In the northern South China Sea (SCS), satel...

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Bibliographic Details
Published inInternational journal of remote sensing Vol. 29; no. 21; pp. 6391 - 6402
Main Authors Chao, Y.-H., Hsu, M.-K., Chen, H.-W., Wang, Y.-H., Chen, G.-Y., Liu, C.-T.
Format Journal Article Conference Proceeding
LanguageEnglish
Published Abingdon Taylor & Francis 01.11.2008
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Summary:Nonlinear internal waves (NLIWs) have been studied as unusual phenomena in the ocean for several decades. As the quality, quantity and variety of satellite images have increased, NLIWs have been found as a ubiquitous phenomenon over the continental shelf. In the northern South China Sea (SCS), satellite images from both optical and microwave sensors show that there are trains of NLIW packets near Dongsha Atoll (20.7° N, 116.8° E). Each packet contains several NLIW fronts. These NLIW packets are nearly parallel to each other and they are refracted, reflected or diffracted by changes in ocean-bottom topography. NLIW propagation speed depends on the stratification of water density and the water depth, and less on the wave amplitude. As NLIWs propagate westwards from the northern SCS at about 3000 m depth, up onto the shelf near Dongsha Atoll, their propagation speed falls with water depth from 2.9 m s −1 to 1 m s −1 or less. This causes difficulty in relating the NLIW packets in various satellite images. Based on archived hydrographical data, the Korteweg-de Vries (KdV) theory of weakly propagating NLIWs and the assumption that the bright/dark lines in the satellite images are centres of convergence/divergence of NLIW fronts, the path and the propagation speed of NLIWs can be predicted with −1% in bias and 4.4% in standard deviation. With this accuracy, we can (1) sort the NLIW packets in the same satellite image into different groups of NLIWs (in each group, NLIWs were generated at the same place but at successive tidal cycles); (2) relate NLIW packets in consecutive satellite images obtained 1 day apart; and (3) confirm or search for faint signals of NLIW fronts in a satellite image.
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ISSN:0143-1161
1366-5901
DOI:10.1080/01431160802175413