Abstract
Internal waves (IWs) are broadly distributed globally and have significant impacts on offshore engineering and underwater navigation. The prediction of IW propagation is a challenging task because of the complex factors involved. In this study, a machine-learning model was developed to predict IW propagation in the Andaman Sea. The model is based on a back-propagation neural network trained by 1189 IW samples, including the crest length and the peak-to-peak distance of IWs, extracted from 123 Moderate-Resolution Imaging Spectroradiometer (MODIS) images and 33 Ocean Land Color Instrument (OLCI) images acquired from 2015 to 2019 and corresponding ocean environment parameters. Using the leading wave crest within an IW packet as input, we ran the model to forecast the IW locations and compare them with satellite observations. The average root-mean-square difference between the model-forecasted and satellite-observed IW leading crest after one tidal cycle was 3.21 km. The corresponding averaged correlation coefficient was 0.95 and the average Fréchet Distance was 11.46 km. We reiterated the model run over two tidal periods and obtained similar statistical results, indicating the robustness of forecasting IW packets. We find that reducing the time step helped to improve forecasting accuracy. The influence of input errors and seasonal variations on model results are discussed and an analysis shows that the initial propagation direction introduced to the model is necessary for cross-propagating IW patterns. Comparisons with the Korteweg-de Vries equation results show that the developed model has better performance and is more robust.
Highlights
I NTERNAL waves (IWs) are frequently observed in the global ocean [1]–[5]
When the mean-square error (MSE) was not reduced, and validation checks increased in epoch 16, the model stopped training in epoch 22
The results indicate that IW propagations in Regions A, B, and D show little seasonal variations, while in Region C, discrepancies in the dry and rainy seasons exist
Summary
I NTERNAL waves (IWs) are frequently observed in the global ocean [1]–[5]. Large-amplitude IWs can travel for hundreds of kilometers and carry a significant volume of energy toward the coastline. Remote sensing has been an effective method for oceanography research in recent years. Both synthetic aperture radar (SAR) and optical satellite images are used for IW studies [10]–[12]. The IWs, which manifest as bright and dark bands on the MODIS images, are generated at the Nicobar Islands and the Andaman Islands and propagate eastward into the deep ocean with long wave crests and large amplitudes [13]–[15]. The imaging mechanism, generation sites, generation mechanisms, and spatial distribution of IWs have
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