Development of the Yearly Mode-1 M2 Internal Tide Model in 2019

Abstract

Abstract The yearly mode-1 M2 internal tide model in 2019 is constructed using sea surface height measurements made by six concurrent satellite altimetry missions: Jason-3, Sentinel-3A, Sentinel-3B, CryoSat-2, Haiyang-2A, and SARAL/AltiKa. The model is developed following a three-step procedure consisting of two rounds of plane wave analysis with a spatial bandpass filter in between. Prior mesoscale correction is made on the altimeter data using AVISO gridded mesoscale fields. The model is labeled Y2019, because it represents the 1-yr-coherent internal tide field in 2019. In contrast, the model developed using altimeter data from 1992 to 2017 is labeled MY25, because it represents the multiyear-coherent internal tide field in 25 years. Thanks to the new mapping technique, model errors in Y2019 are as low as those in MY25. Evaluation using independent altimeter data confirms that Y2019 reduces slightly less variance (∼6%) than MY25. Further analysis reveals that the altimeter data from five missions (without Jason-3) can yield an internal tide model of almost the same quality. Comparing Y2019 and MY25 shows that mode-1 M2 internal tides are subject to significant interannual variability in both amplitude and phase, and their interannual variations are a function of location. Along southward internal tides from Amukta Pass, the energy flux in Y2019 is 2 times larger and the phase speed is about 1.1% faster. This mapping technique has been applied successfully to 2017 and 2018. This work demonstrates that yearly internal tides can be observed by concurrent altimetry missions and their interannual variations can be determined. Significance Statement This work is motivated to study the interannual variations of internal tides using observation-based yearly internal tide models from satellite altimetry. Previous satellite observations of internal tides are usually based on 25 years of altimeter data from 1993 to 2017. The yearly subsetted altimeter data are short, so that the resultant yearly models are overwhelmed by noise. A new mapping technique is developed and demonstrated in this paper. It paves a path to study the interannual and decadal variations of internal tides on a global scale and monitor the global ocean changes by tracking long-range internal tides.