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Markov Chain Monte Carlo inversion of temperature and salinity structure of an internal solitary wave packet from marine seismic data.

Tang, Q. and Hobbs, R.W. and Zheng, C. and Biescas, B. and Caiado, C.C.S. (2016) 'Markov Chain Monte Carlo inversion of temperature and salinity structure of an internal solitary wave packet from marine seismic data.', Journal of geophysical research : oceans., 121 (6). pp. 3692-3709.

Abstract

Marine seismic reflection technique is used to observe the strong ocean dynamic process of nonlinear internal solitary waves (ISWs or solitons) in the near-surface water. Analysis of ISWs is problematical because of their transient nature and limitations of classical physical oceanography methods. This work explores a Markov Chain Monte Carlo (MCMC) approach to recover the temperature and salinity of ISW field using the seismic reflectivity data and in situ hydrographic data. The MCMC approach is designed to directly sample the posterior probability distributions of temperature and salinity which are the solutions of the system under investigation. The principle improvement is the capability of incorporating uncertainties in observations and prior models which then provide quantified uncertainties in the output model parameters. We tested the MCMC approach on two acoustic reflectivity data sets one synthesized from a CTD cast and the other derived from multichannel seismic reflections. This method finds the solutions faithfully within the significantly narrowed confidence intervals from the provided priors. Combined with a low frequency initial model interpreted from seismic horizons of ISWs, the MCMC method is used to compute the finescale temperature, salinity, acoustic velocity, and density of ISW field. The statistically derived results are equivalent to the conventional linearized inversion method. However, the former provides us the quantified uncertainties of the temperature and salinity along the whole section whilst the latter does not. These results are the first time ISWs have been mapped with sufficient detail for further analysis of their dynamic properties.

Item Type:Article
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Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1002/2016JC011810
Publisher statement:Qunshu Tang, Richard Hobbs, Chan Zheng, Berta Biescas, and Camila Caiado, (2016), Markov Chain Monte Carlo inversion of temperature and salinity structure of an internal solitary wave packet from marine seismic data, Journal of geophysical research : oceans, 121, 3692–3709, 10.1002/2016JC011810. To view the published open abstract, go to http://dx.doi.org and enter the DOI.
Date accepted:02 May 2016
Date deposited:31 August 2016
Date of first online publication:02 June 2016
Date first made open access:02 December 2016

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