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

• Published in: Journal of geophysical research. Oceans 2016-06, Vol.121 (6), p.3692-3709
• Main Authors: Tang, Qunshu, Hobbs, Richard, Zheng, Chan, Biescas, Berta, Caiado, Camila
• Format: Article
• Language: English
• Subjects: Acoustic measurement; Acoustic velocity; Bayesian analysis; Brackish; Computer simulation; Confidence intervals; Geophysics; Hydrographic data; internal solitary wave; Internal waves; Inversions; Low frequency; Marine; Markov analysis; Markov Chain Monte Carlo; Markov chains; Mathematical models; Monte Carlo methods; Monte Carlo simulation; Oceanography; Packets (communication); Parameter uncertainty; Physical oceanography; Probability theory; Reflectance; Salinity; Salinity effects; Seismic data; seismic oceanography; Seismic studies; Seismic surveys; Seismological data; Solitary waves; Solitons; Solutions; Statistical methods; Surface water; Temperature; temperature and salinity structure; Temperature effects; Temperature inversions; Uncertainty; Velocity
• ISSN: 2169-9275; 2169-9291
• DOI: 10.1002/2016JC011810

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. Key Points: Temperature and salinity fields of a soliton packet are recovered from seismic data An MCMC approach is developed to address the inversion and uncertainty estimation An accurate starting model is necessary for the strong sub‐mesoscale variations