Spatial variability of geoacoustic parameters in SBCEX17

Since the ocean covers more than two-thirds of the planet and mud covers most of the seabed, understanding the acoustic propagation of mud is essential for acoustic performance prediction. We aim to determine the acoustic properties and their spatial variability on the New England Mud Patch by using data collected during the SBCEX17 experiment. In particular, we use tonal signals between 53 and 953 Hz emitted by sources towed on circular tracks and recorded by vertical line arrays. For Bayesian estimation, we use a new implementation of Metropolis-Hastings Markov chain Monte Carlo (MCMC) sampling that combines adaptive covariance estimation, sequential sampling in eigenvector space, and parallel tempering. Acoustic sound propagation is modeled by an adiabatic modes model that can provide a good tradeoff between inversion speed and modeling accuracy in the moderately range-dependent SBCEX17 environment. Our description of the seafloor includes a mud layer in which the sound speed increases moderately with depth and a thinner mud-sand transition layer where sound speed increases strongly due to a sand content that increases with depth. Preliminary results match well with established results based on broadband reflection-coefficient data. In addition to the spatial variability, we investigate the effects on uncertainty quantification of geoacoustic parameters when switching from a range-independent propagation model to the considered adiabatic modes model.