Land-based seismic observations of microseisms generated during Tropical Storms Ernesto and Florence are dominated by signals in the 0.15 - 0.5Hz band. Data from seafloor hydrophones in shallow water (70m depth, 130 km off the New Jersey coast) show dominant signals in the gravity- wave frequency band, 0.02 - 0.18Hz and low amplitudes from 0.18 - 0.3Hz, suggesting significant opposing wave components necessary for DF microseism generation were negligible at the site. Both storms produced similar spectra, despite differing sizes, suggesting near-coastal shallow water as the dominant region for observed microseism generation. A mathematical explanation for a sign-inversion induced to the passive fathometer response by minimum variance distortionless response (MVDR) beamforming is presented. This shows that, in the region containing the bottom reflection, the MVDR fathometer response is identical to that obtained with conventional processing multiplied by a negative factor. A model is presented for the complete passive fathometer response to ocean surface noise, interfering discrete noise sources, and locally uncorrelated noise in an ideal waveguide. The leading order term of the ocean surface noise produces the cross-correlation of vertical multipaths and yields the depth of sub-bottom reflectors. Discrete noise incident on the array via multipaths give multiple peaks in the fathometer response. These peaks may obscure the sub- bottom reflections but can be attenuated with use of Minimum Variance Distortionless Response (MVDR) steering vectors. A theory is presented for the Signal-to-Noise- Ratio (SNR) for the seabed reflection peak in the passive fathometer response as a function of seabed depth, seabed reflection coefficient, averaging time, bandwidth and spatial directivity of the noise field. The passive fathometer algorithm was applied to data from two drifting array experiments in the Mediterranean, Boundary 2003 and 2004, with 0.34s of averaging time. In the 2004 experiment, the response showed the array depth varied periodically with an amplitude of 1 m and a period of 7 s consistent with wave driven motion of the array. This introduced a destructive interference which prevents the SNR growing with averaging time, unless the motion is removed by use of a peak tracker

Everyday hearing requires inferring the causal factors that produce a sound, as when we separate the acoustic effectsof the environment (reverberation) from those of sound sources. Here we consider perceptual inferences from impactsounds, in which the resonance of a struck object provides cues to its material, but via acoustic effects that might benontrivial to disentangle from reverberation. We investigated whether and how humans separate the effects of objectresonance and reverberation in a material classification task. For comparison, we implemented a Bayesian observer thatinferred material from a generative model of object sounds without reverberation. Humans were robust to reverberation,whereas the model was not. However, human robustness was specific to reverberation consistent with the statistics ofnatural environments. The results suggest that humans use internal models of room and object acoustics to determine theirrespective contributions to sound, providing an example of causal inference in audition.