Ocean Ensemble-Enabled Stochastic Acoustic Prediction With Operational Metrics: New England Shelf Break Acoustics Signals and Noise Experiment

This article describes the results of the New England shelf break acoustics (NESBA) experiment as they pertain to acoustic prediction and the quantification of associated uncertainties in relevant operational metrics. The uncertainties considered here are those due to the imperfect sensing of the water column, ambient noise (AN), and the seabed, and the impact this has on ocean forecasting and acoustic performance prediction accuracy. Operational metrics are designed to provide an acoustic system operator with actionable guidance relating to likely mean source detection ranges and associated uncertainties with specific guidance on the degree to which specific environmental factors (e.g., oceanography, seabed, and ambient noise) contribute to the predicted uncertainty levels. High-resolution regional Navy Coastal Ocean Model (NCOM) ensemble forecasts were generated to capture oceanographic variability and uncertainty. Passive ambient noise-based seabed measurements were conducted to estimate seabed properties. Extensive AN and conductivity, temperature, and depth (CTD) measurements were also conducted. Measurement-based versus model-based acoustic prediction metrics are compared as an initial validation of the underlying methodology. It is shown that Global Hybrid Coordinate Ocean Model (HYCOM) ocean forecasts with databased AN and seabed parameters result in very large metric uncertainties, while leveraging high-resolution NCOM with ensembles and in situ AN and seabed measurements can result in substantially reduced uncertainties. It is also demonstrated that improved ocean modeling and sensing can be leveraged to determine the best receiver depth, associated uncertainty levels, and uncertainty drivers. An operational concept for generating acoustic prediction metrics and associated operator environmental sensing guidance is proposed.