Acoustic prediction using a feature-oriented regional modeling system and acoustic inversion

Abstract

Abstract: Acoustic predictions usually suffer from uncertainties in ocean forecasts, due to the extreme sensitivity of acoustic propagation to the ocean environment. In this regard, the acoustic prediction systems require the best possible specification of initial conditions, demanding high accuracy and synopticity on the ocean circulation modeling. The current work assesses the feasibility of combining a Feature-Oriented Regional Modeling System (FORMS) with acoustic inversion outcomes, for acoustic prediction in the Cabo Frio (Brazil) coastal area. First, the oceanographic prediction model is tested for acoustic applications. Two numerical acoustic simulations were performed, with an acoustic model having as input two different initial fields: i) in situ hydrographic data from the OAEx10 sea trial, and ii) the oceanographic modeling system outputs. The simulations were compared in terms of transmission loss (TL), detection probability and acoustic channel impulse response. The TL differences exhibit standard deviations ranging between 2.29 and 4.32 dB, demonstrating the feature-oriented regional model skill for sonar applications. The quality of the results degrades with distance, as observed in correlations between the impulse responses. This can be explained by an accumulation of forecast error effects during propagation. Another interesting result is that the coastal upwelling may prevent the detection of submarine targets. The second stage of this work concerned acoustic data-model comparison, for OAEx10. Experimental impulse responses correlated fairly well with modeled ones corresponding to the forecasts, with values between 0.72 and 0.89. In an attempt to increase these values, the acoustic data was inverted, for the basement compressional speed, whose estimates led to increased impulse response correlations of as high as 0.96. In summary, the prediction of the acoustic field can be well accomplished by combining a FORMS technique with an acoustic inversion scheme. Keywords: Acoustic prediction, feature model, acoustic inversion, coastal upwelling, model validation