loader graphic

Loading content ...

Real-time Probabilistic Coupled Ocean Physics-Acoustics Forecasting and Data Assimilation for Underwater GPS

Mirabito, C., P.F.J. Lermusiaux, P.J. Haley, Jr., W.H. Ali, E. Dorfman, A. Laferriere, A. Kofford, G. Shepard, M. Goldsmith, K. Heaney, E. Coelho, J. Boyle, J. Murray, L. Freitag, and A. Morozov, 2020. Real-time Probabilistic Coupled Ocean Physics-Acoustics Forecasting and Data Assimilation for Underwater GPS. In: OCEANS '20 IEEE/MTS, 5-30 October 2020, sub-judice.

The POSYDON program aims to develop a Global Positioning System (GPS) for underwater assets. The primary goals of our MIT effort are to: (1) Employ and develop our regional ocean modeling, data assimilation, and uncertainty quantification for the estimation of sound speed variability, coupled oceanographic-acoustic forecasting and inversion relevant to the POINT effort; (2) Apply our theory and schemes for optimal placement, path planning, and persistent ocean sampling with varied assets and acoustic source platforms; and (3) Further quantify the ocean dynamics and variability of the regional areas of interest, utilizing our multi-resolution data-assimilative ocean modeling and process studies.

As part of this program, we completed regional ocean modeling and forecasting for the Middle Atlantic Bight. Our realistic data-assimilative modeling involved real-time forecasting and data-driven simulations and analyses of the sound speed variability. To do so, we built on our experiences, especially on large and collaborative research initiatives. Our methods and software were used and further developed for POINT.

For this project, we also characterized and forecasted the oceanographic variability and uncertainty. Our MIT-MSEAS PE model of the temporal and spatial evolution of physical features and circulations has been validated through extensive measurements, and analysis in many regions. However, due to the uncertain initial and boundary conditions, and sub-grid-scale parameters, the variability of the environmental propagating medium is uncertain. Just as we now utilize probabilities for rain or bad weather on a daily basis, the proposed underwater communication and global positioning system for deep ocean navigation can also utilize and benefit from such information. Real-time integrated oceanographic-acoustic predictions must account for and forecast these uncertainties and their effects on sound propagation and communications.

For this “Precision Ocean Interrogation, Navigation, and Timing (POINT)” effort, we utilized our MIT Multidisciplinary Simulation, Estimation, and Assimilation System (MSEAS) (MSEAS, 2013; Haley et al., 2010, 2015). The MSEAS software is used for fundamental research and for realistic simulations and predictions in varied regions of the world’s ocean, including monitoring, ecosystem prediction and environmental management and, importantly for the present project, real-time oceanographic-acoustic predictions and coupled ocean-acoustic data assimilation. For this exercise, we mainly employed our MIT-MSEAS hydrostatic PE code with a nonlinear free surface, based on second-order structured finite volumes.


Multi-resolution Probabilistic Ocean Physics-Acoustic Modeling: Validation in the New Jersey Continental Shelf

Lermusiaux, P.F.J., P.J. Haley, Jr., C. Mirabito, W.H. Ali, M. Bhabra, P. Abbot, C.-S. Chiu, and C. Emerson, 2020. Multi-resolution Probabilistic Ocean Physics-Acoustic Modeling: Validation in the New Jersey Continental Shelf. In: OCEANS '20 IEEE/MTS, 5-30 October 2020, sub-judice.

The littoral environment is especially demanding on tactical sonar systems, in large part because of the spatial and temporal variability of the highly-dynamic nonlinear ocean fields. The variability occurs on multiple scales in space and time, and involves multiple interacting processes, from internal tides and waves to meandering fronts, eddies, boundary layers, and strong air-sea interactions (Robinson et al., 2002; Robinson and Lermsuiaux, 2004; Lermusiaux et al., 2006, 2010; Duda et al., 2019). The present goal is to improve the detection rate of targets through improved multi-resolution ocean modeling and probabilistic forecasting of littoral ocean variability relevant for underwater propagation. The acoustic emphasis is on transmission loss (TL) variability and on detection performance with 50 to 3000 Hz active signals. To exemplify the multi-resolution probabilistic modeling, we reconstruct the acoustic environment off the New Jersey continental shelf for the end of June 2009 (MAC DG-3 Test), modeling the ocean spatialtemporal variability and its impact on the transmission loss (TL) and detection performance. We utilize ocean and acoustic measurements to validate results.


Stochastic Oceanographic-Acoustic Prediction and Bayesian Inversion for Wide Area Ocean Floor Mapping

Ali, W.H., M.S. Bhabra, P.F.J. Lermusiaux, A. March, J.R. Edwards, K. Rimpau, and P. Ryu, 2019. Stochastic Oceanographic-Acoustic Prediction and Bayesian Inversion for Wide Area Ocean Floor Mapping. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, doi:10.23919/OCEANS40490.2019.8962870

Covering the vast majority of our planet, the ocean is still largely unmapped and unexplored. Various imaging techniques researched and developed over the past decades, ranging from echo-sounders on ships to LIDAR systems in the air, have only systematically mapped a small fraction of the seafloor at medium resolution. This, in turn, has spurred recent ambitious efforts to map the remaining ocean at high resolution. New approaches are needed since existing systems are neither cost nor time effective. One such approach consists of a sparse aperture mapping technique using autonomous surface vehicles to allow for efficient imaging of wide areas of the ocean floor. Central to the operation of this approach is the need for robust, accurate, and efficient inference methods that effectively provide reliable estimates of the seafloor profile from the measured data. In this work, we utilize such a stochastic prediction and Bayesian inversion and demonstrate results on benchmark problems. We first outline efficient schemes for deterministic and stochastic acoustic modeling using the parabolic wave equation and the optimally-reduced Dynamically Orthogonal equations and showcase results on stochastic test cases. We then present our Bayesian inversion schemes and its results for rigorous nonlinear assimilation and joint bathymetry-ocean physics-acoustics inversion.


Multiscale multiphysics data-informed modeling for three-dimensional ocean acoustic simulation and prediction

Duda, T.F., Y.-T. Lin, A.E. Newhall, K.R. Helfrich, J.F. Lynch, W.G. Zhang, P.F.J. Lermusiaux, and J. Wilkin, 2019. Multiscale Multiphysics Data-Informed Modeling for Three-Dimensional Ocean Acoustic Simulation and Prediction. Journal of the Acoustical Society of America, 146(3), 1996–2015. doi:10.1121/1.5126012

Three-dimensional (3D) underwater sound field computations have been used for a few decades to understand sound propagation effects above sloped seabeds and in areas with strong 3D temperature and salinity variations. For an approximate simulation of effects in nature, the necessary 3D sound-speed field can be made from snapshots of temperature and salinity from an operational data-driven regional ocean model. However, these models invariably have resolution constraints and physics approximations that exclude features that can have strong effects on acoustics, example features being strong submesoscale fronts and nonhydrostatic nonlinear internal waves (NNIWs). Here, work to predict NNIW fields to improve 3D acoustic forecasts using an NNIW model nested in a tide-inclusive data-assimilating regional model is reported. The work was initiated under the Integrated Ocean Dynamics and Acoustics project. The project investigated ocean dynamical processes that affect important details of sound-propagation, with a focus on those with strong intermittency (high kurtosis) that are challenging to predict deterministically. Strong internal tides and NNIW are two such phenomena, with the former being precursors to NNIW, often feeding energy to them. Successful aspects of the modeling are reported along with weaknesses and unresolved issues identified in the course of the work.

Issues and Progress in the Prediction of Ocean Submesoscale Features and Internal Waves

Duda T.F., W.G. Zhang, K.R. Helfrich, A.E. Newhall, Y.-T. Lin, J.F. Lynch, P.F.J. Lermusiaux, P.J. Haley Jr., J. Wilkin, 2014. Issues and Progress in the Prediction of Ocean Submesoscale Features and Internal Waves. OCEANS'14 MTS/IEEE.

Data-constrained dynamical ocean modeling for the purpose of detailed forecasting and prediction continues to evolve and improve in quality. Modeling methods and computational capabilities have each improved. The result is that mesoscale phenomena can be modeled with skill, given sufficient data. However, many submesoscale features are less well modeled and remain largely unpredicted from a deterministic event standpoint, and possibly also from a statistical property standpoint. A multi-institution project is underway with goals of uncovering more of the details of a few submesoscale processes, working toward better predictions of their occurrence and their variability. A further component of our project is application of the new ocean models to ocean acoustic modeling and prediction. This paper focuses on one portion of the ongoing work: Efforts to link nonhydrostatic-physics models of continental-shelf nonlinear internal wave evolution to data-driven regional models. Ocean front-related effects are also touched on.


The “Integrated Ocean Dynamics and Acoustics” (IODA) Hybrid Modeling Effort

Duda, T.F., Y.-T. Lin, A.E. Newhall, K.R. Helfrich, W.G. Zhang, M. Badiey, P.F.J. Lermusiaux, J.A. Colosi, and J.F. Lynch, 2014. The “Integrated Ocean Dynamics and Acoustics” (IODA) Hybrid Modeling Effort, Proceedings of the international conference on Underwater Acoustics - 2014 (UA2014), 621-628.

Regional ocean models have long been integrated with acoustic propagation and scattering models, including work in the 1990s by Robinson and Lee. However, the dynamics in these models has been not inclusive enough to represent submesoscale features that are now known to be very important acoustically. The features include internal waves, thermohaline intrusions, and details of fronts. In practice, regional models predict internal tides at many locations, but the nonlinear steepening of these waves and their conversion to short nonlinear waves is often improperly modeled, because computationally prohibitive nonhydrostatic pressure is needed. To include the small-scale internal waves of tidal origin, a nested hybrid model is under development. The approach is to extract long-wavelength internal tide wave information from tidally forced regional models, use ray methods or mapping methods to determine internal-tide propagation patterns, and then solve two-dimensional high-resolution nonhydrostatic wave models to “fill-in” the internal wave details. The resulting predicted three-dimensional environment is then input to a fully three-dimensional parabolic equation acoustic code. The output from the nested ocean model, run in hindcast mode, is to be compared to field data from the Shallow Water 2006 (SW06) experiment to test and ground truth purposes

Time-Evolving Acoustic Propagation Modeling in a Complex Ocean Environment

Colin, M.E.G.D., T.F. Duda, L.A. te Raa, T. van Zon, P.J. Haley, Jr., P.F.J. Lermusiaux, W.G. Leslie, C. Mirabito, F.P.A. Lam, A.E. Newhall, Y.-T. Lin, J.F. Lynch, 2013. Time-Evolving Acoustic Propagation Modeling in a Complex Ocean Environment, Proceedings of OCEANS - Bergen, 2013 MTS/IEEE , vol., no., pp.1,9, 10-14 June 2013, doi: 10.1109/OCEANS-Bergen.2013.6608051.

During naval operations, sonar performance estimates often need to be computed in-situ with limited environmental information. This calls for the use of fast acoustic propagation models. Many naval operations are carried out in challenging and dynamic environments. This makes acoustic propagation and sonar performance behavior particularly complex and variable, and complicates prediction. Using data from a field experiment, we have investigated the accuracy with which acoustic propagation loss (PL) can be predicted, using only limited modeling capabilities. Environmental input parameters came from various sources that may be available in a typical naval operation.

The outer continental shelf shallow-water experimental area featured internal tides, packets of nonlinear internal waves, and a meandering water mass front. For a moored source/receiver pair separated by 19.6 km, the acoustic propagation loss for 800 Hz pulses was computed using the peak amplitude. The variations in sound speed translated into considerable PL variability of order 15 dB. Acoustic loss modeling was carried out using a data-driven regional ocean model as well as measured sound speed profile data for comparison. The acoustic model used a two-dimensional parabolic approximation (vertical and radial outward wavenumbers only). The variance of modeled propagation loss was less than that measured. The effect of the internal tides and sub-tidal features was reasonably well modeled; these made use of measured sound speed data. The effects of nonlinear waves were not well modeled, consistent with their known three-dimensional effects but also with the lack of measurements to initialize and constrain them.


Computational Studies of 3D Ocean sound fields in areas of complex seafloor topography and active ocean dynamics

Duda, T.F., Y.-T. Lin, W.G. Zhang, B.D. Cornuelle, P.F.J. Lermusiaux, 2011. Computational Studies of 3D Ocean sound fields in areas of complex seafloor topography and active ocean dynamics. Proceedings of the 10th International Conference on Theoretical and Computational Acoustics, NTU, Taiwan, 12pp.

Over the last four decades the use of numerical flow models in oceanography has vastly increased. Models are run operationally for regional locations, ocean basins, and the entire earth. In addition, specialized research models targeting specific processes and areas are routinely produced. These models are often coupled with biological and chemical models for research into biological-physical and biogeochemical-physical interactions. The role of some models is to create conditions close to reality, in a deterministic sense, whereas others have the role of imitating mean behavior or fluctuation behavior. The role of yet another family of models is to alter conditions from reality to study the ramifications, examples being interdisciplinary climate models [1-3]. All of these models provide full access to time- evolving three-dimensional fields (4-D fields) for process studies, or for predictive purposes. There is strong motivation for using these models for ocean acoustic studies. Suitably formulated models can include the important flow and water-mass features of the ocean, with the important features covering a wide dynamic range. Each feature has its own acoustic propagation or scattering signature, with some signatures having an interfering effect on underwater acoustic activities. The signature can be in the temporal domain, the spatial domain, or both. An important part of ocean acoustics research at this time is identifying which processes are dominant at specific times and places, and models are well suited to this. Significant acoustic effects of water-column and seafloor features occur in concert. However, they have traditionally been studied individually, sometimes in idealized or very simple form. Despite the isolation of the processes, many of these studies have been very successful. Examples are the analysis of the Pekeris waveguide [4], adiabatic mode propagation in a smoothly varying waveguide [5], and propagation through idealized internal waves [6-8]. The state of our knowledge now demands that the full complexity be analyzed, as can be done using the ocean models. Initial efforts that have coupled four-dimensional ocean fields with 2D acoustics modeling include data assimilation and uncertainty studies [9, 10], end-to-end computations [11], real-time at-sea predictions [12] and coupled adaptive sampling [13]. In the present work, a specific focus is on 3D acoustic effects coupled to 4D ocean predictions. We have thus motivated the use of oceanographic flow models as a straightforward approach for objective and comprehensive study of sound propagation in realistic environments, which we refer to as coupled ocean/acoustics modeling. The alternative of investigating the overall effects of simultaneously occurring feature types by constructing idealized process models with multiple features (straight line internal waves in two-layer fluid over a uniformly sloped bottom and one eddy, for example) is likely to lack objectivity or completeness. In fact, such feature models are mainly utilized to initialize ocean models or describe/assimilate specific features [14]. Coupled ocean/acoustics modeling can have high value, under the condition that the synthesized environments are sufficiently inclusive, representative, and accurate. This is a nontrivial condition; many challenges remain for flow models in terms of boundary conditions and data assimilation, resolution of near-boundary effects and mixing effects, and three-dimensional nonlinear gravity waves with hydrostatic pressure. Note that making acoustic propagation predictions, without analysis of the behavior or the mechanisms at work, is a byproduct of coupled ocean-acoustic modeling. Coupled ocean/acoustics modeling is becoming more common. Nevertheless, the approach is relatively recent and the best research path to take at this time deserves discussion. In this paper we discuss the potential of this method, and inform the discussion with some example computations from recent work in the Mid Atlantic Bight.

Coupled Ocean-Acoustic prediction of transmission loss in a continental shelfbreak region: predictive skill, uncertainty quantification and dynamical sensitivities

Lermusiaux, P.F.J., J. Xu, C.F. Chen, S. Jan, L.Y. Chiu and Y.-J. Yang, 2010. Coupled Ocean-Acoustic prediction of transmission loss in a continental shelfbreak region: predictive skill, uncertainty quantification and dynamical sensitivities. IEEE Transactions, Journal of Oceanic Engineering, 35(4) 895-916. doi:10.1109/JOE.2010.2068611.

In this paper, we quantify the dynamical causes and uncertainties of striking differences in acoustic transmission data collected on the shelf and shelfbreak in the northeastern Taiwan region within the context of the 2008 Quantifying, Predicting, and Exploiting Uncertainty (QPE 2008) pilot experiment. To do so, we employ our coupled oceanographic (4-D) and acoustic (Nx2-D) modeling systems with ocean data assimilation and a best-fit depth-dependent geoacoustic model. Predictions are compared to the measured acoustic data, showing skill. Using an ensemble approach, we study the sensitivity of our results to uncertainties in several factors, including geoacoustic parameters, bottom layer thickness, bathymetry, and ocean conditions. We find that the lack of signal received on the shelfbreak is due to a 20-dB increase in transmission loss (TL) caused by bottom trapping of sound energy during up-slope transmissions over the complex and deeper bathymetry. Sensitivity studies on sediment properties show larger but isotropic TL variations on the shelf and smaller but more anisotropic TL variations over the shelfbreak. Sediment sound-speed uncertainties affect the shape of the probability density functions of the TLs more than uncertainties in sediment densities and attenuations. Diverse thicknesses of sediments lead to only limited effects on the TL. The small bathymetric data uncertainty is modeled and also leads to small TL variations. We discover that the initial transport conditions in the Taiwan Strait can affect acoustic transmissions downstream more than 100 km away, especially above the shelfbreak. Simulations also reveal internal tides and we quantify their spatial and temporal effects on the ocean and acoustic fields. One type of predicted waves are semidiurnal shelfbreak internal tides propagating up-slope with wavelengths around 40-80 km, horizontal phase speeds of 0.5-1 m/s, and vertical peak-to-peak displacements of isotherms of 20-60 m. These waves lead to variations of broadband TL estimates over 5-6-km range that are more isotropic and on bearing average larger (up to 5-8-dB amplitudes) on the shelf than on the complex shelfbreak where the TL varies rapidly with bearing angles.

Merging Multiple Partial-Depth Data Time Series Using Objective Empirical Orthogonal Function Fitting

Lin, Y.-T., A.E. Newhall, T.F. Duda, P.F. J. Lermusiaux and P.J. Haley, Jr., 2010. Merging Multiple Partial-Depth Data Time Series Using Objective Empirical Orthogonal Function Fitting. IEEE Transactions, Journal of Oceanic Engineering. 35(4) 710-721. doi:10.1109/JOE.2010.2052875.

In this paper, a method for merging partial overlap- ping time series of ocean profiles into a single time series of profiles using empirical orthogonal function (EOF) decomposition with the objective analysis is presented. The method is used to handle internal waves passing two or more mooring locations from multiple directions, a situation where patterns of variability cannot be accounted for with a simple time lag. Data from one mooring are decomposed into linear combination of EOFs. Objective analysis using data from another mooring and these patterns is then used to build the necessary profile for merging the data, which is a linear combination of the EOFs. This method is applied to temperature data collected at a two vertical moorings in the 2006 New Jersey Shelf Shallow Water Experiment (SW06). Resulting profiles specify conditions for 35 days from sea surface to seafloor at a primary site and allow for reliable acoustic propagation modeling, mode decomposition, and beamforming.

At-sea Real-time Coupled Four-dimensional Oceanographic and Acoustic Forecasts during Battlespace Preparation 2007

Lam, F.P, P.J. Haley, Jr., J. Janmaat, P.F.J. Lermusiaux, W.G. Leslie, and M.W. Schouten, 2009. At-sea Real-time Coupled Four-dimensional Oceanographic and Acoustic Forecasts during Battlespace Preparation 2007. Special issue of the Journal of Marine Systems on "Coastal processes: challenges for monitoring and prediction", Drs. J.W. Book, Prof. M. Orlic and Michel Rixen (Guest Eds.), 78, S306-S320, doi: 10.1016/j.jmarsys.2009.01.029.

Systems capable of forecasting ocean properties and acoustic performance in the littoral ocean are becoming a useful capability for scientific and operational exercises. The coupling of a data-assimilative nested ocean modeling system with an acoustic propagation modeling system was carried out at sea for the first time, within the scope of Battlespace Preparation 2007 (BP07) that was part of Marine Rapid Environmental Assessment (MREA07) exercises. The littoral region for our studies was southeast of the island of Elba ( Italy) in the Tyrrhenian basin east of Corsica and Sardinia. During BP07, several vessels collected in situ ocean data, based in part on recommendations from oceanographic forecasts. The data were assimilated into a four- dimensional high-resolution ocean modeling system. Sound-speed forecasts were then used as inputs for bearing- and range-dependent acoustic propagation forecasts. Data analyses are carried out and the set-up of the coupled oceanographic-acoustic system as well as the results of its real-time use are described. A significant finding is that oceanographic variability can considerably influence acoustic propagation properties, including the probability of detection, even in this apparently quiet region around Elba. This strengthens the importance of coupling at-sea acoustic modeling to real-time ocean forecasting. Other findings include the challenges involved in downscaling basin-scale modeling systems to high-resolution littoral models, especially in the Mediterranean Sea. Due to natural changes, global human activities and present model resolutions, the assimilation of synoptic regional ocean data is recommended in the region.

Underwater acoustic sparse aperture system performance: Using transmitter channel state information for multipath & interference rejection

Puryear, A., L.J. Burton, P.F.J. Lermusiaux, and V.W.S. Chan, 2009. Underwater acoustic sparse aperture system performance: Using transmitter channel state information for multipath & interference rejection. OCEANS 2009-EUROPE, pp. 1-9, 11-14 May 2009, doi:10.1109/OCEANSE.2009.5278156.

Today’s situational awareness requirements in the undersea environment present severe challenges for acoustic communication systems. Acoustic propagation through the ocean environment severely limits the capacity of existing underwater communication systems. Specifically, the presence of internal waves coupled with the ocean sound channel creates a stochastic field that introduces deep fades and significant intersymbol interference (ISI) thereby limiting reliable communication to low data rates. In this paper we present a communication architecture that optimally predistorts the acoustic wave via spatial modulation and detects the acoustic wave with optimal spatial recombination to maximize reliable information throughput. This effectively allows the system to allocate its power to the most efficient propagation modes while mitigating ISI. Channel state information is available to the transmitter through low rate feedback. New results include the asymptotic distribution of singular values for a large number of apertures. Further, we present spatial modulation at the transmitter and spatial recombination at the receiver that asymptotically minimize bit error rate (BER). We show that, in many applications, the number of apertures can be made large enough so that asymptotic results approximate finite results well. Additionally, we show that the interference noise power is reduced proportional to the inverse of the number of receive apertures. Finally, we calculate the asymptotic BER for the sparse aperture acoustic system.

Spatial and Temporal Variations in Acoustic propagation during the PLUSNet-07 Exercise in Dabob Bay

Xu, J., P.F.J. Lermusiaux, P.J. Haley Jr., W.G. Leslie and O.G. Logutov, 2008. Spatial and Temporal Variations in Acoustic propagation during the PLUSNet-07 Exercise in Dabob Bay. Acoustical Society of America, Proceedings of Meetings on Acoustics (POMA). 155th Meeting, Vol. 4. 11pp. doi: 10.1121/1.2988093.

We present the spatial and temporal variability of the acoustic field in Dabob Bay during the PLUSNet07 Exercise. The study uses a 4-D data-assimilative numerical ocean model to provide input to an acoustic propagation model. The ocean physics models (primitive-equations and tidal models), with CTD data assimilation, provided ocean predictions in the region. The output ocean forecasts had a 300m and 1-5m resolution in the horizontal and vertical directions, at 3-hour time intervals within a 15-day period. This environmental data, as the input to acoustic modeling, allowed for the prediction and study of the temporal variations of the acoustic field, as well as the varying spatial structures of the field. Using a one-way coupled-normal-mode code, along- and across-sections in the Dabob Bay acoustic field structures at 100, 400, and 900 Hz were forecasted and described twice-daily, for various source depths. Interesting propagation effects, such as acoustic fluctuations with respect to the source depth and frequency as a result of the regional ocean variability, wind forcing, and tidal effects are discussed. The novelty of this work lies in the possibility of accurate acoustic TL prediction in the littoral region by physically coupling the real-time ocean prediction system to real-time acoustic modeling.

Prediction Systems with Data Assimilation for Coupled Ocean Science and Ocean Acoustics

Robinson, A.R. and P.F.J. Lermusiaux, 2004. Prediction Systems with Data Assimilation for Coupled Ocean Science and Ocean Acoustics, Proceedings of the Sixth International Conference on Theoretical and Computational Acoustics (A. Tolstoy, et al., editors), World Scientific Publishing, 325-342. Refereed invited Keynote Manuscript.

Ocean science and ocean acoustics today are engaged in coupled interdisciplinary research on both fundamental dynamics and applications. In this context interdisciplinary data assimilation, which melds observations and fundamental dynamical models for field and parameter estimation is emerging as a novel and powerful methodology, but computational demands present challenging constraints which need to be overcome. These ideas are developed within the concept of an interdisciplinary system for assessing sonar system performance. An end-to-end system, which couples meteorology-physical oceanography-geoacoustics-ocean acoustics-bottom-noise-target-sonar data and models, is used to estimate uncertainties and their transfers and feedbacks. The approach to interdisciplinary data assimilation for this system importantly involves a full, interdisciplinary state vector and error covariance matrix. An idealized end-to-end system example is presented based upon the Shelfbreak PRIMER experiment in the Middle Atlantic Bight. Uncertainties in the physics are transferred to the acoustics and to a passive sonar using fully coupled physical and acoustical data assimilation.

Modeling Uncertainties in the Prediction of the Acoustic Wavefield in a Shelfbreak Environment

Lermusiaux, P.F.J., C.-S. Chiu and A.R. Robinson, 2002. Modeling Uncertainties in the Prediction of the Acoustic Wavefield in a Shelfbreak Environment. Refereed invited Manuscript, Proceedings of the 5th International conference on theoretical and computational acoustics, May 21-25, 2001. (Eds: E.-C. Shang, Q. Li and T.F. Gao), World Scientific Publishing Co., 191-200.

The uncertainties in the predicted acoustic wavefield associated with the transmission of low- frequency sound from the continental slope, through the shelfbreak front, onto the continental shelf are examined. The locale and sensor geometry being investigated is that of the New England continental shelfbreak with a moored low-frequency sound source on the slope. Our method of investigation employs computational fluid mechanics coupled with computational acoustics. The coupled methodology for uncertainty estimation is that of Error Subspace Statistical Estimation. Specifically, based on observed oceanographic data during the 1996 Shelfbreak Primer Experiment, the Harvard University primitive-equation ocean model is initialized with many realizations of physical fields and then integrated to produce many realizations of a five-day regional forecast of the sound speed field. In doing so, the initial physical realizations are obtained by perturbing the physical initial conditions in statistical accord with a realistic error subspace. The different forecast realizations of the sound speed field are then fed into a Naval Postgraduate School coupled-mode sound propagation model to produce realizations of the predicted acoustic wavefield in a vertical plane across the shelfbreak frontal zone. The combined ocean and acoustic results from this Monte Carlo simulation study provide insights into the relations between the uncertainties in the ocean and acoustic estimates. The modeled uncertainties in the transmission loss estimate and their relations to the error statistics in the ocean estimate are discussed.