Physical-acoustical data assimilation via ESSE for improved sonar predictions

1. Physical-acoustical data assimilation via ESSE for improved sonar predictions and numerical simulations of the PRIMER ocean physics P.F.J. Lermusiaux, UNITES team June 18, 2003 • ERROR SUBSPACE STATISTICAL ESTIMATION: TWIN EXPERIMENT • COUPLED ASSIMILATION OF SOUND-SPEED AND TRANSMISSION LOSS • REDUCTION OF BROADBAND TL UNCERTAINTIES • NUMERICAL SIMULATIONS OF PRIMER OCEAN PHYSICS • INFORMATION AND UNCERTAINTIES • RESULTS TO DATE • CONCLUSIONS AND UNITES SUMMARY

2. PHYSICAL-ACOUSTICAL FILTERING IN A SHELFBREAK ENVIRONMENT

3. Acoustic paths considered (as in Shelfbreak-PRIMER), overlaid on bathymetry.

4. P =e{(x–xt ) (x – xt)T} ˆ ˆ Coupled Data Assimilation and Uncertainty Initialization: ESSE Interdisciplinary Error Covariances x = [xAxO] Physics: xO = [T, S, U, V, W] Acoustics: xA = [Pressure (p), Phase ()] cO PAA PAO P = POA POO • ESSE ensemble initialization: • Initialize dominant P based on missing/most uncertain variability in IC • - Approach: Multi-variate, 3D, Multi-scale (more than random numbers), see • Lermusiaux et al (QJRMS, 2000) and Lermusiaux (JAOT, 2002).

5. Coupled Prediction of Uncertainties via Error Subspace Statistical Estimation (ESSE) Predicted sound-speed uncertainties Predicted broadband TL uncertainties (C1: sound-speed along cross-section 1) (TL1: Transmission loss along cross-section 1)

7. (a) (b) (c) (d) Coupled ESSE data assimilation of sound-speed and TL data for a joint estimate of sound-speed and TL fields

8. (a) (b) (c) (d)

9. (a) (b) (c) (d)

10. Predicted PDF of broadband TL

11. After Assimilation PDF of broadband TL

12. Ocean Physics Model and Data Uncertainties Bathymetry BCs: surface atmospheric forcings, coastal-estuary and open-boundary fluxes Initial conditions and ocean physics data Parameterized processes: sub-grid-scales, turbulence closures, un-resolved processes e.g. tides and internal tides, internal waves and solitons, microstructure and turbulence Numerical errors: steep topographies/pressure gradient, non-convergence NUMERICAL SIMULATIONS OF PRIMER OCEAN PHYSICS

13. Uncertainties in bathymetry (from data differences and statistical model) NOAA soundings combined with Smith and Sandwell (overlaid with GOM bathymetry) Smith and Sandwell (predicted topography based on gravity anomaly not well compensated for regions with thick sediments)

15. Uncertainties in atmospheric forcings (from buoy-data/3d-model differences) Baugmarter and Anderson, JGR (1996)

16. Three-Hourly Atmospheric Forcings: Adjusted Eta-29km model, 21 July 1996, 2pm EST

17. Averaged wind-stress time-series

22. SST July 9, 1996 SST July 22, 1996

23. Initialization • Slope and shelf objective analyses • 2. Shelfbreak front feature model Ring

24. No Atmos. forcings With Atmos. forcings

28. Oceans physics/acoustics data assimilation: carried-out as a single multi-scale joint estimation for the first time, using higher-moments to characterize uncertainties ESSE nonlinear coupled assimilation recovers fine-scale TL structures (10-100m) and mesoscale ocean physics (10km) from coarse TL data (towed-receiver at 70m depth, one data every 500m) and/or coarse C data (2-3 profiles over 40km) Two notable coupled processes: Shoreward meander of upper-front leads to less loss in acoustic waveguide (cold pool) on shelf Corresponding thickening of thermocline at the front induces phase shifts in ray patterns on the shelf Broadband TL uncertainties predicted to be range and depth dependent Coupled DA sharpens and homogenizes broadband PDFs CONCLUSIONS: Coupled ESSE Twin-experiments

29. Shelfbreak Front (SBF) and atmospheric forcing Intermittent atmospheric forcing impose space and time scales on SBF, controlling some internal instabilities. They must be accounted for in a complete theory! Important consequences for scientific and naval uncertainties Other processes found SBF is stronger where topography is steeper (inflow/outflow in simulation) SBF has a tendency to bifurcate at Hudson Canyon With warm-core rings in slope-water, this leads to sub-surface northeastward flow Numerical mesoscale to sub-mesoscale ocean predictions for acoustic predictions is essential, but substantial progress required, both in data and modeling Uncertainties in bathymetry, surface atmospheric forcing, un-resolved processes and ocean data are the ones that matter: they are being modeled CONCLUSIONS: Numerical Simulations of PRIMER Dynamics

30. Probabilistic performance prediction method presently being evaluated by Navy (SOWG) ECS Passive Sonar End-to-End System (Uncertainty Scientific Workshop) Narrowband Sonar End-to-End System About to Start ECS TL azimuthal variability (ASIAEX) Uncertainty Province Characterization from TL spatial variability at 3 separate locations in ECS PRIMER vertical array beamforming fluctuations, signal and noise * OASIS Group Includes: Abbot, Dyer, Gedney, Emerson, Shanahan OASIS* Accomplishments

31. Peter Cable (BBN) • Characterized environmentally associated temporal and spatial variability of low frequency active sonar signal-to-interference in a well-behaved littoral environment (ACT I) • Modeled implications regarding target detection performance • Jim Fulford (NRL) • Utilized geoacoustic methods either employed by NAVO, or under consideration by NAVO to obtain geoacoustical estimates of means and standard deviations • These statistics have been employed in forward predictions of the active system performance predictions means and standard deviations in littoral settings • Suggest that uncertainty of signal excess in reverberation limited regions will be less than uncertainty in noise limited regions.

32. CS Chiu (NPS) • Analyzed dependence of TL fluctuation statistics on signal bandwidth using both (Shelfbreak) PRIMER and ASIAEX (SCS) data. • Performed model simulation of ASIAEX TL fluctuation statistics, compared modeled statistics to measured statistics, and began studying uncertainty in mean TL prediction. • Integrated PRIMER SeaSoar and moored data to upgrade daily SSP and TL estimates, and examined the sensitivity of the TL estimate to the resolution of the sound speed estimate.

33. Tim Duda (WHOI) • Simulation of propagation through coastal internal waves and fronts • First-order modulation of the mode-coupling impact of nonlinear internal waves by mesoscale features such as fronts • Effects of the small- and large-scale features can't be treated independently. • Quantification of temporal signal variability in SWARM, PRIMER and ASIAEX/SCS experiments • Scintillation index and correlation time of signal energy correlate well with internal wave statistics.

34. Glen Gawarkiewicz, Chris Linder WHOI Physical Oceanography- Data Analysis of shelfbreak frontal response to wind forcing (Winter PRIMER, Southern MAB data sets) Analysis of near-bottom temperatures In MAB using Lobster trap array Comparison of PRIMER fields with MODAS Comparison of ASIAEX mesoscale fields with NRL-Stennis forecast model

35. Jim Lynch (WHOI) A) Described mechanisms/statistics of scattering sound in PRIMER due to the internal waves, bathymetry, front, and "foot-of-front". Three publications exist concerning this PRIMER work. (Am author or co-author). 1) Sperry et al. (2003) “Characteristics of acoustic propagation to the eastern vertical line array receiver during the summer 1996 New England Shelfbreak PRIMER experiment.” Submitted to IEEE J. Oceanic Eng’g. 2) Fredericks, Colosi, and Lynch (2003). “Analysis of multipath scintillations observed during the summer 1996 New England shelfbreak PRIMER study.” Submitted to IEEE J. Oceanic En’g. 3) Lynch et al (2003) “Spatial and temporal variations in acoustic propag. characteristics at the New England shelfbreak front.” IEEE J. Oceanic Eng’g., 28(1), 129-150. B) Described mechanisms/statistics of scattering of sound in the ASIAEX experiment (which can provide a useful comparison to the PRIMER results.) Two publications exist concerning this ASIAEX work. (Am author or co-author). 4) Duda, Lynch, Newhall, Wu, and Chiu (2003). “Fluctuation of 400 Hz sound intensity in the 2001 ASIAEX South China Sea Experiment.”Submitted to IEEE J. Oceani Eng'g. 5) Chiu, Ramp, Miller, Lynch, Duda and Tang (2003). “Acoustic intensity fluctuations induced by South China Sea internal tides and solitons.” Sub. to IEEE J. Oceanic Eng'g.