PLUSNet 1 HARVARD – MIT Modeling, Predictions and Adaptive Sampling Team MB06 – 07 Planning PLUSNet Meeting APL, UW, Oct 25, 2006 Coupled Ocean and Acoustic Modeling, Data Assimilation, Predictions and Adaptive Sampling Recommendations Pierre Lermusiaux, Patrick Haley, Wayne Leslie, Oleg Logutov Ding Wang, Henrik Schmidt and Donald Eickstedt

PLUSNet 2 Goal: To provide (sub)-mesoscale environmental fields/picture to MIT and PLUSNet, using new multi-scale environmental data-driven forecasting systems and new HU-MIT physical-acoustical adaptive sampling schemes Specific objectives are to: (i)Research and develop a new nested sub-mesoscale (non)-hydrostatic ocean modeling system within coarser regional domains for improved acoustic predictions (ii)Investigate and carry out physical-acoustical-seabed estimation and data assimilation (iii)Evaluate oceanic sub-mesocale parameterizations and study selected sub-mesoscale/mesoscale interactions and their acoustical impacts (iv)Collaborate with other efforts sponsored by ONR and NRL (v)Lead the environmental PLUSNet scientific research, coordinating the HU and Scripps contributions ( e.g. internal tide conversions, sub-mesoscale eddy mixing and atmospheric forcing) Harvard PLUSNet Goals and Objectives 2.5 Environmentally Adaptive Sensing and Network Control

PLUSNet 3 Major MB06 Accomplishments 1.Daily ocean environment data assimilation and prediction. 2.Daily acoustic-environment prediction and TL prediction. 3.Daily optimization and recommendations for Adaptive Rapid Environmental Assessment (AREA). 4.Recommendations for capturing fronts. 5.Ocean data management and checks for PLUSNet assets, relay to MBARI COOP. 6.Web-based distribution of all our outputs and results.

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PLUSNet 6 Example of Daily Summary Description s Environmental and acoustic nowcasts and predictions up to 00Z Aug 26 are available from: Product files are in: Upwelling event is ending and our forecasts indicate that relaxation conditions (warmer surface temperatures and no wind-driven currents) will start tomorrow. See for example tomorrow's afternoon surface sound speed and current vectors: Based on our studies of the past week of transmission loss estimates, relaxation conditions correspond to -more- mean loss at 100Hz and 400Hz than upwelling conditions. The average difference at Hz and at 10km range is about 3 to 8db more mean loss. It would be very interesting to find out if the measured mean acoustic performance (TL)at these frequencies over 7 to 15km ranges is lower tomorrow afternoon than it has been in the past days of upwelling conditions. Vertically averaged current velocities in the PLUSNet ops area are expected to be to the northwest, following the coastline. For example, for tomorrow morning: Surface velocities are expected to be patchy. For drifting behaviors, we recommend to combine it with a vertical yoyo so as to be drifting in vertically averaged currents, which are forecast to the northwest. Transmission loss predictions available from:

PLUSNet 7 Major Accomplishment I (cont.) Error Subspace Statistical EstimationHarvard Ocean Prediction System Uncertainty forecasts, Ensemble-based, Multivariate DA, Adaptive sampling, Towards multi-model estimates Free-surface PE, Generalized biological models, Coupled to acoustic models, XML schemes to check configuration I: Daily Ocean Environment DA and Predictions: Methodology

PLUSNet 8 Free-Surface Ocean Model (HOPS) Tidal and atmospheric forcing Twice-daily data assimilation Nested Ocean Modeling with Grid-computing in Two Domains Monterey Bay/San Francisco Domain: 1.5 km resolution PLUSNet - Ano Nuevo Domain: 0.5 km resolution Major Accomplishment I (cont.)

PLUSNet 9 Measured and Estimated Sound Speed Radial 4 Measured and Estimated Averaged Currents 0-200m OPAREA Bathymetry and Analysis Radials Surface SSP and Currents 100m Depth SSP and Currents 30m Depth SSP and Currents 64 See: for twice daily plots and hourly data files (including tides) I: Daily Ocean Environment DA and Predictions “Undersea Weather” Major Accomplishment I (cont.)

PLUSNet 10 APL- HU Collaboration: Use and Evaluation of Surface Drift Predictions by the Seaglider Team Bob Miyamoto, Bruce Howe and APL collaborators utilized our HOPS ocean model predictions of surface currents to plan their drifting missions APL uses the HOPS currents to compute a drift prediction. The result (green curve) is compared to the observed glider drift while on the surface. Case 1: better agreement than dreamed! Note sharp east-west gradient captured by the nested ocean models including tides Case 2: Not good. Atmos. and ocean models seem in phase error in time (see |u| change) and space (see weaker currents to the east)

PLUSNet Forecast Surface Currents (used by PLUSNet assets for planning drifting missions) OPAREA Bathymetry and Analysis Radials Sound Speed Radial 6 64 II: Daily Coupled Acoustic-Environment and TL Predictions: MB06 is the first time this has been done See: for twice daily TL plots and hourly data fileshttp://ocean.deas.harvard.edu/PLUSNet Seabed Modeling (thanks to M.Porter et al) Major Accomplishment II TL Prediction (issued on Aug 22 12Z) along Radial 6, for a source at 5m and a receiver at 75m

PLUSNet 12 Relaxation: B6 D3 8_25_06 Upwelling: B6 D1 8_22_06 f=100Hz, sz=40m SVP(m/s) TL filed (dB) Major Accomplishment II (cont.) II: Daily Acoustic-Environment and TL Predictions (cont.)

PLUSNet 13 Upwelling: B6 D1 8_22_06Relaxation: B6 D3 8_25_06 Relaxation conditions (warmer surface temperatures and no wind- driven currents) correspond to more mean loss at 100Hz and 400Hz than upwelling conditions: 3 to 8db more mean loss over 7 to 15km. Major Accomplishment II (cont.) II: Daily Acoustic-Environment and TL Predictions (cont.)

PLUSNet 14 M I T Data Assimilation Smaller SVP Forecast From HOPS/ESSE Objective: Find the optimal path so as to minimize Acoustic Prediction Uncertainty Acoustic Modeling SVP Nowcast The True Ocean III: Daily Optimization and Recommendations for Adaptive Sampling and AREA Major Accomplishment III

PLUSNet 15 Suboptimal predetermined path Suboptimal yoyo control Suboptimal predetermined path (2-way)Suboptimal on-board adaptive path Major Accomplishment III (cont.) III: Daily Optimization and Recommendations for Adaptive Sampling and AREA

PLUSNet 16 A priori TL std map Posteriori TL std map after the suboptimal predetermined path (m) Smoothed TL std (dB) (km) Major Accomplishment III (cont.) Above TL uncertainty estimates (std) do not account for most internal wave effects. They account for impacts of mesoscale ocean uncertainties and tidal effects. III: Daily Optimization and Recommendations for Adaptive Sampling and AREA

PLUSNet 17 8/22/06 Starting point: lat= , long= Bearing=180 degree clockwise from the north, waypoints are: r: km z: m 2. Bearing=180 degree clockwise from the north, max range=10km, optimal yoyo control parameters are(10, 0.5): XXX.Initialize(5, 100, 0, 10, 0.5)//upper bound: 5m; lower bound: 100m; initial depth: 0m; points:10; threshold: Bearing=180 degree clockwise from the north ADP DW_ADP; DW_ADP.Initialize( ); Major Accomplishment III (cont.) III: Daily Optimization and Recommendations for Adaptive Sampling and AREA Example of sent daily:

PLUSNet 18 Major Accomplishment III (cont.) III: Daily Optimization and Recommendations for Adaptive Sampling and AREA

PLUSNet 19 w 8_24_06 Afternoon w 8_24_06 Morning IV: Recommendations for capturing fronts 1.Make in-situ measurements crossing the fronts. 2.Make a horizontal yoyo control focusing on the fronts. 3.Tracking temperature gradients. Major Accomplishment IV

PLUSNet 20 8/23/06 In the morning: 1. run predetermined path: Waypoints are: (lat= long= ), ( ), ( , ),( , ), depth=0m 2. or run this: Starting point: lat= , long = , depth=0m. DingWang_2D_Gradient DW_Gradient; DW_Gradient.Initialize(270., -1);//the initial AUV direction is 270 degree clockwise from the north; -1: follow the opposite gradient direction let AUV hit the northwest side of PLUSNet box, and then directly come back. In the afternoon: 3. Waypoints are: ( ), ( , ), ( , ), ( ), depth=0m. 4. Starting point: lat= , long = , depth=0m. DingWang_2D_Gradient DW_Gradient; DW_Gradient.Initialize( , -1);//the initial AUV direction is 306 degree clockwise from the north; -1: follow the opposite gradient direction let AUV hit the northwest side of PLUSNet box, and then directly come back. IV: Recommendations for capturing fronts: issued twice Major Accomplishment IV (cont.) Example of one of the sent:

PLUSNet 21 Major Accomplishment IV (cont.) IV: Recommendations for capturing fronts: Realized at sea once

PLUSNet 22 HU MB06 Deliverables and Needs Deliverables Substantial measured T,S data and data-driven ocean-acoustic model estimates, which we will continue to improve and distribute Model estimates also available in relocated area (Monterey Bay) Needs To write collaborative papers, we need quantitative evidence (plots, data) to support successful or failed usage of our estimates, e.g: Marc Stewart’s based on our SE currents predictions in S corner of domain : “Pierre, You'll be interested to know that our Restech reported substantial SE surface current in the S corner of the PLUSNet box today as she attempted to recover a Bluefin in an Avon. I personally doubted it, but now I know better! Thanks, Marc” For FY07, PLUSNet should create a real-time coop web-page where such feedback and other data can be posted (e.g. Warren Fox’s suggestion: Data transfer interface / client-server architecture)

PLUSNet Coupled Physical-Acoustical Data Assimilation in real-time Integrate and optimize physical- acoustical DA software with Mini-HOPS and AREA Initiate coupled physical-acoustical- seabed estimation and DA Couple mini-HOPS/ESSE with selected sonar performance prediction (End-2- End System) Research-Work: FY07 Focus in Blue 1. Multi-Scale and Non-Hydrostatic Nested Ocean Modeling Research and develop relocatable sub- mesoscale nested modeling capability: Higher-resolution hydrostatic model (Mini- HOPS) HOPS coupled with non-hydrostatic models (2D to 3D: Lamb, Smolarkiewicz or MIT-GCM) Compare parameterizations of sub- mesoscales and boundary layers, and evaluate with HOPS and ROMS (run at HU, continue to collaborate with Scripps) 3. Acoustical-Physical Nonlinear Adaptive Sampling with ESSE and AREA Implement and progressively demonstrate in FY automated adaptive environmental sampling, integrating mini-HOPS and ESSE with AREA/NAFCON Continue ocean-TL predictions (done for first time during MB06) Compute TL on denser spatial grids and for varied (higher) frequencies (with APL) Provide field and uncertainty estimates to NAFCON and coordinate with Penn State for real-time display (towards end-to-end TDAs)

PLUSNet 24 Papers with PLUSNet support Published/Submitted Lermusiaux P.F.J., Uncertainty Estimation and Prediction for the Interdisciplinary Ocean. Special issue of the Journal of Computational Physics on ``Uncertainty Quantification''. James Glimm and George Karniadakis, Editors Lermusiaux P.F.J, Adaptive Sampling, Adaptive Data Assimilation and Adaptive Modeling. Special issue of the J. of Inverse Problems on ``Mathematical Issues and Challenges in Data Assimilation for Geophysical Systems: Interdisciplinary Perspectives''. Christopher K.R.T. Jones and Kayo Ide, Eds. Under review. Wang D., P.F.J. Lermusiaux, P.J. Haley, W.G. Leslie and H. Schmidt, Adaptive Acoustical- Environmental Assessment for the Focused Acoustic Field-05 At-sea Exercise, Proceedings of IEEE/MTS Oceans'06 Conference, Boston, MA, September 18-21, 2006, 6pp. In Press. Yilmaz N.K., C. Evangelinos, N.M. Patrikalakis, P.F.J. Lermusiaux, P.J. Haley, W.G. Leslie, A.R. Robinson, D. Wang and H. Schmidt, Path Planning Methods for Adaptive Sampling of Environmental and Acoustical Ocean Fields, Proceedings of IEEE/MTS Oceans'06 Conference, Boston, MA, September 18-21, 2006, 6pp In Press. In Preparation (working titles) Wang, Schmidt, Lermusiaux et al. AREA for PLUSNet: MB06 and FAF05. To be prepared for IEEE. Lermusiaux, Wang, Schmidt, Haley, Leslie, Fox?, Wilson?, et al. Coupled ocean-acoustic Predictions during MB06 for PLUSNet. Short paper to be prepared to JASA Shipley, Stewart, Schmidt et al. PLUSNet-MB06 team short paper? (to do asap?) Seaglider team and HU team. Planning of drifting missions using seaglider and HOPS? Curcio et al. Ocean data from autonomous kayaks for physical oceanography and ocean modeling, JRL