AOSN Monterey Bay Experiment: Creating Sustainable Ocean Observation/Prediction Systems
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1 AOSN Monterey Bay Experiment: Creating Sustainable Ocean Observation/Prediction Systems
2 AOSN II Objectives: To design and build an adaptive coupled observation/modeling system. The system should be sustainable in its operation and capable of being readily relocated, in its final form. Use autonomous in situ platforms to achieve economic operation. Use oceanographic models to assimilate data from a variety of platforms and sensors into synoptic views of oceanographic fields and fluxes. Adapt deployment of mobile assets to improve performance. Test performance of the system in a quantitative fashion. Post results in real-time. Use the results of those tests to guide research and development to improve system performance.
3 Monterey Bay 2003 Participants 1 System Engineering MBARI - Project coordination, definition, infrastructure, hosting (Bellingham, Chandler, Chavez) Modeling: Harvard - Numerical Ocean Modeling / Mesoscale Circulation (Robinson also Project Deputy) JPL - Numerical Ocean Modeling / Atmospheric forcing (Yi) NRL, Stennis - Numerical Ocean Modeling / Small Scale Dispersion (Shulman) NRL-MRY - Atmospheric Forcing (COAMPS) / Targeted Observations (Doyle/Bishop) Ecosystem Dynamics MBARI - Bioluminescence program (Haddock) CalPoly - Bioluminescence program (Moline) UCSB Bioluminescence sensors (Case)
4 Observations: Monterey Bay 2003 Participants 2 MBARI AUV, towfish, ship & mooring observations(chavez, Johnson, Ryan) SIO Deep gliders (Davis) UCSC Ship hydrographic survey (McMannus) WHOI - Physical Observations / Glider Network, Floats, Lagrangian Drifters (Fratantoni) NPS - Surface Currents (CODAR) / Sea Surface Fields (Aircraft) / AXBT (Paduan, Ramp) Adaptive Sampling/Model-Derived Products Princeton - Glider Dynamics, Control, Adaptive Sampling (Leonard, Rowley) Cal Tech - Dynamical Systems Modeling (Coulliette, Marsden)
5 Day N Day N ROMS Modelling 8 Hour Duration HOPS Modelling 5 Hour Duration ROMS Modelling 8 Hour Duration ESSE Compuation(Phys) 28 Hour Duration HOPS Modelling ESSE Comp. (Phys+Bio) 56.5 Hour Duration 5 Hour Duration ROMS Modeling HOPS Graphical Products 1 Hour Duration Super Ens. Computation.5 Hour Duration HOPS Graphical Products 1 Hour Duration Super Ens. Computation.5 Hour Duration HOPS Modeling Super Ensemble LCS Computation 3 Hour Duration RTOC Functions & Lunch Daily Brief Prep 1 Hour Duration RTOC Deliberation 3 Hour Duration Start: 1400 PST Day n End: 1700 PST Day n LCS Computation 3 Hour Duration Daily Brief Prep 1 Hour Duration LCS Asset Tasking NPS A/C Flight & Data Reduce 4 hr flight/4hr data reduction/.5hr drive AS Vehicle Tasking 2 Hour Duration Glider Waypoints NPS A/C Flight & Data Reduce 4 hr flight/4hr data reduction/.5hr drive AS Vehicle Tasking 2 Hour Duration Glider Waypoints Glider Surfacing/Data & Ship Hydrography Every 2 hours for <20 minutes Mooring & CODAR Data Every 1 hour COAMPS & Bottom ADCP Data Every 24 hours J. G. Bellingham, MBARI
6 Science Focus
7 Wind-driven Upwelling Processes Example from Aug
8 Observation Assets
9 AUV WHOI Gliders SIO Gliders Dorado NPS REMUS Cal Poly REMUS Satellite SST SeaWiFS Physical Observations Aircraft Twin Otter P3 / AXBT Moored/Fixed HF Radar M1/M2 NPS ADCP MBARI Profiler Ships Pt. Sur John Martin Drifting Surface Drifters Profilers
10 Speed/Payload Endurance 4 kts 3 kts 1 kts Hours Days Weeks AUVs Cal Poly/NPS REMUS NPS Aries MBARI Dorado SIO & WHOI Gliders
11 DATA BUS EXPERIMENT: Real-Time Data from Bottom-Mounted Profiler ARIES AUV DATA DATA Current Profiler Housing Data Modem Tony Healey Steve Ramp
12 Observation Performance
13 Deployment Schedule WHOIGlider9.mat WHOIGlider8.mat WHOIGlider7.mat WHOIGlider6.mat WHOIGlider5.mat WHOIGlider4.mat WHOIGlider13.mat WHOIGlider12.mat WHOIGlider11.mat WHOIGlider10.mat Towfish1.mat SIOGlider7.mat SIOGlider6.mat SIOGlider5.mat SIOGlider4.mat SIOGlider1.mat PtSurCTD1.mat NPSRemus1.mat MartinCTD1.mat DORADO1.mat CalPolyRemus1.mat Year Day (2003)
14 0-200m August 2003 Glider Tracks 0-400m
15 Dorado Transect
16 Sampling Strategies
17 Non-adaptive best performance (sans modeling) month hh 2 weeks week 3 days day 12 hours hours km 10 km 100 km 8 1 Coverage Rate (m/s) Gliders + AUVs, averaged Gliders only, averaged Gliders + AUVs Best Possible Survey Performance Year Day Year Day
18 Example Coverage Analysis for All Gliders in MB 03 σ varies 2 km (at shore) to 10 km (at 4000m depth), τ = 24 hours, Outside black contour, locations not sampled for 48 hours. Number of WHOI/SIO Profiles Throughout August WHOI SIO Number of Profiles Dynamical Control Systems Princeton University Day in August 2003
19 Coordinated 3-Glider Exp. with Gradient Estimate Aug 6-7, 2003 Aug 6-7, 2003 Glider temperature profiles Dynamical Control Systems Princeton University
20 Models
21 Real-Time AOSN COAMPS Twice Daily Forecasts to 72 h with Data Assimilation NOGAP Lateral Boundary Conditions SGI Origin 3900 at FNMOC DoD HPC Distributed Computing Facility Real-Time Winds and Fluxes are Used to Force Ocean Models 81 km 27 km 9 3 km km 27 km 9 km 3 km
22 Harvard Ocean Prediction System - HOPS The Harvard Ocean Prediction System is a system of integrated software for multidisciplinary oceanographic research. The heart of HOPS is a primitive equation dynamical model, which is supported by data gridding routines, initialization and assimilation field preparation routines, visualization software, data preparation codes and topography conditioning software. A.R. Robinson, P.J. Haley, Jr., P.F.J. Lermusiaux, W.G. Leslie
23 Sustained upwelling: comparison of real-time forecasts (top) with AVHRR SST (right) and reanalysis fields (bottom)
24 Ocean Modeling & Data Assimilation during AOSN JPL Data Server COAMPS Data Server MBARI AOSN Data Server Data Retrieval & Processing ROMS (L1, L2 L3, 3-L nested) DAS Ancillary Data JPL SGI Computer OurOcean LAS
25 Sea Surface Temperature Data & ROMS Reanalysis Aug. 7 Aug. 13 Obs Obs Aircraft ROMS ROMS ROMS
26 Ground-Truth ROMS Analysis against Independent Mooring Observations M1 Lack of data below 150 m (e.g., WHOI glider) near M1; Lack of surface salinity data & deficiencies in the fresh-water flux used in ROMS
27 Model-Derived Products
28 Drifter Trajectory Aug 16 15:00 GMT Aug 18 03:00 GMT The actual trajectory of the drifter follows along LCS (LCS computed from HOPS 5m depth) Dynamical Control Systems Princeton University Control and Dynamical Caltech
29 Accomplishments Highly successful use of autonomous mobile platforms 20 different systems, all successfully operated. Roughly 10 in water at any given time, with peak of 15. Coordinated adaptive sampling Forecasts forced by COAMPS atmospheric predictions Observations generally assimilated into real-time model nowcasts and forecasts within 24 hours of appearance on data server Real-time nowcasts and forecasts of temperature, salinity and velocity released over a period of a month Extensive observational data set obtained for OSE/OSSE analysis. Graphical data products released on web sites in real-time during experiment (
30 Evaluate value added by models Opportunities Predictive skill, observation guidance, etc. Model improvements (tides, etc.) Adaptive sampling strategies (optimization of array, targeted observations, reflexive strategies, etc.) Optimization of observation suite Platform & sensor mix docking? Operational strategies (e.g. glider protection) Communications Analysis tools - OSE/OSSE development of real-time systems & DMA. Model-derived products (LCS, etc.) System engineering & portability provide transition path as way to focus and accelerate development?
31 ONR has supported the development and application of AOSN since 1995 through numerous Grants to investigators at a variety of institutions. The Packard Foundation supported MBARI involvement and hosting of the 2000 and 2003 field programs.
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