Gulf of Maine Circulation Modeling: Prospects for Skill 6 July 2005
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Gulf of Maine Circulation Modeling: Prospects for Skill
6 July 2005
Daniel R. LynchDartmouth College
Hanover NH
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Points of Departure
• Science
• People
• Data
• Problems
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Science
• Well-Established:– Physical Quantities– Equations – Algorithms for solutions
• Distributed across ‘Academe’
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People
• At least 3 different communities– Theory – Observation– Simulation “the third science”
• Algorithms• Systems
• Non-Local• Incentives: Advancement of Learning
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Data
• Unprecedented new abundance• Sampling in (x, y, z, t) necessarily sparse• Real Data is site-specific, event-specific• Necessary to relate theory to facts• By itself, hopelessly incomplete
– Interpolation
– Extrapolation
– Interpretation
– Relation to other information
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Problems
• “Local”• Not alligned with political boundaries• Distributed across agencies• Regulatory context
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Status Quo
• Science: generic, roaming
• Data: local, incomplete
• People: distributed across ‘academe’– Advancent of knowledge, not application
• Problems: regulatory context, local, political boundaries
The Key Challenge is Organizational
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Regional Progress
• 1993 RARGOM Workshop <-------------
• RMRP
• MWRA Mass. Bays
• GLOBEC
• EcoHAB
• Sea Grant (x4)
• GoMOOS
• Multiple NOAA programs
• Canadian Companions
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Data and State Estimation
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Time of Occurrence(Ocean)
Time of Availability(Information)
Future
(Now)
Past
State Estimation
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Time of Occurrence(Ocean)
Time of Availability(Information)
Forecast
Nowcast
Hindcast
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Time of Occurrence(Ocean)
Time of Availability(Information)
Forecast
Nowcast
Hindcast
All Data
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Time of Occurrence(Ocean)
Time of Availability(Information)
Forecast
Nowcast
Hindcast
All Data
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Time of Occurrence(Ocean)
Time of Availability(Information)
Forecast
Nowcast
HindcastAll Data
Model‘Data Product’
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Time of Occurrence(Ocean)
Time of Availability(Information)
Forecast
Nowcast
Hindcast
Data Used
Bell
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Time of Occurrence(Ocean)
Time of Availability(Information)
Forecast
Nowcast
Hindcast
Data Used
Bell Publication
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The Well-Posed Problem(The Mathematical Standard)
Theory
• “The Data” • Necessary and Sufficient
– initial state, simultaneous– boundary conditions (deep
ocean, cross-shelf transports)– forcing (atmospheric fluxes,
rivers)– Parameters (bottom, surface
roughness)
• All roads lead to Rome – (small X)
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The Well-Posed Problem(The Mathematical Standard)
Theory
• “The Data” • Necessary and Sufficient
– initial state, simultaneous– boundary conditions (deep
ocean, cross-shelf transports)– forcing (atmospheric fluxes,
rivers)– Parameters (bottom, surface
roughness)
• All roads lead to Rome – (small X)
Actual
Nonnecessary
Insufficient
X is finite
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The Well-Posed Problem(The Mathematical Standard)
Theory
• “The Data” • Necessary and Sufficient
– initial state, simultaneous– boundary conditions (deep
ocean, cross-shelf transports)– forcing (atmospheric fluxes,
rivers)– Parameters (bottom, surface
roughness)
• All roads lead to Rome – (small X)
Actual
Nonnecessary
Insufficient
X is finite
There is never a well-posed problem in nature
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– Must make up what is not known but necessary
– Use the data you have, deduce what you need
– Criterion: credibility
– Credibility implies a Prior Estimate• mean and variance
Poorly Posed Problems
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What is Truth?
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What is Truth?
Data Model
d m
Misfit
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What is Truth?
Data Model
Truth real but unknowable
Errors unknowable
Prediction a credible blend:
Data + Model
Blend: Invokes statistics of d , m
Prediction Error: blend of statistics of d , m,
d m
Misfit
Prediction
p
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What is Truth?
Data Model
Truth real but unknowable
Errors unknowable
Prediction a credible blend:
Data + Model
Blend: Invokes statistics of d , m
d m
Misfit
Prediction
p
Skill:Misfits
Small, NoisyUnknown Inputs
Small, Smooth
p : grows with time
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Examples
• SAB: resolve the data or burn it
• Great Bay: Hi-resolution Lagrangian exchange
• ECOHAB Results: hindcast trajectories
• Georges Bank: Real-time Wind Forecast Error
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A Data-Assimilative System
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Resolution
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The difference between high-resolution and low-resolution forward simulations
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Inverse Error with Low Resolution-- DA cannot make up for Inadequate Resolution --
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Estuarine Resolution
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Boundary deduced from Interior Data
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Data Assimilative Hindcast
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Mean Separation Rate: 1.78 km/day
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The 2005 Prior
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The 2005 Hindcast
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The 2005 Hindcast
• Data-Assimilative
• Real Time
• At-Sea
•Limited-area
• Hindcast of complete cruise
• May 9- 18
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The 2005 Hindcast
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The 2005 Hindcast
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The 2005 Hindcast
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The 2005 Hindcast
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The 2005 Hindcast
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Who Painted the Bays Red?
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Who Painted the Bays Red?
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Frontal Dispersion - Forecast
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Frontal Dispersion - Forecast
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Frontal Dispersion - Hindcast
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Frontal Dispersion - Hindcast
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Key Challenges
Organizational
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Recommendations
• Accept
– Organizational progress must occur
– Scientific progress must continue in parallel
– Modeling is its own ‘science’
• Focus on
– the modelers, not the tools
– energizing the science community
• do not try to change the scientific culture
• organize the use of the Gulf of Maine as a laboratory
– enabling scientific progress on practical problems
– Circulation Modeling as initial baseline
• Invent
– no new organizations
– one new task: “Gulf of Maine Modeling Roundtable”
– Insist on its ‘standing’ in science and regulatory communities
• Do not distort the University Mission - Announce a new one
• Expect to Pay and Get
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Interagency Agreement• Establish a GoM Modeling Roundtable within a standing organization • Service Populations: Science, Engineering, Management
• Spread the cost among agencies
• Govenance– full time staff– board of overseers– regular users’ group
• ‘Outreach’ workshops on model products and strategies
• Focused publications on Gulf of Maine
• Archive– software– data– simulation results– report series– publication series
• Insist on PI participation as precondition to participation in program
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How to Recognize Success?• Honor thy precursors
• Broad Participation
• Data Standards
• Accumulation of– Data– Software– Reports– Papers
• Progress is enabled
• People are enabled
People are your Investment