Gulf of Maine Circulation Modeling: Prospects for Skill 6 July 2005

1. Gulf of Maine Circulation Modeling: Prospects for Skill6 July 2005 Daniel R. LynchDartmouth CollegeHanover NH

2. Points of Departure • Science • People • Data • Problems

3. Science • Well-Established: • Physical Quantities • Equations • Algorithms for solutions • Distributed across ‘Academe’

5. People • At least 3 different communities • Theory • Observation • Simulation “the third science” • Algorithms • Systems • Non-Local • Incentives: Advancement of Learning

6. 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

7. Problems • “Local” • Not alligned with political boundaries • Distributed across agencies • Regulatory context

8. 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

9. Regional Progress • 1993 RARGOM Workshop <------------- • RMRP • MWRA Mass. Bays • GLOBEC • EcoHAB • Sea Grant (x4) • GoMOOS • Multiple NOAA programs • Canadian Companions

10. Data and State Estimation

11. Time of Occurrence (Ocean) State Estimation Future (Now) Past Time of Availability (Information)

12. Time of Occurrence (Ocean) Forecast Nowcast Hindcast Time of Availability (Information)

13. Time of Occurrence (Ocean) Forecast Nowcast Hindcast All Data Time of Availability (Information)

14. Time of Occurrence (Ocean) Forecast Nowcast Hindcast All Data Time of Availability (Information)

15. Time of Occurrence (Ocean) Forecast Model ‘Data Product’ Nowcast All Data Hindcast Time of Availability (Information)

16. Time of Occurrence (Ocean) Forecast Nowcast Hindcast Data Used Bell Time of Availability (Information)

17. Time of Occurrence (Ocean) Forecast Nowcast Hindcast Data Used Bell Publication Time of Availability (Information)

18. 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 DX) The Well-Posed Problem(The Mathematical Standard)

19. 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 DX) Actual The Well-Posed Problem(The Mathematical Standard) Nonnecessary Insufficient DX is finite

20. 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 DX) Actual The Well-Posed Problem(The Mathematical Standard) Nonnecessary Insufficient DX is finite There is never a well-posed problem in nature

21. Poorly Posed Problems • 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

22. What is Truth?

23. What is Truth? ed em Data Model Misfit d

24. What is Truth? ep ed em Prediction Data Model Misfit d Truth real but unknowable Errors unknowable Prediction a credible blend: Data + Model Blend: Invokes statistics of ed , em Prediction Error: blend of statistics of ed , em, d

25. What is Truth? ep ed em Prediction Data Model Misfit d Skill: Misfits Small, Noisy Unknown Inputs Small, Smooth ep : grows with time Truth real but unknowable Errors unknowable Prediction a credible blend: Data + Model Blend: Invokes statistics of ed , emd

26. 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

27. A Data-Assimilative System

28. Resolution

29. The difference between high-resolution and low-resolution forward simulations

30. Inverse Error with Low Resolution-- DA cannot make up for Inadequate Resolution --

31. Estuarine Resolution

32. Boundary deduced from Interior Data

33. Data Assimilative Hindcast

34. Mean Separation Rate: 1.78 km/day

35. The 2005 Prior

36. The 2005 Hindcast

37. The 2005 Hindcast • Data-Assimilative • Real Time • At-Sea • Limited-area • Hindcast of complete cruise • May 9- 18

38. The 2005 Hindcast

39. The 2005 Hindcast

40. The 2005 Hindcast

41. The 2005 Hindcast

42. The 2005 Hindcast

43. Who Painted the Bays Red?

44. Who Painted the Bays Red?

45. Frontal Dispersion - Forecast

46. Frontal Dispersion - Forecast

47. Frontal Dispersion - Hindcast

48. Frontal Dispersion - Hindcast

49. Key Challenges Organizational

50. 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