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Modeling Puget Sound Circulation Mitsuhiro Kawase School of Oceanography PRISM Retreat, 2002.

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Presentation on theme: "Modeling Puget Sound Circulation Mitsuhiro Kawase School of Oceanography PRISM Retreat, 2002."— Presentation transcript:

1 Modeling Puget Sound Circulation Mitsuhiro Kawase School of Oceanography PRISM Retreat, 2002

2 National Ocean Partnership Program A Partnership for Modeling the Marine Environment of Puget Sound, Washington ONR Award N000140210503 Mitsuhiro Kawase, Allan Devol, Miles Logsdon and Mark Warner, School of Oceanography William Winn, College of Education University of Washington, Seattle, WA FY 02 Funding: $390,924 Objectives: Develop, maintain and operate a system of simulation models of Puget Sound’s circulation and ecosystem, a data management system for oceanographic data and model results, and an effective delivery interface for the model results and observational data for research, education and policy formulation. Develop fundamental understanding of the Sound’s working, and address questions raised by the regional community concerning management of the Sound and its resources. Partners: Department of Natural Resources, King County, Washington (R. Shuman, B. Nairn) Department of Ecology, State of Washington (J. Newton) Puget Sound Naval Shipyard (S. Swanson, R. Johnston) Ocean Inquiry Project (F. Stahr, C. Sarason)

3 Puget Sound Circulation Model Support from National Oceanographic Partnership Program (NOPP), FY 2002 - 2008 In collaboration with King County DNR Based on Princeton Ocean Model (POM) code 360x540m resolution,14 vertical levels Predicted variables: Velocity, temperature, salinity, turbulent kinetic energy, turbulent master length Model domain and bathymetry

4 Puget Sound Circulation Model (Cont’d) Hindcasting Year 2000 (with Bruce Nairn, KC-DNR): –Accurate time-average exchange circulation in the Main Basin –Accurate time-average recirculation around Vashon Island (northward current 30cm/s in Colvos Passage) –Excessive transport into the deep Whidbey Basin (~20%) - dynamics of the Skagit Delta, Deception Pass transport?

5 Puget Sound Circulation Model Tasks FY 2002 Complete coupling with the MM5 weather prediction model Routine hindcasting of Puget Sound circulation Dynamics of Carr Inlet Generate Lagrangian trajectories for study of planktonic genetic diversity (diatoms, geoducks)

6 Variability at Seasonal/Interannual Time Scales Historical data analysis Simple model of Puget Sound circulation for quantitative sensitivity study

7 Schematic of exchange circulation in a fjord (cross-section) Tidal Mixing Entrance Sill Main Basin Marine influence (Salty, Dense) Sharp Pycnocline River Input (Fresh, Light) Outflow Inflow/Reflux

8 Terrestrial Influence = River Runoff Maximum in Winter/Spring Marine Influence = Coastal Upwelling Maximum in Spring/Summer

9 T/S Seasonal Cycle in Puget Sound Main Basin (1992) “Light Phase” “Dense Phase”

10 A Box Model of Puget Sound Circulation Amanda Babson, M.S. Thesis Twelve boxes to represent Puget Sound (six regions, upper and lower layer) Predicts salinity in each box, advective fluxes between boxes and mixing between upper and lower boxes Forced by river discharge and external salinity in deep Admiralty Inlet Conservation of mass and salt, simple parameterization of momentum and vorticity balance, and stratification-dependent vertical mixing

11 Salinity in a Box Model of Puget Sound Circulation (Babson, 2002)

12 Seasonal Transport in the Box Model (positive = out) Outflow at Surface Inflow at Depth JanAprJulOct Volume Transport (x10 9 cubic meters per day) 0 1

13 Potential Temperature 1999 June December Admiralty Inlet Sills SJDF Dalco Passage Main Basin Black line: Last contiguous density surface across Admiralty Inlet 10 12 8 10 12 8

14 Salinity Anomaly, Puget Sound Main Basin at 100m

15 R=0.6 (36% of variance)

16 Salinity and Potential Density in Central Puget Sound, 1990 - 1998 (Blue: 100m Red: 200m) 1997: Year of no density intrusion

17 Salinity 1992-1999 in the Box Model

18 Temperature Anomaly, Puget Sound Main Basin at 100m

19 R=0.57 (33% of variance)

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