Developing Coastal Ocean Forecasting Systems and Their Applications
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1 Developing Coastal Ocean Forecasting Systems and Their Applications Xiaochun Wang a,b LASG/IAP, CAS, July 23, 2010 Contributions from: JPL Yi Chao, John Farrara, Peggy Li, Zhijin Li, Quoc Vu, Hongchun Zhang UCLA Francois Colas, Xin Jin, Changming Dong, A. Shchepetkin, James McWillams a: Jet Propulsion Lab/California Institute of Technology b: Joint Institute for Regional Earth System Science and Engineering, UCLA 1
2 Coastal Ocean Forecasting System Data Collection (In situ, and satellites) Atmospheric Forcing Heat flux, Wind stress, E-P, E Freshwater discharge Data Assimilation 3D variational method Nesting (Boundary condition) Tides Forecasting 48hr, Distributing online SCB 2
3 Coastal Ocean Forecasting Systems for US West Coast Prince William Sound, AK Monterey Bay, CA Southern California Bight, CA 3
4 Oceanic Data Mooring ADCP current Satellite Sea Surface Temperature (SST), Sea Surface Height (SSH) High-Frequency coastal radar Gliders Ship observation 4
5 Regional Ocean Modeling System (ROMS) Community model Features: S-coordinate S in vertical direction, curvilinear grid in horizontal direction, free-surface, one-way nested, open boundary condition, mixing schemes, user tools to configure a model and diagnostic analysis, Shchepetkin and McWilliams 2005, Song and Haidvogel 1994, Marchesiello et al., 2001, Blayo and Debreu, 1999,. 5
6 Data Assimilation and Forecasting Cycle J 3-dimensional variational (3DVAR) method: = 1 f T 1 f T 1 ( x x 2 ) B ( x x ) + 1 ( Hx 2 y) R ( Hx y) 12-hour forecast y: observation x: model 48-hr forecast x a = x f + δx f x f 6-hour forecast Initial condition x a 6-hour assimilation cycle Time Aug.1 14hr Aug.1 20hr Aug.2 02hr Aug.2 08hr Aug.2 14hr 6
7 Online Real-time Distribution 7
8 Results of Data Assimilation 8
9 Boundary Conditions Open Boundary Condition SSH: Chapman condition Tangential Barotropic Velocity: Oblique radiation Normal Barotropic Velocity: Flather condition Closed Boundary Condition SSH: Zero gradient Tangential Velocity: Free slip Normal Velocity: Zero Tide SSH and transport are from the barotropic tide data assimilation system of Oregon State University (TPXO.6 Egbert et. al, 1994, 2002). Eight major tidal constituents (M2, S2, N2, K2, K1, O1, P1, Q1) 9
10 Prince William Sound, Alaska Strong tides Freshwater discharge from rivers, streams, glaciers Oil leaking (Mar. 1989) Complex coastline Field experiments in 2004,
11 Prince William Sound, Alaska Three-Level Nested Model Grid Size Time Step Res. L0: 290*178* s 10km L1: 242*194*40 400s 3km L2: 170*146* s 1km Hinchbrook Entrance Copper River 11
12 Include Freshwater in ROMS Annual Mean Freshwater Discharge (cm/day) Gaussian distribution Spatial Scale 20km Conserve freshwater Suitable for real-time system Inside PWS 3313 m^3/s Mean 2004 DEM Year Copper River Discharge (m 3 /s) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec A scheme was designed to include freshwater discharge from either line sources or rivers in ROMS. Hydrological Digital Elevation Model 12
13 Features of tides (PWS Region) ROMS Tide (alaskatide1m) M2 61 o N cm o N Length of semi-major axis 148 o W 147 o W 146 o W 145 o W 61 o N SSH Amplitude and Phase cm/s o N Largest amplitude: 155cm Largest semi-major axis: 99cm/s o W 147 o W 146 o W 145 o W
14 Accuracy of Tides Compare with multi-satellite altimetry (Open Ocean) Comparison with tide gauges (Coastal Ocean) Open Ocean: Total Discrepancy of 5.3cm, or 5.6% of SSH variability Coastal Ocean: Total Discrepancy of 9.6cm, or 8.2% of SSH variability 14
15 Accuracy of Tidal Current 5m 50m Corr. Coef m 75m 15
16 Seasonal Cycle (2004) Sea Surface Temp Comparison at Temp (C) W/O Tide, W/O Freshwater W/O Tide, W/T Freshwater W/T Tide, W/T Freshwater Obs Julian Day in 2004 SST RMS: 1.63 C Corr Coef Salinity (PSU) W/O Tide, W/O Freshwater W/O Tide, W/T Freshwater W/T Tide, W/T Freshwater Obs. Sea Surface Salinity Comparison at hee Julian Day in 2004 SSS RMS: 1.12psu Corr Coef W/O: without ; W/T: With 16
17 Change in Stratification Observation is from west side of PWS 17
18 Influence of Tides and Freshwater a) W/O Tide, W/O Freshwater, ROMS Current,2004 JAS 0.5m/s b) W/O Tide, W/T Freshwater, ROMS Current,2004 JAS 0.5m/s o N o N W/O Tide, Freshwater 18 W/O Tide, W/T Freshwater o W o W c) W/T Tide, W/T Freshwater, ROMS Current,2004 JAS 0.5m/s 42 d) High frequency Radar Observation, 2004 JAS 0.5m/s o N o N W/T Tide, W/T Freshwater 18 Obs o W o W
19 Total Transport Across HE Transport into the Sound is reduced, negative during summer time. 19
20 Mixed Layer Depth Change Average within the Sound. 20
21 Schoch and Chao, Eos, AGU, Vol. 91, Num. 20, May 18, 21
22 July 18-21, 2009 Strong SE winds, strong north to northwestward flow in the central Sound
23 July 27 30, 2009 Moderate SE winds, weak central Sound eddy
24 July 31 Aug 3, 2009 Weak SW winds, central Sound eddy
25 Trajectory Comparison: SVP 10m Ensemble of Co-located ROMS Simulated Trajectories Using ensemble to quantify the uncertainty
26 SVP 10m Drifter #85936 from July 20, 23 GMT through July 22, 00 GMT Cluster of ROMS simulated trajectories starting from the release location of SVP Drifter #85936 for July 20, 23 GMT through July 22, 00 GMT
27 Sounding Oceanographic Lagrangrian Observer (SOLO) Thermal RECharging (TREC) SOLO-TREC Using temperature difference in ocean surface and in depth to generate electricity Tested around Hawaii Islands since Nov. 2009, 3-4 dives/day 27
28 28
29 Multi-model coastal ocean ensemble forecast Weighting Method Equal Weighting Objective Weighting Guide glider to conduct observation in 24hr cycle
30 RMSE of Daily SST (Nov 1-15, 1 15, 2009) Four individual models ESPRESSO, NYHOPS MARCOOS, COAWSTF Equal Weighting Ensemble Objective Weighting Ensemble
31 RMSE of Hourly U (Nov. 1-15, 1 15, 2009)
32 RMSE of Hourly V (Nov. 1-15, 1 15, 2009)
33 Global Real-time 1km SST Based on multiple satellites, in situ observations, with 2D variation data analysis 33
34 Future Satellite Missions Aquarius (Sea surface salinity) Surface Water and Ocean Topography (~hundreds meter-1km, high resolution surface topography) 34
35 Delayed to Jan
36 SWOT combines surface water hydrology with physical oceanography. 36
37 1. The Problem In-situ cannot measure this 3. Measurements Required maps of h, which give maps of dh/dt and dh/dx Perspective view of dh/dt Ohio R. from SRTM dh/dx h Floods are the number one hazard 2. The Question What is the spatial and temporal variability of freshwater stored in the world s terrestrial water bodies? bprc.osu.edu/water 4. The Solution KaRIN: Ka-band Radar Interferometer. SRTM, WSOA heritage. Maps of h globally and ~weekly. 37
38 Thank You! Questions? 38
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