Developing Coastal Ocean Forecasting Systems and Their Applications

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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 Xiaochun.wang@jpl.nasa.gov 1

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 http://ourocean.jpl.nasa.gov/pws09, SCB 2

Coastal Ocean Forecasting Systems for US West Coast Prince William Sound, AK Monterey Bay, CA Southern California Bight, CA 3

Oceanic Data Mooring ADCP current Satellite Sea Surface Temperature (SST), Sea Surface Height (SSH) High-Frequency coastal radar Gliders Ship observation 4

Regional Ocean Modeling System (ROMS) Community model http://www.myroms.org http://roms.mpl.ird.fr 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

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

Online Real-time Distribution http://ourocean.jpl.nasa.gov/scb 7

Results of Data Assimilation 8

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

Prince William Sound, Alaska Strong tides Freshwater discharge from rivers, streams, glaciers Oil leaking (Mar. 1989) Complex coastline Field experiments in 2004, 2009 10

Prince William Sound, Alaska Three-Level Nested Model Grid Size Time Step Res. L0: 290*178*40 1200s 10km L1: 242*194*40 400s 3km L2: 170*146*40 133.3s 1km Hinchbrook Entrance Copper River 11

Include Freshwater in ROMS 61.2 61 60.8 60.6 60.4 Annual Mean Freshwater Discharge (cm/day) 50 45 40 35 30 Gaussian distribution Spatial Scale 20km Conserve freshwater Suitable for real-time system Inside PWS 3313 m^3/s 60.2 25 60 20 15 6000 5000 Mean 2004 DEM Year 1988 2006 59.8 59.6 211.5 212 212.5 213 213.5 214 214.5 215 10 5 Copper River Discharge (m 3 /s) 4000 3000 2000 1000 0 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

Features of tides (PWS Region) ROMS Tide (alaskatide1m) M2 61 o N 330 40 330 cm 20 322 320 328 60 o N 330 322 320 40 328 330 326 324 Length of semi-major axis 148 o W 147 o W 146 o W 145 o W 61 o N 100 100 100 110 120 130 140 150 160 SSH Amplitude and Phase 40 500 100 200 cm/s 20 100 100 60 o N 100 200 Largest amplitude: 155cm Largest semi-major axis: 99cm/s 40 200 200 148 o W 147 o W 146 o W 145 o W 0 10 20 30 40 50 60 70 80 90 100 13

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

Accuracy of Tidal Current 5m 50m Corr. Coef. 0.64 0.91 30m 75m 15

Seasonal Cycle (2004) Sea Surface Temp Comparison at 46060 Temp (C) 20 15 10 5 W/O Tide, W/O Freshwater W/O Tide, W/T Freshwater W/T Tide, W/T Freshwater Obs. 50 100 150 200 250 300 350 Julian Day in 2004 SST RMS: 1.63 C Corr Coef. 0.95 Salinity (PSU) 32 31 30 29 28 27 26 25 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 50 100 150 200 250 300 350 Julian Day in 2004 SSS RMS: 1.12psu Corr Coef. 0.85 W/O: without ; W/T: With 16

Change in Stratification Observation is from west side of PWS 17

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 42 42 36 36 30 30 60 o N 24.00 60 o N 24.00 18 W/O Tide, Freshwater 18 W/O Tide, W/T Freshwater 12 30 15 147 o W 45 30 12 30 15 147 o W 45 30 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 42 36 36 30 30 60 o N 24.00 60 o N 24.00 18 W/T Tide, W/T Freshwater 18 Obs. 12 30 15 147 o W 45 30 12 30 15 147 o W 45 30 18

Total Transport Across HE Transport into the Sound is reduced, negative during summer time. 19

Mixed Layer Depth Change Average within the Sound. 20

Schoch and Chao, Eos, AGU, Vol. 91, Num. 20, May 18, 21

July 18-21, 2009 Strong SE winds, strong north to northwestward flow in the central Sound

July 27 30, 2009 Moderate SE winds, weak central Sound eddy

July 31 Aug 3, 2009 Weak SW winds, central Sound eddy

Trajectory Comparison: SVP 10m Ensemble of Co-located ROMS Simulated Trajectories Using ensemble to quantify the uncertainty

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

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

http://solo-trec.jpl.nasa.gov/solo-trec 28

Multi-model coastal ocean ensemble forecast Weighting Method Equal Weighting Objective Weighting Guide glider to conduct observation in 24hr cycle http://ourocean.jpl.nasa.gov/ci

RMSE of Daily SST (Nov 1-15, 1 15, 2009) Four individual models ESPRESSO, NYHOPS MARCOOS, COAWSTF Equal Weighting Ensemble Objective Weighting Ensemble

RMSE of Hourly U (Nov. 1-15, 1 15, 2009)

RMSE of Hourly V (Nov. 1-15, 1 15, 2009)

Global Real-time 1km SST Based on multiple satellites, in situ observations, with 2D variation data analysis http://ourocean.jpl.nasa.gov/g1sst 33

Future Satellite Missions Aquarius (Sea surface salinity) Surface Water and Ocean Topography (~hundreds meter-1km, high resolution surface topography) 34

Delayed to Jan 2011 35

2013-2016 SWOT combines surface water hydrology with physical oceanography. 36

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

Thank You! Questions? xiaochun.wang@jpl.nasa.gov 38