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Aquarius Workshop, Woods Hole, MA, USA 11-12 May 2006 &

Aquarius Workshop, Woods Hole, MA, USA 11-12 May 2006 &. SMOS Workshop, Lyngby, Denmark 15-18 May 2006. Observing regional salinity signals of major rivers: Exploring Aquarius and SMOS resolution limits.

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Aquarius Workshop, Woods Hole, MA, USA 11-12 May 2006 &

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  1. Aquarius Workshop, Woods Hole, MA, USA 11-12 May 2006 & SMOS Workshop, Lyngby, Denmark 15-18 May 2006 Observing regional salinity signals of major rivers: Exploring Aquarius and SMOS resolution limits Derek Burrage, Joel Wesson, Jerry Miller, William Teague (NRL, USA), Carlos Martinez (UR, Uruguay) and Malcolm Heron (JCU, Australia).

  2. Observing regional salinity signals of major rivers • Objectives and Motivation • Airborne Observations • Resolution Scales • Land Correction • Open Issues

  3. NRL ESA SMOS project AO-3229 SMOS Salinity Retrieval, Processing and Performance in Coastal Regions and Marginal Seas Objectives • Develop enhanced SSS products for the marginal seas and coastal transition zone. • Validate enhanced SSS products by under-flying SMOS with NRL’s STARRS radiometer system. • Assess and demonstrate benefits of enhanced products on coastal ocean data assimilation systems.

  4. Observing regional salinity signals of major rivers: Exploring Aquarius and SMOS resolution limits Simulated Global Coverage of SMOS 300 km Standard Product ESA SMOS NASA Aquarius NRL NCOM SSS Simulation ¼ Deg Grid Yangtze R. Miss. R. Amazon & Orinoco R. Rio de la Plata Burdekin R.

  5. Salinity-driven Advection in Littoral Deep Areas (SALIDA) J. Wesson, D. Burrage, J. Miller STARRS Salinity, Temperature and Roughness Remote Scanner Piper Navajo STARRS Ocean (Ts, S) Flight Direction Scan 6 km Pixel ~1km System of 6 beam L-band, 6 channel C- and 2 channel IR-band radiometers for measuring SSS, SSR and SST

  6. Sea Surface Salinity (SSS) in Marginal Seas 15 37 SSS psu Can we map it from space at regional scales? Intra-Americas Sea (IAS)/ Gulf of Mexico (GoM) 10 deg Mississippi R. GoM Orinoco R. IAS GDEM3 (MODAS) SSS Climatology Caribbean • Well studied strategically and ecologically important area • Subject to Strong Seasonal Discharge Variations • Various External Forcings – eg. River Discharge, Wind, Tide • Bounded by Complex Topographies

  7. Nominal SMOS, Aquarius + STARRS L-band Radiometer Specifications *After adjusting for dwell time assuming Gaussian error distribution # Assuming Salinity Sensitivity of 2 psu / K

  8. SMOS Std vs Enhanced Regional Product 15 37 37 SSS psu 15 SSS psu Coastal Data Gap 300 km 300 km SMOS Std 50 km Coast Enh. Intra-Americas Sea

  9. Observing Gulf of Mexico SSS in near Real-time 7 day period (~1/8 part of full cycle) ESOV 59 day repeat orbit:

  10. GoM SMOS Coverage – Wide Swath 2 day period (wide swath => full coverage) ESOV 59 day repeat orbit:

  11. SSS Product Specifications STARRS C. PRODUCTS: Resolution Aq/SMOS Std. A. Regional Enh. B. PARAMETERS: • Spatial Resolution 200-300 km 50-100 km 1 km • Temporal Resolution 30 days 3-7 days 0.5 days • Domain Global Regional Local • Coastal Data Gap 300-400 km 50 km 1 km • Salinity Error (psu) 0.1 0.5-2.0* 1.0 * Compensated by higher signal to noise ratios near the coast

  12. STARRS Mississippi River Plume Salinity Mississippi River Plume Characteristics Largest US River Discharge 14000 m3s-1 Salinity Contrast ~ 30 psu Strong Seasonal Discharge Cycle Offshore extent ~ 100 km @ 30 psu Alongshelf Influence ~ 1100 km 3-4 May 2004 7 May 2004 8 May 2004

  13. SEPS South American Target SSS (SMOS End-End Performance Simulator) Coarse Array 1 x 1 deg, Fine Array ½ x ½ deg Amazon River Rio de la Plata plume NCOM SSS field superimposed on the SEPS SSS Target Array. Rio de la Plata Rio de la Plata Plume Brazil Current/ Malvinas Current Confluence Rio de la Plata

  14. South America SEPS Target Run Amr01a,b Orinoco R. Amazon R. Characteristics of the Amazon River Plume Largest World River Discharge 170000 m3s-1 (Orinoco River is 4th. Largest with 31000 m3s-1) Salinity Contrast ~ 10 psu Strong Seasonal Discharge Cycle Offshore extent ~ 200 km @ 34 psu Alongshelf Influence ~ 3500 km

  15. Simulated SMOS single-snapshot view of Amazon River Delta Original Measured Difference Th Tv Amazon SEPS3.1 TB Run amr01b

  16. South America SEPS Target Run Rdp01a,b Characteristics of the Rio de la Plata Plume Large River Discharge ~ 25,000 m3s-1 Salinity Contrast ~ 10 psu Weakly Seasonal Discharge Cycle Strong influence of Earth Rotation and Winds Offshore extent ~ 200 km @ 33 psu Alongshelf Influence ~ 1200 km Rio de la Plata

  17. STARRS Plata Plume Winter 2003 Observations Florianopolis Rio Grande Rio de la Plata Plata Plume D=1100 km dS=10 psu Mar del Plata Patos Lagoon Outflow Plume (STARRS) Casa 212

  18. Original Measured Measured-Original Coarse Array Rio de la Plata Fine Array Rio de la Plata Rio de la Plata SEPS 3.1Target TB Rdp01b Simulation and Analysis of a Single Snapshot

  19. 17.0 200 m 17.5 Tully River 18.0 200 m 18.5 Latitude [°S] Herbert River Great Barrier Reef 19.0 Towns- ville 19.5 Burdekin River 20.0 5 10 0 15 20 25 148 146 147 Longitude [°E] Herbert- Burdekin River System Characteristics of the Burdekin Plume Mean/Max Annual Discharge ~ 322/~3,000 m3s-1 Peaks to 25000 m3s-1, Salinity Contrast ~ 10 psu Event-based Tropical Monsoon Flood Cycle Moderate Rotation Tide and Wind Influence Offshore extent ~ 25/50 km @ 30/34 psu Alongshelf Influence ~ 600 km Confined within Great Barrier Reef Lagoon SLFMR SSS Map 24 Mar., 2000

  20. Ocean Feature Salinity Resolution Resolution: A150 km / 0.1 psu B300 km / 0.2 psu C50 km / 1.0 psu

  21. Idealized Aquarius Beam #2 Coastal Crossing FOV #3 300K FOV #1 Land Main Beams Tb Land Coast FOV #2 Sea Tb Sea 100K Side Lobe FOV #2

  22. Idealized Aquarius Beam 2 Antenna Pattern 30 dB Peak Gain Mixed Pixel Target Temperature Idealized Antenna Gain Pattern Tb [K] Land 300 Gain [dB] Coast Sky Sea Sky 27 100 -13 3 -180 -150 -50 -3 3 50 150 180 Azimuth [deg] – not to scale E-plane (solid line) and H-plane cuts for the co-pol pattern of the middle beam at vertical polarization. Source: “Aquarius Antenna Patterns” David le Vine (personal communication)

  23. Idealized Aquarius Beam Crossing Coast Errors after Correcting for Land in Field of View Corrected Uncorrected Land Sea

  24. SMOS Sampling Pattern NIR Reference Radiometer FOV Land FOV Aliases Alias-free Field of View (AF-FOV) Pixels (~50 km) AF-FOV (~300 km) Open Sea FOV

  25. STARRS Mixed-Pixel Survey NIR Reference Radiometer FOV Land STARRS Flight Lines ~50 km Coast MIRAS Pixels Mixed Pixel Alias-free Field of View (AF-FOV) Sea

  26. Optimizing resolution in the coastal transition zone Land Alias and Mixed Pixel Corrections • Account for Land Temperatures entering FOV • Use measured SMOS overland Tb’s • for current or prior overpass? • Alternatively, use land Tb’s derived from models or • Thermal IR measurements and IR emissivity? • Extrapolate these toward coast. • Use detailed coastal outline for region of interest • SSS Freshwater signal typically increases toward coast => Can trade-off radiometric resolution for better spatial resolution in the coastal transition zone

  27. Open Issues for SMOS/Aq. Science Team What are the practical limits and options to approach the coast? How should OS Mixed pixel processing be performed? How can we optimize spatial and radiometric resolution near coasts? Do we need a ‘coastal transition zone ’ (L3) data product? What possible modifications to L2 OS would facilitate this? Are new data products or algorithms/modules/apodization required for inclusion in the SMOS and Aquarius processing chain? What mission and auxiliary data are needed for this chain? How can we best validate coastal transition products?

  28. SMOS Salinity Retrieval, Processing and Performance in Coastal Regions and Marginal Seas • Regional/Coastal Data Processing: • SMOS Level 1c • SMOS Level 2 OS Ocean Product • (with 200-300 km land overlap) • … and Depending upon Mixed Pixel Algorithms: • SMOS Level 1b • SMOS Level 2 (Soil Moisture Product) Product Requirements

  29. Open Issues for SMOS/Aq. Science Team What are the practical limits and options to approach the coast? How should OS Mixed pixel processing be performed? How can we optimize spatial and radiometric resolution near coasts? Do we need a ‘coastal transition zone ’ (L3) data product? What possible modifications to L2 OS would facilitate this? Are new data products or algorithms/modules/apodization required for inclusion in the SMOS and Aquarius processing chain? What mission and auxiliary data are needed for this chain? How can we best validate coastal transition products?

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