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ROMS Real-Time Modeling, Data Assimilation and Forecasting during AOSN II

JPL. JPL. Other NASA . Other NASA . Non. Non. -. -. NASA . NASA . DAAC. DAAC. DAACs. DAACs. Data Centers. Data Centers. Data. Data. Ancillary. Ancillary. 3D Model. 3D Model. Retrieval &. Retrieval &. Data. Data. Assimilation. Assimilation. Processing. Processing.

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ROMS Real-Time Modeling, Data Assimilation and Forecasting during AOSN II

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  1. JPL JPL Other NASA Other NASA Non Non - - NASA NASA DAAC DAAC DAACs DAACs Data Centers Data Centers Data Data Ancillary Ancillary 3D Model 3D Model Retrieval & Retrieval & Data Data Assimilation Assimilation Processing Processing Research Research Application Application Server (POET) Server (POET) Server (GIS) Server (GIS) ROMS SciGIS SciGIS COVO Server Server Feedback Feedback ROMS Real-Time Modeling, Data Assimilation and Forecasting during AOSN II Yi Chao, Zhijin Li, Jei Choi, Peggy Li Jet Propulsion Laboratory California Institute of Technology & Jim McWilliams, Xavier Capet, Patrick Marchesiello, Kayo Ide University of California, Los Angeles ASAP Meeting, Feb. 2005

  2. Observation 2.5-km 5-km 10-km 15/5/1.5-km 20-km (Marchesiello et al., 2003) Regional Ocean Modeling System (ROMS): 3-Level On-Line Nesting

  3. 3-dimensional variational (3DVAR) method: J = 0.5 (x-xf)T B-1 (x-xf) + 0.5 (h x-y)T R-1 (h x-y) 12-hour forecast 3-day forecast xf 6-hour forecast Xa = xf + xf Xa Initial condition Time Aug.2 00Z Aug.1 18Z Aug.1 06Z Aug.1 12Z Aug.1 00Z ROMS Data Assimilation System y: observation x: model 6-hour assimilation cycle

  4. Sea Surface Temperature Data &ROMS Reanalysis Aircraft

  5. August 10, 2003 Observed SST ROMS-Simulated SST

  6. 03Z Aug.21, 2003 09Z 15Z 21Z

  7. Subsurface salinity minimal 23 Distance (km) AUV Remus ROMS Reanalysis (M. Moline) 15 Aug 16 Aug 17 Aug 18 Aug 0

  8. Ground-Truth ROMS Reanalysis against Independent Mooring Observations M1

  9. Ground-Truth ROMS Reanalysis against Independent Mooring Observations M2

  10. Near-Term (3-year) Challenges • Remote forcing from basin-scale climate (ENSO, PDO) • COAMPS (short- & long-wave) radiative fluxes • Tidal processes • Real-time interactive feedback via OSSE (Observing System Simulation/Sensitivity Experiment) or “On-Demand Modeling”

  11. How to provide large-scale B.C.? 2003 summer off the U.S. West coast is anomalously warm!

  12. 1989 2001 El Nino’s Impact on U.S. West Coast Circulation

  13. PDO- PDO+ Pacific Decadal Oscillation (PDO)’s Impact on California Coastal Circulation (Chao et al., GRL, 2001)

  14. 15/5/1.5-km Regional Ocean Modeling System: Nesting High-Resolution Regional Models in Coarse-Resolution Models One-Way Coupling

  15. SSH Simulating El Nino and La Nina with Pacific ROMS Temp Observations ROMS

  16. Simulated PDO: Sea Surface Temperature

  17. Net Incoming Short-Wave radiation • Reduction in the morning (diurnal cycle) • Reduction during the relaxation phase • COAMPS didn’t reproduce these features, mostly due to the lack of clouds (low-level), which can be approximated with (1-0.7nc)

  18. Net Outgoing Long-Wave Radiation Red: COAMPS Blue: Outgoing computed by blackbody (0.985T4) radiation MINUS the computed (0.38-0.05e0.5) incoming radiation in the absence of clouds Green: Blackbody outgoing MINUS mooring measured incoming long-wave radiation * Cloud correction (1-0.6nc2)

  19. Tidal Processes

  20. End-to-End System Engineering: Autonomous Real-Time Operations Integrated Ocean Observing and Prediction Systems

  21. OSSE Engine (On-Demand Modeling)

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