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Building Bluelink

Bluelink is a strategic partnership involving the Bureau of Meteorology, CSIRO, and the Royal Australian Navy, focused on improving ocean forecasting in Australia. This initiative encompasses several systems including the Ocean Forecasting Australia Model (OFAM), the Bluelink Ocean Data Assimilation System (BODAS), and the Bluelink ReAnalysis (BRAN). With a high-resolution regional analysis capability, it assimilates various ocean observation data to provide accurate forecasts, including sea-level anomalies and sea surface temperatures. Bluelink aims to enhance understanding of ocean dynamics and contribute significantly to marine resource management.

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Building Bluelink

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  1. Building Bluelink David Griffin, Peter Oke, Andreas Schiller et al. March 2007 CSIRO Marine and Atmospheric Research

  2. Introduction • Bluelink: a partnership between the • Bureau of Meteorology, CSIRO and • the Royal Australian Navy

  3. Introduction • Bluelink: a partnership between the • Bureau of Meteorology, CSIRO and • the Royal Australian Navy • Talk Outline • Ocean Forecasting Australia Model, OFAM • Bluelink Ocean Data Assimilation System, BODAS • Bluelink ReANalysis, BRAN • Bluelink High-Resolution Regional Analysis HRRA

  4. What users want:(a week in advance?)

  5. Where they want it:

  6. Minimum resolution: ~100km ~10km resolution Ocean Forecasting Australia Model, OFAM • Global configuration of MOM4 • Eddy-resolving around Australia • 10 m vertical resolution to 200 m, then coarser • Surface fluxes from ECMWF (for reanalyses) … every 10th grid point shown

  7. Bluelink Ocean Data Assimilation System, BODAS • Ensemble OI … sequential assimilation technique

  8. Bluelink Ocean Data Assimilation System, BODAS • Ensemble OI … sequential assimilation technique • Assimilates observations of SLA, SST, in situ T and S

  9. Bluelink Ocean Data Assimilation System, BODAS • Ensemble OI … sequential assimilation technique • Assimilates observations of SLA, SST, in situ T and S • To constrain the model to match reality, then make a forecast

  10. Bluelink Ocean Data Assimilation System, BODAS • Multivariate assimilation system: • sea level obs correct h,T,S,U,V Single point assimilation …

  11. Bluelink Ocean Data Assimilation System, BODAS • The spatial structure of the covariances are determined by the statistics of the free-running model. Influence of sealevel obs at x

  12. Ensemble OI: vertical projection of surface observations- similar to multiple linear regression Plan view of sea-level increments Cross-section of temperature increments

  13. -> need both SST and SLA. Plan view of sea-level increments Cross-section of temperature bkgnd (grey) & analysis (black-colour)

  14. BRAN1.0  BRAN1.5  BRAN2.0

  15. BRAN1.0  BRAN1.5  BRAN2.0

  16. Free-running model:

  17. HRRA - Gridded altimetry and SST,statistically projected to depth:

  18. BRAN1.0:

  19. BRAN1.5smoother, more realistic, no warm bias

  20. BRAN1.5 cf HRRA – 2005

  21. Conclusion • BRAN1.0  plenty of lessons learnt • BRAN1.5 realistically reproduces the 3-d time-varying mesoscale ocean circulation around Australia • Major threat to real-time equivalent of BRAN: • Less data available for assimilation

  22. Thank you

  23. An application: dispersal of the larvaeof Southern Rock Lobster

  24. Bluelink ReANalysis, BRAN • BRAN1.5: • 1/2003 – 6/2006 • Forced with ECMWF forecast fluxes • Assimilates observations once per week • Assimilates SLA from Jason, Envisat and GFO (T/P with-held) • Assimilates AMSRE SST • Assimilates T and S from Argo and ENACT database

  25. BRAN1.5 vs TAO ADCP zonal currents 165E 170W 147E 140W 110W

  26. ANALYSIS 0-DAY FORECAST 7-DAY FORECAST BRAN1.5 vs CLS 1/3o GSLA

  27. Comparisons with with-held T/P altimetry (top) and AMSRE (bottom) Comparisons between BRAN1.5 and with-held T/P altimetry:  RMS error of 8-10 cm  anomaly correlations of 0.6 Comparisons between BRAN1.5 and AMSRE (every 7th day is assimilated):  RMS error of 0.7o  anomaly correlations of 0.7

  28. Observing System Experiments Experiment design • With-hold each component of the observing system • 6-month integration (1st half of 2003) • compare to with-held observations • treat BRAN1.5, with all observations assimilated, as the “truth”

  29. Assimilation of Argo and SST reduces the forecast error of SLA by ~50% compared to the assimilation of altimetry Assimilation of Altimetry and Argo only reduces the forecast error of SST by a small amount Observing System Experiments 2003

  30. Observing System Experiments Metric • Depth average (0-1000 m) of the RMS “error” in potential temperature For the 2003 - GOOS: each component of the GOOS has a unique and important contribution to the forecast skill of upper ocean temperature each component has comparable impact on the forecast skill of the upper ocean temperature

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