1. Introduction Objective: Develop regional ocean forecasting capability AU$15M co-investment for Phase 1 Partners: Bureau, CSIRO, Navy Launched 2003, Phase1 due for completion in early 2007 An ocean forecasting system for Australia, providing reliable and accurate ocean information for the national public good, enhancing the sustainability and management of our marine environment and ensuring safe and effective operations at sea Phase 2 has been negotiated, near AU$17M further co-investment http://www.cmar.csiro.au/bluelink

2. Priorities 1. Core operational ocean forecast model (OFAM)  Maintain world-class core system 2. New Regional/Coastal Forecast System  Synergy with regional mesoLAPS, e.g. SE Aust  Applications drawn to GBR and NWS Regional System: coupled ocean-atmosphere (3-5km resolution)  Improved fine-scale nesting, e.g. for ROAM 3. Enhanced relocatable ocean model  ROAM ↔ Navy  Other marine, coastal applications

3. Priorities 4. Coupling  Coupled ocean-atmosphere, e.g. TCs  Ecosystem/biogeochemistry  “new” weather prediction 5. Observing system  Infrastructure for AusIOOS, initial contributions from IMOS  New data: satellites, CODAR, salinity, …

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

5. Bluelink Ocean Data Assimilation System, BODAS Assimilates observations of SLA, SST, in situ T and S Model SLA + SST in situ T + S Observations Analysis SOOP XBT

6. Observing System Experiments How important are different components of the Global Ocean Observing System (GOOS) for ocean reanalysis? Experiment design  With-hold each component of the observing system  6-month integrations (1 st half of 2003 and 2006)  compare to with-held observations  treat BRAN1.5, with all observations assimilated, as the “truth”

7. Observing System Experiments Assimilation of Argo/XBT 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 2003

8. Observing System Experiments: Impact on upper ocean temperature (0-1000 m) Depth average (0-1000 m) of the temperature error introduced by with-holding:  all obs (top)  SST  Altimetry  Argo/XBT (bottom) …in 2003 (left) and 2006 (right); and the zonal average (left panels) in the Australian region.  All components offer a unique and essential contribution to the ocean reanalysis. Importance of Argo/XBT Importance of SST Importance of ALTIMETRY