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Use of Envisat RA2 sea level observations in the Bluelink ocean modelling system David Griffin, Peter Oke and Madeleine Cahill. CSIRO Marine and Atmospheric

Use of Envisat RA2 sea level observations in the Bluelink ocean modelling system

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Use of Envisat RA2 sea level observations in the Bluelink ocean modelling system. David Griffin, Peter Oke and Madeleine Cahill. CSIRO Marine and Atmospheric. What is Bluelink?. - PowerPoint PPT Presentation

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Page 1: Use of Envisat RA2 sea level observations in the Bluelink ocean  modelling system

Use of Envisat RA2 sea level observations in the Bluelink ocean modelling system

David Griffin, Peter Oke and Madeleine Cahill. CSIRO Marine and Atmospheric

Page 2: Use of Envisat RA2 sea level observations in the Bluelink ocean  modelling system

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What is Bluelink?

• Goal: An ocean forecasting system to meet the needs of the entire marine sector for timely and detailed information on the physical state of the ocean

• sub-systems:• Assembly and processing of observations• Global ocean model • Limited-area model• Relocatable model• Littoral-zone model• Product delivery

• A partnership of three Australian Government Agencies: Royal Australian Navy, Bureau of Meteorology and CSIRO.

• (cf MyOcean)• A sustained effort: 2002-2006, 2006-2010, 2010-2013. ~$5M/yr

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The Bluelink global ocean model

• OFAM1: An implementation of MOM4p1, with 0.1ºx0.1º resolution in Australasia, grading to 2ºx2º far away, eg Norway.

• Is the basis of Australia’s national operational ocean forecasting system implemented at the Bureau of Meteorology

• Assimilates altimetry, SST, Argo, moorings etc using Multivariate Ensemble Optimal Interpolation

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Multivariate Ensemble Optimal Interpolation

1. run model for ~15 years → large database of realistic ocean states (u,v,t,s,eta), a.k.a ‘the Ensemble’

2. commence run of model with data assimilation: 3. every few days:

1. compute model difference from available observations (u,v,t,s,eta)

2. use the ensemble as a set of (multivariate) basis functions to project a sparse array of model-data misfits onto the full state space of the model

3. apply the corrections to the model in a way that minimises shocks4. integrate model forwards to the end of the forecast

→ Observed sea level (altimetry), SST (IR imagery) and T,S (Argo) correct all model variables in a realistic way

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New version of data assimilating model: smaller SLA residuals than previous version

R

old (loose fit)

new (tight fit)

MSLA

|model-obs|

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Despite tight fit, no obvious shocksNB sparsity of obs

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Around Australia in 4 years, comparing the model with un-assimilated drifters

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Median energy flux of ocean currents

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Finding WWII wreck AHS Centaur (in1400m, 50km offshore Brisbane)

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One day of good SST: model basically right

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More typical: fast laminar flow

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Sydney Morning Herald, 22 May 2010

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Conclusions

• Australians are intrigued by what they hear about the ocean, especially the East Australian and Leeuwin Current.

• Mariners across the spectrum from industry to recreation are all seeing opportunities to optimize their day-to-day operations by using ocean observations and forecasts

• In Australia we continue to use events like hunts for shipwrecks, or periods of extreme beach temperature anomalies, to educate the population about the nature of the ocean and how knowledge of the ocean is being increased by satellites like ENVISAT.

• The present constellation, however, of three nadir-sampling altimeters is only barely adequate for sampling the rapidly changing conditions over the continental margin, where most users’ interest is focused.

• As Johnny Johannessen said on Tuesday: we still have to tackle the sub-mesoscale.

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Thankyou

• Acknowledgement: Bluelink is a big project. We thank all the other team members for their contributions.

• We also thank the many people and agencies (ESA, EuMetSat, CNES, NASA, NOAA, Argo, Drifter program, ECMWF,…) responsible for the many data products we use.

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How rare is an eddy like that?