Open ocean forecasting: FOAM – Forecasting Ocean Assimilation Model [email protected]
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www.ncof.gov.u k Developments within FOAM Adrian Hines, Dave Storkey, Rosa Barciela, John Stark, Matt Martin IGST, 16 Nov 2005
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Developments within FOAM Adrian Hines, Dave Storkey, Rosa Barciela, John Stark, Matt Martin IGST, 16 Nov 2005. Present systems & recent developments. Open ocean forecasting: FOAM – Forecasting Ocean Assimilation Model [email protected]. Overview of the FOAM system. - PowerPoint PPT Presentation
Transcript of Open ocean forecasting: FOAM – Forecasting Ocean Assimilation Model [email protected]
www.ncof.gov.uk
Developments within FOAM Adrian Hines, Dave Storkey, Rosa Barciela, John Stark, Matt Martin IGST, 16 Nov 2005
www.ncof.gov.uk
Open ocean forecasting:FOAM – Forecasting Ocean Assimilation Model
Present systems & recent developments
www.ncof.gov.uk
Overview of the FOAM system
• Operational real-time deep-ocean forecasting system• Daily analyses and forecasts out to 5 days• Hindcast capability (back to 1997)• Relocatable high resolution nested model capability
FOAM = Forecasting Ocean Assimilation Model
Real-time data
Obs QC & processing Analysis Forecast to T+120
NWP 6 hourly fluxes
Automatic verification
T+24 forecast used in QC
Product dissemination
Operational system
Hindcast system
www.ncof.gov.uk
Model & Operational system
• Ocean model– Z-level, primitive equation model– Same code as used in Hadley Centre climate models– Rigid lid– Kraus-Turner + K-profile vertical mixing– Simple advective sea-ice model – Flow Relaxation Scheme at open boundaries for nested models
• Operational system– Three suites of nested models:
• QO00: Global, North Atlantic and Mediterranean, starts at 05:00Z• QN00: Indian Ocean, starts at 00:30Z• QV00: Antarctic, starts at 01:45Z
– Run daily on 7 NEC SX6 processors– Responsibility of operational teams; 7-day operator support– Boundary data provided to operational Shelf Seas model– Automated verification system running at T+7 days
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Operational configurations
12km (1/9º) Mediterranean
36km (1/3º) North Atlantic and Arctic
12km (1/9º) North Atlantic
1º Global
36km (1/3º) Indian Ocean
12km (1/9º) Arabian Sea
27km (1/4º) Antarctic• All configurations run daily in the operational suite• Output available on HORACE
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Data assimilation
• Data assimilation is key to initialising the models for effective forecasting
• All FOAM configurations assimilate a range of data:
– Temperature and salinity profiles including Argo floats
– Satellite altimeter Sea Surface Height – In situ and satellite Sea Surface
Temperature • New generation of satellite SST
products being tested
– Sea-ice concentration
Argo float distributionat end of March
Improved satellite SST data
Current SatSST data: c. 3000 obs daily New data: Atlantic > 2.5 million obs daily
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Partial Cell Bathymetries
• Improved topographic steering of currents
Model bathymetry Model streamfunction
Full cells
Partial cells
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Dependence of forecast bias on advection scheme
Annual mean of analysis temperature increments along 65ºW
3D QUICK 4th order + biharmonic GM
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Assessments of Mixed Layer
• Careful assessment of mixed layer schemes using Argo and OWS Papa data
• More reliable diagnostic of mixed layer developed
Global mean mixed layer depth error
Old MLD New MLD
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Ecosystem, air-sea CO2 fluxesand water clarity
• Hadley Centre Ocean Carbon Cycle model (HadOCC) has been coupled with the FOAM system• FOAM-HadOCC running at 1º, 1/3º and 1/9º resolution• Assessment of initial year-long integrations underway
• Diagnostics of pCO2 and water clarity
•Ocean colour data assimilation scheme (developed by NOCS) implemented and testing commenced
Chlorophyll for mid-March 2000
1º FOAM-HadOCC
SeaWIFS data
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Sea-ice data assimilation
• A system for assimilating sea-ice concentration data into FOAM has been developed with funding from ESA
– Assimilation improves representation of the ice, especially the ice edge
• A scheme for the assimilation of ice velocity has also been developed which adapts the stresses on the ice to match observations
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Assimilation of Altimeter Data
Surface pressure difference
Identical twin experiments used to explore poor performance
Bottom pressure errors are up to 30% of surface errors
Old MLD New MLD
Bottom pressure difference
