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Assimilating SST and Ocean Colour into ocean forecasting models Rosa Barciela, NCOF, Met Office

Assimilating SST and Ocean Colour into ocean forecasting models Rosa Barciela, NCOF, Met Office. rosa.barciela@metoffice.gov.uk. Contents. Introduction Operational FOAM Biogeochemical modelling Satellite data assimilation in FOAM Medspiration SST SeaWiFS Ocean Colour Future plans

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Assimilating SST and Ocean Colour into ocean forecasting models Rosa Barciela, NCOF, Met Office

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  1. Assimilating SST and Ocean Colour into ocean forecasting modelsRosa Barciela, NCOF, Met Office rosa.barciela@metoffice.gov.uk

  2. Contents • Introduction • Operational FOAM • Biogeochemical modelling • Satellite data assimilation in FOAM • Medspiration SST • SeaWiFS Ocean Colour • Future plans • Operational Requirements - GlobCOLOUR

  3. Forecasting the open ocean: the FOAM system Input boundary data NWP 6 hourly fluxes Obs QC Forecast to T+144 Analysis Output boundary data Real-time data Automatic verification Product delivery FOAM = Forecasting Ocean Assimilation Model • Operational real-time deep-ocean forecasting system • Daily analyses and forecasts out to 6 days • Low resolution global to high resolution nested configurations • Relocatable system deployable in a few weeks • Hindcast capability (back to 1997) • Assimilates T and S profiles, SST, SSH, sea-ice concentration

  4. Operational configurations 36km (1/3º) North Atlantic and Arctic 12km (1/9º) North Atlantic 1º Global 6km (1/20º) North East Atlantic 36km (1/3º) Indian Ocean 12km (1/9º) Mediterranean 27km (1/4º) Antarctic • All configurations run daily in the operational suite 12km (1/9º) Arabian Sea

  5. Hadley Centre Ocean Carbon Cycle Model (HadOCC) Model description - ‘NPZD’ ecosystem model - Coupled to carbon and alkalinity - Variable C:Chl ratio - Transported around the ocean by physical processes - Normally used for climate studies Aims - Air-sea fluxes of CO2 using high-resolution GCM (1º go, 1/3º & 1/9º NA) • Assimilation of Ocean Colour & EO data to improve these fluxes • 10 year hindcast (1997-2006) with/without data assimilation

  6. Contents • Introduction • Operational FOAM • Biogeochemical modelling • Satellite data assimilation in FOAM • Medspiration SST • SeaWiFS Ocean Colour • Future plans • Operational Requirements - GlobCOLOUR

  7. Operational FOAM assimilation of GHRSST-PP products Assimilation of Medspiration data • FOAM adapted to use GHRSST obs • 3-month hindcast run with/without assimilation of Medspiration data • Main differences in Gulf stream region • Assimilation of Medspiration obs improve the ocean temperature analysis by 0.1K RMS. • Improvement not only at the surface but over the top 600 m

  8. Future Plans To use GHRSST-PP data operationally from next year (development work required)

  9. Contents • Introduction • Operational FOAM • Biogeochemical modelling • Satellite data assimilation in FOAM • Medspiration SST • SeaWiFS Ocean Colour • Future plans • Operational Requirements - GlobCOLOUR

  10. Assimilation of Derived Chlorophyll Results from 3-D twin experiments Phytoplankton background error before the first analysis. Phytoplankton analysis error after the first analysis, with data everywhere. Phytoplankton errors (mmolN/m3)

  11. Daily Mean RMS Errors in the North Atlantic from 3-D Twin Experiments Control - truth Assimilation - truth Assimilation of Derived Chlorophyll Total Dissolved Inorganic Carbon (mmolC/m3) - Air-sea exchange of CO2 significantly improved after assimilating ocean colour data - Joint assimilation of Medspiration SST and ocean colour is desirable as carbon solubility is strongly dependent on temperature - 10 year hindcast will benefit from using a long-term SST, ocean colour dataset

  12. Free Run Chlorophyll DA • 10-day test run Mean error = -0.28 RMS error = 0.46 Mean error = -0.11 RMS error = 0.27 Assimilation of Derived Chlorophyll Aim: Improvement of pCO2 estimation by assimilating ocean colour

  13. Future plans To transition the FOAM-HadOCC system into pre-operational state by 2008 (assimilation of ocean colour products)

  14. Contents • Introduction • Operational FOAM • Biogeochemical modelling • Satellite data assimilation in FOAM • Medspiration SST • SeaWiFS Ocean Colour • Future plans • Operational Requirements - GlobCOLOUR

  15. GlobCOLOUR/Ocean Colour Operational User Requirements • Specific requirements for GlobCOLOUR • L2 Global Area Coverage of chl a plusquantified errors from • merged and individual sensors - Best possible accuracy: essential to decrease errors in derived chl below 35% - Spatial resolution: 4 Km spacing (highest resolution models have) - Extensive product quality control: include quantified errors and quality flags - Validation against in situ data and across biogeochemical regions. - Large biases in the merged product corrected by in situ data - Bias information from individual sensors - Product format: WMO GRIB or netCDF - Delivery method: FTP

  16. GlobCOLOUR/Ocean ColourOperational User Requirements For operational purposes … • Long-term provision of quality-controlled products in a timely (within 1 day) manner. • sustainability is key as lots of investment required to use the data • stable formats and delivery: (very) high availability and reliability • Joint GlobCOLOUR/Medspiration products would be an advantage: • single file format • single file delivery • reduced data processing time • diagnostic data set applied to GlobCOLOUR data • NW European Shelf (NOOS) user requirements may need to be gathered • (martin.holt@metoffice.gov.uk)

  17. Rosa Barcielarosa.barciela@metoffice.gov.uk

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