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

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Presentation on theme: "Assimilating SST and Ocean Colour into ocean forecasting models Rosa Barciela, NCOF, Met Office"— Presentation transcript:

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

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 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 FOAM = Forecasting Ocean Assimilation Model Real-time data Obs QC Analysis Forecast to T+144 NWP 6 hourly fluxes Automatic verification Product delivery Input boundary data Output boundary data

4 Operational configurations 12km (1/9º) Mediterranean 6km (1/20º) North East Atlantic 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

5 Hadley Centre Ocean Carbon Cycle Model (HadOCC) Model description - Variable C:Chl ratio - Coupled to carbon and alkalinity - Normally used for climate studies - Transported around the ocean by physical processes - ‘NPZD’ ecosystem model Aims - Air-sea fluxes of CO 2 using high- resolution GCM (1º go, 1/3º & 1/9º NA) - Assimilation of Ocean Colour & EO data to improve these fluxes - 10 year hindcast ( ) 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 Phytoplankton background error before the first analysis. Phytoplankton analysis error after the first analysis, with data everywhere. Phytoplankton errors (mmolN/m 3 ) Assimilation of Derived Chlorophyll Results from 3-D twin experiments

11 Assimilation of Derived Chlorophyll Total Dissolved Inorganic Carbon (mmolC/m 3 ) Control - truth Assimilation - truth Daily Mean RMS Errors in the North Atlantic from 3-D Twin Experiments - Air-sea exchange of CO 2 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 10-day test run Free Run Chlorophyll DA RMS error = 0.46RMS error = 0.27Mean error = -0.28Mean error = Aim: Improvement of pCO 2 estimation by assimilating ocean colour Assimilation of Derived Chlorophyll

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 plus quantified errors from merged and individual sensors - Best possible accuracy: essential to decrease errors in derived chl below 35% - Extensive product quality control: include quantified errors and quality flags - Validation against in situ data and across biogeochemical regions. - Product format: WMO GRIB or netCDF - Delivery method: FTP - Large biases in the merged product corrected by in situ data - Spatial resolution: 4 Km spacing (highest resolution models have) - Bias information from individual sensors

16 GlobCOLOUR/Ocean Colour Operational User Requirements 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 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 NW European Shelf (NOOS) user requirements may need to be gathered

17 Rosa Barciela


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