rosa.barciela@metoffice.uk

Use of ocean colour (GlobColour) data for operational oceanographyRosa Barciela, NCOF, Met OfficeThanks to Matt Martin (Met Office) and John Hemmings (NOCS) rosa.barciela@metoffice.gov.uk

The Talk • Coupled physical-biogeochemical operational models • Use of ocean colour data: validation and data assimilation • - What are the aims? • - What tools are we using? • - What have we developed so far? • - Assimilation of satellite-derived chlorophyll • - What will we be doing next? • - What can we do as champion user of GlobColour ?

The Talk • What are the aims? • What tools are we using? • What have we developed so far? • Assimilation of satellite-derived chlorophyll • What will we be doing next? • What can we do as champion user of GlobColour?

What are the aims? • This work is part of the Centre for observation of Air-Sea Interactions and fluXes (CASIX), a UK project. • The primary goal of CASIX is to quantify accurately the global air-sea fluxes of carbon dioxide. • More accurate knowledge of the ocean biology is also required for: • water clarity predictions. • improvement of light attenuation estimates: SST, MLD, sea-ice. • the Royal Navy’s ability to minimise risks to the maritime environment when deploying active sonar systems. • supplying boundary conditions for the Shelf Seas system.

HadOCC • Hadley Centre Ocean Carbon Cycle Model What tools are we using? • Coupling together two models … • FOAM • Forecasting Ocean Assimilation Model

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

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

Hadley Centre Ocean Carbon Cycle model • HadOCC is a NPZD (plus DIC and alkalinity) biogeochemical model used at the Hadley Centre for climate studies. • HadOCC has been coupled (on-line) within the FOAM system. • Initial tests have been run with 1˚ global, 1/3˚ NA and Arctic and 1/9˚ NA FOAM configurations. Palmer, J.R. & Totterdell, I.J. (2001). Deep-Sea Research I, 48, 1169-1198

FOAM-HadOCC at 1º & 1/3 º resolutions, Mar 27th 2003 pCO2 (ppm) Chlorophyll (mg m-3) 1º Global 1/3º NA & Arctic

Validation of FOAM-HadOCC results Validation of surface chlorophyll against SeaWiFS data Daily mean North Atlantic fields for 20th April 2003 1/3º North Atlantic & Arctic 1º Global 1/9º North Atlantic SeaWiFS 5-day composite

Observations • SeaWiFS data processed at the University of Plymouth: derived chl (GSM) • For each observation, an estimate of the error is also provided. • Data assimilation schemes generally assume observations to have Gaussian error statistics. However, chlorophyll obs do not have this property. • To get around this problem, the data is converted into observations of log10(Chl) which has been shown to then have approximately Gaussian behaviour.

Chlorophyll data assimilation scheme • A 2D analysis of log10(Chl) is performed using the same method as for SST (OI-type scheme). This uses the error statistics described in the previous slide. The output from this is a field of surface log10(Chl) increments. • These can then be converted into surface phytoplankton increments using the model’s N:Chl ratio. • In order to start the model from a “balanced” state, increments to the other ecosystem model variables are calculated using a scheme jointly developed by NOCS and Met Office (next slide). • The analysed ecosystem model variables are then used directly as the starting conditions for the next model forecast. 3D analysis Observations ΔN Δalk N:Chl 2D analysis of log(Chl) 2D analysis of P Model forecast ΔP ΔZ ΔDIC ΔD

Chlorophyll data assimilation scheme • Two stage analysis scheme: • Model chlvs. satellite obs: increments (ACS) • Balancing increments to biogeochemical variables • Increments to other pools (N, Z, D, DIC, Alk) depend on the likely contributions to phytoplankton error from errors in growth and loss • Increments constrained to conserve total nitrogen & carbon at each grid point (if sufficient nitrogen is available) • Surface increments applied to mixed layer. Nutrient-profile correction increments below mixed layer. • Hemmings, Barciela and Bell (2007). Accepted by JMS.

3-D Twin experiments: daily mean RMS errors in the North Atlantic Phytoplankton (mmol N/m3) Zooplankton (mmol N/m3) Total DIC (mmol C/m3) Free run BDA run Control - truth Detritus (mmol N/m3) Nutrients (mmol N/m3) Assimilation - truth • 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

Real world experiments – annual mean Phytoplankton Nutrients No biological assimilation With biological assimilation

Real world experiments Green – no data assimilation Black – with physical data assimilation Red – physical and biological assimilation Global average RMS (solid lines) and mean (dashed lines) errors compared to the satellite chlorophyll data.

Inter-annual variability • FOAM-HadOCC run from Jan 2003 to Jan 2005 37.5⁰N 27.5 ⁰W 2003 47.5⁰N 27.5 ⁰W 2003 Red: Chlorophyll Blue: Nutrient Solid line: physical da only Dashed line: chl + physical da • Chlda has large impact on chl and • other biological compartments • Chlda wipes out seasonal variability • Smoothing in chl assimilation or variability not present in obs? 47.5⁰N 27.5 ⁰W 37.5⁰N 27.5 ⁰W 2004 2004

Summary of ocean colour assimilation work • An ocean colour data assimilation scheme has been designed and implemented within FOAM-HadOCC. • Initial identical twin experiments seem to indicate that the scheme has potential. • Real-world experiments show that the scheme is able to improve the chlorophyll – is difficult to verify other biological fields but some work is underway in this area. • Further work needed to explore the lack of seasonal variability in oligotrophic regions: • - smoothing of assimilation? • - absence of variability in satellite data?

What will be doing next? • Operational • pre-operational status from January 2008. • Climate • 10-year re-analysis of FOAM-HadOCC with/without chlorophyll and physical assimilation. • biological assimilation scheme to be assessed for implementation in Hadley Centre Carbon Cycle Data Assimilation System (CCDAS) – IPCC report

What can we do as champion user of GlobColour? • Met Office has developed the capability for the simulation of surface and deep ocean biogeochemistry in NRT • unique operational system fully coupled (on-line!)to an ecosystem and carbon cycle model • state of the art data assimilation scheme for ocean colour/derived chl • hindcast capability back to 1997, which makes possible the quantification of impact of GlobColour products on variables of climate interest: air-sea CO2 flux, carbon sequestration, acidity, PP, chl, etc. • well positioned to add value to the merged data by ensuring suitability for use for both operational oceanography and climate research • transitioning of R&D product into operations • However: • development work will be required • funding

Rosa Barcielarosa.barciela@metoffice.gov.uk

Experiments – identical twin set-up • Start from a spun-up model state, then run the model forced by 6 hourly NWP fluxes for 1 year, with physical (T, S, SST) data assimilation. This is called the “true” run. • Observations of Chl are taken from this “true” model state once a day. • The ecosystem model variables are initialised using the biological fields from March 2003, with the physical fields taken from the true run. • Starting from these new initial conditions, the model is run from April 2003 without (“control”) and with (“assim”) the Chl observations assimilated.

Real world experiments – on 1st July 2003 Log(chl) observations Log(chl) from model with no biological assimilation Log(chl) from model with biological assimilation

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

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)

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)

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

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

rosa.barciela@metoffice.uk

rosa.barciela@metoffice.uk

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