IGST-XII: UK Progress Report John Siddorn, August 2007

Contents Update on NCOF Progress with NEMO ocean model framework FOAM update Data assimilation Ecosystems Downscaling OSTIA Data delivery development

Update on NCOF NCOF was launched in March 2005 Partners are the Met Office and the NERC marine research institutes –POL, NOCS, ESSC, PML –CEFAS are Observers, with a view to joining The Consortium Agreement is nearing completion –Discussion on IPR, but with strong support at director level NCOF Activities –50 on spreadsheet NCOF Workshops –Annual gatherings

Progress with NEMO NEMO is the Nucleus for European Modelling of the Ocean –The Met Office is committed to transitioning it’s ocean modelling activities to use NEMO –Includes development of NEMO for use in shelf seas modelling NEMO Consortium Agreement –CNRS and Met Office ready to sign –NOCS NERC are also now going to be signatories (also ready) NEMO Systems Team –Core of team at CNRS (Paris), but consortium agreement commits resources from NOCS (Southampton) and Met Office (Exeter) NEMO Users –Includes the open ocean, shelf seas, seasonal forecasting and climate prediction communities –Intention to use NEMO as the primary open ocean modelling tool across all communities

FOAM-NEMO: Current status Operational: 1/3° Atlantic-Arctic model as a parallel system –Enable assessment of forecast skill –Provide baseline for optimising system –Other Atlantic models will be added in a couple of months –Full switch depends on data delivery systems Semi-operational: 1/16° NE Atlantic MERSEA vn2 system

NEMO at NOCS Running a ORCA1 66 level NEMO –uses the CORE forcing (with 6-hourly variability) –increased upper ocean resolution for ecosystem modelling –run for 12 years at present without problems. Ice SST

12 year changes in MOC Indicate reduced poleward flow of warm water

NEMO at ESSC ESSC undertaking research and development into data assimilation techniques for use with open ocean models. –includes the use of the FOAM and NEMO systems to facilitate pull- through into the operational forecasting system. –1 o 46 level global NEMO model used for hindcast data assimilation experiments over the Argo period –Later this year 40 year reanalyses will be performed using all available hydrographic data using S(T) and S(density) methods

NEMO: Plans Met Office –Mercator will be running ORCA025 global (¼ o ) and NAtl 1/12 o with 50 levels –Met Office plans to provide equivalent daily running parallel systems as part of the MyOceans proposal Differences in assimilation and sea ice –FOAM regional/zoom configurations will transition to NEMO by mid 2009 NOCS –64 level ORCA025 global (¼ o ) including biogeochemistry. –Preliminary tests of a full “LOBSTER” biogechemical model within the ORCA1 configuration. ESSC –a ¼ o NEMO configuration for reanalysis work in collaboration with ECMWF is planned for later this year. –Later this year 40 year reanalyses will be performed using all available hydrographic data, and using S(T) and S(density) methods. –¼ o NEMO will be run for a 3 year hindcast assimilating Argo and Rapid THC array data later this year.

FOAM: current operational configurations 36km (1/3º) North Atlantic and Arctic 12km (1/9º) Mediterranean 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 Boundaries to shelf seas systems

FOAM status: recent upgrades Changes to mixed layer scheme –Use of the Kara et al. (2000) optimal mixed layer depth –Parameter tuning Parameters explored using 1D model and Argo float data Verification statistics for global FOAM MLD mean error (m)MLD RMS error (m)

Old SatSST data: c obs daily New NSST100 data: c obs daily FOAM status: recent upgrades Satellite SST data used in FOAM has recently been upgraded –Previous data was low resolution (2.5º) AVHRR Data reliability had deteriorated since early last year –New SST data is a NESDIS product 100km gridded data delivered daily 50km gridded data delivered twice a week –Eventual aim is to use GHRSST data Sea-ice concentration data also upgraded –OSISAF data replaced old CMC product

FOAM status: on-going work Validation of surface currents –Detailed validation of surface currents from 1/9º North Atlantic FOAM –Validation against surface drifter data Taylor diagram (RMS error, correlation, and standard deviation)

Operational system Trial all remaining models in parallel NEMO-FOAM suite Full switch to NEMO-FOAM when –Scientific accuracy confirmed (analyses and forecasts) –System efficiency acceptable –Data delivery mechanisms fully tested Data assimilation Complete production of model MDT from long hindcasts Implement bias correction techniques for altimeter assimilation Investigations into density and ‘spiciness’ as control variables. Assimilate GHRSST high resolution SST data operationally. Implement an advanced data assimilation scheme (3D,4D-Var, EnKF) Continued developments of ecosystem data assimilation FOAM: Plans

No altimeter assimilation With altimeter assimilation Altimetry Assimilation: Mean Dynamic Topography No assimilation of altimeter data on the shelf Mean dynamic topography (MDT) of model not consistent with Rio05 Causes generation of spurious shelf-break currents Solution chosen is to use model MDT from a long hindcast instead of Rio05 Will use bias correction techniques (both model and observed biases) Mean velocities from FOAM-NEMO (over 3 months)

Improved MDT from GRACE/GOCE data by careful treatment of omission errors in MSSH and Satellite Geoid =>ESA toolbox for GOCE Allowing MDT errors to be treated as an observation bias during altimeter assimilation => Improved SLA predictions in FOAM 1/3  model (Drecourt et al 2006) Typical aliasing errors from MSSH-Geoid FOAM MDT MDT Error Variance Altimetry Assimilation: Mean Dynamic Topography

Altimeter Assimilation: Impact of applying balancing velocity increments In FOAM-NEMO, without and with applying the balancing velocity increments Both animations show difference between a run with and a run without the altimeter assimilation over a 10 day period No balancing velocity increments With balancing velocity increments

Density /kg m -3 Spiciness increment π (ρ) Density level depth z(ρ) before and after assimilation Can spread spiciness over larger spatial scales on ρ levels T(z), S(z) → z(ρ), π (ρ) → Assimilate → T(z), S(z) Spiciness /kg m -3 Altimeter Assimilation: Assimilating “spiciness”

Assimilation: Meridional Overturning Circulation Perform 1º and ¼ º global simulations over 40 years, using novel technique to assimilate T and S observations (along isotherms/isopycnals) Determine how well the MOC, MHT and water mass transformation budgets are constrained by data assimilation. Focus on roles of Argo and Rapid Array data Meridional velocity anomaly at 26N MOC Strength at 26N (Sv)

Ecosystem modelling Development of open ocean water clarity capability –Hadley Centre Ocean Carbon Cycle model (HadOCC) has been coupled with the FOAM system NPZD ecosystem model –FOAM-HadOCC running at 1º, 1/3º and 1/9º resolution –Assessment of initial year-long integrations underway –Ocean colour data assimilation scheme (developed by NOCS) implemented and testing commenced Schematic of HadOCC

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

Downscaling: Shelf seas model development and testing Shelf seas developments are being added to NEMO by several European groups Met Office testing is starting with tides-only, building up to 3D baroclinic simulations, aiming to replace POLCOMS Tides-only simulations with M2 tidal-harmonic boundary forcing Cotidal charts (solid contours show amplitude, dashed show phase) POLCOMS NEMO

Operational Sea surface Temperature and sea Ice Analysis Daily 1/20° global analysis using optimal interpolation. Near real time. Using GHRSST-PP satellite (microwave & IR) and in situ data. Persistence based analysis. Includes satellite bias correction. Analysis results available from O.I. Analysis

Data Delivery: The GODIVA2 Server Reading e-Science Centre developing OGC compliant Geobrowsers for NCOF and other data Interactively renders images from gridded NetCDF data. Currently uses Google maps but moving to OpenLayers for OGC compliance and more general map projections Likely to be adopted in MERSEA viewing service v2 Can overlay data from different URLs in same image (eg. different Mersea/GODAE WMS compliant sites) Moving towards DEWS

Data Delivery: DEWS portal The DEWS portal: Provides quick pre- made views Provides advanced views with user selection of data, time, location etc. Produces time series and animations OGC compliant

Data Delivery: Operational dissemination of data Direct links to Royal Navy forecasters. For commercial use, data is available from the Met Office’s Data and Products Distribution System (DPDS) at DPDS is now being superceded by FTPOPS. Will be used in MyOceans. Planned operational WMS at Met Office