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MyOcean Monitoring and Forecasting Centre for the North West European Continental Shelf (NWS MFC ):
• One of the operational production centres of the GMES FP7 MyOcean project
• Aims to provide the fully validated ocean hindcast, nowcast and forecast products, free of charge at the point of delivery
• Services are in four areas of use: maritime safety; marine resources; coastal and marine environment; and weather, seasonal forecasting & climate
• The MyOcean NWS MFC has built upon the NOOS (North West Shelf Operational Oceanography System ) collaboration and cooperation to deliver improved products, systems and services for users of the Marine Core Services in the NOOS region
NWS MFC: Products + Users• Safety at sea: Ship routing services, offshore operations and
search and rescue operations + oil spill response and remediation.
• Key users: European Maritime Safety Agency (EMSA), users delivering assessments for the Convention for the Marine Environment of the North East Atlantic (OSPAR) and national maritime safety agencies.
• Protection and the sustainable management of living marine resources: aquaculture, fishery research or regional fishery organisations.
• Key users:ICES (International Council for the Exploitation of the Sea ), the FAO (Food and Agriculture Organization of the United Nations ) and national fisheries agencies.
• Water quality monitoring and pollution control• Key users in this context are EEA (The European Environment
Agency ), OSPAR and national environmental agencies. • Support of weather, seasonal and climate prediction services.
• Key Users National and European Weather Services and Climate Research centres should benefit from the NWS MFC products, e.g. bottom boundary conditions for atmospheric models.
• Provided by the operational meteorological centres of the UK and Norway (the Met Office and met.no), with the nominal service being provided by the Met Office and a backup forecast being available to operational users from met.no.
• The hindcast products are provided by the Institute of Marine Research, Bergen (IMR) and the National Oceanography Centre, Liverpool (NOC).
• The dissemination of products is from operationally supported servers maintained at the Met Office and met.no, with full redundancy in the production.
• The Met Office forecast production has been updated from the Medium-Resolution Continental Shelf (MRCS; Siddorn et al., 2006) configuration based upon the POLCOMS ocean model (Holt and James, 2001) coupled with the ERSEM ecosystem model (Blackford et al., 2004) system to the Atlantic-Margin Model (AMM7)
• Uses Optimal Interpolation (OI) data assimilation scheme (Martin et al, 2007) already used at the Met Office for the open ocean Forecasting Ocean Assimilation Model (FOAM; Storkey et al., 2010) suite of configurations.
Some Background on Global and Regional Models• Global ORCA025 (Drévillon et al., 2008)
configuration feeding boundary conditions to a North Atlantic rotated grid 1/12˚ model (the NATL12)
• The sea ice component is currently modelled using the 2nd version of the Louvain-le-Neuve(LIM2) model (Fichefet and Morales Maqueda, 1997) (no sea ice mode in AMM7!)
• A wide range of data is assimilated including in-situ data from moorings, profiling floats andsatellite sea-surface temperature, sea-surface elevation and sea-ice data (Only SST assim in AMM7 presently)
The Physical Model for AMM7(A shelf seas application of NEMO)
Joint MO and POL(NOCL) developments to NEMO
• Horizontal pressure gradient scheme (POL) • River inputs (MO)• S coordinates with sub-bed points (MO)• Semi-implicit bed stress (POL and MO) and log layer (MO)• Tide generating force (MO)• Sponge layer, s coordinate horizontal diffusion and Smag.
(MO)• Tidal boundary condition (using BDY) with Flather (MO)• Depth dependant attenuation coefficient (MO)• GLS TKE (kindly provided by Mercator)
There are two main functions to the real-time validation:
1) Daily monitoring of products to detect major problems, and to identify significant features in the forecast
2) Monthly examination of accuracy statistics to detect gradual deteriorations in the quality of products, and to confirm that the accuracy level is consistent with the results of the calibration hindcast.
• Maps of all products at various depths. • Differences between the daily mean surface
temperature and the OSTIA analysis for the same day• Timeseries of the extreme values of the model fields• Maps of data assimilation innovations• Maps of data assimilation increments• Maps of anomalies against climatologies• Maps of statistics derived from assimilation innovations• Volume transports
• To capture gradual deteriorations in the accuracy, daily accuracy statistics are monitored on a monthly basis.
• Variations in accuracy are also compared to the calibration hindcast to detect deviations from the normal seasonal and interannual variability of the errors.
• If potential problems are detected, then the plots from the monitoring section are useful for investigating the cause.
References(1)• Blackford JC, Allen JI and Gilbert FJ (2004). Ecosystem dynamics at six
contrasting sites: a generic model study. Journal of Marine Systems, 52, 191-215.• Drévillon M, Bourdallé-Badie R, Derval C, Drillet Y, Lellouche J-M, Rémy E,
Tranchant B, Benkiran M, Greiner E, Guinhut S, Verbrugge N, Garric G, Testut C-E, Laborie M, Nouel L, Bahurel P, Bricaud C, Crosnier L, Dombrowsky E, Durand E, Ferry N, Hernandez F, Le Galloudec O, Messal F, and Parent L. (2008). The GODAE/Mercator-Océan global ocean forecasting system: results, applications and prospects. J. Operational Ocean. 1: 51-57.
• Edwards KP, Barciela R, Butenschön M, Validation of the NEMO-ERSEM operational ecosystem model for the North West European Continental Shelf. Submitted to Ocean Sciences
• Fichefet T and Morales Maqueda MA (1997) Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics. J Geophys Res 102:12609–12646
• Holt, J.T. and James, I.D. (2001) An s coordinate density evolving model of the northwest European continental shelf 1, Model description and density structure, Journal of Geophysical Research, Oceans, 106, C7, 14015-14034.
• Madec G (2008). « NEMO ocean engine". Note du Pole de modélisation, Institut
Pierre-Simon Laplace (IPSL), France, No 27 ISSN No 1288-1619
References(2)• Martin MJ, Hines A, and Bell MJ (2007). Data assimilation in the FOAM
operational short-range ocean forecasting system: a description of the scheme and its impact. Q.J.R. Meterol. Soc. 133, 981-995
• O'Dea EJ, While J, Furner R, Arnold A, Hyder P, Storkey D, Edwards KP, Siddorn JR, Martin MJ, Liu H and Holt JT (2011). An operational ocean forecast system incorporating SST data assimilation for the tidally driven European North West European shelf. Submitted to J. Oper. Oceanography.
• Siddorn, J.R., Allen, J.I., Blackford, J.C., Gilbert, F.J., Holt, J.T., Holt, M.W., Osborne, J.P., Proctor, R., Mills, D.K. (2006). Modelling the hydrodynamics and ecosystem of the North West European continental shelf for operational oceanography. Journal of Marine Systems, doi:10.1016/j.jmarsys.2006.08.001
• Storkey D, Blockley EW, Furner R, Giuavarc'h C, Lea D, Martin MJ, Barciela RM, Hines A, Hyder P and Siddorn JR (2010) Forecasting the ocean state using NEMO: The new FOAM system. J. Operational Oceanography, 3, 3-15.
• The Global Ocean Data Assimilation Experiment (GODAE; Bell et al., 2009) metrics are used as a basis for use in evaluating model-based products.
• There are two groups of metrics used: analysis statistics and forecast statistics.
• At present these statistics are all computed in observation space (GODAE class 4), and averaged over pre-defined regions.
• The analysis statistics are derived from the data assimilation innovations (observation minus model differences). These differences are computed using model background fields before the observations are assimilated, and are therefore indicative of the accuracy of the 1-day forecasts.
• Because the data assimilation uses an FGAT (First Guess at Appropriate Time) scheme, these differences use the model value at the same time as the observation