Applied Science & Research Standing Committee Action from IICWG-VII Co-Chairs Lars-Anders...

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  • Applied Science & ResearchStanding CommitteeAction from IICWG-VIICo-ChairsLars-Anders Breivik & Pablo Clemente-Coln

  • SC6.2:Re-identify ice service/national Science representatives for all member nations. For those services which do not have Science sections, Heads of Ice Service will be contacted to propose appropriate national representatives as a contactResponsible:Science Committee Co-ChairsTarget Date(s): December 2006Status:Open

    Applied Science and Research IICWG-7 Action Items

  • National representatives, draft listCanada: Roger DeAbreuDenmark: (Sren Andersen)Finland: Jari HaapalaGermany:Iceland: Ingibjrg JnsdttirJapan:Norway: Lars-Anders BreivikRussia:Sweden:USA: Pablo Clemente-ColnLithuania: UK: John Stark Australia: Tony WorbyWCRP / CliC: (Tony Worby will make contact)

  • SC6.7:Each national member requested to give a brief summary of Top Research priorities and plans to facilitate identification of complementary &/or common activities and areas for collaboration. An updated list will be put on the IICWG web pageResponsible:Science Committee Co-Chairs (Breivik)Target Date(s):December 2006Status:Open

    Applied Science and Research IICWG-7 Action Items

  • SC6.8:Develop a process for rotation of Committee Co-Chairs.Flett stepping down as Co-Chair for IICWG-7.Clements-Colon step in.Suggested procedure: Rotation with a change every 2. meeting (3 years ?)Co-Chairs from Canada/USA and Europe(+) Overlap in rotationResponsible:AllTarget Date(s):IICWG-8Status:OPEN

    Applied Science and Research IICWG-7 Action Items

  • Applied Science and Research IICWG-7 Action ItemsSC7.1:IICWG, IPY data assimilation and modelling project: Send out to each project partner template for project outline (Carrieres). This shall be completed and sent back within December 2006.

    Responsible:Tom Carrieres

    Target Date:December 2006

    Status:Closed (see 7.2)

  • Applied Science and Research IICWG-7 Action ItemsSC7.2:

    IICWG, IPY data assimilation and modelling project: Prepare and arrange a dedicated workshop.ice modelling and data assimilationPlace: met.no, OsloTime: May 2006:Responsible:Breivik with support from CarrieresTarget Date:May 2006Status:Closed

  • Status on sea ice data assimilationReport from IICWG work shop Oslo 14-16 May, 2007

  • IICWG - data assimilation historyTroms 2002, ice modeling and DA defined as a main priority St Petersburg 2003, White paperHamburg 2004, dedicated science workshopOttawa 2005, IPY proposalHelsinki 2006, Oslo 2007, Dedicated workshop

  • Sea Ice Ocean modeling, status

  • Sea ice modeling, statusRelying on a two-dimensional continuum hypothesis for description of the ice, and uses Viscous-Plastic rheology. None of the groups are using discrete element models, or other Lagrangian types of models, despite that some of the forecast systems are operating with a few km horizontal resolution. climate applications has been the main constraint.

    How complex a model system is needed for the ice forecasts (uncoupled ice, coupled ice-ocean, fully coupled atmosphere-ice-ocean, or a hybrid in between those) depends on the type and length of the forecast, and on what kind of physical processes that are the most important for that specific case.

  • Data assimilation challenge From a limited set of surface observations - obtain a well balanced 4-dimensional ice-ocean model fieldFirst approach:Simple nudging of Ice concentration and SST towards observations (externally analyzed fields)satellitesatelliteModel + 0 hModel + 120 h

  • Main challengeSpecifying the background (model) error covariances for a coupled ice-ocean analysis Especially important for:Unobserved variables (e.g. under-ice ocean variables)when the horizontal coverage of ice observations is not complete over the analysis domain (e.g. SAR or AVHRR data)Ignoring important spatial and multivariate covariances can lead to imbalances or artificial spatial discontinuities in the analyzed model state.

  • Facing the main challenge:

    The groups are working on more advanced methods for estimating model error covariances:EnKFSEIK

  • Example of estimating background error covariances using EnKF for one ice-season Alain Caya, Meteorological Research Division, Environment Canada

  • ObservationsIce concentration analysisIce drift vectorsHigh resolution dataOSI SAF, AMSR-E, ice concOctober 14 2007IFREMER, AMSR-E, 3day ice drift, May 1 2007

    FIMR, SAR & Insitu Ice Thickness charts

  • Observation errorsExample: use of Ice drift data:Recommendations:Specify accurate start and end times of displacement vectorsSpecify elaborate error statistics3-day coarse resolutionIFREMER ->1-day fine resolutionDNSC ->->

  • Very brief summaryNot as far as hoped for in 2002 (Troms)HoweverPromising results in advanced methods (3DVAR, EnKF, SEIK), Long term R&D focus is neededSimple pragmatic approaches for short term forecast systems are implemented and worksTo be followed up by new workshop in fall 2008 (at DMI)