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    Sea ice forecast verification in the Canadian Global Ice Ocean Prediction System

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    Authors
    Smith, G.C.
    Roy, F.
    Reszka, M.
    Surcel Colan, D.
    He, Z.
    Deacu, D.
    Belanger, J.-M.
    Skachko, S.
    Liu, Y.
    Dupont, F.
    Lemieux, J.-F.
    Beaudoin, C.
    Tranchant, B.
    Drévillon, M.
    Garric, G.
    Testut, C.-E.
    Lellouche, J.-M.
    Pellerin, P.
    Ritchie, H.
    Lu, Y.
    Davidson, F.
    Buehner, M.
    Caya, A.
    Lajoie, M.
    Show allShow less
    Discipline
    Earth and related Environmental sciences
    Subject
    Atmospheric temperature
    Forecasting
    Oceanography
    Sea ice
    Sea level
    Surface waters
    Verification
    Canadian
    Data assimilation
    Global
    Ocean modelling
    Operational oceanography
    Ice
    Audience
    Scientific
    Date
    2016
    Metadata
    Show full item record
    Description
    Recent increases in marine traffic in the Arctic have amplified the demand for reliable ice and marine environmental predictions. This article presents the verification of ice forecast skill from a new system implemented recently at the Canadian Meteorological Centre called the Global Ice Ocean Prediction System (GIOPS). GIOPS provides daily global ice and ocean analyses and 10-day forecasts on a 1/4°-resolution grid. GIOPS includes a multivariate ocean data assimilation system that combines satellite observations of sea-level anomaly and sea-surface temperature (SST) together with in situ observations of temperature and salinity. Ice analyses are produced using a 3D-Var method that assimilates satellite observations from SSM/I and SSMIS together with manual analyses from the Canadian Ice Service. Analyses of total ice concentration are projected onto the thickness categories used in the ice model using spatially and temporally varying weighting functions derived from ice model tendencies. This method may reduce deleterious impacts on the ice thickness distribution when assimilating ice concentration, as it can directly modulate (and reverse) nonlinear processes such as ice deformation. An objective verification of sea ice forecasts is made using two methods: analysis-based error assessment focusing on the marginal ice zone, and a contingency table approach to evaluate ice extent as compared to an independent analysis. Together the methods demonstrate a consistent picture of skilful medium-range forecasts in both the Northern and Southern Hemispheres as compared to persistence. Using the contingency table approach, GIOPS forecasts show a significant open-water bias during spring and summer. However, this bias depends on the choice of threshold used. Ice forecast skill is found to be highly sensitive to the assimilation of SST near the ice edge. Improved observational coverage in these areas (including salinity) would be extremely valuable for further improvement in ice forecast skill. © 2015 Royal Meteorological Society May 2015.
    Citation
    Smith, G.C.; Roy, F.; Reszka, M.; Surcel Colan, D.; He, Z.; Deacu, D.; Belanger, J.-M.; Skachko, S.; Liu, Y.; Dupont, F.; Lemieux, J.-F.; Beaudoin, C.; Tranchant, B.; Drévillon, M.; Garric, G.; Testut, C.-E.; Lellouche, J.-M.; Pellerin, P.; Ritchie, H.; Lu, Y.; Davidson, F.; Buehner, M.; Caya, A.; Lajoie, M. (2016). Sea ice forecast verification in the Canadian Global Ice Ocean Prediction System. , Quarterly Journal of the Royal Meteorological Society, Vol. 142, Issue 695, 659-671, DOI: 10.1002/qj.2555.
    Identifiers
    uri: https://orfeo.belnet.be/handle/internal/3219
    doi: http://dx.doi.org/10.1002/qj.2555
    scopus: 2-s2.0-84929430917
    Type
    Article
    Peer-Review
    Yes
    Language
    eng
    Links
    NewsHelpdeskBELSPO OA Policy

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