Climate Dynamics

, Volume 49, Issue 3, pp 775–789 | Cite as

Arctic sea ice in the global eddy-permitting ocean reanalysis ORAP5

  • Steffen Tietsche
  • Magdalena A. Balmaseda
  • Hao Zuo
  • Kristian Mogensen


We discuss the state of Arctic sea ice in the global eddy-permitting ocean reanalysis Ocean ReAnalysis Pilot 5 (ORAP5). Among other innovations, ORAP5 now assimilates observations of sea ice concentration using a univariate 3DVar-FGAT scheme. We focus on the period 1993–2012 and emphasize the evaluation of model performance with respect to recent observations of sea ice thickness. We find that sea ice concentration in ORAP5 is close to assimilated observations, with root mean square analysis residuals of less than 5 % in most regions. However, larger discrepancies exist for the Labrador Sea and east of Greenland during winter owing to biases in the free-running model. Sea ice thickness is evaluated against three different observational data sets that have sufficient spatial and temporal coverage: ICESat, IceBridge and SMOSIce. Large-scale features like the gradient between the thickest ice in the Canadian Arctic and thinner ice in the Siberian Arctic are simulated well by ORAP5. However, some biases remain. Of special note is the model’s tendency to accumulate too thick ice in the Beaufort Gyre. The root mean square error of ORAP5 sea ice thickness with respect to ICESat observations is 1.0 m, which is on par with the well-established PIOMAS model sea ice reconstruction. Interannual variability and trend of sea ice volume in ORAP5 also compare well with PIOMAS and ICESat estimates. We conclude that, notwithstanding a relatively simple sea ice data assimilation scheme, the overall state of Arctic sea ice in ORAP5 is in good agreement with observations and will provide useful initial conditions for predictions.


Ocean reanalysis Arctic Sea ice 



This research was supported by the MyOcean2 project funded by the European Union and by the APPOSITE project funded by the UK National Environment Research Council. We thank two anonymous reviewers for valuable comments that helped to improve the manuscript.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Steffen Tietsche
    • 1
    • 2
  • Magdalena A. Balmaseda
    • 2
  • Hao Zuo
    • 2
  • Kristian Mogensen
    • 2
  1. 1.NCAS-Climate/Department of MeteorologyUniversity of ReadingReadingUK
  2. 2.European Centre for Medium-Range Weather ForecastsReadingUK

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