|Title||Arctic sea ice in the ECMWF MyOcean2 ocean reanalysis ORAP5|
|Year of Publication||2014|
|Authors||Tietsche, S, Alonso-Balmaseda, M, Zuo, H, Mogensen, K|
|Secondary Title||Technical Memorandum|
|Type of Work||Technical Memorandum|
We discuss the state of Arctic sea ice in ORAP5, a prototype for the ORAS5 ocean reanalysis, which was run as the ECMWF contribution to MyOcean2. Among other innovations, ORAP5 assimilates observations of sea ice concentration. For the period 1993-2012, we find that sea ice concentration fields in ORAP5 are very close to observations in general, with root mean square analysis residuals of less than 5% in most regions. However, larger differences exist for the Labrador Sea and east of Greenland during winter. In coastal areas, the model consistently simulates lower sea ice concentration than observed, which is probably due to problems with sea ice concentration observations in conjunction with the high model resolution. 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 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 is 1.0 m, which is on par with the well-established PIOMAS sea ice reconstruction. Interannual variability and trend of sea ice volume in ORAP5 also compare well with PIOMAS and ICESat estimates. Validation of thin sea ice areas against SMOSIce is a promising prospect for future operational developments, but initial analysis shows that improvements in both observations and model are necessary before this can be done consistently. We conclude that the overall state of Arctic sea ice in ORAP5 is in reasonable agreement with observations and will provide useful initial conditions for predictions. Nevertheless, the simulation of sea ice thickness remains to be a challenge.