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Long dynamical atmospheric reanalyses are widely used for climate studies,but data-assimilative reanalyses of ocean and sea ice in the Arctic are lesscommon. TOPAZ4 is a coupled ocean and sea ice data assimilation system forthe North Atlantic and the Arctic that is based on the HYCOM ocean model andthe ensemble Kalman filter data assimilation method using 100 dynamicalmembers. A 23-year reanalysis has been completed for the period 1991–2013and is the multi-year physical product in the Copernicus Marine EnvironmentMonitoring Service (CMEMS) Arctic Marine Forecasting Center (ARC MFC). Thisstudy presents its quantitative quality assessment, compared to bothassimilated and unassimilated observations available in the whole Arcticregion, in order to document the strengths and weaknesses of the system forpotential users. It is found that TOPAZ4 performs well with respect to near-surfaceocean variables, but some limitations appear in the interior of theocean and for ice thickness, where observations are sparse. In the course ofthe reanalysis, the skills of the system are improving as the observationnetwork becomes denser, in particular during the International Polar Year.The online bias estimation successfully maintains a low bias in our system.In addition, statistics of the reduced centered random variables (RCRVs)confirm the reliability of the ensemble for most of the assimilatedvariables. Occasional discontinuities of these statistics are caused by thechanges of the input data sets or the data assimilation settings, but thestatistics remain otherwise stable throughout the reanalysis, regardless ofthe density of observations. Furthermore, no data type is severely lessdispersed than the others, even though the lack of consistently reprocessedobservation time series at the beginning of the reanalysis has provenchallenging

Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991–2013