Abstract
Abstract. Long dynamical atmospheric reanalyses are widely used for climate studies, but data-assimilative reanalyses of ocean and sea ice in the Arctic are less common. TOPAZ4 is a coupled ocean and sea ice data assimilation system for the North Atlantic and the Arctic that is based on the HYCOM ocean model and the ensemble Kalman filter data assimilation method using 100 dynamical members. A 23-year reanalysis has been completed for the period 1991–2013 and is the multi-year physical product in the Copernicus Marine Environment Monitoring Service (CMEMS) Arctic Marine Forecasting Center (ARC MFC). This study presents its quantitative quality assessment, compared to both assimilated and unassimilated observations available in the whole Arctic region, in order to document the strengths and weaknesses of the system for potential users. It is found that TOPAZ4 performs well with respect to near-surface ocean variables, but some limitations appear in the interior of the ocean and for ice thickness, where observations are sparse. In the course of the reanalysis, the skills of the system are improving as the observation network 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 assimilated variables. Occasional discontinuities of these statistics are caused by the changes of the input data sets or the data assimilation settings, but the statistics remain otherwise stable throughout the reanalysis, regardless of the density of observations. Furthermore, no data type is severely less dispersed than the others, even though the lack of consistently reprocessed observation time series at the beginning of the reanalysis has proven challenging.
Highlights
The Arctic Ocean plays an important role in the global climate system, where the sea ice at the interface between atmosphere and ocean regulates the fluxes of heat, moisture and momentum
The focus of this study is to provide a quantitative assessment of the reanalysis performance in the pan-Arctic region in order to guide the user through its skills and limitations
The proposed reanalysis is unique compared to other reanalysis products
Summary
The Arctic Ocean plays an important role in the global climate system, where the sea ice at the interface between atmosphere and ocean regulates the fluxes of heat, moisture and momentum. The recent warming of the Arctic and the change of its water cycle has been linked to the following manifestations: a significant reduction and thinning of the sea ice cover (Johannessen et al, 2004; Shimada et al, 2006; Rothrock et al, 2008; Kwok and Rothrock, 2009), more freshwater in the Arctic in the 2000s (Haine et al, 2015) and more mobility and faster deformations of the Arctic sea ice (Rampal et al, 2009; Spreen et al, 2011) The interpretation of such changes is severely hampered by the sparseness of the concerned observations, which should not be improved dramatically in the near future. The present paper follows the pilot TOPAZ4 reanalysis by Sakov et al (2012) in which the performance of the same system has been demonstrated for the period of 2003–2008 They proposed an implementation of the EnKF data assimilation method that avoids ensemble collapse, provides reliable state-dependent error estimates and improves the match to independent observations compared to a freerunning simulation.
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