Evaluation of sea-ice thickness reanalysis data from the coupled ocean-sea-ice data assimilation system TOPAZ4. Issue 262 (13th April 2021)

• Record Type: Journal Article
• Authors: Xiu, Yongwu; Min, Chao; Xie, Jiping; Mu, Longjiang; Han, Bo; Yang, Qinghua
• Is Part Of: Journal of Glaciology. Volume 67:Issue 262(2021)
• Page Start: 353
• Page End: 365
• Publication Date: 2021-04-13
• Subjects: Sea ice, -- TOPAZ4, -- sea-ice modelling
• DOI: 10.1017/jog.2020.110
• Languages: English
• ISSNs: 0022-1430

Abstract

Abstract: With the assimilation of satellite-based sea-ice thickness (SIT) data, the new SIT reanalysis from the Towards an Operational Prediction system for the North Atlantic European coastal Zones (TOPAZ4) was released from 2014 to 2018. Apart from assimilating sea-ice concentration and oceanic variables, TOPAZ4 further assimilates CS2SMOS SIT. In this study, the 5-year reanalysis is compared with CS2SMOS, the Pan-Arctic Ice-Ocean Modeling and Assimilating System (PIOMAS) and the Combined Model and Satellite Thickness (CMST). Moreover, we evaluate TOPAZ4 SIT with field observations from upward-looking sonar (ULS), ice mass-balance buoys, Operation IceBridge Quicklook and Sea State Ship-borne Observations. The results indicate TOPAZ4 well reproduces the spatial characteristics of the Arctic SIT distributions, with large differences with CS2SMOS/PIOMAS/CMST mainly restricted to the Atlantic Sector and to the month of September. TOPAZ4 shows thinner ice in March and April, especially to the north of the Canadian Arctic Archipelago with a mean bias of −0.30 m when compared to IceBridge. Besides, TOPAZ4 simulates thicker ice in the Beaufort Sea when compared to ULS, with a mean bias of 0.11 m all year round. The benefit from assimilating SIT data in TOPAZ4 is reflected in a 34% improvement in root mean square deviation.