Utilizing the ASPeCt sea ice thickness data set to evaluate a global coupled sea ice-ocean model

• Published in: Journal of Geophysical Research
• Main Authors: Timmermann, R, Worby, A, Goosse, Hugues, Fichefet, Thierry
• Other Authors: UCL - SC/PHYS - Département de physique, UCL - SST/ELI/ELIC - Earth & Climate
• Format: Article in Journal/Newspaper
• Language: English
• Published: Amer Geophysical Union 2004
• Subjects: Southern Ocean; sea ice thickness; ASPeCt; Antarc*; Antarctic; Antarctic Peninsula; Bellingshausen Sea; Ross Sea; Sea ice; Weddell Sea
• Online Access: http://hdl.handle.net/2078.1/40054; https://doi.org/10.1029/2003JC002242

[1] Simulated sea ice thickness in the ORCA2-LIM coupled sea ice - ocean model is compared with thicknesses from the Antarctic Sea Ice Processes and Climate (ASPeCt) database. We find a qualitative agreement of the large-scale patterns of ice thickness distribution. Regional averages for the various sectors of the Southern Ocean yield a very good correspondence between observations and model data. Exceptions are the eastern Bellingshausen and northwestern Weddell Seas. A poor representation of the Antarctic Peninsula in the atmospheric forcing data and the related overestimation of westerly winds in this region lead to a spurious accumulation of sea ice on the western side of the peninsula and to an underestimation of sea ice coverage on the eastern side. Since the spatial scale of observations is not comparable to the size of a model grid cell, there is little agreement between individual observations and the corresponding model ice thicknesses. A model analysis of the seasonal and interannual variability indicates that the ASPeCt data underestimate the climatological ice thickness in the central and southern Weddell Sea and the eastern Ross Sea by up to 1 m. Because of a winter bias in the observations an overestimation of similar magnitude is expected in the Bellingshausen Sea. Ice thickness data in most of the Indo-Pacific sector appear to be representative for the long-term climatology. A model estimate of the bias is used to compute a revised distribution of climatological sea ice thickness.