Seasonal and interannual variability of the Arctic sea ice : a comparison between AO-FVCOM and observations

Author Posting. © American Geophysical Union, 2016. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 121 (2016): 8320–8350, doi:10.1002/2016JC011841.A high-resolution (up to 2 km), unstructured-grid, fully ice-sea coupled Arctic Ocean Finite-Volume Community Ocean Model (AO-FVCOM) was used to simulate the sea ice in the Arctic over the period 1978–2014. The spatial-varying horizontal model resolution was designed to better resolve both topographic and baroclinic dynamics scales over the Arctic slope and narrow straits. The model-simulated sea ice was in good agreement with available observed sea ice extent, concentration, drift velocity and thickness, not only in seasonal and interannual variability but also in spatial distribution. Compared with six other Arctic Ocean models (ECCO2, GSFC, INMOM, ORCA, NAME, and UW), the AO-FVCOM-simulated ice thickness showed a higher mean correlation coefficient of ∼0.63 and a smaller residual with observations. Model-produced ice drift speed and direction errors varied with wind speed: the speed and direction errors increased and decreased as the wind speed increased, respectively. Efforts were made to examine the influences of parameterizations of air-ice external and ice-water interfacial stresses on the model-produced bias. The ice drift direction was more sensitive to air-ice drag coefficients and turning angles than the ice drift speed. Increasing or decreasing either 10% in water-ice drag coefficient or 10° in water-ice turning angle did not show a significant influence on the ice drift velocity simulation results although the sea ice drift speed was more sensitive to these two parameters than the sea ice drift direction. Using the COARE 4.0-derived parameterization of air-water drag coefficient for wind stress did not significantly influence the ice drift velocity simulation.This work was supported by NSF grants OCE-1203393 for the UMASSD team and PLR-1203643 for R. C. Beardsley.2017-05-2