MIZMAS Forecast of Sea Ice Thickness and Drift in the Beaufort Sea Marginal Ice Zone

Abstract:

A significant decline of Arctic sea ice has been observed in recent years. The decline was particularly steep during summers 2007–2013, when the arctic sea ice extent decreased to the lowest levels observed in the satellite era. The summer melt back was most severe in the Pacific sector including the Beaufort Sea where increasing areas of warming open water and marginal ice zone (MIZ) have been observed. To enhance our understanding of MIZ processes, an Office of Naval Research MIZ initiative is under way, which is an integrated program of observations and numerical simulations to investigate ice–ocean–atmosphere dynamics in and around the Beaufort Sea MIZ. In early 2014, the observation team of this program deployed 4 clusters of instruments of various platforms in the Beaufort Sea in order to capture the processes that affect MIZ evolution during the ice melt season.

To assist the field work, we have developed a numerical framework for 48-hour forecast of sea ice thickness and drift in and around the Beaufort Sea MIZ using the Marginal Ice Zone ice/ocean Modeling and Assimilation System (MIZMAS). MIZMAS is a variant of the Pan-arctic Ice/Ocean Modeling and Assimilation System (PIOMAS), with a high-resolution focus of the Chukchi, Beaufort, and Bering seas. The 48-hour sea ice forecast system is forced by the forecast atmospheric data from the NCEP (National Center for Environmental Prediction) Climate Forecast System version 2 (CFSv2). The CFSv2 forecast ranges from hours to months and the forecast atmospheric data are widely accessible, thus ideal for forcing our sea ice forecast over a range of time scales. The sea ice forecast system has been used to predict sea ice thickness in the Beaufort Sea MIZ 48 hours in advance, focusing on the areas around the 4 clusters. It has also been used to predict the movement of these clusters. In this presentation, we will assess MIZMAS’ forecast skills by comparing available ice thickness observations and the actual cluster trajectories. We will examine ways to improve the forecast system. We will also explore the possibility to extend the forecast to a seasonal time scale.