Predictability of Arctic sea-ice linear kinematic features in high-resolution ensemble simulations


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maragh [ at ] awi.de

Abstract

Linear kinematic features (LKFs) in sea ice, potentially important for short-term forecast users as for climate simulations, emerge as viscous-plastic sea ice models are used at high (<10km) resolution. Here we analyze the short-range (up to 10 days) potential predictability of LKFs in Arctic sea ice using an ocean/sea-ice model with a grid point separation of ~4.5 km. We analyze the sensitivity of predictability to idealized initial perturbations, resembling uncertainties in sea ice analyses, and to growing uncertainty of the atmospheric forcing caused by the chaotic nature of the atmosphere. For the latter we use different members of ECMWF ensemble forecasts to drive ocean/sea-ice forecasts. For our analysis, we diagnose LKFs occurrence and investigate different sea ice characteristics. On the 10-day-time scale, the model has lower predictive skill for LKFs and deformation than for sea-ice thickness and concentration.



Item Type
Conference (Poster)
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Not peer-reviewed
Publication Status
Published
Event Details
Polar predictability workshop, 04 May 2016 - 06 May 2016, Palisades, New York, USA.
Eprint ID
40996
Cite as
Mohammadi-Aragh, M. , Losch, M. , Goessling, H. F. and Hutter, N. (2016): Predictability of Arctic sea-ice linear kinematic features in high-resolution ensemble simulations , Polar predictability workshop, Palisades, New York, USA, 4 May 2016 - 6 May 2016 .


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