Improving the Arctic sea-ice numerical forecasts by assimilation using a local SEIK filter


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qinghua.yang [ at ] awi.de

Abstract

Appropriate initial conditions are essential for accurate forecasts of sea ice conditions in the Arctic. We present a prototype of an assimilation and forecast system, where a new sea ice thickness data set based on the Soil Moisture and Ocean Salinity (SMOS) satellite data and sea ice concentration data (SSMIS) are assimilated with a local Singular Evolutive Interoplated Kalman (SEIK) [3] filter. The system is run for 3 months in the transition between autumn and winter 2011/2012. Forecasts of different length are evaluated and compared to independent in-situ data.



Item Type
Conference (Poster)
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Not peer-reviewed
Publication Status
Published
Event Details
International Symposium on Sea Ice in a Changing Environment, 10 Mar 2014 - 14 Mar 2014, Hobart, Australia.
Eprint ID
35272
Cite as
Yang, Q. , Loza, S. , Losch, M. , Tian-Kunze, X. , Nerger, L. , Liu, J. , Kaleschke, L. and Zhang, Z. (2014): Improving the Arctic sea-ice numerical forecasts by assimilation using a local SEIK filter , International Symposium on Sea Ice in a Changing Environment, Hobart, Australia, 10 March 2014 - 14 March 2014 .


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