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Assimilation of Sea-ice Concentration in a Global Climate Model – Physical and Statistical Aspects : Volume 9, Issue 1 (15/01/2013)

By Tietsche, S.

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Book Id: WPLBN0004020639
Format Type: PDF Article :
File Size: Pages 18
Reproduction Date: 2015

Title: Assimilation of Sea-ice Concentration in a Global Climate Model – Physical and Statistical Aspects : Volume 9, Issue 1 (15/01/2013)  
Author: Tietsche, S.
Volume: Vol. 9, Issue 1
Language: English
Subject: Science, Ocean, Science
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Jungclaus, J. H., Notz, D., Marotzke, J., & Tietsche, S. (2013). Assimilation of Sea-ice Concentration in a Global Climate Model – Physical and Statistical Aspects : Volume 9, Issue 1 (15/01/2013). Retrieved from

Description: Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany. We investigate the initialisation of Northern Hemisphere sea ice in the global climate model ECHAM5/MPI-OM by assimilating sea-ice concentration data. The analysis updates for concentration are given by Newtonian relaxation, and we discuss different ways of specifying the analysis updates for mean thickness. Because the conservation of mean ice thickness or actual ice thickness in the analysis updates leads to poor assimilation performance, we introduce a proportional dependence between concentration and mean thickness analysis updates. Assimilation with these proportional mean-thickness analysis updates leads to good assimilation performance for sea-ice concentration and thickness, both in identical-twin experiments and when assimilating sea-ice observations. The simulation of other Arctic surface fields in the coupled model is, however, not significantly improved by the assimilation. To understand the physical aspects of assimilation errors, we construct a simple prognostic model of the sea-ice thermodynamics, and analyse its response to the assimilation. We find that an adjustment of mean ice thickness in the analysis update is essential to arrive at plausible state estimates. To understand the statistical aspects of assimilation errors, we study the model background error covariance between ice concentration and ice thickness. We find that the spatial structure of covariances is best represented by the proportional mean-thickness analysis updates. Both physical and statistical evidence supports the experimental finding that assimilation with proportional mean-thickness updates outperforms the other two methods considered. The method described here is very simple to implement, and gives results that are sufficiently good to be used for initialising sea ice in a global climate model for seasonal to decadal predictions.

Assimilation of sea-ice concentration in a global climate model – physical and statistical aspects

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