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Ungermann, Mischa; Tremblay, L Bruno; Martin, Torge; Losch, Martin (2017): Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files. PANGAEA,, Supplement to: Ungermann, M et al. (2017): Impact of the Ice Strength Formulation on the Performance of a Sea Ice Thickness Distribution Model in the Arctic. Journal of Geophysical Research: Oceans, 122(3), 2090-2107,

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The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness and drift speed with an semi-automatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed.
Further details:
Hilber III, W D (1979): A dynamic thermodynamic sea ice model. Journal of Physical Oceanography, 9(4), 815-846,;2
Rothrock, Drew A (1975): The energetics of the plastic deformation of pack ice by ridging. Journal of Geophysical Research, 80(33), 4514-4519,
Latitude: 90.000000 * Longitude: 0.000000
pan-Arctic * Latitude: 90.000000 * Longitude: 0.000000 * Location: Arctic
Monthly mean values for sea ice thickness, concentration, drift and ice strength from model simulations.
The model area covers the Arctic Ocean; thickness, concentration and drift are given from 1979 to 2009, ice strength is given from 1999 to 2011. The different model configurations are as described in the article.
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1File contentContentLosch, Martin
2File nameFile nameLosch, Martin
3File formatFile formatLosch, Martin
4File sizeFile sizekByteLosch, Martinzipped
5Uniform resource locator/link to fileURL fileLosch, Martin
30 data points

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