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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/tc-2018-159
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2018-159
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 17 Aug 2018

Research article | 17 Aug 2018

Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal The Cryosphere (TC) and is expected to appear here in due course.

New insight from CryoSat-2 sea ice thickness for sea ice modelling

David Schröder1, Danny L. Feltham1, Michel Tsamados2, Andy Ridout2, and Rachel Tilling3 David Schröder et al.
  • 1Centre for Polar Observation and Modelling, Departme nt of Meteorology, University of Reading, Reading, RG6 6BB, UK
  • 2Centre for Polar Observation and Modelling, Department of Earth Sciences, University College London, London, WC1E 6BT, UK
  • 3Centre for Polar Observation and Modelling, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK

Abstract. Estimates of Arctic sea ice thickness are available from the CryoSat-2 (CS2) radar altimetry mission during ice growth seasons since 2010. We derive the sub-grid scale ice thickness distribution (ITD) with respect to 5 ice thickness categories used in a sea ice component (CICE) of climate simulations. This allows us to initialize the ITD in stand-alone simulations with CICE and to verify the simulated cycle of ice thickness. We find that a default CICE simulation strongly underestimates ice thickness, despite reproducing the inter-annual variability of summer sea ice extent. We can identify the underestimation of winter ice growth as being responsible and show that increasing the ice conductive flux for lower temperatures (bubbly brine scheme) and accounting for the loss of drifting snow results in the simulated sea ice growth being more realistic. Sensitivity studies provide insight into the impact of initial and atmospheric conditions and, thus, on the role of positive and negative feedback processes. During summer, atmospheric conditions are responsible for 50% of September sea ice thickness variability through the positive sea ice and melt pond albedo feedback. However, atmospheric winter conditions have little impact on winter ice growth due to the dominating negative conductive feedback process: the thinner the ice and snow in autumn, the stronger the ice growth in winter. We conclude that the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season rather than by winter temperature. Our optimal model configuration does not only improve the simulated sea ice thickness, but also summer sea ice concentration, melt pond fraction, and length of the melt season. It is the first time CS2 sea ice thickness data have been applied successfully to improve sea ice model physics.

David Schröder et al.
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
David Schröder et al.
David Schröder et al.
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Short summary
This paper uses sea ice thickness data (CryoSat-2) to identify and correct shortcomings in simulating winter ice growth in the widely used sea ice model CICE. Adding a model of snow drift and using a different scheme for calculating the ice conductivity improve model results. Sensitivity studies demonstrate that atmospheric winter conditions have little impact on winter ice growth, and the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season.
This paper uses sea ice thickness data (CryoSat-2) to identify and correct shortcomings in...
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