Articles | Volume 12, issue 12
The Cryosphere, 12, 3949–3965, 2018
https://doi.org/10.5194/tc-12-3949-2018
The Cryosphere, 12, 3949–3965, 2018
https://doi.org/10.5194/tc-12-3949-2018

Research article 21 Dec 2018

Research article | 21 Dec 2018

Estimation of sea ice parameters from sea ice model with assimilated ice concentration and SST

Siva Prasad et al.

Related subject area

Discipline: Sea ice | Subject: Data Assimilation
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Cited articles

Banzon, V., Smith, T. M., Chin, T. M., Liu, C., and Hankins, W.: A long-term record of blended satellite and in situ sea-surface temperature for climate monitoring, modeling and environmental studies, Earth Syst. Sci. Data, 8, 165–176, https://doi.org/10.5194/essd-8-165-2016, 2016. a
Barré, H. M., Duesmann, B., and Kerr, Y. H.: SMOS: The mission and the system, IEEE T. Geosci. Remote, 46, 587–593, 2008. a
Bell, W.: A preprocessor for SSMIS radiances scientific description, Met Office, UK, 2006. a
Bouzinac, C.: CryoSat product handbook, ESA User Manual, ESA, ESRIN, Italy, 2014. a
Carsey, F. D.: Microwave remote sensing of sea ice, American Geophysical Union, 1992. a
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Short summary
A numerical sea ice model, CICE, was used along with data assimilation to derive sea ice parameters in the region of Baffin Bay, Hudson Bay and Labrador Sea. The modelled ice parameters were compared with parameters estimated from remote-sensing data. The ice concentration, thickness and freeboard estimates from the model assimilated with both ice concentration and SST were found to be within the uncertainty of the observations except during March.