The Cryosphere
The Cryosphere
TC
Articles | Volume 10, issue 2
Articles | Volume 10, issue 2
https://doi.org/10.5194/tc-10-761-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-10-761-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 10, issue 2
Brief communication
 | 
06 Apr 2016
Brief communication |  | 06 Apr 2016

Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation

Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, Lars Nerger, and Thomas Lavergne

Data sets

A change in atmospheric circulation National Snow & Ice Data Center http://nsidc.org/arcticseaicenews/2010/07/

ESA-CCI Sea-Ice-ECV Projekt Integrated Climate Data Center – ICDC http://icdc.zmaw.de/projekte/esa-cci-sea-ice-ecv0.html

Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1 National Snow & Ice Data Center http://nsidc.org/data/docs/daac/nsidc0051_gsfc_seaice.gd.html

Beaufort Gyre Exploration Project Woods Hole Oceanographic Institution http://www.whoi.edu/beaufortgyre

Report 2014: Variability of Melt Cold Regions Research and Engineering Laboratory http://imb.erdc.dren.mil/index.htm

TIGGE – global ensemble forecast data ECMWF http://tigge.ecmwf.int

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Short summary
We assimilate the summer SICCI sea ice concentration data with an ensemble-based Kalman Filter. Comparing with the approach using a constant data uncertainty, the sea ice concentration estimates are further improved when the SICCI-provided uncertainty are taken into account, but the sea ice thickness cannot be improved. We find the data assimilation system cannot give a reasonable ensemble spread of sea ice concentration and thickness if the provided uncertainty are directly used.
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