Articles | Volume 15, issue 5
https://doi.org/10.5194/tc-15-2429-2021
https://doi.org/10.5194/tc-15-2429-2021
Research article
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04 Jun 2021
Research article | Highlight paper |  | 04 Jun 2021

Faster decline and higher variability in the sea ice thickness of the marginal Arctic seas when accounting for dynamic snow cover

Robbie D. C. Mallett, Julienne C. Stroeve, Michel Tsamados, Jack C. Landy, Rosemary Willatt, Vishnu Nandan, and Glen E. Liston

Data sets

NASA Eulerian Snow On Sea Ice Model (NESOSIM) NASA Cryospheric Sciences Laboratory https://earth.gsfc.nasa.gov/cryo/data/nasa-eulerian-snow-sea-ice-model-nesosim

Lagrangian Snow Distributions for Sea-Ice Applications, Version 1 G. E. Liston, J. Stroeve, and P. Itkin https://doi.org/10.5067/27A0P5M6LZBI

ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from the Envisat satellite on a monthly grid (L3C), v2.0 S. Hendricks, S. Paul, and E. Rinne https://doi.org/10.5285/f4c34f4f0f1d4d0da06d771f6972f180

Northern hemisphere sea ice thickness from the CryoSat-2 satellite on a monthly grid (L3C), v2.0 S. Hendricks, S. Paul, and E. Rinne https://doi.org/10.5285/ff79d140824f42dd92b204b4f1e9e7c2

Model code and software

SnowModel-LG_SIT_Impacts robbiemallett https://github.com/robbiemallett/SnowModel-LG_SIT_Impacts

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Short summary
We re-estimate pan-Arctic sea ice thickness (SIT) values by combining data from the Envisat and CryoSat-2 missions with data from a new, reanalysis-driven snow model. Because a decreasing amount of ice is being hidden below the waterline by the weight of overlying snow, we argue that SIT may be declining faster than previously calculated in some regions. Because the snow product varies from year to year, our new SIT calculations also display much more year-to-year variability.