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    Retrieving sea ice drag coefficients and turning angles from in situ and satellite observations using an inverse modeling framework

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    Date
    2019-08-14
    Author
    Heorton, Harold  Concept link
    Tsamados, Michel  Concept link
    Cole, Sylvia T.  Concept link
    Ferreira, Ana M. G.  Concept link
    Berbellini, Andrea  Concept link
    Fox, Matthew  Concept link
    Armitage, Thomas  Concept link
    Metadata
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    Citable URI
    https://hdl.handle.net/1912/25275
    As published
    https://doi.org/10.1029/2018JC014881
    DOI
    10.1029/2018JC014881
    Keyword
     sea ice drift; observations; inverse modeling; drag coefficients 
    Abstract
    For ice concentrations less than 85%, internal ice stresses in the sea ice pack are small and sea ice is said to be in free drift. The sea ice drift is then the result of a balance between Coriolis acceleration and stresses from the ocean and atmosphere. We investigate sea ice drift using data from individual drifting buoys as well as Arctic‐wide gridded fields of wind, sea ice, and ocean velocity. We perform probabilistic inverse modeling of the momentum balance of free‐drifting sea ice, implemented to retrieve the Nansen number, scaled Rossby number, and stress turning angles. Since this problem involves a nonlinear, underconstrained system, we used a Monte Carlo guided search scheme—the Neighborhood Algorithm—to seek optimal parameter values for multiple observation points. We retrieve optimal drag coefficients of CA=1.2×10−3 and CO=2.4×10−3 from 10‐day averaged Arctic‐wide data from July 2014 that agree with the AIDJEX standard, with clear temporal and spatial variations. Inverting daily averaged buoy data give parameters that, while more accurately resolved, suggest that the forward model oversimplifies the physical system at these spatial and temporal scales. Our results show the importance of the correct representation of geostrophic currents. Both atmospheric and oceanic drag coefficients are found to decrease with shorter temporal averaging period, informing the selection of drag coefficient for short timescale climate models.
    Description
    Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans 124(8), (2019): 6388-6413, doi: 10.1029/2018JC014881.
    Collections
    • Physical Oceanography (PO)
    Suggested Citation
    Heorton, H. D. B. S., Tsamados, M., Cole, S. T., Ferreira, Ana M. G., Berbellini, A., Fox, M., & Armitage, T. W. K. (2019). Retrieving sea ice drag coefficients and turning angles from in situ and satellite observations using an inverse modeling framework. Journal of Geophysical Research-Oceans, 124(8), 6388-6413.
     

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