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The Cryosphere An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/tc-2020-8
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2020-8
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 03 Feb 2020

Submitted as: research article | 03 Feb 2020

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This preprint is currently under review for the journal TC.

Estimating statistical errors in retrievals of ice velocity and deformation parameters from satellite images and buoy arrays

Wolfgang Dierking1,2, Harry Stern3, and Jennifer K. Hutchings4 Wolfgang Dierking et al.
  • 1Center for Integrated Remote Sensing and Forecasting for Arctic Operations, University in Tromsø, 9019 Tromsø, Norway
  • 2Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, 27570 Bremerhaven, Germany
  • 3Polar Science Center, Applied Physics Laboratory, University of Washington, 1013 NE 40th Street, Seattle, WA 98105, USA
  • 4College of Earth Ocean and Atmospheric Sciences, Oregon State University, 104 CEOAS Administration building, Corvallis OR 97331, USA

Abstract. The objective of this note is to provide the background and basic tools to estimate the statistical error of deformation parameters that are calculated from displacement fields retrieved from synthetic aperture radar (SAR) imagery or from location changes of position sensors in an array. We focus here specifically on sea ice drift and deformation. In the most general case, the uncertainties of divergence/convergence, shear, vorticity, and total deformation are dependent on errors in coordinate measurements, the size of the area and the time interval over which these parameters are determined, and the velocity gradients within the boundary of the area. If displacements are calculated from sequences of SAR images, also a tracking error has to be considered. Timing errors in position readings are usually very small and can be neglected. We give examples for magnitudes of position and timing errors typical for buoys and SAR sensors, in the latter case supplemented by magnitudes of the tracking error, and apply the derived equations on geometric shapes frequently used for deriving deformation from SAR images and buoy arrays. Our case studies show that the size of the area and the time interval for calculating deformation parameters have to be chosen within certain limits to make sure that the uncertainties are smaller than the magnitudes of deformation parameters.

Wolfgang Dierking et al.

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Wolfgang Dierking et al.

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Latest update: 23 Feb 2020
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Short summary
Monitoring deformation of sea ice is useful for studying effects of ice compression and divergent motion on the ice mass balance and ocean-ice-atmosphere interactions. In calculations of deformation parameters not only the measurement uncertainty of drift vectors has to be considered. The size of the area and the time interval used in the calculations have to be chosen within certain limits to make sure that the uncertainties of deformation parameters are smaller than their real magnitudes.
Monitoring deformation of sea ice is useful for studying effects of ice compression and...
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