Elementa: Science of the Anthropocene (Jul 2018)

Seasonal evolution of the sea-ice floe size distribution in the Beaufort and Chukchi seas

  • Harry L. Stern,
  • Axel J. Schweiger,
  • Margaret Stark,
  • Jinlun Zhang,
  • Michael Steele,
  • Byongjun Hwang

DOI
https://doi.org/10.1525/elementa.305
Journal volume & issue
Vol. 6, no. 1

Abstract

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The size distribution of ice floes in the polar seas affects the dynamics and thermodynamics of the ice cover, and ice-ocean models are beginning to include the floe size distribution (FSD) in their simulations. The FSD has previously been reported to follow a power law of the form 'x' '-a', where 'x' is the floe size and –'a' characterizes how steeply the number of floes decreases as 'x' increases. Different studies have found different values of 'a' and different ranges of 'x' over which the power law applies. We found that a power law describes the FSD in the Beaufort and Chukchi seas reasonably well over floe sizes from 2 to 30 km, based on 187 visible-band satellite images (resolution 250 m) acquired during spring through fall of 2013 and 2014. The mean power-law exponent goes through a seasonal cycle in which a increases in spring, peaks in July or August, and decreases in fall. June is the transition month from spring FSD to summer FSD. This cycle is consistent with the processes of floe break-up in spring followed by preferential melting of smaller floes in summer and the return of larger floes after fall freeze-up. We also analyzed 12 high-resolution satellite images acquired near the low-resolution images in space and time. We found that the FSDs from the high-resolution images follow power laws over floe sizes from 10 m to 3 km. While the power-law exponents of the corresponding high- and low-resolution images do not always match in a strict statistical sense, they suggest the plausibility that the FSD follows a single power law over a wide range of floe sizes. This study covers a larger spatial and temporal sampling space and is based on more satellite images than previous studies. Results have been used for model calibration and validation.

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