Physical length scales of wind-blown snow redistribution and accumulation on relatively smooth Arctic first-year sea ice

Moon, Woosok; Nandan, Vishnu; Scharien, Randall K.; Wilkinson, Jeremy ORCID: https://orcid.org/0000-0002-7166-3042; Yackel, John J.; Barrett, Andrew; Lawrence, Isobel; Segal, Rebecca A.; Stroeve, Julienne C.; Mahmud, Mallik; Duke, Patrick J.; Else, Brent. 2019 Physical length scales of wind-blown snow redistribution and accumulation on relatively smooth Arctic first-year sea ice. Environment Research Letters, 14 (10), 104003. https://doi.org/10.1088/1748-9326/ab3b8d

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Official URL: https://iopscience.iop.org/article/10.1088/1748-93...

Abstract/Summary

Snow thickness measurements over relatively smooth Arctic first-year sea ice, obtained near Cambridge Bay, Nunavut, Canada (2014, 2016 and 2017) and near Elson Lagoon, Alaska, USA (2003 and 2006), are analyzed to quantify physical length-scales and their relevant scaling behaviors. We use the Multi-Fractal Temporally Weighted Detrended Fluctuation Analysis  (MF-TWDFA) method to detect two major physical length-scales from both the study areas. Our results suggest that physical processes underlying the formation of snow dunes are consistent and that the wind is the main process shaping the redistribution and variability of snow thickness. One scale, around 10 m, appears to be related to the formation of the snow "dunes", while the other scale, between 30 m and 60 m, is likely associated with the various interactions of the snow dunes including merging, calving and lateral linking showing self-organized characteristics. We suggest that a simple cellular automata model can be used to generate the variability of snow thickness on smooth Arctic first-year sea ice.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1088/1748-9326/ab3b8d
Additional Keywords:	snow thickness, first-year sea ice, multi-fractal analysis, snow dune, self-organized criticality, MF-TWDFA, cellular automata
Date made live:	20 Aug 2019 14:59 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/523377

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1088/1748-9326/ab3b8d

Additional Keywords:

snow thickness, first-year sea ice, multi-fractal analysis, snow dune, self-organized criticality, MF-TWDFA, cellular automata

Date made live:

20 Aug 2019 14:59 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/523377