Anisotropy of seasonal snow measured by polarimetric phase differences in radar time series

Snow settles under the force of gravity and recrystallizes by vertical temperature gradients. Both effects are assumed to form oriented ice crystals which induce an anisotropy in mechanical, thermal, and dielectric properties of the snow pack. On microscopic scales, the anisotropy could be hitherto...

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Bibliographic Details
Published in:The Cryosphere
Main Authors: Leinss, Silvan, Löwe, H., Proksch, M., Lemmetyinen, Juha, Wiesmann, A., Hajnsek, Irena
Format: Article in Journal/Newspaper
Language:unknown
Published: Copernicus Publications 2015
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Online Access:https://elib.dlr.de/100786/
http://www.the-cryosphere-discuss.net/9/issue6.html
Description
Summary:Snow settles under the force of gravity and recrystallizes by vertical temperature gradients. Both effects are assumed to form oriented ice crystals which induce an anisotropy in mechanical, thermal, and dielectric properties of the snow pack. On microscopic scales, the anisotropy could be hitherto determined only from stereology or computer tomography of samples taken from snow pits. In this paper we present an alternative method and show how the anisotropy of a natural snow pack can be observed contact- and destruction-free with polarimetric radar measurements. The copolar phase differences (CPD) of polarized microwaves transmitted through dry snow were analyzed for four winter seasons (2009–2013) from the SnowScat Instrument, installed at a test site near the town of Sodankylä, Finnland. An electrodynamic model was established based on anisotropic optics and on Maxwell–Garnett-type mixing formulas to provide a link between the structural anisotropy and the measured CPD. The anisotropy values derived from the CPD were compared with in-situ anisotropy measurements obtained by computer tomography. In addition, we show that the CPD measurements obtained from SnowScat show the same temporal evolution as space-borne CPD measurements from the satellite TerraSAR-X. The presented dataset provides a valuable basis for the future development of snow models capable of including the anisotropic structure of snow.