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Changes in the Structure of the Snow Cover of Hansbreen (S Spitsbergen) Derived from Repeated High-Frequency Radio-Echo Sounding.

Authors :
Kachniarz, Kamil
Grabiec, Mariusz
Ignatiuk, Dariusz
Laska, Michał
Luks, Bartłomiej
Source :
Remote Sensing; Jan2023, Vol. 15 Issue 1, p189, 26p
Publication Year :
2023

Abstract

This paper explores the potential of ground-penetrating radar (GPR) monitoring for an advanced understanding of snow cover processes and structure. For this purpose, the study uses the Hansbreen (SW Spitsbergen) records that are among the longest and the most comprehensive snow-cover GPR monitoring records available on Svalbard. While snow depth (HS) is frequently the only feature derived from high-frequency radio-echo sounding (RES), this study also offers an analysis of the physical characteristics (grain shape, size, hardness, and density) of the snow cover structure. We demonstrate that, based on GPR data (800 MHz) and a single snow pit, it is possible to extrapolate the detailed features of snow cover to the accumulation area. Field studies (snow pits and RES) were conducted at the end of selected accumulation seasons in the period 2008–2019, under dry snow conditions and HS close to the maximum. The paper shows that although the snow cover structure varies in space and from season to season, a single snow pit site can represent the entire center line of the accumulation zone. Numerous hard layers (HLs) (up to 30% of the snow column) were observed that reflect progressive climate change, but there is no trend in quantity, thickness, or percentage contribution in total snow depth in the study period. HLs with strong crystal bonds create a "framework" in the snowpack, which reduces compaction and, consequently, the ice formation layers slow down the rate of snowpack metamorphosis. The extrapolation of snow pit data through radar profiling is a novel solution that can improve spatial recognition of snow cover characteristics and the accuracy of calculation of snow water equivalent (SWE). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
1
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
161183006
Full Text :
https://doi.org/10.3390/rs15010189