Preprints
https://doi.org/10.5194/tc-2021-314
https://doi.org/10.5194/tc-2021-314

  13 Oct 2021

13 Oct 2021

Review status: this preprint is currently under review for the journal TC.

Potential of X-band polarimetric SAR co-polar phase difference for Arctic snow depth estimation

Joëlle Voglimacci-Stephanopoli1,2, Anna Wendleder3, Hugues Lantuit4,5, Alexandre Langlois1,2, Samuel Stettner3,6, Jean-Pierre Dedieu7,2, Achim Roth3, and Alain Royer1,2 Joëlle Voglimacci-Stephanopoli et al.
  • 1Centre d’Applications et de Recherches en Télédétection, Université de Sherbrooke, Sherbrooke, J1K 2R1, Canada
  • 2Centre d’Études Nordiques, Université Laval, Québec, Québec, G1V 0A6, Canada
  • 3German Remote Sensing Data Center, German Aerospace Center, Oberpfaffenhofen, Germany
  • 4Institute of Geosciences, University of Potsdam, Potsdam, Germany
  • 5Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, 14473 Potsdam, Germany
  • 6German Space Agency, German Aerospace Center, Bonn, Germany
  • 7Institute of Environmental Geosciences, Université Grenoble-Alpes/CNRS/IRD, 38058 Grenoble, France

Abstract. Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar—SAR) can address the issue and outperform methods based on passive microwaves. Thus, high spatial resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) quantified the spatio-temporal variability of the geophysical properties of the snowpack in an Arctic catchment, we then (2) studied the links between snow properties and CPD, considering ground vegetation. Snow depth (SD) could be extracted using the CPD when certain conditions are met. A high incidence angle (> 30°) with a high Topographic Wetness Index (TWI) (> 7.0) showed correlation between SD and CPD (R-squared up to 0.72). Further, future work should address a threshold of sensitivity to TWI and incidence angle to map snow depth in such environments and assess the potential of using interpolation tools to fill in gaps in SD information on drier vegetation types.

Joëlle Voglimacci-Stephanopoli et al.

Status: open (until 08 Dec 2021)

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Joëlle Voglimacci-Stephanopoli et al.

Joëlle Voglimacci-Stephanopoli et al.

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Short summary
Changes in the state of the snowpack in the context of observed global warming must be considered to improve our understanding of the processes within the cryosphere. This study aims to characterize an arctic snowpack using TerraSAR-X satellite. Using a high spatial resolution vegetation classification, we were able to quantify the variability of snow depth as well as the topographic soil wetness index which provided a better understanding of the electromagnetic wave-ground interaction.