Modeling the Vertical Backscattering Distribution in the Percolation Zone of the Greenland Ice Sheet With SAR Tomography

Abstract

The penetration of microwave signals into snow and ice, especially in dry conditions, introduces a bias in digital elevation models generated by means of synthetic aperture radar (SAR) interferometry. This bias depends directly on the vertical backscattering distribution in the subsurface. At the same time, the sensitivity of interferometric SAR measurements on the vertical backscattering distribution provides the potential to derive information about the subsurface of glaciers and ice sheets from SAR data, which could support the assessment of their dynamics. The aim of this paper is to improve the interferometric modeling of the vertical backscattering distribution in order to support subsurface structure retrieval and penetration bias estimation. Vertical backscattering distributions are investigated at different frequencies and polarizations on two test sites in the percolation zone of Greenland using fully polarimetric X-, C-, Land nd P-band SAR data. The vertical backscattering distributions were reconstructed by means of SAR tomography and compared to different vertical structure models. The tomographic assessment indicated that the subsurface in the upper percolation zone is dominated by scattering layers at specific depths, while a more homogeneous scattering structure appears in the lower percolation zone. The performance of the evaluated structure models, namely an exponential function with a vertical shift, a Gaussian function and a Weibull function, was evaluated. The proposed models improve the representation of the data compared to existing models while the complexity is still low to enable potential model inversion approaches. The tomographic analysis and the model assessment is therefore a step forward towards subsurface structure information and penetration bias estimation from SAR data.

Synergistic Use of Single-Pass Interferometry and Radar Altimetry to Measure Mass Loss of NEGIS Outlet Glaciers between 2011 and 2014

“…This is likely leading to a thin layer of relatively dry snow on the ice surface. A SAR tomography study with X-C-and L-band over the percolation zone [55] confirmed that the fresh and dry snow layer is generally transparent to the radar and that the scattering takes place at the previous summer layers. We therefore assume that a difference in the already small precipitation in the form of snowfall does not affect the captured surface elevation changes.…”

Modeling and Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at Different Frequencies

“…The snow and firn conditions are considered stable during the acquisition period so that temporal decorrelation can be neglected [12]. The tomographic analysis of the data is discussed in [14]. The tomograms confirm the presence of dominant scattering layers at the South Dome test site, as also shown in the GPR data in Fig.…”

“…Therefore, despite the nadir-looking acquisition geometry and the single frequency, they indicate the subsurface scattering properties for SAR acquisitions at larger incidence angles and higher frequencies. More information about the campaign can be found in [12] and [14].…”

“…An alternative, more flexible model, based on the Weibull function, is introduced and compared. The presented approaches address both random and oriented volume assumptions, since the vertical backscattering profiles in ice sheets were shown to be polarization dependent [14]. The accuracy of the penetration bias estimates is assessed against GNSS surface elevation measurements.…”

Author response to Referee #1

“…Completely frozen percolation zones produce some of the largest radar backscatter responses on the terrestrial earth (Jezek, Gogineni et al 1994). Because frozen snow and percolation facies are essentially transparent, C-band SAR will be sensitive to the presence of liquid water across the volume of a snowpack or firn strata (Fischer, Jäger et al 2019). Signals of delayed refreeze across subregions are indicative of meltwater storage within the percolation volume due to meltwater retention ( Supplementary Fig.…”