Abstract

Abstract. Synthetic aperture radar interferometry (InSAR) is an efficient technique for mapping the surface elevation and its temporal change over glaciers and ice sheets. However, due to the penetration of the SAR signal into snow and ice, the apparent elevation in uncorrected InSAR digital elevation models (DEMs) is displaced versus the actual surface. We studied relations between interferometric radar signals and physical snow properties and tested procedures for correcting the elevation bias. The work is based on satellite and in situ data over Union Glacier in the Ellsworth Mountains, West Antarctica, including interferometric data of the TanDEM-X mission, topographic data from optical satellite sensors and field measurements on snow structure, and stratigraphy undertaken in December 2016. The study area comprises ice-free surfaces, bare ice, dry snow and firn with a variety of structural features related to local differences in wind exposure and snow accumulation. Time series of laser measurements of NASA's Ice, Cloud and land Elevation Satellite (ICESat) and ICESat-2 show steady-state surface topography. For area-wide elevation reference we use the Reference Elevation Model of Antarctica (REMA). The different elevation data are vertically co-registered on a blue ice area that is not affected by radar signal penetration. Backscatter simulations with a multilayer radiative transfer model show large variations for scattering of individual snow layers, but the vertical backscatter distribution can be approximated by an exponential function representing uniform absorption and scattering properties. We obtain estimates of the elevation bias by inverting the interferometric volume correlation coefficient (coherence), applying a uniform volume model for describing the vertical loss function. Whereas the mean values of the computed elevation bias and the elevation difference between the TanDEM-X DEMs and the REMA show good agreement, a trend towards overestimation of penetration is evident for heavily wind-exposed areas with low accumulation and towards underestimation for areas with higher accumulation rates. In both cases deviations from the uniform volume structure are the main reason. In the first case the dense sequence of horizontal structures related to internal wind crust, ice layers and density stratification causes increased scattering in near-surface layers. In the second case the small grain size of the top snow layers causes a downward shift in the scattering phase centre.

Highlights

  • Digital elevation models (DEMs) derived from across-track interferometric synthetic aperture radar (InSAR) data are a main data source for mapping the surface elevation and its temporal change over glaciers and ice sheets

  • In this study we investigated the feasibility for estimating the penetration-related elevation bias of interferometric topographic products over snow and ice by inverting the volumetric coherence

  • Single-pass across-track SAR interferometry has been widely applied for comprehensive, spatially detailed measurements of glacier and ice sheet topography as the measurements are not impaired by temporal decorrelation of the interferometric signal, variations in atmospheric propagation conditions, cloudiness and variable illumination

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Summary

Introduction

Digital elevation models (DEMs) derived from across-track interferometric synthetic aperture radar (InSAR) data are a main data source for mapping the surface elevation and its temporal change over glaciers and ice sheets. Hoen and Zebker (2000, 2001) derived a formulation for estimating the power penetration depth in dry snow from the interferometric coherence, applying a radiative transfer model for estimating spatial decorrelation in a volume of uniformly distributed and uncorrelated scatterers characterised by exponential extinction. They applied this formulation to derive the C-band penetration depth for different sites in Greenland from the coherence of 3 d repeat-pass InSAR data of the ERS-1 synthetic aperture radar (SAR) mission. We show simulations for vertical backscatter distributions at snow pit sites and compares these with exponential backscatter functions

Surface mass balance and orographic effects
TanDEM-X data
Topographic data from optical satellite sensors
Snow pit measurements
Interferometric coherence and penetration-related elevation bias
Topographic reference and vertical co-registration
Notations for elevation differences
Temporal stability of surface elevation
Vertical co-registration of the DEMs
Spatial pattern of backscatter signals and coherence
Estimation of the interferometric elevation bias
Findings
Discussion
Conclusion
Full Text
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