Analysis of snowpack properties and structure from TerraSAR-X data, based on multilayer backscattering and snow evolution modeling approaches

TL;DR

This paper presents a novel method combining high-frequency SAR data and electromagnetic modeling to improve snowpack characterization and evolution modeling, validated with TerraSAR-X data and in-situ measurements.

Contribution

It adapts an electromagnetic backscattering model for X-band SAR to constrain detailed snowpack models and develops a variational data assimilation scheme for better snow evolution predictions.

Findings

Snow stratigraphic profiles improved after data assimilation

SAR data effectively constrains snowpack models

Method demonstrates high potential for cryosphere observation

Abstract

Recently launched high precision Synthetic Aperture Radar (SAR) satellites such as TerraSAR-X, COSMO-SkyMed, etc. present a high potential for better observation and characterization of the cryosphere. This study introduces a new approach using high frequency (X-band) SAR data and an Electromagnetic Backscattering Model (EBM) to constrain the detailed snowpack model Crocus. A snowpack EBM based on radiative transfer theory, previously used for C-band applications, is adapted for the X-band. From measured or simulated snowpack stratigraphic profiles consisting of snow optical grain radius and density, this forward model calculates the backscattering coefficient for different polarimetric channels. The output result is then compared with spaceborne TerraSAR-X acquisitions to evaluate the forward model. Next, from the EBM, the adjoint operator is developed and used in a variational analysis scheme in order to minimize the discrepancies between simulations and SAR observations. A time series of TerraSAR-X acquisitions and in-situ measurements on the Argenti\`ere glacier (Mont-Blanc massif, French Alps) are used to evaluate the EBM and the data assimilation scheme. Results indicate that snow stratigraphic profiles obtained after the analysis process show a closer agreement with the measured ones than the initial ones, and therefore demonstrate the high potential of assimilating SAR data to model of snow evolution.