New Inversion Method for Snow Density and Snow Liquid Water Content Retrieval Using C - Band Data from Envisat / Asar Alternating Polarization in Alpine Environment

This study presents a new method to analyse some parameters of snow in alpine region: density, wetness. Here are developed the methodology and first results obtained from a set of ASAR-ENVISAT images registered during 2004 spring period over an experimental river basin located in the French Alps (N 45° 05’/ E 6° 10’). For ENVISAT/ASAR data, a topographic processing is done using a Digital Elevation Model (DEM) in order to correct the strong slope effects and determine the local incidence angles. During each ENVISAT data acquisition, intensive field measurements of snow pack properties (snow lines, snow pits) and weather conditions were gathered on 7 representative test sites. We propose a new inversion method for snow wetness and snow density retrievals by assimilating times series of ENVISAT/ASAR Alternating Polarization data. We use a forecast snow parameters and the covariance of the forecast error in order to produce inferred parameters compatible with the radar satellite measurements. An iterative method is set to find the maximum probably solution to a non-linear retrieval problem. This performs an inversion of the backscattering signal in VV and VH polarizations to retrieve simultaneously the snow liquid water content and snow density. This method provides a powerful tool since it consists in: 1) a fully physical method, involving calculations for each snow profile of corresponding backscattering signal by the ‘forward model’ in VV and VH polarization (and of derivatives of backscattering with respect to profile parameters); and 2) a statistical method, since it uses the covariance of forecast error as a constraint. The theory of this new approach is presented and the application to ENVISAT/ASAR data is discussed. Error characteristics of this method are investigated. The results of using as ‘the first guess’ as the snow characteristics profile given by the distributed SAFRAN/CROCUS snow model (Météo-France) are presented. The results are very satisfactory. Furthermore, for the wet snow condition in alpine environment, an appropriate methodology to have accurate radar measurements and simulated backscattering is proposed.