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Task 4: snow physical characteristic & remote sensing

by Vincent Favier - 23 February 2016 ( maj : 15 January 2017 )

The overarching objective of this task is to relate snow physical properties observed in the field to SMB and satellite data. For this, a comprehensive set of measurements of snow physical properties will be collected along the traverse at the stations. This includes 1) profiles of snow grain size and density up to 10m depth, 2) 10-m deep temperature 3) surface roughness height and orientation, hardness 4) surface albedo 5) qualitative analysis of the core (crust layer, ...). These measurements will be acquired with instruments owned or developed at LGGE: POSSSUM for the grain size (Arnaud et al., 2011), a rapid and accurate photography system for the density (Leduc-Leballeur et al., submitted), laserscan (Optec ILRIS-LR (long range)), etc. In addition, we will prepare and deploy two nivo-meteorological stations in contrasted areas (based on the phase of the altimeter backscatter time-series or other satellite data) to monitor common meteorological variables and take weekly pictures of the surface to “see” the surface state and roughness evolution, the snowfall and blowing snow events, etc (Champollion et al., 2013). These stations will be autonomous in energy and data transmission (satellite link) and their expected life time is 3 years or more. In the area close to the coast subjected to occasional surface melting in summer (0 – 50km from Cap Prud’homme), we will focus on the time evolution of surface snow grain. Rapid grain growth is indeed an indicator of surface melting and has an influence on the albedo which further enhanced growth owing to wet metamorphism. Based on ANR MONISNOW expertise (PI: G. Picard, 2012-15) which is dedicated in developing new generation of instruments to observe physical properties of the snow , we will develop a lightweight and low-power optical device to acquire snow reflectances at selected wavelengths from which optical grain size will be derived using well-known relationships. These devices will be deployed on basic station along the logistical traverse track and data collection will be done every year. The equipments will be developed in 2015 and 2016 and set up in the field during the traverse.

Using this large data set in conjunction with SMB measured in task 2, and for the interpretation of ice core measurements from task 3, correlations will be explored to understand SMB local anomaly and eventually determine the processes responsible for the meso-scale spatial variations of SMB. At last, these data will be used in radiative transfer model to interpret altimeter radar backscatter and passive micro-wave data and improve our understanding of the satellite signals. The PhD student in collaboration between LEGOS and LGGE will work mostly on this goal. Ultimately, this will help to improve the existing relationships between SMB and passive microwave data and the accuracy of elevation estimates provided by altimeters.