Event Details

DSNE seminar with Catherine Ritz and Marion Leduc-Leballeur

Catherine Ritz¹, Marion Leduc-Leballeur², Giovanni Macelloni², Ghislain Picard¹

¹IGE, CNRS, Univ. Grenoble Alpes, Grenoble, France

²IFAC-CNR, Firenze, Italy

Up to now temperature profile was available in few boreholes or from glaciological models. Recently, Macelloni et al. (2016) opened up new opportunities for probing ice temperature from space with the low-frequency passive sensors. Indeed, at L-band frequency, the very low absorption of ice and the low scattering by particles (grain size, bubbles in ice) allow a large penetration in the dry snow and ice (several hundreds of meters).

Here, we propose a method based on a Bayesian approach in order to infer the ice temperature profile over Antarctica and to provide an uncertainty estimation along the profiles. For that the European Space Agency (ESA)’s Soil Moisture and Ocean Salinity (SMOS) satellite observations are associated with an ice temperature model. As a first step, a one-dimensional ice temperature profile model (Robin 1955) is used, which limits the retrieval to the Antarctic Plateau. Then, the new temperature emulator based on the three-dimensional glaciological GRISLI (Quiquet et al., 2018) should be used to enable retrievals over the entire continent. In a second part, we will present the development of this emulator based on a deep neural network (DNN) to reproduce GRISLI temperature field. To train the emulator, we use GRISLI outputs that come from 4 simulations, each covers 900000 years (8 glacial-interglacial cycles) to get rid of the initial configuration influence. The simulations differ by the geothermal flux map used as boundary condition. The first results are very encouraging with a RMSE of ~ 0.6 °C (calculated for the difference between emulated temperature and GRISLI over all the samples and all the depths).

This work is performed within the framework of the ESA 4D-Antarctica project.

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