X-Ray Tomography-Based Microstructure Representation in the Snow Microwave Radiative Transfer Model

Melody Sandells, Henning Löwe, Ghislain Picard, Marie Dumont, Richard Essery, Nicolas Floury, Anna Kontu, Juha Lemmetyinen, William Maslanka, Samuel Morin, Andreas Wiesmann, Christian Mätzler

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Abstract

The modular Snow Microwave Radiative Transfer (SMRT) model simulates microwave scattering behaviour in snow via different selectable theories and snow microstructure representations, which is well suited to intercomparisons analyses. Here, five microstructure models were parameterized from microCT and thin section images of snow samples and evaluated with SMRT. Three field experiments provided observations of scattering and absorption coefficients, brightness temperature and/or backscatter with increasing complexity of snowpack. These took place in Sodankyl¨a, Finland, and Weissfluhjoch, Switzerland. Simulations of scattering and absorption coefficients agreed
well with observations, with higher errors for snow with predominantly vertical structures. For simulation of brightness temperature, difficulty in retrieving stickiness with the Sticky Hard Sphere microstructure model resulted in relatively poor performance for two experiments, but good agreement for the third. Exponential microstructure gave generally good results, near to the best performing models for two field experiments. The Independent Sphere model gave intermediate results. New Teubner-Strey and Gaussian Random Field models demonstrated advantages of SMRT over microwave models with restricted microstructural geometry. Relative model performance are assessed by the quality of the microstructure model fit to micro-CT data and further improvements may be possible with different fitting techniques. Careful consideration of simulation stratigraphy is required in this new era of high-resolution microstructure measurement as layers thinner than the wavelength introduce artificial scattering boundaries not seen by the instrument.
Original languageEnglish
Pages (from-to)1-15
Number of pages15
JournalIEEE Transactions on Geoscience and Remote Sensing
Early online date15 Jun 2021
DOIs
Publication statusE-pub ahead of print - 15 Jun 2021

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