The Microwave Snow Grain Size: A New Concept to Predict Satellite Observations Over Snow‐Covered Regions

International audience Snow is a random heterogeneous medium composed of ice, air and possibly water and impurities. All its physical properties depend not only on the properties of these constituent materials but also on their geometrical arrangement at the micrometer scale, the so called microstru...

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Bibliographic Details
Published in:AGU Advances
Main Authors: Picard, Ghislain, Löwe, H., Domine, F., Arnaud, L., Larue, F., Favier, V., Le Meur, E., Lefebvre, E., Savarino, J., Royer, A.
Other Authors: Université Grenoble Alpes (UGA), Université Joseph Fourier - Grenoble 1 (UJF), University of Sheffield Sheffield, Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Takuvik Joint International Laboratory ULAVAL-CNRS, Université Laval Québec (ULaval)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Centre d'Applications et de Recherches en TELédétection Sherbrooke (CARTEL), Département de géomatique appliquée Sherbrooke (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS), Centre d'Etudes Nordiques (CEN), Université Laval Québec (ULaval)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2022
Subjects:
Online Access:https://hal.science/hal-04389380
https://hal.science/hal-04389380/document
https://hal.science/hal-04389380/file/picard_2022_microwave_grain_size.pdf
https://doi.org/10.1029/2021av000630
Description
Summary:International audience Snow is a random heterogeneous medium composed of ice, air and possibly water and impurities. All its physical properties depend not only on the properties of these constituent materials but also on their geometrical arrangement at the micrometer scale, the so called microstructure (Torquato, 2002). This applies in particular to the electromagnetic properties that control the propagation of waves in snow, such as the scattering and absorption coefficients. Scattering in snow is caused by the dielectric contrast between air and ice, and its amplitude highly depends on the length scales of the microstructure. The "snow grain size" is an intuitive property commonly estimated in the field (Fierz et al., 2009). However, it is loosely defined from a geometrical point of view because snow crystals often have very complex shapes, leading to imprecise and subjective measurements. Moreover this single metric is insufficient to fully describe all the length scales. Finding a rigorous mathematical representation Abstract Satellite observations of snow-covered regions in the microwave range have the potential to retrieve essential climate variables such as snow height. This requires a precise understanding of how microwave scattering is linked to snow microstructural properties (density, grain size, grain shape and arrangement). This link has so far relied on empirical adjustments of the theories, precluding the development of robust retrieval algorithms. Here we solve this problem by introducing a new microstructural parameter able to consistently predict scattering. This "microwave grain size" is demonstrated to be proportional to the measurable optical grain size and to a new factor describing the chord length dispersion in the microstructure, a geometrical property known as polydispersity. By assuming that the polydispersity depends on the snow grain type only, we retrieve its value for rounded and faceted grains by optimization of microwave satellite observations in 18 Antarctic sites, and for ...