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Article Dans Une Revue AGU Advances Année : 2022

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

Résumé

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 depth hoar in 86 Canadian sites using ground-based observations. The value for the convex grains (0.6) compares favorably to the polydispersity calculated from 3D microcomputed tomography images for alpine grains, while values for depth hoar show wider variations (1.2-1.9) and are larger in Canada than in the Alps. Nevertheless, using one value for each grain type, the microwave observations in Antarctica and in Canada can be simulated from in-situ measurements with good accuracy with a fully physical model. These findings improve snow scattering modeling, enabling future more accurate uses of satellite observations in snow hydrological and meteorological applications. Plain Language Summary Satellites are unique tools to observe the snow cover, especially in vast remote areas. Space-borne microwave sensors provide information about snow thickness and other properties, but with large uncertainties due to a poor understanding of how microwaves interact with the snow grains. Additional uncertainties are related to the snow effective grain size, which is a crucial but loosely-defined quantity, difficult to precisely measure in the field. Here, we introduce the concept of "microwave grain size." This quantity has a clear theoretical definition and can be estimated from the product of the measurable optical grain size and a factor called polydispersity. Over 104 sites in Antarctica and Canada, we test the hypothesis that the polydispersity only depends on snow grain type, an observable quantity. The results show excellent modeling performance and yield polydispersity estimates: small values are found for rounded and faceted grains and high values are for cup-shaped crystals known as depth hoar. We explain these differences by differing degrees of microstructural arrangements. This study paves the way toward an improved use of satellite microwave remote sensing in hydrological and meteorological applications.
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Dates et versions

hal-04389380 , version 1 (11-01-2024)

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Ghislain Picard, H. Löwe, F. Domine, L. Arnaud, F. Larue, et al.. The Microwave Snow Grain Size: A New Concept to Predict Satellite Observations Over Snow‐Covered Regions. AGU Advances, 2022, 3 (4), ⟨10.1029/2021av000630⟩. ⟨hal-04389380⟩
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