The Microwave Snow Grain Size: A New Concept to Predict Satellite Observations Over Snow‐Covered Regions. Issue 4 (4th July 2022)

• Record Type: Journal Article
• Authors: Picard, G.; Löwe, H.; Domine, F.; Arnaud, L.; Larue, F.; Favier, V.; Le Meur, E.; Lefebvre, E.; Savarino, J.; Royer, A.
• Is Part Of: AGU advances. Volume 3:Issue 4(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-07-04
• Subjects: snow -- remote sensing -- microwave -- porous media -- microstructure -- modeling; Earth sciences -- Periodicals; Space sciences -- Periodicals; 550
• DOI: 10.1029/2021AV000630
• Languages: English
• ISSNs: 2576-604X

Abstract

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 micro‐computed 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. Key Points: Microwave scattering by snow is reformulated as a function of snow physical and measurable variables only, without empirical adjustments Two new metrics, microwave grain size and polydispersity, are introduced to describe the length scale complexity of the snow microstructure The new formulation offers consistent prediction of microwave observations across many regions in the Arctic, the boreal area and Antarctica