Relating optical and microwave grain metrics of snow: the relevance of grain shape

Grain shape is commonly understood as a morphological characteristic of snow that is independent of the optical diameter (or specific surface area) influencing its physical properties. In this study we use tomography images to investigate two objectively defined metrics of grain shape that naturally...

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Bibliographic Details
Main Authors: Q. Krol, H. Löwe
Format: Article
Language:English
Published: Copernicus Publications 2016-11-01
Series:The Cryosphere
Online Access:http://www.the-cryosphere.net/10/2847/2016/tc-10-2847-2016.pdf
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Summary:Grain shape is commonly understood as a morphological characteristic of snow that is independent of the optical diameter (or specific surface area) influencing its physical properties. In this study we use tomography images to investigate two objectively defined metrics of grain shape that naturally extend the characterization of snow in terms of the optical diameter. One is the curvature length <i>λ</i><sub>2</sub>, related to the third-order term in the expansion of the two-point correlation function, and the other is the second moment <i>μ</i><sub>2</sub> of the chord length distributions. We show that the exponential correlation length, widely used for microwave modeling, can be related to the optical diameter and <i>λ</i><sub>2</sub>. Likewise, we show that the absorption enhancement parameter <i>B</i> and the asymmetry factor <i>g</i><sup>G</sup>, required for optical modeling, can be related to the optical diameter and <i>μ</i><sub>2</sub>. We establish various statistical relations between all size metrics obtained from the two-point correlation function and the chord length distribution. Overall our results suggest that the characterization of grain shape via <i>λ</i><sub>2</sub> or <i>μ</i><sub>2</sub> is virtually equivalent since both capture similar aspects of size dispersity. Our results provide a common ground for the different grain metrics required for optical and microwave modeling of snow.
ISSN:1994-0416
1994-0424