Linking snowflake microstructure to multi-frequency radar observations
Article first published online: 19 APR 2013
©2013. American Geophysical Union. All Rights Reserved.
Journal of Geophysical Research: Atmospheres
Volume 118, Issue 8, pages 3259–3270, 27 April 2013
How to Cite
2013), Linking snowflake microstructure to multi-frequency radar observations, J. Geophys. Res. Atmos., 118, 3259–3270, doi:10.1002/jgrd.50163., , and (
- Issue published online: 22 MAY 2013
- Article first published online: 19 APR 2013
- Accepted manuscript online: 22 FEB 2013 01:33PM EST
- Manuscript Accepted: 4 JAN 2013
- Manuscript Revised: 14 DEC 2012
- Manuscript Received: 21 SEP 2012
- Academy of Finland. Grant Numbers: 125180, 128255, 128328
Vol. 118, Issue 12, 6708–6709, Article first published online: 28 JUN 2013
 Spherical or spheroidal particle shape models are commonly used to calculate numerically the radar backscattering properties of aggregate snowflakes. A more complicated and computationally intensive approach is to use detailed models of snowflake structure together with numerical scattering models that can operate on arbitrary particle shapes. Recent studies have shown that there can be significant differences between the results of these approaches. In this paper, an analytical model, based on the Rayleigh-Gans scattering theory, is formulated to explain this discrepancy in terms of the effect of discrete ice crystals that constitute the snowflake. The ice crystals cause small-scale inhomogeneities whose effects can be understood through the density autocorrelation function of the particle mass, which the Rayleigh-Gans theory connects to the function that gives the radar reflectivity as a function of frequency. The derived model is a weighted sum of two Gaussian functions. A term that corresponds to the average shape of the particle, similar to that given by the spheroidal shape model, dominates at low frequencies. At high frequencies, that term vanishes and is gradually replaced by the effect of the ice crystal monomers. The autocorrelation-based description of snowflake microstructure appears to be sufficient for multi-frequency radar studies. The link between multi-frequency radar observations and the particle microstructure can thus be used to infer particle properties from the observations.