Linking snowflake microstructure to multi-frequency radar observations

Jussi Leinonen, D. Moisseev, T. Nousiainen

Research output: Contribution to journalArticleScientificpeer-review

18 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)3259-3270
Number of pages12
JournalJournal of Geophysical Research: Atmospheres
Volume118
Issue number8
DOIs
Publication statusPublished - 27 Apr 2013
MoE publication typeA1 Journal article-refereed

Keywords

  • backscattering
  • microphysics
  • radar
  • snowfall

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