Classification and Quantification of Snow Based on Spatial Variability of Radar Reflectivity

Abstract

In this study, a classification methodology of snow particle types, i.e., crystals, aggregates, rimed snow, and graupel, by using spatial variability of the equivalent radar reflectivity factor is proposed. The methodology is formulated on the basis of the analysis of vertically pointing Doppler radar, scanning dual-polarization weather radar, and supporting surface observations. It is arguedthat by using the proposedsnow-type identification methodology, it is possible to guide the choice of the particular parameters of power law relations of equivalent radar reflectivity factorliquid equivalent snowfall rate. The validity of the classification results are demonstrated by comparing the classification output to Vaisala WXT observations, which can be used to detect presence of high-density particles in snow. The performance of the proposedquantitative snowfall estimation algorithm is illustratedusing an example of the d ata collectedfrom the C-bandoperational Helsinki Vantaa rad ar andgroundinstruments (Vaisala PWD-11, Pluvio).