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

Journal of the Meteorological Society of Japan. Ser. II

Venkatachalam CHANDRASEKAR¹  Dong-Ryul LEE³  Dmitri MOISSEEV²  Sanghun LIM³ 

[1] Colorado State University, Fort Collins, CO, USA;University of Helsinki, Helsinki, Finland;Korea Institute of Construction Technology, Ilsan, Korea

关键词: weather radar;    classification;    quantification;    snow;   

DOI  :  10.2151/jmsj.2013-603

学科分类：大气科学

来源: Meteorological Society of Japan

【 摘 要 】

 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 argued that by using the proposed snow-type identification methodology, it is possible to guide the choice of the particular parameters of power law relations of equivalent radar reflectivity factor-liquid 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 proposed quantitative snowfall estimation algorithm is illustrated using an example of the data collected from the C-band operational Helsinki Vantaa radar and ground instruments (Vaisala PWD-11, Pluvio).

【 授权许可】

Unknown