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contributor authorBukovčić, Petar
contributor authorRyzhkov, Alexander
contributor authorZrnić, Dusan
contributor authorZhang, Guifu
date accessioned2019-09-19T10:06:15Z
date available2019-09-19T10:06:15Z
date copyright9/29/2017 12:00:00 AM
date issued2017
identifier otherjamc-d-17-0090.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261567
description abstractAbstractAccurate measurements of snow amounts by radar are very difficult to achieve. The inherent uncertainty in radar snow estimates that are based on the radar reflectivity factor Z is caused by the variability of snow particle size distributions and snow particle density as well as the large diversity among snow growth habits. In this study, a novel method for snow quantification that is based on the joint use of radar reflectivity Z and specific differential phase KDP is introduced. An extensive dataset of 2D-video-disdrometer measurements of snow in central Oklahoma is used to derive polarimetric relations for liquid-equivalent snowfall rate S and ice water content IWC in the forms of bivariate power-law relations S = and along with similar relations for the intercept N0s and slope ?s of the exponential snow size distribution. The physical basis of these relations is explained. Their multipliers are sensitive to variations in the width of the canting angle distribution and to a lesser extent the particles? aspect ratios and densities, whereas the exponents are practically invariant. This novel approach is tested against the S(Z) relation using snow disdrometer measurements in three geographical regions (Oklahoma, Colorado, and Canada). Significant improvement in snow estimates relative to the traditional Z-based methods is demonstrated.
publisherAmerican Meteorological Society
titlePolarimetric Radar Relations for Quantification of Snow Based on Disdrometer Data
typeJournal Paper
journal volume57
journal issue1
journal titleJournal of Applied Meteorology and Climatology
identifier doi10.1175/JAMC-D-17-0090.1
journal fristpage103
journal lastpage120
treeJournal of Applied Meteorology and Climatology:;2017:;volume 057:;issue 001
contenttypeFulltext


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