skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Polarimetric Radar Relations for Quantification of Snow Based on Disdrometer Data

Abstract

Accurate 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 = $$γ_1K^{α_1}_{DP}Z^{β_1}$$ and $$IWC = γ_2K^{α_2}_{DP}Z^{β_2}$$, along with similar relations for the intercept N0s and slope Λs 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). Finally, significant improvement in snow estimates relative to the traditional Z-based methods is demonstrated.

Authors:
 [1];  [2];  [3];  [4]
  1. NOAA/National Severe Storms Laboratory, and Cooperative Institute for Mesoscale Meteorological Studies, and School of Meteorology, and Advanced Radar Research Center, University of Oklahoma, Norman, Oklahoma
  2. Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma
  3. NOAA/National Severe Storms Laboratory, Norman, Oklahoma
  4. School of Meteorology, and Advanced Radar Research Center, University of Oklahoma, Norman, Oklahoma
Publication Date:
Research Org.:
Univ. of Oklahoma, Norman, OK (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1416478
Alternate Identifier(s):
OSTI ID: 1541811
Grant/Contract Number:  
Grant DE-SC0008811; SC0008811
Resource Type:
Published Article
Journal Name:
Journal of Applied Meteorology and Climatology
Additional Journal Information:
Journal Name: Journal of Applied Meteorology and Climatology Journal Volume: 57 Journal Issue: 1; Journal ID: ISSN 1558-8424
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; meteorology & atmospheric sciences; precipitation; snow; cloud microphysics; in situ atmospheric observations

Citation Formats

Bukovčić, Petar, Ryzhkov, Alexander, Zrnić, Dusan, and Zhang, Guifu. Polarimetric Radar Relations for Quantification of Snow Based on Disdrometer Data. United States: N. p., 2018. Web. doi:10.1175/JAMC-D-17-0090.1.
Bukovčić, Petar, Ryzhkov, Alexander, Zrnić, Dusan, & Zhang, Guifu. Polarimetric Radar Relations for Quantification of Snow Based on Disdrometer Data. United States. doi:10.1175/JAMC-D-17-0090.1.
Bukovčić, Petar, Ryzhkov, Alexander, Zrnić, Dusan, and Zhang, Guifu. Wed . "Polarimetric Radar Relations for Quantification of Snow Based on Disdrometer Data". United States. doi:10.1175/JAMC-D-17-0090.1.
@article{osti_1416478,
title = {Polarimetric Radar Relations for Quantification of Snow Based on Disdrometer Data},
author = {Bukovčić, Petar and Ryzhkov, Alexander and Zrnić, Dusan and Zhang, Guifu},
abstractNote = {Accurate 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 = $γ_1K^{α_1}_{DP}Z^{β_1}$ and $IWC = γ_2K^{α_2}_{DP}Z^{β_2}$, along with similar relations for the intercept N0s and slope Λs 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). Finally, significant improvement in snow estimates relative to the traditional Z-based methods is demonstrated.},
doi = {10.1175/JAMC-D-17-0090.1},
journal = {Journal of Applied Meteorology and Climatology},
number = 1,
volume = 57,
place = {United States},
year = {2018},
month = {1}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1175/JAMC-D-17-0090.1

Citation Metrics:
Cited by: 2 works
Citation information provided by
Web of Science

Figures / Tables:

FIG. 1 FIG. 1: Summary of $Z(S)$ relations for dry snowlisted in the literature and utilized by the WSR-88D network in the United States.

Save / Share: