contributor author | Liao, Liang | |
contributor author | Meneghini, Robert | |
contributor author | Tokay, Ali | |
contributor author | Bliven, Larry F. | |
date accessioned | 2017-06-09T16:51:14Z | |
date available | 2017-06-09T16:51:14Z | |
date copyright | 2016/09/01 | |
date issued | 2016 | |
identifier issn | 1558-8424 | |
identifier other | ams-75322.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4217646 | |
description abstract | he focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro-/macrophysical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow-scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager/Particle Image Probe (SVI/PIP) during the winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia. | |
publisher | American Meteorological Society | |
title | Retrieval of Snow Properties for Ku- and Ka-Band Dual-Frequency Radar | |
type | Journal Paper | |
journal volume | 55 | |
journal issue | 9 | |
journal title | Journal of Applied Meteorology and Climatology | |
identifier doi | 10.1175/JAMC-D-15-0355.1 | |
journal fristpage | 1845 | |
journal lastpage | 1858 | |
tree | Journal of Applied Meteorology and Climatology:;2016:;volume( 055 ):;issue: 009 | |
contenttype | Fulltext | |