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Abstract The potential of millimeter-wavelength radar-based ice water content (IWC) estimation is demonstrated using a Ka-band Scanning Polarimetric Radar (KASPR) for the U.S. northeast coast winter storms. Two IWC relations for Ka-band polarimetric radar measurements are proposed: one that uses a combination of the radar reflectivityZand the estimated total number concentration of snow particlesN_tand the other based on the joint use ofZ, specific differential phaseK_DP, and the degree of rimingf_rim. A key element of the algorithms is to obtain the “Rayleigh-equivalent” value ofZmeasured at the Ka band, i.e., the correspondingZat a longer radar wavelength for which Rayleigh scattering takes place. This is achieved via polarimetric retrieval of the mean volume diameterD_mand incorporating the relationship between the dual-wavelength ratio DWR_S/KaandD_m. Those techniques allow for retrievals from single millimeter-wavelength radar measurements and do not necessarily require the dual-wavelength ratio (DWR) measurements, if the DWR–D_mrelation and Rayleigh assumption for Ka-bandK_DPare valid. Comparison between the quasivertical profile product obtained from KASPR and the columnar vertical profile product generated from the nearby WSR-88D S-band radar measurements demonstrates that the DWR_S/Kacan be estimated from the two close radars without the need for collocated radar beams and synchronized antenna scanning and can be used for determining the Rayleigh-equivalent value ofZ. The performance of the suggested techniques is evaluated for seven winter storms using surface disdrometer and snow accumulation measurements. Significance StatementIce water content (IWC) estimation using millimeter-wavelength radar measurements has been challenging for decades, because of the complexity of snow particle properties and size, which can cause complex scattering at the shorter radar wavelengths. The suggested polarimetric techniques overcome this difficulty via utilizing specific differential phaseK_DPwhich is higher at millimeter wavelengths than at centimeter wavelengths. This study proposes new IWC relationships for Ka-band polarimetric radar measurements and evaluates them using a Ka-band Scanning Polarimetric Radar (KASPR) and a nearby NEXRAD (S-band) polarimetric radar for the U.S. northeast coast winter storms. The proposed techniques can be applied to other millimeter-wavelength radars and shed light on the millimeter-wavelength polarimetric radar IWC estimation. 

Abstract This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed K dp and Z DR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using Z DR and K dp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals. significance statement Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting. 

Abstract The intrinsic uncertainty of radar-based retrievals in snow originates from a large diversity of snow growth habits, densities, and particle size distributions, all of which can make interpreting radar measurements of snow very challenging. The application of polarimetric radar for snow measurements can mitigate some of these issues. In this study, a novel polarimetric method for quantification of the extinction coefficient and visibility in snow, based on the joint use of radar reflectivity at horizontal polarization Z and specific differential phase K DP , is introduced. A large 2D-video-disdrometer snow dataset from central Oklahoma is used to derive a polarimetric bivariate power-law relation for the extinction coefficient, . The relation is derived for particle aspect ratios ranging from 0.5 to 0.8 and the width of the canting angle distribution ranging from 0° to 40°, values typical of aggregated snow, and validated via theoretical and analytical derivations/simulations. The multiplier of the relation is sensitive to variations in particles’ densities, the width of the canting angle distribution, and particles’ aspect ratios, whereas the relation’s exponents are practically invariant to changes in the latter two parameters. This novel approach is applied to polarimetric S-band WSR-88D data and verified against previous studies and in situ measurements of the extinction coefficient for four snow events in the eastern United States. The polarimetric radar estimates of the extinction coefficient exhibit smaller biases in comparison to previous studies concerning the ground measurements. The results indicate that there is good potential for reliable radar estimates of visibility from polarimetric weather radars, a parameter inversely proportional to the extinction coefficient. 

Abstract In a 2018 paper by Bukovčić et al., polarimetric bivariate power-law relations for estimating snowfall rate S and ice water content (IWC), and , were developed utilizing 2D video disdrometer snow measurements in Oklahoma. Herein, these disdrometer-based relations are generalized for the range of particle aspect ratios from 0.5 to 0.8 and the width of the canting angle distribution from 0° to 40° and are validated via analytical/theoretical derivations and simulations. In addition, a novel S ( K DP , Z dr ) polarimetric relation utilizing the ratio between specific differential phase K DP and differential reflectivity Z dr , , is derived. Both K DP and are proportionally affected by the ice particles’ aspect ratio and width of the canting angle distribution; therefore, the variables’ ratio tends to be almost invariant to the changes in these parameters. The S ( K DP , Z ) and S ( K DP , Z dr ) relations are applied to the polarimetric S-band WSR-88D data obtained from three geographical locations in Virginia, Oklahoma, and Colorado, and their performance is compared with estimations from the standard S ( Z ) relations and ground snow measurements. The polarimetric estimates of snow accumulations from the three cases exhibit smaller bias in comparison with the S ( Z ), indicating good potential for more reliable radar snow measurements.