A Polarimetric Analysis of Ice Microphysical Processes in Snow, Using Quasi-Vertical Profiles

Abstract

This study implements a new quasi-vertical profile (QVP) methodology to investigate the microphysical evolution and significance of intriguing winter polarimetric signatures and their statistical correlations. QVPs of transitional stratiform and pure snow precipitation are analyzed using WSR-88D S-band data, alongside their corresponding environmental thermodynamic High-Resolution Rapid Refresh model analyses. QVPs of KDP and ZDR are implemented to demonstrate their value in interpreting elevated ice processes. Several fascinating and repetitive signatures are observed in the QVPs for differential reflectivity ZDR and specific differential phase KDP, in the dendritic growth layer (DGL), and at the tops of clouds. The most striking feature is maximum ZDR (up to 6 dB) in the DGL occurring near the −10-dBZ ZH contour within low KDP and during shallower and warmer cloud tops. Conversely, maximum KDP (up to 0.3° km−1) in the DGL occurs within low ZDR and during taller and colder cloud tops. Essentially, ZDR and KDP in the DGL are anticorrelated and strongly depend on cloud-top temperature. Analyses also show correlations indicating larger ZDR within lower ZH in the DGL and larger KDP within greater ZH in the DGL. The high-ZDR regions are likely dominated by growth of a mixture of highly oblate dendrites and/or hexagonal plates, or prolate needles. Regions of high KDP are expected to be overwhelmed with snow aggregates and crystals with irregular or nearly spherical shapes, seeded at cloud tops. Furthermore, QVP indications of hexagonal plate crystals within the DGL are verified using in situ microphysical measurements, demonstrating the reliability of QVPs in evaluating ice microphysics in upper regions of winter clouds.

Toward Exploring the Synergy Between Cloud Radar Polarimetry and Doppler Spectral Analysis in Deep Cold Precipitating Systems in the Arctic

“…The results of the first combined polarimetric and Doppler spectral radar measurements in precipitating deep Arctic clouds presented herein are generally in agreement with previous studies performed in midlatitude stratiform clouds using longer-wavelength radars operating at S, C, and X bands (e.g., Andrić et al, 2013;Bechini et al, 2013;Griffin et al, 2017;Kennedy & Rutledge, 2011;Moisseev et al, 2015;Schrom et al, 2015;Schrom & Kumjian, 2016;Thompson et al, 2014;Williams et al, 2015). All of these studies document notable enhancement of Z DR and/or K DP in the DGL although the Z DR and K DP signatures may not occur simultaneously and not be collocated.…”

“…For a cloud with warmer cloud top temperatures, the opposite is true: K DP is low and Z DR is high due to a larger contribution from anisotropic slow-falling ice and lower overall concentration of ice particles. Such a pattern is commonly observed in the midlatitude precipitating stratiform clouds in the cold season as well (Griffin et al, 2017). Journal of Geophysical Research: Atmospheres…”

“…A quite different interpretation has recently been proposed by Moisseev et al (2015) who claim that increased K DP is "an indicator of the onset of aggregation rather than an indicator of a dendritic growth zone". This view is shared by Griffin et al (2017), who emphasized strong anticorrelation between Z DR and K DP in the dendritic growth layer and also found a clear link between the height of the top of the cloud and the magnitudes of K DP and Z DR within the dendritic growth layer. According to Griffin et al (2017), colder cloud tops favor higher K DP resulting from high number concentration of seeding ice particles, whereas the highest values of Z DR were observed in clouds with little ice above DGL.…”

Examining Storm Asymmetries in Hurricane Irma (2017) Using Polarimetric Radar Observations

“…Dual‐polarization radar has been instrumental in improving quantitative rainfall estimation (e.g., Cifelli et al, ; Giangrande & Ryzhkov, ; Ryzhkov et al, ), hydrometeor classification (Dolan & Rutledge, ; Chandrasekar et al, ; Park et al, ; Ryzhkov et al, ; Vivekanandan et al, ), microphysical fingerprinting (Kumjian & Prat, ; Kumjian & Ryzhkov, , ; Schrom & Kumjian, ), and advancing our understanding of organized precipitation systems including supercells (e.g., Kumjian & Ryzhkov, ; Snyder et al, ), mesoscale convective systems (e.g., Zrnić et al, ), and winter storms (e.g., Griffin et al, ; Kumjian & Lombardo, ). All of these studies have focused on storm systems that occur predominantly over land.…”

10th European Conference on Radar in Meteorology and Hydrology (ERAD 2018) : 1-6 July 2018, Ede-Wageningen, The Netherlands

“…On the other hand, the magnitude of K DP in ice and snow is relatively small, particularly at longer radar wavelengths. At S band, K DP in dry ice and snow is usually smaller than 0.3 deg km -1 and typical values are below 0.05 deg km -1 in aggregated snow at warmer temperatures Griffin et al 2018). Because the mean volume diameter D m is inversely proportional to the cubic root of K DP , the fractional standard deviation of the D m estimate is proportional to the ratio 1/3 SD(K DP )/K DP ..…”