How dual‐polarization radar observations can be used to verify model representation of secondary ice

Abstract

In this paper it is discussed how dual‐polarization radar observations can be used to verify model representations of secondary ice production. An event where enhanced specific differential phase, Kdp, signatures in snow occur at the altitudes where temperatures lie in the range between −8 and −3°C is investigated. By combining radar and surface‐based precipitation observations it is shown that these dual‐polarization radar signatures are most likely caused by ice with concentrations exceeding those expected from primary ice parameterizations. It is also shown that the newly formed ice particles readily aggregate, which may explain why Kdp values seem to be capped at 0.2–0.3°/km for a C band radar. For the event of interest, multiple high‐resolution (1 km) Weather Research and Forecasting (WRF) model simulations are conducted. When the default versions of the Morrison microphysics schemes were used, the simulated number concentration of frozen hydrometeors is much lower than observed and the simulated ice particle concentrations are comparable with values expected from primary ice parameterizations. Higher ice concentrations, which exceed values expected from primary ice parameterizations, were simulated when ad hoc thresholds for rain and cloud water mixing ratio in the Hallett‐Mossop part of the Morrison scheme were removed. These results suggest that the parameterization of secondary ice production in operational weather prediction models needs to be revisited and that dual‐polarization radar observations, in conjunction with ancillary observations, can be used to verify them.

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

“…The signature of needle and/or columnar crystals in a temperature range from À8 to À3°C, where ice particles seeded in the MPL and secondary ice formation via the Hallett-Mossop ice multiplication mechanism (Hallett & Mossop, 1974) could be active, is often observed in Arctic mixed-phase clouds in linear depolarization ratio measurements . Similar signatures were observed in midlatitude winter storms and convective systems (e.g., Giangrande, Toto, Bansemer, et al, 2016;Kumjian et al, 2016;Kumjian & Lombardo, 2017;Sinclair et al, 2016;Zawadzki et al, 2001). Kumjian et al (2016) observed K DP enhancements produced by needle and columnar crystals in secondary ice formation regions.…”

“…Schrom et al (2015) suggested a polarimetric technique to separate contributions from aggregates and dendrites in the DGL of midlatitude winter storms. Polarimetric signatures of the secondary ice mixed with aggregated and rimed snow in layers with temperature around À5°C were found by cloud and precipitation radar measurements in high-latitude deeper snow clouds Sinclair et al, 2016), midlatitude mesoscale convective systems Kumjian et al, 2016), and midlatitude snowstorms (Kumjian & Lombardo, 2017). However, combining polarimetric measurements with the analysis of Doppler spectra yields a much better chance to identify and separate different types of ice, and to quantify their amounts if their corresponding fall velocities are associated with separate peaks in the Doppler spectrum.…”

Radiative Effects of Secondary Ice Enhancement in Coastal Antarctic Clouds

“…Sinclair et al (2016) found a similar result when modeling a frontal cloud over Finland with WRF, where model results compared best with radar-derived N ice with similar H-M changes. Sinclair et al (2016) found a similar result when modeling a frontal cloud over Finland with WRF, where model results compared best with radar-derived N ice with similar H-M changes.…”

Unsupervised classification of vertical profiles of dual polarization radar variables

“…By identifying particle types in observations, we may conclude what processes took place. Currently, dual-polarization radar observations are used in fuzzy logic classification to identify the dominant hydrometeor type present in a radar volume (e.g., Chandrasekar et al, 2013;Thompson et al, 2014). Such methods work very well for classification of hydrometeors of summer precipitations and some features of winter precipitation types.…”