Use of X-Band Differential Reflectivity Measurements to Study Shallow Arctic Mixed-Phase Clouds

Abstract

Microphysical processes in shallow Arctic precipitation clouds are illustrated using measurements of differential reflectivity ZDR from the U.S. Department of Energy Atmospheric Radiation Measurement Program polarimetric X-band radar deployed in Barrow, Alaska. X-band hemispheric range height indicator scans used in conjunction with Ka-band radar and lidar measurements revealed prolonged periods dominated by vapor depositional, riming, and/or aggregation growth. In each case, ice precipitation fell through at least one liquid-cloud layer in a seeder–feeder situation before reaching the surface. A long period of sustained low radar reflectivity ZH (<0–5 dBZ) and high ZDR (6–7.5 dB) throughout the depth of the cloud and subcloud layer, coinciding with observations of large pristine dendrites at the surface, suggests vapor depositional growth of large dendrites at low number concentrations. In contrast, ZDR values decreased to 2–3 dB in the mean profile when surface precipitation was dominated by aggregates or rimed dendrites. Small but consistent differences in zenith Ka-band radar Doppler velocity and lidar depolarization measurements were found between aggregation- and riming-dominated periods. The clean Arctic environment can enhance ZDR signals relative to more complex midlatitude cases, producing higher values.

Observing ice particle growth along fall streaks in mixed-phase clouds using spectral polarimetric radar data

“…The second term is the displacement time due to the cloud system dynamics, t dyn . The calculation of the displacement contributions t α and t dyn is done following the steps of Pfitzenmaier et al (2017). The initial condition for the retrieval algorithm (cloud base height and averaging time for the wind profiles) are set individually per case, applying the suggested method in Pfitzenmaier et al (2017).…”

“…Analyses of ice particle growth processes within mixed-phase cloud systems are primarily based on cloud radar data. Among them, Oue et al (2016) uses polarimetric radar (K a -, and X-band) and lidar measurements to study ice particle growth processes in the cloud. Kalesse et al (2016) analyzes Doppler spectra (K a -band) during a riming event and compare their findings of particle growth rates from the observations to simulations of such a riming event.…”

“…Therefore, using this radar and its configuration, it is possible to identify and study microphysical processes of ice particles within complex mixedphase clouds. On top of that, TARA measurements are rearranged along fall streaks according to the recently developed fall streak retrieval algorithm (Pfitzenmaier et al, 2017). Fall streaks are considered to be the precipitating path of a population of particles from top to bottom of the cloud system.…”

“…Fall streaks are considered to be the precipitating path of a population of particles from top to bottom of the cloud system. Therefore, the analyses of microphysical changes along the fall streaks contain information of microphysical evolution of the same particle population (Pfitzenmaier et al, 2017;Kalesse et al, 2016). The retrieval technique reconstructs the precipitation path based on the obtained TARA wind information.…”

“…Good agreement was obtained. Pfitzenmaier et al (2017) developed a retrieval algorithm to reconstruct fall streaks within the TARA measurements to improve the study of ice particle growth due to supercooled liquid water presence within the cloud system.…”