Quasi-Vertical Profiles—A New Way to Look at Polarimetric Radar Data

Abstract

A novel methodology is introduced for processing and presenting polarimetric data collected by weather surveillance radars. It involves azimuthal averaging of radar reflectivity Z, differential reflectivity ZDR, cross-correlation coefficient ρhv, and differential phase ΦDP at high antenna elevation, and presenting resulting quasi-vertical profiles (QVPs) in a height-versus-time format. Multiple examples of QVPs retrieved from the data collected by S-, C-, and X-band dual-polarization radars at elevations ranging from 6.4° to 28° illustrate advantages of the QVP technique. The benefits include an ability to examine the temporal evolution of microphysical processes governing precipitation production and to compare polarimetric data obtained from the scanning surveillance weather radars with observations made by vertically looking remote sensors, such as wind profilers, lidars, radiometers, cloud radars, and radars operating on spaceborne and airborne platforms. Continuous monitoring of the melting layer and the layer of dendritic growth with high vertical resolution, and the possible opportunity to discriminate between the processes of snow aggregation and riming, constitute other potential benefits of the suggested methodology.

Precipitation and microphysical processes observed by three polarimetric X-band radars and ground-based instrumentation during HOPE

“…However, this reduction is expected to be more intense for riming than for aggregation. Riming makes the ice particles more spherical leading to a lower Z DR by 0.1-0.3 dB (Ryzhkov et al, 2016). Thus, we speculate that riming causes the "sagging" effects of Z DR and ρ HV combined with relatively low Z DR above the ML around 12:00 and 13:00 UTC.…”

“…Figure 13 shows so-called quasi-vertical profiles (QVPs) of Z H , Z DR , ρ HV and K DP based on JuXPol measurements at 18 • elevation angle between 06:00 and 14:30 UTC. QVPs were first used by Trömel et al (2014a) to reliably estimate backscatter differential phase, and Ryzhkov et al (2016) further expanded the QVP methodology and demonstrated its multiple benefits. The QVPs of polarimetric variables are obtained by azimuthal averaging of the radar data collected during conical PPIs at higher antenna elevation angles in order to reduce statistical errors of the variables and assign their average vertical profiles to a conical volume in a time-height display.…”

“…These rimed snowflakes may grow fast and reach large sizes with higher terminal velocity before they fall through the ML. Due to their enhanced terminal velocity, they melt at a lower height and lead to the "sagging" signature of the bright band in terms of Z DR and ρ HV (Ryzhkov et al, 2016).…”

Quantifying the effect of riming on snowfall using ground‐based observations

“…To compute these profiles, reflectivity and differential reflectivity measurements for each ray were averaged using range gates located within 1 km ground range of the measurement site. It should be noted that because of the availability of the range height indicator (RHI) scans, quasi‐vertical profiles [ Ryzhkov et al , ] were not used.…”

Investigation of Weather Radar Quantitative Precipitation Estimation Methodologies in Complex Orography

“…The use of quasi-VPR, when dealing with dual polarization radar variables, is a key aspect of this study. The term "quasi-VPR" actually refers to the fact that we are not looking at vertical radar observations but instead we derive vertical information by exploiting slanted paths [25]. In this study, quasi-VPRs are used to overcome the complication that would result if we attempted to perform QPEs using dual polarization estimators (i.e., using Z hh , Z dr , and K dp or a subset of them at the same time).…”