In Situ Microphysical Observations of the 29–30 May 2012 Kingfisher, OK, Supercell With a Balloon‐Borne Video Disdrometer

Abstract

The microphysical characteristics of deep convective storms are a critically important, yet difficult aspect of storm morphology to observe in situ. These observations play a large role in several areas of ongoing research, but detailed observations in key portions of clouds do not exist with the currently available measurement platforms. To facilitate these observations, a balloon‐borne particle imaging device known as the PArticle Size, Image, and Velocity (PASIV) probe was developed at the National Severe Storms Laboratory, which is capable of measuring particle counts on scales as small as 50 m. The videosonde observations from the PASIV showed that precipitation particle counts change rapidly between analysis layers, sometimes by as much as a few orders of magnitude (102–104 in adjacent layers), and radar reflectivities calculated directly from observed particle size distributions agree with mobile radar measurements. Furthermore, the observations allow the distributions to be partitioned into various particle types, which sheds light on which particles are dominating the radar signal at various times. These distributions per particle type, and their associated mixing ratios, agree with independent model analysis. Additionally, single‐, double‐, and triple‐moment parameterized particle size distribution functions are fit to various layers, with the general result that ice particles are easily represented by exponential distributions while rain is better fit with a gamma distribution. The parametric fits for ice and rain distributions found here support previous work and some portions of modeled microphysics, but also suggest room for improvement when deciding which schemes to use with cloud modeling.

In Situ Microphysical Observations of a Multicell Storm Using a Balloon‐Borne Video Disdrometer During Deep Convective Clouds and Chemistry

“…The overall PASIV design and operation has been extensively covered in Waugh et al (2015), Waugh (), and Waugh et al (), along with details regarding the image‐processing program and the particle classifications. Given this, only a brief description is presented here for the sake of the reader.…”

“…Image of the PASIV, adapted from Waugh et al (). (a) Side video of the body construction with indicated camera, Parsivel, and LED battery locations; (b) a detailed view of the particle intake and deflection fins to reduce particle splashing; (c) a top‐down view into the illuminated particle viewing chamber, where the HD camera is directed into the chamber from the “top” of the image; (d) a schematic drawing of the PASIV from (a).…”

“…Regular ice also serves as a generic category for any ice particles that are not clearly identifiable as either graupel/hail or irregular ice particles. The four precipitation particle classification categories and the design and training of the random forest hydrometeor classification method are discussed in detail in Waugh () and Waugh et al ().…”

“…The PASIV has been utilized in a number of storm environments, including supercells (Waugh et al, ), and was a component of the Oklahoma‐Texas venue observations during the Deep Convective Clouds and Chemistry (DC3) experiment (Barth et al, ). One of the storms sampled during the DC3 experiment was a multicell cluster of storms loosely resembling a large stratiform region with embedded updrafts on 21 June 2012.…”

Introduction to the Deep Convective Clouds and Chemistry (DC3) 2012 Studies

“…Journal of Geophysical Research: Atmospheres 2.7. Cloud Structure Analyses of cloud physical properties were conducted using aircraft measurements of cloud particle size distributions (Stith et al, 2016) and water vapor (Diao et al, 2017), as well as balloon-borne video disdrometer (Waugh et al, 2018). The recently developed balloon-borne microphysics probe can provide observations at fine scales and give calculated cloud particle mixing ratios and reflectivity in agreement with radar and cloud-resolving, kinematic model results.…”