An overview of the 29 May 2012 Kingfisher supercell during DC3

Abstract

On 29–30 May 2012, the Deep Convective Clouds and Chemistry experiment observed a supercell thunderstorm on the southern end of a broken line of severe storms in Oklahoma. This study focuses on an approximately 70 min period during which three mobile Doppler radars operated and a balloon‐borne electric field meter, radiosonde, and particle imager flew through the storm. An overview of the relationships among flash rates, very high frequency (VHF) source densities, and Doppler‐radar‐derived storm parameters is presented. Furthermore, the evolution of the flash distribution relative to the midlevel storm's kinematics and microphysics is examined at two times during a period of rapid storm intensification. The timing of increases in VHF counts in the 8–10 km above ground level (agl) layer, which contained the largest VHF source counts, is similar to the timing of increases in updraft mass flux, in updraft volume, and in graupel volume at approximately 5–9 km agl. Although some increases in VHF source counts had little or no corresponding increase in one or more of the other storm parameters, at least one other parameter had an increase near the time of every VHF increase, a pattern which suggests a common dependence on updraft pulses, as expected from the noninductive graupel‐ice electrification mechanism. A classic bounded weak lightning region was observed initially during storm intensification, but late in the period it appeared to be due to a wake in the flow around the updraft, rather than due to a precipitation cascade around the updraft core as is usually observed.

Evaluation of deep convective transport in storms from different convective regimes during the DC3 field campaign using WRF‐Chem with lightning data assimilation

“…During the sampling time period, the Doppler‐derived vertical motion in the southern supercell was sustained at greater than 35 m s −1 with several updraft pulses greater than 45 m s −1 . The strongest updraft, of about 65 m s −1 , was observed at 2330 UTC [ DiGangi et al , , Figure 11]. The movement of the storm system was approximately 8.5 m s −1 toward the southeast.…”

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

“…The dielectric factor for water is used as traditional radars have no knowledge of particle type and use the factor for water for all calculations. To facilitate the comparison with the camera‐derived PSD reflectivity, the time‐spaced analyses of dual‐Doppler reflectivity fields (DiGangi et al, ) are linearly interpolated from the radar analyses to the balloon's GPS sonde time‐space location. In comparing the observed reflectivity to the total PSD‐derived reflectivity, generally close agreement (typically less than 5 dBZ) is obtained throughout the depth of the sounding (Figure ).…”

“…A summation of the individual particle masses over the number of particles leads to the total mass per particle type, from which the mixing ratio is derived with appropriate scaling of total sampling volume by the average dry air density. To provide an independent comparison against the PSD‐derived mixing ratios, the time‐dependent, 3‐D dual‐Doppler airflow and reflectivity fields were assimilated via a diabatic Lagrangian analysis or DLA (DiGangi et al, ; Ziegler, , ) that obtains time‐dependent 3‐D fields of predicted potential temperature, water vapor mixing ratio, and cloud water and cloud ice mixing ratio. The DLA diagnoses the time‐dependent, 3‐D precipitation fields of rain, graupel/hail, and snow particle mixing ratio utilizing a supercell storm simulation and partitioning functions that depend on radar reflectivity, temperature, updraft speed, and trajectory paths (DiGangi et al, ; Ziegler, , ).…”

“…To provide an independent comparison against the PSD‐derived mixing ratios, the time‐dependent, 3‐D dual‐Doppler airflow and reflectivity fields were assimilated via a diabatic Lagrangian analysis or DLA (DiGangi et al, ; Ziegler, , ) that obtains time‐dependent 3‐D fields of predicted potential temperature, water vapor mixing ratio, and cloud water and cloud ice mixing ratio. The DLA diagnoses the time‐dependent, 3‐D precipitation fields of rain, graupel/hail, and snow particle mixing ratio utilizing a supercell storm simulation and partitioning functions that depend on radar reflectivity, temperature, updraft speed, and trajectory paths (DiGangi et al, ; Ziegler, , ). The DLA utilizes an IE distribution form for rain, graupel/hail, and snow particles following the Lin‐Farley‐Orville microphysics parameterization by Gilmore et al ().…”

“…In comparison, the DLA increases steadily above 4.5 km AGL to roughly 0.4–0.6 g/kg in the 6–7 km AGL layer and decreases sharply above 7 km AGL. The DLA‐derived snow mixing ratio field is capped at Q max = 1 g/kg (DiGangi et al, ). Thus, the PSD‐derived total snow mixing ratio reveals maximum values that are roughly a factor of 2 larger than the DLA values in the 6–7 km AGL layer.…”