Rapid-Scan, Polarimetric, Doppler Radar Observations of Tornadogenesis and Tornado Dissipation in a Tornadic Supercell: The “El Reno, Oklahoma” Storm of 24 May 2011*

Abstract

On 24 May 2011, a mobile, rapid-scan, X-band, polarimetric, Doppler radar (RaXPol) collected data on a supercell as it produced two tornadoes near El Reno, Oklahoma. The first tornado, rated an EF-3, was documented from intensification to decay, and the genesis and intensification of a second tornado that was rated an EF-5 was subsequently also documented. The objective of this study is to examine the spatiotemporal evolution of the rotation associated with the tornadoes (i) as the first tornado weakened to subtornadic intensity and (ii) as the second tornado formed and intensified. It is found that weakening did not occur monotonically. The transition from tornadic to subtornadic intensity over the depth of the radar volume (~4 km) occurred in less than 30 s, but this behavior is contingent upon the threshold for Doppler shear used to define the tornado. Similarly, the onset of a tornadic-strength Doppler velocity couplet occurred within a 30-s period over all elevations. Additionally, the evolution of storm-scale features associated with tornado dissipation and tornadogenesis is detailed. These features evolved considerably over relatively short time intervals (1–4 min). It is shown that during the transition period between the two tornadoes, two mesocyclones were present, but neither the tornadoes nor the mesocyclones evolved in a manner entirely consistent with any published conceptual model of supercell cycling, although certain aspects were similar to classic conceptual models. The mesocyclone and the tornado evolved differently from each other, in a manner that resembles a hybrid between the occluding and nonoccluding cyclic mesocyclogenesis models presented by Adlerman and Droegemeier.

A Finescale Radar Examination of the Tornadic Debris Signature and Weak-Echo Reflectivity Band Associated with a Large, Violent Tornado

“…Although beam smearing increases the effective beamwidth to 1.48-1.58, the data are oversampled every 1.18. For the majority of the data examined in this study, the Nyquist velocity was between 30 and 33 m s 21 , depending upon the specific scanning strategy employed, and the range resolution was 75 m, oversampled every 15 m, except for the first several minutes when range resolution was 150 m, oversampled every 75 m. For more details about RaXPol and the details of this dataset, the reader is referred to Pazmany et al (2013) and Houser et al (2015), respectively.…”

“…2 The range to the tornado at this time was about 12 km, and at the analyzed elevation angle of 48, the beam height was approximately 880 m above radar level. 3 Here and in Houser et al (2015), the vortex was considered ''subtornadic'' when the maximum difference between inbound and outbound Doppler velocities (DV max ) decreased below 50 m s 21 . While this criterion is higher than others found in the literature, the observations were taken at 650-750 m ARL while others use lower velocity thresholds for observations taken at heights closer to the ground.…”

“…When studying atmospheric phenomena that evolve quickly [e.g., ;O(10) s] such as tornadoes, it is imperative to be able to retrieve volumetric data rapidly in order to resolve the processes associated with the evolving structures and kinematics. Recent studies have concluded that rapidly evolving features such as secondary (or internal) rearflank momentum surges (e.g., Marquis et al 2012;Kosiba et al 2013;Skinner et al 2014;Schenkman et al 2014;Kurdzo et al 2015), descending reflectivity cores (Rasmussen et al 2006;Kennedy et al 2007;Byko et al 2009), and rapidly evolving low-level vortices/ mesocyclones (Skinner et al 2014;Houser et al 2015; likely play a role in the processes associated with tornadogenesis, maintenance., intensification, and/or decay. Thus, the implementation of rapid-scan technology onto mobile platforms is showing promise for improving scientific understanding of tornadoes Isom et al 2013;Wurman et al 2014;Houser et al 2015) and even for aiding the development of applications relevant to operational forecasting (e.g., Tanamachi and Heinselman 2016).…”

“…Visual observations suggest that tornadoes can undergo rapid changes in the size and shape of both the funnel cloud and the debris field (e.g., Houser et al 2015;Wakimoto et al 2016). Certain features apparent in the debris structure may be tied to dynamically and kinematically important storm-scale features such as secondary (internal) rear-flank momentum surges (Kurdzo et al 2015).…”

Automated Detection of Polarimetric Tornadic Debris Signatures Using a Hydrometeor Classification Algorithm

“…Doppler weather radar has proven to be an effective tool for the detection of tornadoes (e.g., Zrni c et al 1977;Zrni c and Istok 1980;Bluestein and Unruh 1989;Bluestein et al 1993;Wurman and Gill 2000;French et al 2009;Tanamachi et al 2012;Houser et al 2015). Scattering of radar-emitted electromagnetic radiation by debris lofted within tornadoes can produce distinct structures in radar fields that may confirm to operational meteorologists that a tornado is occurring.…”