Observations of tornado-scale processes using a novel rapid-scan, polarimetric, mobile, Doppler radar

Mobile radar observations of tornadoes have been acquired since the mid-1990's, and spatial resolution used to examine tornado-scale processes has been steadily improving over this time. However, attempts have been made to increase the temporal resolution of mobile radar data acquisition only in the past few years. Because tornadoes form over timescales on the order of 10 s, improved temporal resolution is critical for understanding the processes involved with tornadogenesis. In order for a mobile radar to observe tornado-scale processes ideally, including tornadogenesis, it must be capable of resolving such processes both spatially and temporally. Unfortunately, designing such an instrument conventionally has been a difficult task to accomplish.

Despite over 4 decades of tornado studies, the exact sequence of events just prior to and during tornadogenesis has evaded scientists. On 24 May 2011, in Central Oklahoma, a new mobile Rapid-Scan X-band polarimetric (RaXPol) radar successfully collected a dataset of sufficient temporal (15-sec volumes) and spatial (1° beamwidth, 75 m gate spacing) resolution to observe tornadogenesis and intensification of the tornado to EF-5 strength. The evolution of the strength and size of the velocity couplet (maximum outbound – maximum inbound Doppler velocity) associated with the tornado and parent mesocyclone is investigated to determine how the rotation associated with the tornado reaches the surface, and how the rotation behaves over time and height while the tornado is intensifying. Changes in tornado structure based off the polarimetric variables are also investigated. Finally, the rapid evolution of storm kinematics acquired by dual-Doppler analysis from two rapid-scan radars during four minutes encompassing tornadogenesis is considered. From this study, we hope to illuminate more clearly the sequence of events just prior to and during tornadogenesis in order to advance scientific understanding of this process and to hypothesize forecasting improvements and decision modifications that could be made with such knowledge.