Observations of Severe Local Storms and Tornadoes with the Atmospheric Imaging Radar

Abstract

Mobile radar platforms designed for observation of severe local storms have consistently pushed the boundaries of spatial and temporal resolution in order to allow for detailed analysis of storm structure and evolution. Digital beamforming, or radar imaging, is a technique that is similar in nature to a photograwphic camera, where data samples from different spaces at the same range are collected simultaneously. This allows for rapid volumetric update rates compared to radars that scan with a single narrow beam. The Atmospheric Imaging Radar (AIR) is a mobile X-band (3.14-cm wavelength) imaging weather radar that transmits a vertical, 20° fan beam and uses a 36-element receive array to form instantaneous range–height indicators (RHIs) with a native beamwidth of 1° × 1°. Rotation in azimuth allows for 20° × 90° volumetric updates in under 6 s, while advanced pulse compression techniques achieve 37.5-m range resolution. The AIR has been operational since 2012 and has collected data on tornadoes and supercells at ranges as close as 6 km, resulting in high spatial and temporal resolution observations of severe local storms. The use of atmospheric imaging is exploited to detail rapidly evolving phenomena that are difficult to observe with traditional scanning weather radars.

Observations of a Cold Front at High Spatiotemporal Resolution Using an X-Band Phased Array Imaging Radar

“…As opposed to the standard 5.25 µs waveform used by the AIR for studies of severe local storms [56], a 13.25 µs pulse was developed for use on transmit. This waveform offers an approximate 4 dB gain in SNR.…”

“…Due to a 2% duty cycle limitation, the PRT was chosen to be 757 µs, corresponding to a Nyquist velocity of 10.4 m·s −1 . Digital beamforming offers several advantages over more traditional 'pencil-beam' radar VCPs, mainly in generating simultaneous RHIs, such that vertical advection is not an issue [47,48,56,57]. Additionally, the AIR offers significant processing flexibility (adjustable temporal sampling and beamforming type for sensitivity and clutter mitigation).…”

Adaptive Beamspace Processing for Phased-Array Weather Radars

“…It is important to test the adaptive beamspace processing with real data collected in the field to ensure that it can still function when some of the assumptions in the simulator may be violated. An ideal instrument to collect data to evaluate adaptive beamspace processing is The University of Oklahoma's AIR [38], [39]. The AIR is a mobile X-band weather radar that transmits a 20 • vertical fan beam and utilizes a ULA consisting of 36 receiving elements.…”

“…Section III describes the simulation setup and presents simulation results that show the superior performance of adaptive beamspace processing. Section IV shows the performance of the proposed algorithm on real data collected by the Atmospheric Imaging Radar (AIR) [38], [39]. A summary of this paper and suggestions for future work are presented last.…”

Mobile Radar Observations of the Evolving Debris Field Compared with a Damage Survey of the Shawnee, Oklahoma, Tornado of 19 May 2013

“…structure of tornadoes such as suction vortices and improved definition of the low-level wind field (e.g., Wurman and Gill 2000;Bluestein et al 2004Bluestein et al , 2007aBluestein et al , 2015Bluestein et al , 2019Lee and Wurman 2005;Kosiba and Wurman 2010;Wakimoto et al 2011;Wurman and Kosiba 2013;Wurman et al 2013Wurman et al , 2014Kurdzo et al 2017). More recently, discrimination between hydrometeors and regions of lofted debris is possible with the addition of polarimetric measurements (e.g., Ryzhkov et al 2005;Bluestein et al 2007bBluestein et al , 2015Bluestein et al , 2019Kumjian and Ryzhkov 2008;Bodine et al 2013Bodine et al , 2014Snyder and Bluestein 2014;Kurdzo et al 2015;Tanamachi et al 2012;Wakimoto et al 2015Wakimoto et al , 2016Mahre et al 2018). The tornadic debris signature (TDS) was first proposed by Ryzhkov et al (2005) 1 to approximately delineate lofted debris based on high equivalent radar reflectivity factor, 2 low differential radar reflectivity (Z DR ), and low cross-correlation coefficient (r hv ) that are collocated with the tornadic rotational couplet observed in radial velocity.…”