Abstract X-band and shorter radar wavelengths are preferable for mobile radar systems because a narrow beam can be realized with a moderately sized antenna. However, attenuation by precipitation becomes progressively more severe with decreasing radar wavelength. As a result, X band has become a popular choice for meteorological radar systems that balances these two considerations. Dual-polarization provides several methods by which this attenuation (and differential attenuation) can be detected and corrected, mitigating one of the primary disadvantages of X-band radars. The dynamics of severe convective storms depend, to some extent, on the distribution and type of hydrometeors within the storm. To estimate the three-dimensional distribution of hydrometeors using X-band radar data, it is necessary to correct for attenuation before applying commonly used hydrometeor classification algorithms. Since 2002, a mobile dual-polarized Doppler weather radar designed at the University of Massachusetts, Amherst has ...

Attenuation correction and hydrometeor classification of high-resolution, X-band, dual-polarized mobile radar measurements in severe convective storms

Mobile weather radars often utilize rapid-scan strategies when collecting observations of severe weather. Various techniques have been used to improve volume update times, including the use of agile and multibeam radars. Imaging radars, similar in some respects to phased arrays, steer the radar beam in software, thus requiring no physical motion. In contrast to phased arrays, imaging radars gather data for an entire volume simultaneously within the field of view (FOV) of the radar, which is defined by a broad transmit beam. As a result, imaging radars provide update rates significantly exceeding those of existing mobile radars, including phased arrays. The Advanced Radar Research Center (ARRC) at the University of Oklahoma (OU) is engaged in the design, construction, and testing of a mobile imaging weather radar system called the atmospheric imaging radar (AIR). Initial tests performed with the AIR demonstrate the benefits and versatility of utilizing beamforming techniques to achieve high spatial...

The Atmospheric Imaging Radar: Simultaneous Volumetric Observations Using a Phased Array Weather Radar

This study investigates the use of tornadic debris signature (TDS) parameters to estimate tornado damage severity using Norman, Oklahoma (KOUN), polarimetric radar data (polarimetric version of the Weather Surveillance Radar-1988 Doppler radar). Several TDS parameters are examined, including parameters based on the 10th or 90th percentiles of polarimetric variables (lowest tilt TDS parameters) and TDS parameters based on the TDS volumetric coverage (spatial TDS parameters). Two highly detailed National Weather Service (NWS) damage surveys are compared to TDS parameters. The TDS parameters tend to be correlated with the enhanced Fujita scale (EF) rating. The 90th percentile reflectivity, TDS height, and TDS volume increase during tornado intensification and decrease during tornado dissipation. For 14 tornado cases, the maximum or minimum TDS parameter values are compared to the tornado’s EF rating. For tornadoes with a higher EF rating, higher maximum values of the 90th percentile ZHH, TDS height, ...

Tornado Damage Estimation Using Polarimetric Radar

In this paper, a compact, transportable, and dual-polarization X-band weather radar was developed at the Advanced Radar Research Center of the University of Oklahoma. The radar was designed using a software-defined radio (SDR) approach for waveform versatility. One of the key innovations in this paper is the combination of SDR design and the mitigation of blind range, which is inherent in pulse compression radars, using a time-frequency multiplexed waveform while compression is performed in pure software architecture. Internally, this radar has been referred to as the PX-1000. It is primarily used as a platform for waveform studies and various signal processing techniques, such as pulse compression, polarimetric signal processing, refractivity retrieval, and support of various field campaigns. The radar system has been completed and is operational. It has two identical and independent power amplifiers, one for each polarization. The system also features a 1.2-m parabolic reflector dish with dual-polarization feed, which provides a 1.8 ° beamwidth. A majority of the components are housed above the turntable of an azimuth-over-elevation pedestal. We also took this opportunity to design and develop a new software suite that includes signal processing, system control, and graphical user interface. The raw I/Q time series can be recorded and streamed out of the radar system in real time. In this paper, a detailed description of the radar and some experimental data will be presented.

PX-1000: A Solid-State Polarimetric X-Band Weather Radar and Time–Frequency Multiplexed Waveform for Blind Range Mitigation

Nonmeteorological scatter, including debris lofted by tornadoes, may be detected using the polarimetric radar variables. For the 17 months from January 2012 to May 2013, radar data were examined for each tornado reported in the domain of an operational polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). Characteristics of the tornadic debris signature (TDS) were recorded when a signature was present. Approximately 16% of all tornadoes reported in Storm Data were associated with a debris signature, and this proportion is shown to vary regionally. Signatures were more frequently seen with tornadoes that were rated higher on the enhanced Fujita (EF) scale, with tornadoes causing higher reported total property damage, with tornadoes that were closer to the radar and thus intercepted by the beam at lower altitude, and associated with tornadoes with greater total pathlength. Tornadic debris signatures were most common in spring, when more strong tornadoes occur, and in autumn, when natural d...

/pdf/spatial-and-temporal-characteristics-of-polarimetric-3u1xu38sab.pdf

Spatial and Temporal Characteristics of Polarimetric Tornadic Debris Signatures

The advantages of dual-polarimetric radar observations have been studied for some time (Zrnic and Ryzhkov 1999) and certain signatures have been found to exist in supercell thunderstorms. These signatures include the tornado debris signature (TDS; Ryzhkov et al. 2002, 2005a), the low-level ZDR arc (e.g., Kumjian 2008; Kumjian and Ryzhkov 2008, 2008; Outinen and Teittinen 2007; Snyder 2008), ZDR and KDP columns (e.g., Caylor and Illingworth 1987; Illingworth et al. 1987; Tuttle et al. 1989; Meischner et al. 1991; Conway and Zrnic 1993; Brandes et al. 1995; Hubbert et al. 1998; Kennedy et al. 2001; Loney et al. 2002; Ryzhkov et al. 2005; Kumjian and Ryzhkov 2008), midlevel ZDR and ρHV rings (Kumjian and Ryzhkov 2008; Kumjian 2008), updraft signature (Kumjian and Ryzhkov 2008), and hail signatures (Heinselman and Ryzhkov 2006). Each signature reveals a distinguishing distribution of hydrometeors. Varying hypotheses have correlated these characteristics to different kinematic properties of the parent storm and its interaction with the environmental flow. Most dual-polarimetric studies have been performed at Sand C-bands (e.g., Kumjian and Ryzhkov 2008, Romine et al. 2008, Ryzhkov et al. 2005a, Ryzhkov et al. 2002, Van Den Broeke 2008), but relatively few studies have been made at X-band. Snyder (2008) examines X-band dual-polarimetric observations from UMass X-Pol using different cases for different estimates of attenuation and differential attenuation in order to mitigate the impacts of both. Among his findings (see the paper for more details) is that the correction technique called the ZPHI-Rain Profiling Algorithm (Testud et al. 2000) performs amongst the best of all the tested cases. The techniqued is used in results presented in this paper. Some details and limitations of the algorithm will be briefly described as well. The main focus of this paper is to provide a summarized analysis of storm evolution obtained from the NOAA (NSSL) X-Band Polarized (NOXP) mobile weather radar during the Verification of the Origins of Rotation in Tornadoes EXperiment, Part 2 (VORTEX2) field project. Herein the hail signature, ZDR arc, and ZDR and KDP column signature evolution are analyzed in

Verification of the origin of rotation in tornadoes experiment, part 2 (VORTEX2): data from the NOAA (NSSL) x-band dual-polarized radar

Most dual-polarimetric (dual-pol) studies have been performed at Sand C-bands (e.g., Kumjian and Ryzhkov 2008, Romine et al. 2008, Ryzhkov et al. 2005a, Ryzhkov et al. 2002, Van Den Broeke 2008), but relatively few studies have been made at X-band. Certain signatures have been found to exist in supercell thunderstorms. These signatures include the tornado debris signature (TDS; Ryzhkov et al. 2002, 2005a), the low-level ZDR arc (e.g., Kumjian and Ryzhkov 2008, 2009; Snyder 2008), ZDR and KDP columns (e.g., Caylor and Illingworth 1987; Hubbert et al. 1998; Loney et al. 2002; Kumjian and Ryzhkov 2008), midlevel ZDR and !HV rings (Kumjian and Ryzhkov 2008; Kumjian 2008), updraft signature (Kumjian and Ryzhkov 2008), and hail signatures (Heinselman and Ryzhkov 2006). Each signature reveals a distinguishing distribution of hydrometeors. Varying hypotheses have correlated these characteristics to different kinematic properties of the parent storm and its interaction with the environmental flow. However, attenuation AH,V and differential attenuation ADP are problematic at X-band. Using results from Snyder et al. (2010), the ZPHI RainProfiling algorithm (Testud et al. 2000), and the “Gamma” method (e.g., Bringi et al. 1990) are used to correct for AH and ADP, respectively. This paper gives a general overview of the observations and evolution seen at X-band (3-cm) wavelength. The main focus is to provide a summary of storm evolution obtained from the NOAA (NSSL) XBand Polarized (NOXP) mobile weather radar during the Verification of the ORigins of Tornadoes EXperiment, Part 2 (VORTEX2) field project. Herein, the hail signature, ZDR arc, and ZDR and KDP column signatures and evolution are analyzed in correspondence to the evolution of the updraft signature from three supercells; one tornadic (5 June 2009), one nontornadic (7 June 2009), and one cyclic, tornadic (10 May 2010).

Supercell polarimetric signatures at X-band: Data from VORTEX2

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Verification of the origin of rotation in tornadoes experiment, part 2 (VORTEX2): data from the NOAA (NSSL) x-band dual-polarized radar

Supercell polarimetric signatures at X-band: Data from VORTEX2