National Weather Radar Testbed Research Articles

Optimal Temporal Frequency of NSSL Phased Array Radar Observations for an Experimental Warn-on-Forecast System

Abstract A potential replacement candidate for the aging operational WSR-88D infrastructure currently in place is the phased array radar (PAR) system. The current WSR-88Ds take ~5 min to produce a full volumetric scan of the atmosphere, whereas PAR technology allows for full volumetric scanning of the same atmosphere every ~1 min. How this increase in temporal frequency of radar observations might affect the National Severe Storms Laboratory’s (NSSL) Warn-on-Forecast system (WoFS), which is a storm-scale ensemble data assimilation and forecast system for severe convective weather, is unclear. Since radar data assimilation is critical for the WoFS, this study explores the optimal temporal frequency of PAR observations for storm-scale data assimilation using the 31 May 2013 El Reno, Oklahoma, tornadic supercell event. The National Severe Storms Laboratory’s National Weather Radar Testbed PAR in Norman, Oklahoma, began scanning this event more than an hour before the first (and strongest) tornado developed near El Reno, and scanned most of the tornadic supercell’s evolution. Several experiments using various cycling and data frequencies to synchronously and asynchronously assimilate these PAR observations are conducted to produce analyses and very short-term forecasts of the El Reno supercell. Forecasts of low-level reflectivity and midlevel updraft helicity are subjectively evaluated and objectively verified using spatial and object-based techniques. Results indicate that assimilating more frequent PAR observations can lead to more accurate analyses and probabilistic forecasts of the El Reno supercell at longer lead times. Hence, PAR is a promising radar platform for WoFS.

Rapid-Scan Radar Observations of an Oklahoma Tornadic Hailstorm Producing Giant Hail

AbstractRapid-scan radar observations of a supercell that produced near-record size hail in Oklahoma are examined. Data from the National Weather Radar Testbed Phased Array Radar (PAR) in Norman, Oklahoma, are used to study the overall character and evolution of the storm. Data from the nearby polarimetric KOUN WSR-88D and rapid-scanning X-band polarimetric (RaXPol) mobile radar are used to study the evolution of low- to midaltitude dual-polarization parameters above two locations where giant hailstones up to 16 cm in diameter were observed. The PAR observation of the supercell’s maximum storm-top divergent outflow is similar to the strongest previously documented value. The storm’s mesocyclone rotational velocity at midaltitudes reached a maximum that is more than double the median value for similar observations from other storms producing giant hail. For the two storm-relative areas where giant hail was observed, noteworthy findings include 1) the giant hail occurred outside the main precipitation core, in areas with low-altitude reflectivities of 40–50 dBZ; 2) the giant hail was associated with dual-polarization signatures consistent with past observations of large hail at 10-cm wavelength, namely, low ZDR, low ρHV, and low KDP; 3) the giant hail fell along both the northeast and southwest edges of the primary updraft at ranges of 6–10 km from the updraft center; and 4) with the exception of one isolated report, the giant hail fell to the northeast and northwest of the large tornado and the parent mesocyclone.

Adaptive Range Oversampling Processing for Nontraditional Radar-Variable Estimators

AbstractAdaptive range oversampling processing can be used either to reduce the variance of radar-variable estimates without increasing scan times or to reduce scan times without increasing the variance of estimates. For example, an implementation of adaptive pseudowhitening on the National Weather Radar Testbed Phased-Array Radar (NWRT PAR) led to a twofold reduction in scan times. Conversely, a proposed implementation of adaptive pseudowhitening the U.S. Next Generation Weather Radar (NEXRAD) network would reduce the variance of dual-polarization estimates while keeping current scan times. However, the original version of adaptive pseudowhitening is not compatible with radar-variable estimators for which an explicit variance expression is not readily available. One such nontraditional estimator is the hybrid spectrum-width estimator, which is currently used in the NEXRAD network. In this paper, an extension of adaptive pseudowhitening is proposed that utilizes lookup tables (rather than analytical solutions based on explicit variance expressions) to obtain range oversampling transformations. After describing this lookup table (LUT) adaptive pseudowhitening technique, its performance is compared to that of the original version of adaptive pseudowhitening using traditional radar-variable estimators. LUT adaptive pseudowhitening is then applied to the hybrid spectrum-width estimator, and simulation results are confirmed with a qualitative analysis of radar data.

Spectral Processing for Step Scanning Phased-Array Radars

On phased-array radars, scanning is done by stepping the beam from one direction to the next direction and dwelling long enough at each direction to achieve acceptable errors of estimates. Combining data from the three directions is suggested to obtain superresolution similar to that available on the national network of weather radar (Weather Surveillance Radar-1988 Doppler or WSR-88D). Spectral analysis of such data is addressed, and it is demonstrated that the Doppler spectra of simply concatenated time series have very strong sidebands due to the discontinuity of the signals from the three beam positions. This artifact degrades the performance of the spectral clutter filters and other methods that rely on spectral processing to enhance the weather signal. Special adjustments of the signals at each range location before concatenating (splicing) are proposed to mitigate the effects of discontinuities in time and thus improve clutter filtering. The adjustment is such that the total information contained in the signal can be preserved in subsequent processing. Spectral quality of the concatenated signals is quantified via results from simulations. Samples of spectra obtained with the National Weather Radar Testbed are presented to substantiate the predictions. A ground clutter detector/filter accepted by the National Weather Service is applied to the conditioned time series data, and the ensuing fields of reflectivity factor and Doppler velocity are compared to the fields from which clutter had not been removed.

Rapid-Update Radar Observations of Downbursts Occurring within an Intense Multicell Thunderstorm on 14 June 2011

AbstractOn 14 June 2011, an intense multicell thunderstorm produced one nonsevere and three severe downbursts within 35 km of the rapid-update, S-band phased array radar (PAR) at the National Weather Radar Testbed in Norman, Oklahoma, and the nearby polarimetric research Weather Surveillance Radar 1988-Doppler (KOUN). Data collected from these radars provided the opportunity to conduct a quantitative analysis of downburst precursor signature evolution depicted by 1-min PAR data and the associated evolution of differential reflectivity ZDR depicted by 5-min KOUN data. Precursors analyzed included descent of the reflectivity core, evolution of the magnitude and size of midlevel convergence (i.e., number of bins), and descending “troughs” of ZDR. The four downbursts exhibited midlevel convergence that rapidly increased to peak magnitude as the reflectivity core (65-dBZ isosurface) bottom and top descended. The ZDR troughs seen in the 5-min KOUN data appeared to descend along with the core bottom. Midlevel convergence size increased to a peak value and decreased as the reflectivity core descended in the three severe downbursts. In contrast, midlevel convergence size exhibited little change in the nonsevere downburst. The time scale of trends seen in the PAR data was 11 min or less and happened several minutes prior to each downburst’s maximum intensity. These results point to the importance of 1-min volumetric data in effectively resolving the evolution of downburst precursors, which could be beneficial to forecast operations.

Adaptive-Weather-Surveillance and Multifunction Capabilities of the National Weather Radar Testbed Phased Array Radar

The National Weather Radar Testbed (NWRT) is maintained and operated by NOAA's National Severe Storm Laboratory in Norman, OK, USA. It is a phased array radar (PAR) that was established to evaluate the potential to perform aircraft and weather surveillance with a single, multifunction radar. The NWRT PAR is also being used to demonstrate advanced weather-surveillance concepts that are well suited to the unique capabilities offered by phased arrays. This paper provides an overview of the adaptive-weather-surveillance and multifunction capabilities of this system.

Adaptive Nullforming to Mitigate Ground Clutter on the National Weather Radar Testbed Phased Array Radar

With the decreasing cost of phased array antennas, their use for weather surveillance is becoming more practical. A significant advantage of phased arrays that can be applied to weather surveillance is spatial filtering. Using adaptive nullforming to spatially filter clutter is a novel approach to clutter mitigation, which is not possible with conventional parabolic reflector antennas. Moreover, spatial filtering is also applicable to phased-array-specific techniques such as beam multiplexing and adaptive scanning when only a few pulses are available for processing; this situation is particularly challenging for conventional ground clutter filters. The National Weather Radar Testbed Phased Array Radar (NWRT PAR) provides an opportunity to test some of these new capabilities. In this paper, a linearly constrained minimum power algorithm with an additional quadratic constraint is applied to weather data collected using the NWRT PAR and its multichannel receiver. Both the original algorithm and a recursive least squares version are utilized to show reflectivity and velocity data where both weather and ground clutter are present. Doppler spectra from selected range gates are examined to illustrate the performance of adaptive nullforming. Issues such as the number of samples needed to estimate the covariance matrix are explored. As far as we know, this is the first time that these types of techniques have been used to mitigate ground clutter contamination on a weather surveillance radar.

Considerations for Oversampling in Azimuth on the Phased Array Weather Radar

AbstractWhen spectral moments in the azimuth are spaced by less than a beamwidth, it is called oversampling. Superresolution is a type of oversampling that refers to sampling at half a beamwidth on the national network of Doppler weather radars [Weather Surveillance Radar-1988 Doppler (WSR-88D)]. Such close spacing is desirable because it extends the range at which small severe weather features, such as tornadoes or microbursts, can be resolved. This study examines oversampling for phased array radars. The goal of the study is to preserve the same effective beamwidth as on the WSR-88D while obtaining smaller spectral moment estimate errors at the same or faster volume update times. To that effect, a weighted average of autocorrelations of radar signals from three consecutive radials is proposed. Errors in three spectral moments obtained from these autocorrelations are evaluated theoretically. Methodologies on how to choose weights that preserve the desirable effective beamwidth are presented. The results are demonstrated on the fields of spectral moments obtained with the National Weather Radar Testbed (NWRT), a phased array weather radar at NOAA’s National Severe Storms Laboratory (NSSL).

31 May 2013 El Reno Tornadoes: Advantages of Rapid-Scan Phased-Array Radar Data from a Warning Forecaster’s Perspective*

Abstract On 31 May 2013, a supercell produced a tornado rated as 3 on the enhanced Fujita scale (EF3) near El Reno, Oklahoma, which was sampled by the S-band phased-array radar (PAR) at the National Weather Radar Testbed in Norman, Oklahoma. Collaboration with the forecaster who issued tornado warnings for the El Reno supercell during real-time operations focused the analysis on critical radar signatures frequently assessed during warning operations. The wealth of real-world experience provided by the forecaster, along with the quantitative analysis, highlighted differences between rapid-scan PAR data and the Weather Surveillance Radar-1988 Doppler located near Oklahoma City, Oklahoma (KTLX), within the context of forecast challenges faced on 31 May 2013. The comparison revealed that the 70-s PAR data proved most advantageous to the forecaster’s situational awareness in instances of rapid storm organization, sudden mesocyclone intensification, and abrupt, short-term changes in tornado motion. Situations where PAR data were most advantageous in the depiction of storm-scale processes included 1) rapid variations in mesocyclone intensity and associated changes in inflow magnitude; 2) imminent radar-indicated development of the short-lived (EF0) Calumet, Oklahoma, and long-lived (EF3) El Reno tornadoes; and 3) precise location and motion of the tornado circulation. As a result, it is surmised that rapid-scan volumetric radar data in cases like this would augment a forecaster’s ability to observe rapidly evolving storm features and deliver timely, life-saving information to the general public.

Impacts of a Storm Merger on the 24 May 2011 El Reno, Oklahoma, Tornadic Supercell

Abstract On 24 May 2011, a tornadic supercell (the El Reno, Oklahoma, storm) produced tornadoes rated as category 3 and 5 events on the enhanced Fujita scale (EF3 and EF5, respectively) during a severe weather outbreak. The transition (“handoff”) between the two tornadoes occurred as the El Reno storm merged with a weaker, ancillary storm. To examine the impacts of the merger on the dynamics of these storms, a series of three-dimensional cloud-scale analyses are created by assimilating 1-min volumetric observations from the National Weather Radar Testbed’s phased array radar into a numerical cloud model using the local ensemble transform Kalman filter technique. The El Reno storm, its updrafts, and vortices in the analyzed fields are objectively identified, and the changes in these objects before, during, and after the merger are examined. It is found that the merger did not cause the tornado handoff, which preceded the updraft merger by about 5 min. Instead, the handoff likely resulted from midlevel mesocyclone occlusion, in which the midlevel mesocyclone split and a portion is shed rearward with respect to storm motion. During the merger process, the midlevel mesocyclone and updraft structure in the El Reno storm became relatively disorganized. New updraft pulses that formed above colliding outflow boundaries between the two storms tilted environmental vorticity from low levels to generate an additional midlevel vortex that later merged with the El Reno storm’s midlevel mesocyclone. Once the ~10-min merger process was complete, the El Reno storm and its mesocyclone rapidly reintensified, as access to buoyant inflow sector air was restored.

Simulation of Spaced Antenna Wind Retrieval Performance on an X-Band Active Phased Array Weather Radar

Abstract Spaced antenna baseline wind retrievals, in conjunction with traditional Doppler measurements, are a potential means of fine angular resolution weather radar wind vector retrieval. A spaced antenna implementation on an X-band active phased array architecture is investigated via Monte Carlo simulations of the backscattered electric fields at the antenna array. Several retrieval methods are exercised on the data produced by the simulator. Parameters of the X-band spaced-antenna design are then optimized. Benefiting from the parametric fitting procedure inherent in the time domain slope at zero lag and full correlation analysis, the study finds both of these algorithms to be more immune to thermal noise than the spectral retrieval algorithms investigated. With appropriately chosen baselines, these time domain algorithms are shown to perform adequately for 5-dB SNR and above. The study also shows that the Gaussian slope at zero lag (G-SZL) algorithm leads to more robust estimates over a wider range of beamwidths than the Gaussian full correlation analysis (G-FCA) algorithm. The predicted performance of the X-band array is compared to a similar spaced antenna implementation on the S-band National Weather Radar Testbed (NWRT). Since the X-band signal decorrelates more rapidly (relative to S band), the X-band array accumulates more independent samples, thereby obtaining lower retrieval uncertainty. However, the same rapid decorrelation also limits the maximum range of the X-band array, as the pulse rate must be sufficiently high to sample the cross-correlation function. It also limits the range of tolerable turbulence velocity within the resolution cell.

Simulated Vortex Detection Using a Four-Face Phased-Array Doppler Radar

Abstract The National Weather Radar Testbed was established in Norman, Oklahoma, in 2002 to evaluate, in part, the feasibility of eventually replacing mechanically scanned parabolic antennas with electronically scanned phased-array antennas on weather surveillance radars. If a phased-array antenna system is to replace the current antenna, among the important decisions that must be made are the design (flat faces, cylinder, etc.) that will be needed to cover 360° in azimuth and the choice of an acceptable beamwidth. Investigating the flat-face option, four faces seem to be a reasonable choice for providing adequate coverage. To help with the beamwidth decision-making process, the influence of beamwidth on the resolution of various-sized simulated vortices is investigated. It is found that the half-power beamwidth across the antenna should be no more than 1.0° (equating to a broadside beamwidth of 0.75°) in order to provide National Weather Service forecasters with at least the same quality of data resolution that is currently available for making tornado and severe storm warnings.

Evolution of a Quasi-Linear Convective System Sampled by Phased Array Radar

Abstract On 2 April 2010, a quasi-linear convective system (QLCS) moved eastward through Oklahoma during the early morning hours. Wind damage in Rush Springs, Oklahoma, approached (enhanced Fujita) EF1-scale intensity and was likely associated with a mesovortex along the leading edge of the QLCS. The evolution of the QLCS as it produced its first bow echo was captured by the National Weather Radar Testbed Phased Array Radar (NWRT PAR) in Norman, Oklahoma. The NWRT PAR is an S-band radar with an electronically steered beam, allowing for rapid volumetric updates (~1 min) and user-defined scanning strategies. The rapid temporal updates and dense vertical sampling of the PAR created a detailed depiction of the damaging wind mechanisms associated with the QLCS. Key features sampled by the PAR include microbursts, an intensifying midlevel jet, and rotation associated with the mesovortex. In this work, PAR data are analyzed and compared to data from nearby operational radars, highlighting the advantages of using high-temporal-resolution data to monitor storm evolution. The PAR sampled the events preceding the Rush Springs circulation in great detail. Based on PAR data, the midlevel jet in the QLCS strengthened as it approached Rush Springs, creating an area of strong midlevel convergence where it impinged on the system-relative front-to-rear flow. As this convergence extended to the lower levels of the storm, a preexisting azimuthal shear maximum increased in magnitude and vertical extent, and EF1-scale damage occurred in Rush Springs. The depiction of these events in the PAR data demonstrates the complex and rapidly changing nature of QLCSs.

Exploring Impacts of Rapid-Scan Radar Data on NWS Warning Decisions

Abstract Rapid-scan weather radars, such as the S-band phased array radar at the National Weather Radar Testbed in Norman, Oklahoma, improve precision in the depiction of severe storm processes. To explore potential impacts of such data on forecaster warning decision making, 12 National Weather Service forecasters participated in a preliminary study with two control conditions: 1) when radar scan time was similar to volume coverage pattern 12 (4.5 min) and 2) when radar scan time was faster (43 s). Under these control conditions, forecasters were paired and worked a tropical tornadic supercell case. Their decision processes were observed and audio was recorded, interactions with data displays were video recorded, and the products were archived. A debriefing was conducted with each of the six teams independently and jointly, to ascertain the forecaster decision-making process. Analysis of these data revealed that teams examining the same data sometimes came to different conclusions about whether and when to warn. Six factors contributing toward these differences were identified: 1) experience, 2) conceptual models, 3) confidence, 4) tolerance of possibly missing a tornado occurrence, 5) perceived threats, and 6) software issues. The three 43-s teams issued six warnings: three verified, two did not verify, and one event was missed. Warning lead times were the following: tornado, 18.6 and 11.5 min, and severe, 6 min. The three tornado warnings issued by the three 4.5-min teams verified, though warning lead times were shorter: 4.6 and 0 min (two teams). In this case, use of rapid-scan data showed the potential to extend warning lead time and improve forecasters’ confidence, compared to standard operations.

Multichannel Receiver Design, Instrumentation, and First Results at the National Weather Radar Testbed

When the National Weather Radar Testbed (NWRT) was installed in 2004, a single-channel digital receiver was implemented so that the radar could mimic typical Weather Surveillance Radar (WSR) version 1988 Doppler (WSR-88D) capability. This, however, left unused eight other channels, built into the antenna. This paper describes the hardware instrumentation of a recently completed project that digitizes the radar signals produced by these channels. The NWRT is the nation's first phased array devoted to weather observations, and this testbed serves as an evaluation platform to test new hardware and signal processing concepts. The multichannel digital data will foster a new generation of adaptive/fast scanning techniques and space-antenna/interferometry measurements, which will then be used for improved weather forecasting via data assimilation. The multichannel receiver collects signals from the sum, azimuth-difference, elevation-difference, and five broad-beamed auxiliary channels. One of the major advantages of the NWRT is the capability to adaptively scan weather phenomena at a higher temporal resolution than is possible with the WSR-88D. Access to the auxiliary channels will enable clutter mitigation and advanced array processing for higher data quality with shorter dwell times. Potential benefits of higher quality and higher resolution data include: better understanding of storm dynamics and convective initiation; better detection of small-scale phenomena, including tornadoes and microbursts; and crossbeam wind, shear, and turbulence estimates. These items have the distinct possibility to ultimately render increased lead time for warnings and improved weather prediction. Finally, samples of recently collected data are presented in the results section of this paper.

Adaptive Range Oversampling to Achieve Faster Scanning on the National Weather Radar Testbed Phased-Array Radar

Abstract This paper describes a real-time implementation of adaptive range oversampling processing on the National Weather Radar Testbed phased-array radar. It is demonstrated that, compared to conventional matched-filter processing, range oversampling can be used to reduce scan update times by a factor of 2 while producing meteorological data with similar quality. Adaptive range oversampling uses moment-specific transformations to minimize the variance of meteorological variable estimates. An efficient algorithm is introduced that allows for seamless integration with other signal processing functions and reduces the computational burden. Through signal processing, a new dimension is added to the traditional trade-off triangle that includes the variance of estimates, spatial coverage, and update time. That is, by trading an increase in computational complexity, data with higher temporal resolution can be collected and the variance of estimates can be improved without affecting the spatial coverage.

Phased array weather / multipurpose radar

The first phased array radar dedicated to weather observation and analysis is now instrumented with eight simultaneous digital receivers. The addition of these additional channels will enable the use of advanced signal processing to improve signal/clutter in an adaptive mode. Elimination of strone point and ground clutter returns from the low-level, volumetrically-distributed weather cell returns is a new application of adaptive processing. The NSF funded 8-channel receiver has been added to the National Weather Radar Testbed (NWRT) system in Norman, Oklahoma, to enable operation as a multi-function and/or adaptive processing system. Herein, we describe the system concept, system installation and early results from fielded weather data returns.

Lightning Activity in a Hail-Producing Storm Observed with Phased-Array Radar

Abstract This study examined lightning activity relative to the rapidly evolving kinematics of a hail-producing storm on 15 August 2006. Data were provided by the National Weather Radar Testbed Phased-Array Radar, the Oklahoma Lightning Mapping Array, and the National Lightning Detection Network. This analysis is the first to compare the electrical characteristics of a hail-producing storm with the reflectivity and radial velocity structure at temporal resolutions of less than 1 min. Total flash rates increased to approximately 220 min−1 as the storm’s updraft first intensified, leveled off during its first mature stage, and then decreased for 2–3 min despite the simultaneous development of another updraft surge. This reduction in flash rate occurred as wet hail formed in the new updraft and was likely related to the wet growth; wet growth is not conducive to hydrometeor charging and probably contributed to the formation of a “lightning hole” without a mesocyclone. Total flash rates subsequently increased to approximately 450 min−1 as storm volume and inferred graupel volume increased, and then decreased as the storm dissipated. The vertical charge structure in the storm initially formed a positive tripole (midlevel negative charge between upper and lower positive charges). The charge structure in the second updraft surge consisted of a negative charge above a deep midlevel positive charge, a reversal consistent with the effects of large liquid water contents on hydrometeor charge polarity in laboratory experiments. Prior to the second updraft surge, the storm produced two cloud-to-ground flashes, both lowering the usual negative charge to ground. Shortly before hail likely reached ground, the storm produced four cloud-to-ground flashes, all lowering the positive charge. Episodes of high singlet VHF sources were observed at approximately 13–15 km during the initial formation and later intensification of the storm’s updraft.

Multipatterns of the National Weather Radar Testbed Mitigate Clutter Received via Sidelobes

Abstract The phased-array radar (PAR) of the National Weather Radar Testbed (NWRT) has a unique hybrid (mechanical and electrical) azimuth scan capability, allowing weather observations with different antenna patterns. Observations show the standard deviation of the sample mean power of weather echoes received through the main lobe of a set of squinted beams is less than the clutter received via sidelobes. This then allows use of a multipattern technique to cancel sidelobe echoes from moving scatterers, echoes that cannot be filtered with a ground-clutter canceler. Although the multipattern technique was developed to cancel clutter received through sidelobes, results show clutter from objects moving within the beam can also be canceled.

High-Temporal-Resolution Capabilities of the National Weather Radar Testbed Phased-Array Radar

Abstract Since 2007 the advancement of the National Weather Radar Testbed Phased-Array Radar (NWRT PAR) hardware and software capabilities has been supporting the implementation of high-temporal-resolution (∼1 min) sampling. To achieve the increase in computational power and data archiving needs required for high-temporal-resolution sampling, the signal processor was upgraded to a scalable, Linux-based cluster with a distributed computing architecture. The development of electronic adaptive scanning, which can reduce update times by focusing data collection on significant weather, became possible through functionality added to the radar control interface and real-time controller. Signal processing techniques were implemented to address data quality issues, such as artifact removal and range-and-velocity ambiguity mitigation, absent from the NWRT PAR at its installation. The hardware and software advancements described above have made possible the development of conventional and electronic scanning capabilities that achieve high-temporal-resolution sampling. Those scanning capabilities are sector- and elevation-prioritized scanning, beam multiplexing, and electronic adaptive scanning. Each of these capabilities and related sampling trade-offs are explained and demonstrated through short case studies.