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 reflectivity and radial velocity structure at temporal resolutions of <1 min. Total flash rates increased to ~220 / min 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 ~450 / min as storm volume and inferred graupel volume increased, and then decreased as the storm dissipated. Vertical charge structure in the storm initially formed a positive tripole (midlevel negative charge between upper and lower positive charges). Charge structure in the second updraft surge consisted of negative charge above deep midlevel positive charge, a reversal consistent with the effect 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 positive charge. Episodes of high singlet VHF sources were observed at ~13–15 km during the initial formation and later intensification of the storm’s updraft.

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.

A case study illustrating the impact of moisture variability on convection initiation in a synoptically active environment without strong moisture gradients is presented. The preconvective environment on 30 April 2007 nearly satisfied the three conditions for convection initiation: moisture, instability, and a low-level lifting mechanism. However, a sounding analysis showed that a low-level inversion layer and high LFC would prevent convection initiation because the convective updraft velocities required to overcome the convective inhibition (CIN) were much higher than updraft velocities typically observed in convergence zones. Radar refractivity retrievals from the Twin Lakes, Oklahoma (KTLX), Weather Surveillance Radar-1988 Doppler (WSR-88D) showed a moisture pool contributing up to a 2°C increase in dewpoint temperature where the initial storm-scale convergence was observed. The analysis of the storm-relative wind field revealed that the developing storm ingested the higher moisture associated with the moisture pool. Sounding analyses showed that the moisture pool reduced or nearly eliminated CIN, lowered the LFC by about 500 m, and increased CAPE by 2.5 times. Thus, these small-scale moisture changes increased the likelihood of convection initiation within the moisture pool by creating a more favorable thermodynamic environment. The results suggest that refractivity data could improve convection initiation forecasts by assessing moisture variability at finer scales than the current observation network.

Advancements in radar technology since the deployment of the Weather Surveillance Radar-1988 Doppler (WSR-88D) network have prompted consideration of radar replacement technologies. In order for the outcomes of advanced radar research and development to be the most beneficial to users, an understanding of user needs must be established early in the process and considered throughout. As an important early step in addressing this need, this study explored the strengths and limitations of current radar systems for nine participants from two key stakeholder groups: NOAA's NWS and broadcast meteorologists. Critical incident interviews revealed the role of each stakeholder group and attained stories that exemplified radar strengths and limitations in their respective roles.

NWS forecasters emphasized using radar as an essential tool to assess the current weather situation and communicate hazards to key stakeholder groups. TV broadcasters emphasized adding meaning and value to NWS information and using radar to effectively communicate weather information to viewers. The stories told by our participants vividly illustrated the advancing nature of weather detection with radar, and why there are still issues with weather radar and radar-derived information. Analysis of the stories, which ranged from accounts of severe weather to winter weather, revealed four underlying radar needs: 1) clean, accurate data without intervention, 2) higher spatial- and temporal-resolution data than that provided by the WSR-88D, 3) consistent and low-altitude information, and 4) more accurate information on precipitation type, size, intensity, and distribution.

A supplement to this article is available online:

DOI: 10.1175/2009BAMS2830.2

This study investigates the potential for estimating mixed-layer depth by taking advantage of the radial gradients in the radar reflectivity field produced by the large vertical gradients in water vapor mixing ratio that are characteristic of the mixing height. During the day, this relationship often results in a ring of maximum reflectivity observed to progress radially outward from the radar as mixed-layer depth increases. A comparison of mixed-layer depths estimated from the Oklahoma City WSR-88D (KTLX) with those estimated from a nearby 915 MHz profiler reveals that mixed-layer depths from the WSR-88D are slightly too high (up to 0.3 km) during the first three hours of the diurnal cycle, nearly unbiased midday, and slightly too low (0.2 km or less) thereafter. The procedure estimates mixed-layer depths only during the daytime hours from 1300–2300 UTC. The weather conditions for the 17 days studied were fairly quiescent, with sunny skies and light winds.

The 2007 and 2008 spring refractivity experiments at KTLX investigated the potential utility of high-resolution, near-surface refractivity measurements to operational forecasting. During these experiments, forecasters at the Norman, Oklahoma, National Weather Service Forecast Office (NWSFO) assessed refractivity and scan-to-scan refractivity change fields retrieved from the Weather Surveillance Radar-1988 Doppler weather radar near Oklahoma City—Twin Lakes, Oklahoma (KTLX). Both quantitative and qualitative analysis methods were used to analyze the 41 responses from seven forecasters to a questionnaire designed to measure the impact of refractivity fields on forecast operations. The analysis revealed that forecasts benefited from the refractivity fields on 25% of the days included in the evaluation. In each of these cases, the refractivity fields provided complementary information that somewhat enhanced the forecasters’ capability to analyze the near-surface environment and boosted their confidence in moisture trends. A case in point was the ability to track a retreating dryline after its location was obscured by a weak reflectivity bloom caused by biological scatterers. Forecasters unanimously agreed, however, that the impact of this complementary information on their forecasts was too insignificant to justify its addition as an operational dataset. The applicability of these findings to other NWSFOs may be limited to locations with similar weather situations and access to surface data networks like the Oklahoma Mesonet.

Available online at http://www.nwas.org/newsletters/pdf/news_jan2009.pdf.

The National Weather Radar Testbed (NWRT) Phased Array Radar (PAR), located in Norman Oklahoma, consists of a single antenna array capable of electronically scanning a 90 degree azimuthal sector at any given moment. The antenna is mounted on a pedestal which can be commanded to move in any azimuthal direction allowing researchers to follow areas of interesting weather. Until now, when tracking a weather feature, an operator had to decide when and where to move the pedestal in order to keep the feature in the field of view, which imposed a significant operational burden. This paper describes an adaptive algorithm that uses reflectivity data to track an operator-defined weather feature and automatically adjusts the pedestal position to optimally keep it in the field of view.

It is well understood that high-temporal resolution data has the potential to improve the understanding, detection, and warning of hazardous weather phenomena. In fact, in a 2008 survey about scanning strategy improvements conducted by the US National Weather Service, 62% of forecasters indicated the need for faster updates. One of the strongest advantages of using phased-array radars for weather observations is their potential to produce data with very high temporal resolution. Naturally, this has been a major research and development thrust on the National Severe Storms Lab’s (NSSL) National Weather Radar Testbed Phased-Array Radar (NWRT PAR).
One way to get faster updates without loss in data quality is by adaptively focusing observations to the regions of interest. This is the purpose of the Adaptive DSP Algorithm for Timely Scans (ADAPTS), which was first demonstrated in 2009. ADAPTS works by activating or deactivating individual beam positions within a scanning strategy based on elevation, significance, and neighborhood criteria. Preliminary evaluations of ADAPTS showed significant time savings, but also helped identify areas for further improvement. This paper describes the initial implementation of ADAPTS, its recent evolution, and outlines a plan for future enhancements towards obtaining the best weather observations in the shortest amount of time.

The National Weather Radar Testbed phased-array radar (NWRT PAR) has unique electronic scanning capabilities for weather surveillance. A key objective of the 2010 Phased-Array Radar Innovative Sensing Experiment (PARISE) is the demonstration and testing of the radar's capability to produce efficient and effective rapid sampling of severe storms. Rapid sampling is achieved through the implementation of electronic adaptive scanning, range oversampling, and other techniques, over a 90-degree sector. At the same time, an enhanced depiction of storm structure is attained through dense vertical sampling (22 tilts) and 50% azimuthal oversampling. The high-quality, rapid update data collected in spring 2010 provides the opportunity to improve understanding of storm processes in bowing line segments, hail storms, and fast moving tornadic storms.

The social science-component of the 2010 PARISE engaged 12 forecasters from three regions of the National Weather Service in the analysis of NWRT PAR data and took place during the last three weeks of April 2010. The primary objective of this user-focused experiment is to build an understanding of potential operational impacts of higher-temporal resolution data on the warning decision process and warning lead time. To accomplish this objective, on Tuesday and Wednesday of each week the four participants received training on the NWRT PAR instrumentation and gained experience analyzing the data and issuing warnings using three playback events. The three events included a microburst, quasi-linear convective system, and isolated supercell. On Thursdays forecasters participated in day-long experiment for which NWRT PAR data for two cases were used with two different update times for each case: one with the full-temporal resolution data, and the other with WSR-88D-like temporal resolution data. The two events included a low-topped supercell that formed in a tropical environment and a supercell that formed in more of a traditional Southern Plains environment. Following each event, each team discussed their warning decision making process with their facilitators, and then met with the other team to compare and contrast their warning decision experiences. These debriefings produced a very rich dataset that illustrates possible impacts of higher-temporal resolution data on the warning decision making process and how NWRT PAR data may be eventually be introduced to the field.

Available online at http://ams.confex.com/ams/91Annual/webprogram/Paper184192.html.

The current Tornado Detection Algorithm (TDA) used with the Weather Surveillance Radar- 1988 Doppler network utilizes an input velocity field that is often noisy and subject to de-aliasing errors. The current TDA also relies on azimuthal shear calculations, which are affected by noisy velocity data and can degrade significantly with range. Because of these and other data accuracy issues, the current TDA is prone to producing false detections and inaccurate circulation tracks.

Coincident with the advent of new radar-derived products and ongoing research involving new weather radar systems (e.g., Phased Array Radar), the National Severe Storms Laboratory is developing an improved TDA. A primary component of this algorithm will be the local, linear least squares derivatives (LLSD) azimuthal shear field. The LLSD method uses rotational derivatives of the velocity field and is less affected by noisy velocity data in comparison to the more traditional “peak-to-peak” azimuthal shear calculations.

Initial detections will be made on a field of maximum low-level LLSD shear and diagnosed for potentially tornadic characteristics. Although LLSD shear is less range-dependent than peak-to-peak shear, some range dependency is unavoidable. A preliminary study of 31 tornadoes indicated that the threshold LLSD shear value needed to detect tornadoes was moderately dependent on range from the radar. A regression analysis was completed to determine the relationship between range and shear values such that range-corrected shear values could be estimated.

Predictors in the regression equation include circulation diameter and calculated LLSD shear. The circulation diameter was estimated by calculating the distance between minimum and maximum velocity values at a constant range. This value is assumed to represent the diameter of a mesocyclone-scale circulation, with the understanding that small-scale circulations will not be resolvable at far ranges. The resulting regression equation was applied to range-degraded shear values from tornadic circulations in the initial test set. Range-corrected shear values were compared to actual tornado intensities, as determined by damage surveys, to assess their validity.

Available online at http://ams.confex.com/ams/91Annual/webprogram/Paper184514.html.

The current Tornado Detection Algorithm (TDA) used with the Weather Surveillance Radar-1988 Doppler (WSR-88D) network utilizes an input velocity field that is often noisy and subject to de-aliasing errors. The current TDA also depends on azimuthal shear calculations, which are affected by noisy velocity data and can degrade significantly with range. Because of these and other data accuracy issues, the current TDA is prone to producing false detections and inaccurate circulation tracks.

Coincident with the advent of new radar-derived products and ongoing research involving new weather radar systems (e.g., Phased Array Radar; PAR), the National Severe Storms Laboratory is developing an improved TDA. A primary component of this algorithm will be the local, linear least squares derivatives (LLSD) azimuthal shear field. The LLSD method uses rotational derivatives of the velocity field and is less affected by noisy velocity data in comparison to the more traditional “peak-to-peak” azimuthal shear calculations.

Initial detections will be made on a field of maximum low-level LLSD shear and diagnosed for potentially tornadic characteristics. Although LLSD shear is less range-dependent than peak-to-peak shear, some range dependency is unavoidable. A preliminary study of 31 tornadoes indicated that the threshold LLSD shear value needed to detect tornadoes was moderately dependent on range from the radar. A regression analysis was completed to determine the relationship between range and shear values so that range-corrected shear values could be estimated.

In addition to range, azimuthal sampling is an important consideration in tornado detection. Of particular interest for this work is the azimuthal resolution of the National Weather Radar Testbed PAR in Norman, Oklahoma. The beamwidth of the PAR increases smoothly with increasing angle from boresight, ranging from 1.5° at boresight to 2.1° at an angle of 45° from boresight. Although overlapped sampling is applied to the PAR to increase the azimuthal resolution, the PAR does not currently reach the super-resolution capabilities in use with the WSR-88D network. A two -dimensional Rankine vortex model was used to demonstrate the effects of azimuthal resolution and range on peak-to-peak and LLSD shear calculations. Simulated Rankine vortices were sampled with azimuthal resolution mimicking that of the PAR and a typical WSR-88D radar and results were compared.

Available online at http://ams.confex.com/ams/25SLS/techprogram/paper_175382.htm.

On 2 April 2010, a quasi-linear convective system (QLCS) formed in southwestern Oklahoma and northern Texas and moved eastward through central Oklahoma during the early morning hours. Storm formation was initially limited to the Oklahoma panhandle and southern Kansas, where an advancing cold front merged with a retreating dry line in an uncapped environment. An upper-level trough approached from the west overnight, supporting large-scale ascent and a strengthening southwesterly low-level jet. Soundings in central and northern Oklahoma on the evening prior to the event indicated a strongly capped environment with a deep elevated mixed layer. The arrival of the upper-level trough during the early morning hours of 2 April 2010 provided the ascent necessary to overcome convective inhibition and promote storm formation.

Marginally severe hail was reported with the earlier storms in southern Kansas, but the most severe damage resulted from the QLCS in southwestern Oklahoma. After the QLCS formed in southwestern Oklahoma, it moved eastward into a corridor of moderately high instability, with mixed-layer CAPE values exceeding 1000 J kg-1. Strong unidirectional low-level wind shear was supportive of organized bow echo structures and low-level mesovortices. Wind damage in Rush Springs, Oklahoma approached EF1-scale intensity and was likely associated with one of the mesovortices that formed along the leading edge of the QLCS.

The evolution of the QLCS 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 evolution and damaging wind mechanisms associated with the QLCS. Features in the PAR data include microbursts, multicellular storm evolution, an intensifying rear-inflow jet, and a bowing segment and rotation associated with the Rush Springs damage. PAR data are analyzed and compared to data from the nearby S-band WSR-88D radar in Twin Lakes, Oklahoma and C-band Terminal Doppler Weather Radar in Oklahoma City, Oklahoma.

Available online at http://ams.confex.com/ams/91Annual/webprogram/Paper184493.html.

During severe weather events, a tornado may develop on the order of minutes or seconds. Operational radars such as the WSR-88D are capable of detecting tornadic vortex signatures (TVSs), but the WSR-88Ds are limited to using predefined volume coverage patterns with an update interval of 4.5 min or longer. Such update times are insufficient to track the rapid evolution of TVSs that persist for only a few minutes. Additionally, more frequent volumetric updates are needed to detect and monitor the rapid evolution of radar-based signatures that may indicate tornadic development.

This study uses data from the National Weather Radar Testbed Phased-Array Radar (NWRT PAR) to evaluate the impact of rapid sampling during two short-lived tornado events. In each event, volumetric updates were obtained with a maximum update time of 60 s; this scanning method provided frequent updates on the evolution of the observed circulations. On 19 August 2007, 45-s updates depicted the life cycle of a circulation associated with a tornado that formed between 0144 and 0147 UTC. Two minutes prior to tornado development, strong gate-to-gate shear of 40—50 m s-1 was found over a depth of 2 km, and this shear persisted through a 10-min period including the tornado lifetime. A second circulation was sampled on 07 May 2008, when a mesoscale convective vortex (MCV) developed in the vicinity of a surface cyclone. A tornado developed at the western edge of the MCV and remained on the ground through the period 2221—2226 UTC. Strong gate-to-gate shear in excess of 30 m s-1 was detected at 1.5 km AGL as early as 2217 UTC, providing indications that a strong circulation developed several minutes before the tornado reached the ground.

To examine the impact of sampling intervals on the evolution of these circulations, the original NWRT PAR data from both events are modified to produce temporal updates that are comparable with WSR-88D scanning strategies. Changes in gate-to-gate shear within the TVS are measured to compare the depiction and evolution of the tornadic vortex signatures. In addition, the positions of the TVSs are compared to evaluate the improvement that rapid sampling provides when tracking the location of a possible tornado.

Available online at http://ams.confex.com/ams/91Annual/webprogram/Paper182379.html.

Officially commissioned in 2008, the Oklahoma City Micronet (OKCNET) deployed a dense network of in situ surface stations that measure atmospheric variables including air temperature, relative humidity, pressure, wind speed, wind direction, and precipitation at enhanced spatial (~3 km average station spacing) and temporal (1-minute) scales. Because Oklahoma City is embedded within a region climatologically favored for severe weather combined with the fact that the spatial dimensions of Oklahoma City are large compared to many urban areas, numerous severe weather events have been sampled by OKCNET including squall lines and tornadic supercells. When combined with additional operational and experimental observing systems in central Oklahoma (including the Phased Array Radar), Oklahoma City represents a testbed for studying (1) the impacts of severe weather across an urban area and (2) modification of severe events by the underlying urban zone. This study documents a number of specific cases including severe squall lines on 27 May 2008, 19 August 2009, and 2 April 2010 as well as tornadic supercells on 10 February 2009 and 13 May 2009.

High-resolution polarimetric radar measurements in numerous supercells and tornadoes were obtained by the Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) during the 10 May 2010 tornado outbreak. These observations include a supercell that produced an EF-4 tornado that developed near Moore, Oklahoma, only 10–15 km from OU-PRIME. The supercell's reflectivity appendage developed cyclonic curvature 15 min prior to the first tornado observations, coincident with an increase in low-level mesocyclone intensity and a protrusion of the rear-flank downdraft into the inflow region. Numerous cyclonic and anticyclonic flares were observed along the rear-flank downdraft (RFD) with cyclonic and anticyclonic rotation below 100 m, indicative of possible tornadoes or gustnadoes. As the RFD gust front extended further into the inflow region, vortices developed along the RFD gust front after a significant increase in near-surface convergence along the RFD gust front. In general, the vortex diameter and the spatial concentration both decreased as height increased.

To analyze the evolution of low-level rotation during tornadogenesis, single-radar approximations of vorticity and convergence in the RFD region are computed. Vorticity and convergence are computed using radial velocity differences between two gates over a fixed number of gates. The possible role of vorticity along the RFD gust front in tornadogenesis will be discussed, along with other vorticity sources identified in the analysis.

Available online at http://ams.confex.com/ams/25SLS/techprogram/paper_175834.htm.

Faster scanning of hazardous weather with radar is a primary need of users. This need is exemplified by the implementation of faster volume coverage patterns (e.g., VCP 12) by the National Weather Service, responses to studies of user needs, and reports by the National Research Council. Traditional VCPs modified to provide faster updates require trade-offs such as data quality and/or spatial resolution.

The electronic steering of the National Weather Radar Testbed Phased Array Radar (NWRT PAR) is capable of collecting higher temporal resolution data without some of the limitations of mechanically scanning radars. Most importantly, electronic steering allows scanning focused solely on areas of interest without having to collect data contiguously. This capability, termed adaptive scanning, produces higher temporal resolution data through more efficient use of radar resources.

This paper describes the technical PAR capabilities, software improvements, and scanning strategy developments that have led to the advancement of a SPY-1A antenna from a military-surveillance radar to a weather-surveillance radar with basic adaptive scanning capability. Individual weather events sampled by the NWRT PAR illustrate the evolution of high-temporal sampling capabilities of the NWRT PAR since spring 2007. Future enhancements to improve current adaptive scanning capabilities are discussed.

The National Weather Radar Testbed Phased Array Radar (NWRT PAR) sampled a cyclic, tornadic supercell on 10 February 2009 as it moved northeast across the western side of Oklahoma City. During its lifetime the storm moved over the Oklahoma City Micronet (OKCNET) and Oklahoma Mesonet stations. The rapid updates of the NWRT PAR and the highspatial and temporal resolution of the OKCNET, collected near a high–population center, make this a unique event. Low–level analyses of these data show the storm exhibited cyclic tornadogenesis; two cycles of the supercell were examined in this study. After the tornado associated with the first cycle lifted, a new circulation formed along a bulge in the rear flank gust front. During both cycles of the supercell, a number of small cells developed south of the supercell and merged with the storm. This study documents the evolution and characteristics of these cells as they merge with the main supercell. These mergers often disrupted the organization of the hook echo.

Available online at http://ams.confex.com/ams/25SLS/techprogram/paper_176091.htm.

Over the last year, radar-derived refractivity has been continuously estimated at the University of Oklahoma using two Oklahoma WSR-88D radars (KTLX, KFDR). Refractivity is calculated using phase measurements derived from stationary clutter targets in the radar's domain, which is typically limited to 40-60 km due to earth curvature. Previous work has shown the utility of short-term refractivity changes as a proxy for low-level moisture perturbations. These may in turn be used as a predictor for focal points of convection initiation.

Unfortunately using current quality control (QC) methods, the domain used for refractivity can contain clutter points with poor phase coherency, which should be removed before being used in the algorithm. The algorithm interpolates and spatially filters the data due to the inherent statistically uncertainty and the general sparseness of the phase measurements, resulting in a spatial resolution of approximately 4 km. If clutter points with questionable phase data are allowed to pass through the algorithm, surrounding data points (up to a distance of 4 km) may be impacted, especially in regions with a low number of clutter points. Consequently, estimates of phase and refractivity will have degraded quality. This occurs most frequently near the edge of the clutter domain or where clutter signals may be dominated by tress. It can be shown that the existing algorithm had deteriorated refractivity quality when used on windy days, when these clutter targets were moving irregularly and introducing error-prone phase data into the algorithm. By determining which targets move in these situations using their spectral characteristics and phase coherency, we can censor these points and improve estimates of the refractivity field. An extensive statistical study will be presented using the Oklahoma Mesonet data as ground truth. In addition, an improved phase QC methodology will be proposed, which significantly improves the ultimate quality of the refractivity data.

During the course of this project a diurnal refractivity bias between Mesonet surface observations and the radar has been observed. This bias tends to peak around 00 UTC, and is most prevalent in the summertime. The observations of this bias has led to a field experiment aimed at answering the underlying cause. The experiment includes a modified Mesonet station, which can monitor refractivity at 1.5 and 9 meters at one-minute intervals, as well as vertical profiles provided by an unmanned aerial vehicle (UAV) outfitted with a full array of meteorological sensors. The Mesonet tower provides insight as to the near-surface refractivity gradient during periods of bias, and whether or not it may be due to changes in sampling height as a side effect of beam propagation changes. The UAV provides a refractivity profile over a deep layer, and can sample the evolution of the changing profile in accompaniment to Mesonet data during periods of bias. Profiles of refractivity for periods of bias using both data sources, as well as an analysis of correlation with the intensity and duration of observed bias, will be presented.

As part of the 2009 Phased Array Radar (PAR) Innovative Sensing Experiment (PARISE), a customized scanning strategy was developed using an unusually large number of elevation scans. This “dense sampling” strategy is intended to provide a large amount of vertical detail for analyzing hailstorms and other events. One such event is a heat burst, which is defined as a region of air that experiences significant warming as it descends rapidly. Heat bursts can create localized temperature spikes and dew point depressions of 10°C in as little as 15 min. People sensitive to heat may be threatened by this sudden change in temperature. Wind gusts of 25 m s-1 or higher may also occur, leading to potential property or agricultural damage. Because rapidly descending air precedes heat bursts, it is likely that analyses of detailed radar observations in elevation will lead to better understanding of how and when they may occur.

In the early morning hours of 13 May 2009, a series of heat bursts was observed by approximately 70 Oklahoma Mesonet stations. Rawinsonde data obtained from Norman, Oklahoma at 0000 UTC 13 May 2009 indicate a nearly dry-adiabatic lapse rate and relatively dry air between 750 and 400 mb. As thunderstorms moved into the region and dissipated, precipitation evaporated aloft and generated descent. The lapse rate allowed the descending air to increase in velocity and warm rapidly, resulting in heat bursts that spread over a large area. At 0320 UTC, a 15-min temperature increase of 8.0°C, dew point depression of 6.7°C and maximum wind gust of 23 m s-1 were observed in southwestern Oklahoma. Seven hours later, another 15-min temperature spike of 6.0°C, dew-point depression of 6.0°C and maximum wind gust of 15 m s-1 were observed in north-central Oklahoma. The other Mesonet stations reported weaker heat burst activity over this time period.

During this event, the NWRT PAR performed scans for a 2.5-hr period using the dense sampling strategy. To evaluate the usefulness of the closely spaced elevation scans, it is necessary to compare these results with those from a scan with fewer elevations. For this study, individual elevations will be selectively removed from the PAR dense sampling data to form a second “sparse” scan. Vertical cross-sections will be constructed at selected Mesonet sites, in order to demonstrate the detail obtained from both scans. Vertical reflectivity profiles will also be produced from both scans in order to provide a quantitative comparison of heat burst observations. The analysis will provide insight into which radar features are significant in analyzing and predicting heat burst activity. In addition, the results will provide guidance on how to implement PAR scanning when a large amount of vertical detail is necessary.

Since reported at the previous radar conference, significant enhancements have been made to the National Weather Radar Testbed (NWRT) phased array radar (PAR). As part of an ongoing effort, the radar control interface (RCI) has been improved to support system development, operations, and research. For example, as the adaptive scanning capabilities of the phased array radar are being explored and developed, further improvements to the RCI are being made to provide an effective interface between the PAR and the developers, scientists, and users.
This paper describes the improvements to the NWRT RCI and discusses the impacts of these in terms of increasing the usability of this unique radar system.

Available online at http://ams.confex.com/ams/34Radar/techprogram/paper_155633.htm.