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Steven V. Vasiloff

The potential role of the Federal Aviation Administration's Terminal Doppler Weather Radar (TDWR) to supplement the Weather Surveillance Radar-1988 Doppler (WSR-88D) for tornado detection is discussed. Compared to the WSR-88D, the TDWR has a narrower beam, lower scan angles, and faster update rates. The 11 August 1999 Salt Lake City, Utah, tornado is used as an illustration of the utility of the TDWR. The Salt Lake City TDWR was much closer to the tornado than the WSR-88D and the WSR-88D was 750 m higher than the TDWR. Because the tornado developed rapidly upward from a surface convergence line, the TDWR detected the formation earlier than the WSR-88D. Also, the vortex signatures associated with the tornado were much better defined by the TDWR.

The enhanced spatial and temporal coverage provided by the TDWR network is shown. A significant improvement in tornado detection, as well as other low-altitude phenomena, would be gained. However, ground clutter and signal attenuation can degrade coverage. Ongoing efforts by the National Weather Service to incorporate TDWR data into operations are described.

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Steven V. Vasiloff and Kenneth W. Howard

Abstract

A Shared Mobile Atmospheric Research and Teaching Radar (SMART-R) was deployed near Phoenix, Arizona, during the summer of 2004. The goal was to capture a severe microburst at close range to understand the low-altitude wind structure and evolution. During the evening of 27 July, a severe storm formed along the Estrella Mountains south of Phoenix and moved south of the SMART-R as well as the National Weather Service’s (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) in Phoenix (KIWA). Several microburst–downburst pulses were observed by radar and a surface wind gust of 67 mi h−1 was reported. The radar data illustrate the finescale structure of the microburst pulses, with the SMART-R’s higher-resolution data showing Doppler velocities 3–4 m s−1 greater than the KIWA radar. SMART-R wind shear values were 2–3 times greater with the finer resolution of the SMART-R revealing smaller features in the surface outflow wind structure. Asymmetric outflow may have been a factor as well in the different divergence values. The evolution of the outflow was very rapid with the 5-min KIWA scan intervals being too course to sample the detailed evolution. The SMART-R scans were at 3–5-min intervals and also had difficulty resolving the event. The storm environment displayed characteristics of both moderate-to-high-reflectivity microbursts, typical of the high plains of Colorado.

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Lawrence B. Dunn and Steven V. Vasiloff

Abstract

On 11 August 1999 a climatologically rare F2 tornado developed just west of downtown Salt Lake City, Utah (SLC), and moved directly through the city during the noon hour. Tornadogenesis was observed from a mountaintop WSR-88D Doppler radar 76 km (41 n mi) to the northwest of and 0.7 km (2300 ft) above SLC and also from a Terminal Doppler Weather Radar (TDWR) located only 22.2 km (12 n mi) north of and at the same elevation as SLC. Data from the TDWR offer an unambiguous view of the development of a nondescending tornado as an intensifying updraft became juxtaposed over enhanced cyclonic shear along a surface-based convergence zone. The convergence zone intensified and developed upward with a circulation center directly beneath the updraft eventually contracting to the scale of a tornado vortex. After tornadogenesis, the previously disorganized thunderstorm displayed characteristics commonly associated with supercells, such as a hook echo, bounded weak-echo region, a WSR-88D algorithm detection of a mesocyclone, and a visible wall cloud.

The mountaintop WSR-88D was able to identify the tornado in the base velocity data and via the latest operational version of the Tornado Detection Algorithm. However, interpretation of velocity products produced by the radar system for real-time operations was problematic due to degradation with range of the displayed data. Without access to the full-resolution velocity data in real time, it would be impossible for a forecaster to corroborate the algorithm tornado detection.

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Steven V. Vasiloff, Kenneth W. Howard, and Jian Zhang

Abstract

The principal source of information for operational flash flood monitoring and warning issuance is weather radar–based quantitative estimates of precipitation. Rain gauges are considered truth for the purposes of validating and calibrating real-time radar-derived precipitation data, both in a real-time sense and climatologically. This paper examines various uncertainties and challenges involved with using radar and rain gauge data in a severe local storm environment. A series of severe thunderstorm systems that occurred across northeastern Montana illustrates various problems with comparing radar precipitation estimates and real-time gauge data, including extreme wind effects, hail, missing gauge data, and radar quality control. Ten radar–gauge time series pairs were analyzed with most found to be not useful for real-time radar calibration. These issues must be carefully considered within the context of ongoing efforts to develop robust real-time tools for evaluating radar–gauge uncertainties. Recommendations are made for radar and gauge data quality control efforts that would benefit the operational use of gauge data.

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Vincent T. Wood, Rodger A. Brown, and Steven V. Vasiloff

Abstract

About one-third of the Weather Surveillance Radar-1988 Doppler (WSR-88D) radars located in the western third of the United States are on the tops of mountains. These mountaintop radars employ scanning strategies that were designed for flatland radars, with the lowest elevation angle being +0.5°. Consequently, the radar signals are sent well above the populace and terrain surrounding the radar. The inability to adequately detect low-altitude weather events results in missed warnings of severe weather and in underestimates of the amount and areal extent of precipitation. Mountaintop radars could be utilized much more effectively if the scanning strategies included negative elevation angles. The state of Utah has the disadvantage that all three of the WSR-88Ds used by the National Weather Service to monitor weather events in the state are located on the tops of mountains. To determine the extent to which negative elevation angles would improve the detection capabilities of these radars over Utah and portions of the adjacent states, a WSR-88D simulation model is used to compare the existing scanning strategies with those that incorporate negative elevation angles. As might be expected, the use of negative elevation angles enhances low- to midaltitude detection of weather events over a much larger area than is possible using the existing scanning strategies. For example, the area where the centers of the beams from the three radars currently are within 1 km of the ground encompasses only 2% of the area within 230 km of the radars. Using negative elevation angles, the areal coverage within 1 km of the ground increases to over 30%.

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Steven V. Vasiloff, Richard J. Doviak, and Michael T. Istok

Abstract

The Next Generation Weather Radar (NEXRAD) may use a 5-min volume scan to monitor thunderstorms and provide hazard warnings. Short-lifetime, low-altitude wind shear near airports is a hazard to safe flights that deserves special attention. An interlaced scanning strategy is examined for its effects on the accuracy and reliability of some NEXRAD storm analysis and tracking algorithms that require noninterlaced data. By increasing the elevation step to twice its normal value and starting every other scan at the second step of the corresponding 5-min sequence, a pair of 2½-min sequences is achieved. These can be recombined for use in the NEXRAD algorithms while providing a shorter period between observations of rapidly developing phenomena such as low-altitude wind shear. It is found that differences between storm cell attributes derived from successive non-interlaced scans are about the same as differences between values obtained from interlaced and noninterlaced volume scans for the same time period. Thus, interlaced scanning may halve the wind shear warning time to be provided by the proposed NEXRAD noninterlaced scan strategy without significantly compromising the evaluation of storm attributes. Growth rates of reflectivity and updraft speed for several cells during the growth stage of a severe thunderstorm have been assessed in relation to the need for 2½-min updates to resolve severe thunderstorm phenomena. Results indicate that the growth rates are not so rapid as to require interlaced scanning for this purpose.

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Steven V. Vasiloff, Edward A. Brandes, Robert P. Davies-Jones, and Peter S. Ray

Abstract

Nearly 2½ hours of dual-Doppler radar data with high temporal and spatial resolution are used to examine the evolution and morphology of a thunderstorm that evolved from a complex of small cells into a supercell storm. Individual storm cells and updrafts moved east-northeastward, nearly with the mean wind, while the storm complex, which encompassed the individual cells, propagated toward the south–southeast. Cells were first detected at middle levels (5–10 km) on the storm's right flank and dissipated on the left flank. Generally, the storm contained three cells—a forming cell, a mature cell, and a dissipating cell; life stages were apparently dictated by the source of updraft air. During the growth stage, cell inflow had a southerly component. As the cell moved through the storm complex, it started ingesting stable air from the north and soon dissipated.

A storm-environment feedback mechanism of updraft–downdraft interactions, in conjunction with increasing environmental vertical wind shear and buoyancy, is deemed responsible for an increase in the size and intensity of successive cells and updrafts. With time, a large region of background updraft, containing the updrafts of individual cells, formed on the storm's right flank. Unlike the individual cells, which moved nearly parallel to the mean wind and low-level shear vector, the region of background updraft moved to the right of the mean wind and low-level shear vector. It is believed that the formation and rightward motion of the background updraft region led to strong rotation on the storm's right flank. The larger cell and updraft size, with the same center-to-center spacing as at earlier times, made individual cell identification difficult, resulting in a nearly steady-state reflectivity structure.

The data support a growing consensus that a continuum of storm types, rather than a dichotomy, exists.

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E. De Wayne Mitchell, Steven V. Vasiloff, Gregory J. Stumpf, Arthur Witt, Michael D. Eilts, J. T. Johnson, and Kevin W. Thomas

Abstract

The National Severe Storms Laboratory (NSSL) has developed and tested a tornado detection algorithm (NSSL TDA) that has been designed to identify the locally intense vortices associated with tornadoes using the WSR-88D base velocity data. The NSSL TDA is an improvement over the current Weather Surveillance Radar-1988 Doppler (WSR-88D) Tornadic Vortex Signature Algorithm (88D TVS). The NSSL TDA has been designed to address the relatively low probability of detection (POD) of the 88D TVS algorithm without a high false alarm rate (FAR). Using an independent dataset consisting of 31 tornadoes, the NSSL TDA has a POD of 43%, FAR of 48%, critical success index (CSI) = 31%, and a Heidke skill score (HSS) of 46% compared to the 88D TVS, which has a POD of 3%, FAR of 0%, CSI of 3%, and HSS of 0%. In contrast to the 88D TVS, the NSSL TDA identifies tornadic vortices by 1) searching for strong shear between velocity gates that are azimuthally adjacent and constant in range, and 2) not requiring the presence of an algorithm-identified mesocyclone. This manuscript discusses the differences between the NSSL TDA and the 88D TVS and presents a performance comparison between the two algorithms. Strengths and weaknesses of the NSSL TDA and NSSL’s future work related to tornado identification using Doppler radar are also discussed.

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Steven V. Vasiloff, Dong-Jun Seo, Kenneth W. Howard, Jian Zhang, David H. Kitzmiller, Mary G. Mullusky, Witold F. Krajewski, Edward A. Brandes, Robert M. Rabin, Daniel S. Berkowitz, Harold E. Brooks, John A. McGinley, Robert J. Kuligowski, and Barbara G. Brown

Accurate quantitative precipitation estimates (QPE) and very short term quantitative precipitation forecasts (VSTQPF) are critical to accurate monitoring and prediction of water-related hazards and water resources. While tremendous progress has been made in the last quarter-century in many areas of QPE and VSTQPF, significant gaps continue to exist in both knowledge and capabilities that are necessary to produce accurate high-resolution precipitation estimates at the national scale for a wide spectrum of users. Toward this goal, a national next-generation QPE and VSTQPF (Q2) workshop was held in Norman, Oklahoma, on 28–30 June 2005. Scientists, operational forecasters, water managers, and stakeholders from public and private sectors, including academia, presented and discussed a broad range of precipitation and forecasting topics and issues, and developed a list of science focus areas. To meet the nation's needs for the precipitation information effectively, the authors herein propose a community-wide integrated approach for precipitation information that fully capitalizes on recent advances in science and technology, and leverages the wide range of expertise and experience that exists in the research and operational communities. The concepts and recommendations from the workshop form the Q2 science plan and a suggested path to operations. Implementation of these concepts is expected to improve river forecasts and flood and flash flood watches and warnings, and to enhance various hydrologic and hydrometeorological services for a wide range of users and customers. In support of this initiative, the National Mosaic and Q2 (NMQ) system is being developed at the National Severe Storms Laboratory to serve as a community test bed for QPE and VSTQPF research and to facilitate the transition to operations of research applications. The NMQ system provides a real-time, around-the-clock data infusion and applications development and evaluation environment, and thus offers a community-wide platform for development and testing of advances in the focus areas.

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