Microburst Wind Structure and Evaluation of Doppler Radar for Airport Wind Shear Detection

Wilson, James W.; Roberts, Rita D.; Kessinger, Cathy; McCarthy, John

doi:10.1175/1520-0450(1984)023<0898:mwsaeo>2.0.co;2

Cited by 309 publications

(93 citation statements)

References 11 publications

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“…The low-level coverage of IP1 is important for dual-Doppler retrievals in that it provides a better initial condition for the upward integration technique, and allows for detection of divergence often associated with low-level downdrafts. These types of observations could help detect downbursts in future cases (Wilson et al 1984), as well as strong areas of outflow.…”

Section: Discussionmentioning

confidence: 99%

Using CASA IP1 to Diagnose Kinematic and Microphysical Interactions in a Convective Storm

Dolan

Rutledge

2010

Monthly Weather Review

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Data from the Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project I (IP1) network of polarimetric X-band radars are used to observe a convective storm. A fuzzy logic hydrometeor identification algorithm is employed to study microphysical processes. Dual-Doppler techniques are used to analyze the 3D wind field. The scanning strategy, sensitivity, and low-level scanning focus of the radars are investigated for influencing bulk hydrometeor identification and dual-Doppler wind retrievals. Comparisons are made with the nearby S-band polarimetric Next Generation Weather Radar (NEXRAD) prototype radar (KOUN), for consistency. Lightning data are used as an independent indicator of storm evolution for comparison with radar observations.A new methodology for retrieving the vertical wind utilizing upward and variational integration techniques is employed and shown to illustrate trends in mean wind, with particularly good results at low levels. IP1 observations of a case on 10 June 2007 show the development of the updraft, subsequent graupel echo volume evolution, and a descending downdraft preceded by significant graupel in the midlevels, with updraft and graupel volumes leading the onset of lightning. Many of these trends are corroborated by KOUN. The high temporal resolution of three minutes and near-ground sampling provided by IP1 is integral to resolving upand downdrafts, as well as hydrometeor evolution. IP1 coverage of the upper levels is diminished compared to KOUN, impacting the quality of the dual-Doppler derived vertical winds and ice echo volumes, although the low-level coverage helps to mitigate some errors. However, IP1 coverage of the low-to midlevels is demonstrated to be comparable or better than coverage by KOUN for this storm location.

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Section: Discussionmentioning

confidence: 99%

Using CASA IP1 to Diagnose Kinematic and Microphysical Interactions in a Convective Storm

Dolan

Rutledge

2010

Monthly Weather Review

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“…In particular, phenomena like tornadogenesis (Lemon and Doswell 1979;Brandes 1984;Ziegler et al 2001) and microbursts (Fujita 1981) that occur on short time and space scales (e.g., Wilson et al 1984), or damaging straight-line winds from bow echoes (Johns 1993;Przybylinski 1995;Weisman 2001) that require observations of the low levels of the atmosphere, are generally not well sampled by the WSR-88D network. This is also true for infrequent events, like landfalling hurricanes (e.g., Powell et al 1991).…”

Section: The Need For Mobile Observing Systemsmentioning

confidence: 99%

The Shared Mobile Atmospheric Research and Teaching Radar: A Collaboration to Enhance Research and Teaching

Biggerstaff¹,

Wicker²,

Guynes³

et al. 2005

Bull. Amer. Meteor. Soc.

112

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Overcoming numerous challenges, a unique partnership created two C-band mobile Doppler weather radars capable of accurately measuring both clear-air circulations and damaging winds in heavy rain. Starting with acquisition of two decommissioned 1974 C-band National Weather Service (NWS) Weather Surveillance Radars (WSR-74Cs) in early 1998, a coalition of scientists from the University of Oklahoma (OU), National Severe Storms Laboratory (NSSL), Texas A&M University (TAMU), and Texas Tech University (TTU) embarked on a project to build and deploy two mobile C-band Doppler weather radars for storm-scale research and to enhance graduate and undergraduate education in radar meteorology. This project culminated in the successful development and deployment of the first mobile C-band Doppler weather radar, dubbed SR-1, in 2001 (Fig. 1). To

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“…Because surface wind damage is frequently caused by microbursts and tornadoes, whose wind speeds attain maximum values at around 200 m AGL and decrease with altitude (Wilson et al 1984;Wurman and Kosiba 2013), it is important to monitor the wind field at altitudes that are as low as possible. Therefore, the error factors of WS PPI-VAR and WS CAPPI-VAR at the lowest level (500 m AGL) are discussed in detail.…”

Section: Resultsmentioning

confidence: 99%

Impact of Observation Operators on Low-Level Wind Speed Retrieved by Variational Multiple-Doppler Analysis

Shimose

Shimizu

Maesaka

et al. 2016

SOLA

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This study investigated the impact of observation operators on low-level wind speed analysis. An evaluation of wind speeds retrieved by variational multiple-Doppler analyses using radial velocities (V r ) based on the formats of both a Plan Position Indicator (PPI) (hereafter, PPI-VAR) and a Constant Altitude Plan Position Indicator (CAPPI) (hereafter, CAPPI-VAR) was performed for comparison with wind speeds observed by a wind profiler during the warm season of three consecutive years. The statistical analysis showed that PPI-VAR was more accurate than CAPPI-VAR at 500 m above ground level (AGL). The error of CAPPI-VAR at 500 m AGL was caused by a representative error of CAPPI-formatted V r derived from a certain radar whose beam height was far from the analysis level, and this error became more obvious the greater the vertical difference in wind speed across the analysis level. CAPPI-VAR uses CAPPI-formatted V r from each radar equally; thus, the representative error might cause performance degradation of CAPPI-VAR at 500 m AGL. Conversely, PPI-VAR uses PPI-formatted V r from each radar with appropriate weighting based on the beam height distance from the analysis level. PPI-VAR showed better results at 500 m AGL because the observation grid points were dense around 500 m AGL.

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Microburst Wind Structure and Evaluation of Doppler Radar for Airport Wind Shear Detection

Cited by 309 publications

References 11 publications

Using CASA IP1 to Diagnose Kinematic and Microphysical Interactions in a Convective Storm

Using CASA IP1 to Diagnose Kinematic and Microphysical Interactions in a Convective Storm

The Shared Mobile Atmospheric Research and Teaching Radar: A Collaboration to Enhance Research and Teaching

Impact of Observation Operators on Low-Level Wind Speed Retrieved by Variational Multiple-Doppler Analysis

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