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Vivek N. Mahale
,
Guifu Zhang
, and
Ming Xue

Abstract

On 14 June 2011, thunderstorms developed along a cold front in central Oklahoma in a thermodynamic environment that was conducive for downbursts. One of the thunderstorms produced a wet downburst in Norman, Oklahoma, that resulted in surface winds in excess of 35 m s−1 (>80 mi h−1) and hailstones in excess of 4 cm in diameter. Unique 1-min observations of the downburst were recorded by an Oklahoma Mesonet station. These observations indicated a 6.6-hPa pressure rise that was coincident with a rain rate of 213 mm h−1 at the center of the downburst. In this event, both the research KOUN (Norman) and operational KTLX (Oklahoma City, Oklahoma) Weather Surveillance Radar-1988 Doppler (WSR-88D) instruments were scanning this downburst and its parent storm at close range (<30 km). KOUN provided polarimetric radar data (PRD) while both radars provided limited dual-Doppler coverage. The evolution of the downburst is analyzed mostly through the use of reconstructed range–height indicators of the PRD. A hydrometeor classification algorithm (HCA) is applied to the PRD to gain further understanding of the microphysical evolution of the downburst. Through the analyses, it is seen that graupel aloft made a transition to a nearly all rain and hail mixture above the 0°C level. This large area of mixed rain and hail eventually descended to the ground, causing the downburst. In this study, the HCA analyses are utilized to develop a conceptual model that characterizes the hydrometeor evolution of the parent downburst storm.

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Vivek N. Mahale
,
Guifu Zhang
, and
Ming Xue

Abstract

The three-body scatter signature (TBSS) is a radar artifact that appears downrange from a high-radar-reflectivity core in a thunderstorm as a result of the presence of hailstones. It is useful to identify the TBSS artifact for quality control of radar data used in numerical weather prediction and quantitative precipitation estimation. Therefore, it is advantageous to develop a method to automatically identify TBSS in radar data for the above applications and to help identify hailstones within thunderstorms. In this study, a fuzzy logic classification algorithm for TBSS identification is developed. Polarimetric radar data collected by the experimental S-band Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN), are used to develop trapezoidal membership functions for the TBSS class of radar echo within a hydrometeor classification algorithm (HCA). Nearly 3000 radar gates are removed from 50 TBSSs to develop the membership functions from the data statistics. Five variables are investigated for the discrimination of the radar echo: 1) horizontal radar reflectivity factor Z H , 2) differential reflectivity Z DR, 3) copolar cross-correlation coefficient ρ hv, 4) along-beam standard deviation of horizontal radar reflectivity factor SD(Z H ), and 5) along-beam standard deviation of differential phase SD(ΦDP). These membership functions are added to an HCA to identify TBSSs. Testing is conducted on radar data collected by dual-polarization-upgraded operational WSR-88Ds from multiple severe-weather events, and results show that automatic identification of the TBSS through the enhanced HCA is feasible for operational use.

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Vivek N. Mahale
,
Jerald A. Brotzge
, and
Howard B. Bluestein

Abstract

On 2 April 2010, a developing quasi-linear convective system (QLCS) moved rapidly northeastward through central Oklahoma spawning at least three intense, mesoscale vortices. At least two of these vortices caused damage rated as category 0 to 1 on the enhanced Fujita scale (EF0–EF1) in and near the town of Rush Springs. Two radar networks—the National Weather Service Weather Surveillance Radar-1988 Doppler network (WSR-88D) and the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network—collected high spatial and temporal resolution data of the event. This study is an in-depth polarimetric analysis of mesovortices within a QLCS. In this case study, the storm development and evolution of the QLCS mesovortices are examined. Significant findings include the following: 1) The damage in Rush Springs was caused by a combination of the fast translation speed and the embedded circulations associated with QLCS vortices. The vortices’ relative winds nearly negated the storm motion to the left of the vortex, but doubled the ground-relative wind to the right of the vortex. 2) A significant differential reflectivity (Z DR) arc developed along the forward flank of the first vortex. The Z DR arc propagated northeastward along the QLCS with the development of each new vortex. 3) A minimum in the copolar correlation coefficient ( ρ hv) in the center of the strongest vortex was observed, indicating the likely existence of a polarimetric tornado debris signature (TDS). A secondary ρ hv minimum also was found just to the right of the vortex center, possibly associated with lofted debris from straight-line winds.

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Vivek N. Mahale
,
Jerald A. Brotzge
, and
Howard B. Bluestein

Abstract

Adding a mix of X- or C-band radars to the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network could address several limitations of the network, including improvements to spatial gaps in low-level coverage and temporal sampling of volume scans. These limitations can result in missing critical information in highly dynamic events, such as tornadoes and severe straight-line wind episodes. To evaluate the potential value of a mixed-band radar network for severe weather operations, a case study is examined using data from X- and S-band radars. On 13 May 2009, a thunderstorm complex associated with a cold front moved southward into southwest Oklahoma. A tornado rapidly developed from an embedded supercell within the complex. The life cycle of the tornado and subsequent wind event was sampled by the experimental Collaborative Adaptive Sensing of the Atmosphere (CASA) radar testbed of four X-band radars as well as two operational WSR-88Ds. In this study, the advantages of a mixed-band radar network are demonstrated through a chronological analysis of the event. The two radar networks provided enhanced overall situational awareness. Data from the WSR-88Ds provided 1) clear-air sensitivity, 2) a broad overview of the storm complex, 3) a large maximum unambiguous range, and 4) upper-level scans up to 19.5°. Data from the CASA radars provided 1) high-temporal, 1-min updates; 2) overlapping coverage for dual-Doppler analysis; and 3) dense low-level coverage. The combined system allowed for detailed, dual- and single-Doppler observations of a wind surge, a mesocyclone contraction, and a downburst.

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Vivek N. Mahale
,
Guifu Zhang
,
Ming Xue
,
Jidong Gao
, and
Heather D. Reeves

Abstract

A variational retrieval of rain microphysics from polarimetric radar data (PRD) has been developed through the use of S-band parameterized polarimetric observation operators. Polarimetric observations allow for the optimal retrieval of cloud and precipitation microphysics for weather quantification and data assimilation for convective-scale numerical weather prediction (NWP) by linking PRD to physical parameters. Rain polarimetric observation operators for reflectivity Z H, differential reflectivity Z DR, and specific differential phase K DP were derived for S-band PRD using T-matrix scattering amplitudes. These observation operators link the PRD to the physical parameters of water content W and mass-/volume-weighted diameter D m for rain, which can be used to calculate other microphysical information. The S-band observation operators were tested using a 1D variational retrieval that uses the (nonlinear) Gauss–Newton method to iteratively minimize the cost function to find an optimal estimate of D m and W separately for each azimuth of radar data, which can be applied to a plan position indicator (PPI) radar scan (i.e., a single elevation). Experiments on two-dimensional video disdrometer (2DVD) data demonstrated the advantages of including ΦDP observations and using the nonlinear solution rather than the (linear) optimal interpolation (OI) solution. PRD collected by the Norman, Oklahoma (KOUN) WSR-88D on 15 June 2011 were used to successfully test the retrieval method on radar data. The successful variational retrieval from the 2DVD and the radar data demonstrate the utility of the proposed method.

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