Quasi-vertical profiles (QVPs) obtained from a database of U.S. WSR-88D data are used to document polarimetric characteristics of the melting layer (ML) in cold-season storms with high vertical resolution and accuracy. A polarimetric technique to define the top and bottom of the ML is first introduced. Using the QVPs, statistical relationships are developed to gain insight into the evolution of microphysical processes above, within, and below the ML, leading to a statistical polarimetric model of the ML that reveals characteristics that reflectivity data alone are not able to provide, particularly in regions of weak reflectivity factor at horizontal polarization ZH. QVP ML statistics are examined for two regimes in the ML data: ZH≥ 20 dB Z and ZH< 20 dB Z. Regions of ZH≥ 20 dB Z indicate locations of MLs collocated with enhanced differential reflectivity ZDRand reduced copolar correlation coefficient ρhv, while for ZH< 20 dB Z a well-defined ML is difficult to discern using ZHalone. Evidence of large ZDRup to 4 dB, backscatter differential phase δ up to 8°, and low ρhvdown to 0.80 associated with lower ZH(from −10 to 20 dB Z) in the ML is observed when pristine, nonaggregated ice falls through it. Positive correlation is documented between maximum specific differential phase KDPand maximum ZHin the ML; these are the first QVP observations of KDPin MLs documented at S band. Negative correlation occurs between minimum ρhvin the ML and ML depth and between minimum ρhvin the ML and the corresponding enhancement of ZH(Δ ZH= ZHmax− ZHrain).
Mobile Radar Observations of the Evolving Debris Field Compared with a Damage Survey of the Shawnee, Oklahoma, Tornado of 19 May 2013
A detailed damage survey is combined with high-resolution mobile, rapid-scanning X-band polarimetric radar data collected on the Shawnee, Oklahoma, tornado of 19 May 2013. The focus of this study is the radar data collected during a period when the tornado was producing damage rated EF3. Vertical profiles of mobile radar data, centered on the tornado, revealed that the radar reflectivity was approximately uniform with height and increased in magnitude as more debris was lofted. There was a large decrease in both the cross-correlation coefficient ( ρ hv ) and differential radar reflectivity ( Z DR ) immediately after the tornado exited the damaged area rated EF3. Low ρ hv and Z DR occurred near the surface where debris loading was the greatest. The 10th percentile of ρ hv decreased markedly after large amounts of debris were lofted after the tornado leveled a number of structures. Subsequently, ρ hv quickly recovered to higher values. This recovery suggests that the largest debris had been centrifuged or fallen out whereas light debris remained or continued to be lofted. Range–height profiles of the dual-Doppler analyses that were azimuthally averaged around the tornado revealed a zone of maximum radial convergence at a smaller radius relative to the leading edge of lofted debris. Low-level inflow into the tornado encountering a positive bias in the tornado-relative radial velocities could explain the existence of the zone. The vertical structure of the convergence zone was shown for the first time.
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- NSF-PAR ID:
- 10149719
- Date Published:
- Journal Name:
- Monthly Weather Review
- Volume:
- 148
- Issue:
- 5
- ISSN:
- 0027-0644
- Page Range / eLocation ID:
- 1779 to 1803
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This study utilizes data collected by the University of Oklahoma Advanced Radar Research Center’s Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) C-band radar as well as the federal KTLX and KOUN WSR-88D S-band radars to study a supercell that simultaneously produced a long-track EF-4 tornado and an EF-2 landspout tornado (EF indicates the enhanced Fujita scale) near Norman, Oklahoma, on 10 May 2010. Contrasting polarimetric characteristics of two tornadoes over similar land cover but with different intensities are documented. Also, the storm-scale sedimentation of debris within the supercell is investigated, which includes observations of rotation and elongation of a tornadic debris signature with height. A dual-wavelength comparison of debris at S and C bands is performed. These analyses indicate that lofted debris within the tornado was larger than debris located outside the damage path of the tornado and that debris size outside the tornado increased with height, likely as the result of centrifuging. Profiles of polarimetric variables were observed to become more vertically homogeneous with time.more » « less
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Abstract A novel polarimetric radar algorithm for melting-layer (ML) detection and determination of its height has been developed and tested for a large number of cold-season weather events. The algorithm uses radial profiles of the cross-correlation coefficient ( ρ hv or CC) at the lowest elevation angles (<5°–6°). The effects of beam broadening on the spatial distribution of CC have been taken into account via theoretical simulations of the radial profiles of CC assuming intrinsic vertical profiles of polarimetric radar variables within the ML with varying heights and depths of the ML. The model radial profiles of CC and their key parameters are stored in lookup tables and compared with the measured CC profiles. The matching of the model and measured CC radial profiles allows the algorithm to determine the “true” heights of the top and bottom of the ML, H t and H b , at distances up to 150 km from the radar. Integrating the CC information from all available antenna elevations makes it possible to produce accurate maps of H t and H b over large areas of radar coverage as opposed to the previous ML detection methods including the existing algorithm implemented on the U.S. network of the WSR-88Ds. The initial version of the algorithm has been implemented in C++ and tested for a multitude of cold-season weather events characterized by a low ML with different degrees of spatial nonuniformity including cases with sharp frontal boundaries and rain–snow transitions. The new ML detection algorithm (MLDA) exhibits robust performance, demonstrating spatial and temporal continuity, and showing general consistency of the ML designations matching those obtained from the regional model and the quasi-vertical profiles (QVP) methodology output.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/MWR-D-19-0215.1
