Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Range-Correcting Azimuthal Shear in Doppler Radar Data

Range-Correcting Azimuthal Shear in Doppler Radar Data The current tornado detection algorithm (TDA) used by the National Weather Service produces a large number of false detections, primarily because it calculates azimuthal shear in a manner that is adversely impacted by noisy velocity data and range-degraded velocity signatures. Coincident with the advent of new radar-derived products and ongoing research involving new weather radar systems, the National Severe Storms Laboratory is developing an improved TDA. A primary component of this algorithm is the local, linear least squares derivatives (LLSD) azimuthal shear field. The LLSD method incorporates rotational derivatives of the velocity field and is affected less strongly by noisy velocity data in comparison with traditional “peak to peak” azimuthal shear calculations. LLSD shear is generally less range dependent than peak-to-peak shear, although some range dependency is unavoidable. The relationship between range and the LLSD shear values of simulated circulations was examined to develop a range correction for LLSD shear. A linear regression and artificial neural networks (ANNs) were investigated as range-correction models. Both methods were used to produce fits for the simulated shear data, although the ANN excelled as it could capture the nonlinear nature of the data. The range-correction methods were applied to real radar data from tornadic and nontornadic events to measure the capacity of the corrected shear to discriminate between tornadic and nontornadic circulations. The findings presented herein suggest that both methods increased shear values during tornadic periods by nearly an order of magnitude, facilitating differentiation between tornadic and nontornadic scans in tornadic events. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Weather and Forecasting American Meteorological Society

Loading next page...
 
/lp/american-meteorological-society/range-correcting-azimuthal-shear-in-doppler-radar-data-GYOBwYuw5t

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
American Meteorological Society
Copyright
Copyright © 2011 American Meteorological Society
ISSN
0882-8156
eISSN
1520-0434
DOI
10.1175/WAF-D-11-00154.1
Publisher site
See Article on Publisher Site

Abstract

The current tornado detection algorithm (TDA) used by the National Weather Service produces a large number of false detections, primarily because it calculates azimuthal shear in a manner that is adversely impacted by noisy velocity data and range-degraded velocity signatures. Coincident with the advent of new radar-derived products and ongoing research involving new weather radar systems, the National Severe Storms Laboratory is developing an improved TDA. A primary component of this algorithm is the local, linear least squares derivatives (LLSD) azimuthal shear field. The LLSD method incorporates rotational derivatives of the velocity field and is affected less strongly by noisy velocity data in comparison with traditional “peak to peak” azimuthal shear calculations. LLSD shear is generally less range dependent than peak-to-peak shear, although some range dependency is unavoidable. The relationship between range and the LLSD shear values of simulated circulations was examined to develop a range correction for LLSD shear. A linear regression and artificial neural networks (ANNs) were investigated as range-correction models. Both methods were used to produce fits for the simulated shear data, although the ANN excelled as it could capture the nonlinear nature of the data. The range-correction methods were applied to real radar data from tornadic and nontornadic events to measure the capacity of the corrected shear to discriminate between tornadic and nontornadic circulations. The findings presented herein suggest that both methods increased shear values during tornadic periods by nearly an order of magnitude, facilitating differentiation between tornadic and nontornadic scans in tornadic events.

Journal

Weather and ForecastingAmerican Meteorological Society

Published: Dec 14, 2011

There are no references for this article.