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Proceedings Paper

Wavelet-based algorithm for mesocyclone detection
Author(s): Paul R. Desrochers; Samuel Y. K. Yee
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Paper Abstract

Severe weather such as tornadoes and large hail often emanates from thunderstorms that have persistent, well organized, rotating updrafts. These rotating updrafts, which are generally referred to as mesocyclones, appear as couplets of incoming and outgoing radial velocities to a single Doppler radar. Observations of mesocyclones reveal useful information on the kinematics in the vicinity of the storm updraft that, if properly interpreted, can be used to assess the likelihood and intensity of the severe weather. Automated algorithms for such assessments exist, but are inconsistent in their wind shear estimations and are prone to high false alarm rates. Reported here are the elements of a new approach that we believe will alleviate the shortcomings of previous mesocyclone detection algorithms. This wavelet-based approach enables us to focus on the known scales where mesocyclones reside. Common data quality problems associated with radar data such as noise and data gaps are handled effectively by the approach presented here. We demonstrate our approach with a 1D test pattern, then with a 2D synthetic mesocyclone vortex, and finally with a case study.

Paper Details

Date Published: 30 October 1997
PDF: 11 pages
Proc. SPIE 3169, Wavelet Applications in Signal and Image Processing V, (30 October 1997); doi: 10.1117/12.279702
Show Author Affiliations
Paul R. Desrochers, Air Force Research Lab. (United States)
Samuel Y. K. Yee, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 3169:
Wavelet Applications in Signal and Image Processing V
Akram Aldroubi; Andrew F. Laine; Michael A. Unser, Editor(s)

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