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The Bounded Weak Echo Region Algorithm

Bounded Weak Echo Regions (BWERs) are radar features that are often associated with supercell thunderstorms. A BWER is a region of relatively low radar reflectivity which extends upward into, and is surrounded by, higher reflectivities aloft. This radar signature is usually indicative of a high speed updraft.For a detailed description of the BWER algorithm including the features considered and how they are computed, the reader is directed to Lakshmanan and Witt (1997).

The BWER algorithm first computes both two-dimensional and three-dimensional features of candidate regions by filtering the radar elevation scans. The features associated with a candidate are used as inputs to a fuzzy rule base. The rule base then provides a confidence estimate that the candidate region is a BWER. In the work described in this paper, the second part of the BWER algorithm - obtaining a confidence estimate of a candidate BWER from a set of features using a fuzzy rule base - is optimized.

The first stage of the BWER algorithm (see Fig. 1) is an image processing stage in which the radar elevation scans are preprocessed and filtered to yield regions of low reflectivity adjoining regions of high reflectivity. The regions in each radar elevation scan are labeled at this stage. Labeled regions from successive elevations scans of the radar are stacked vertically together to form a three-dimensional (3D) set of regions. This 3D set along with the 3D set of original Cartesian grids similarly stacked is used for further processing.

Figure 1: The stages of the BWER detection algorithm. The first row of figures is an image processing stage in which reflectivity scans are processed, candidate regions identified and their features computed. The computed features are passed through a bank of fuzzy sets that have been optimized by the genetic algorithm and the resulting fuzzy values are used by a rule base to determine whether the candidate region is a BWER.

Various measures are computed from the properties of these 3D sets. For example, the degree to which a region is capped is obtained from four fuzzy sets that are evaluated for the region:

Note, in particular, that the properties that determine the 45 dBZ capping extent correspond either to the region itself or to one of the regions above/below it and from which it can inherit attributes (see Fig. 2).

All computed attributes of a region are carried over to the optimization stage. It is over this second stage (the second row of diagrams in Fig. 1) that we will optimize the membership functions of the fuzzy sets corresponding to each of the attributes.

Figure 2: Candidate regions found at different elevation scans of the radar are stacked spatially to form a volume. Areas with reflectivity greater than 45 dBZ are shown shaded. The dotted lines show all the possible mechanisms through which a region can inherit 3D attributes.

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