A Technique to Censor Biological Echoes in Radar Reflectivity Data

Existing techniques of quality control of radar reflectivity data rely on local texture and vertical profiles to discriminate between precipitating echoes and non-precipitating echoes. Non-precipitating echoes may be due to artifacts such as anamalous propagation, ground clutter, electronic interference, sun strobe, and biological contaminants (i.e., birds, bats and insects). The local texture of reflectivity fields suffices to remove most artifacts, except for biological echoes. Biological echoes, also called ”bloom” echoes because of their circular shape and expanding size during the night time, have proven difficult to remove, especially in peak migration seasons of various biological species, because they can have local and vertical characteristics similar to that of stratiform rain or snow. In this paper, we describe a technique that identifies candidate bloom echoes based on the range-variance of reflectivity in areas of bloom, and uses the global, rather than local, characteristic of the echo to discriminate between bloom and rain. Every range gate is assigned a probability that it corresponds to bloom using morphological (shape-based) operations and a neural network is trained using this probability as one of the input features. We demonstrate that this technique is capable of identifying and removing echoes due to biological targets and other types of artifacts while retaining echoes that correspond to precipitation. Citation: author = {Valliappa Lakshmanan and Jian Zhang and Kenneth