Taxonomic resolution in dual‐polarization weather radar observations of biological scatterers: A systematic review

Abstract The derivation of biological information—abundance, diversity, movement of organisms—from dual‐polarization weather surveillance radars (WSRs) presents an opportunity for novel large‐scale biodiversity monitoring. This review takes a systematic approach to ask what degree of taxonomic resolution has so far been achieved in dual‐polarization WSR observations. A range of methods are described that can be classified as observational, algorithmic, or modeling‐based approaches. While progress toward finer taxonomic resolution (species, genus, family) so far has been limited, machine learning methods demonstrate that the information for at least some degree of taxonomic resolution is present in the data, and electromagnetic modeling provides a valuable research direction. A more systematic, interdisciplinary approach that incorporates zoological understanding, radar physics, and machine learning is recommended for future research.