Gauthreaux, S. A., Jr, and R. H. Diehl. Discrimination of biological scatterers in weather radar data: opportunities and challenges
Summary
This WSR-88D weather radar dataset includes different types of scatterers hand-screened and identified based on a combination of scientific literature and media reports of biological events, knowledge of animal natural history in confirming radar sweeps characterized by a given type, and a re-evaluation and subsampling process to avoid inclusion of non-focal types. The dataset is comprised of eight scatterers, seven biological and one meteorological: trans-gulf migrants, purple martins (Progne subis), waterfowl and sandhill cranes, black-necked grebes (i.e., eared grebe, Podiceps nigricollis), Brazilian free-tailed bats (Tadarida brasiliensis), diurnal insects, mayflies and midges, and precipitation. This dataset currently includes [...]
Summary
This WSR-88D weather radar dataset includes different types of scatterers hand-screened and identified based on a combination of scientific literature and media reports of biological events, knowledge of animal natural history in confirming radar sweeps characterized by a given type, and a re-evaluation and subsampling process to avoid inclusion of non-focal types. The dataset is comprised of eight scatterers, seven biological and one meteorological: trans-gulf migrants, purple martins (Progne subis), waterfowl and sandhill cranes, black-necked grebes (i.e., eared grebe, Podiceps nigricollis), Brazilian free-tailed bats (Tadarida brasiliensis), diurnal insects, mayflies and midges, and precipitation. This dataset currently includes six radar metrics (radar reflectivity, radial velocity, spectrum width, differential reflectivity, correlation coefficient, differential phase) for each of nearly 4.5 million sample volumes across 130 radar sweeps. These samples comprise the master dataset, available below, that are the basis for analyses in Gauthreaux and Diehl (2020).
