On the Processing of Radar Data for Mayfly Population Estimation in the Upper Mississipi River Region (UMRR)

This paper introduces a methodology for estimating mayfly populations by utilizing radar data from the US National Weather Service's NEXRAD system. The research emphasizes the integration of Python-based tools, including PyEphem, Boto3, and Py-ART, to efficiently retrieve, process, and filter radar data, thereby improving the accuracy of mayfly emergence monitoring. The filtration process leverages advanced polarimetric radar techniques, allowing for the effective distinction between meteorological and biological targets, such as insects. The method estimates mayfly population density by calculating the total backscattering area from radar reflectivity data, which is then used to derive the number of mayflies in the surveyed region. This approach provides a robust and reliable technique for ecological monitoring and can be applied to studies of insect migrations and environmental shifts within the Upper Mississippi River Region (UMRR).