bioRad: biological analysis and visualization of weather radar data

Abstract

Weather surveillance radars are increasingly used for monitoring the movements and abundances of animals in the airspace. However, analysis of weather radar data remains a specialised task that can be technically challenging. Major hurdles are the difficulty of accessing and visualising radar data on a software platform familiar to ecologists and biologists, processing the low‐level data into products that are biologically meaningful, and summarizing these results in standardized measures. To overcome these hurdles, we developed the open source R package bioRad, which provides a toolbox for accessing, visualizing and analyzing weather radar data for biological studies. It provides functionality to access low‐level radar data, process these data into meaningful biological information on animal speeds and directions at different altitudes in the atmosphere, visualize these biological extractions, and calculate further summary statistics. The package aims to standardize methods for extracting and reporting biological signals from weather radars. Here we describe a roadmap for analyzing weather radar data using bioRad. We also define weather radar equivalents for familiar measures used in the field of migration ecology, such as migration traffic rates, and recommend several good practices for reporting these measures. The bioRad package integrates with low‐level data from both the European radar network (OPERA) and the radar network of the United States (NEXRAD). bioRad aims to make weather radar studies in ecology easier and more reproducible, allowing for better inter‐comparability of studies.

MistNet: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks

“…This shows that simple dual‐pol‐based thresholding provides effective training signal: the trained model only has access to legacy data and exceeds the performance of the dual‐pol‐based training labels. However, note that more accurate predictions could be obtained using dual‐pol data if this were the final goal, for example, using despeckling (Kilambi et al, ) or spatial post‐processing (Dokter, Desmet, et al, ). Our goal is only to obtain a cheap and ‘good enough’ training signal.…”

Revealing patterns of nocturnal migration using the European weather radar network

“…During the time period we investigated, most migration generally passed through a site during only a few of the nights, and the pattern was heavily affected by wind conditions. This implies that migration should be forecastable (Van Belle et al ), and that directed conservation efforts over relatively few days could have large impacts (Hüppop et al ). Such directed efforts could involve shutting down wind turbines in certain areas (Hüppop et al 2006), decreasing artificial lights during specific times (McLaren et al , Van Doren et al ) or altering flight plans for aviation (Shamoun‐Baranes et al ).…”

“…Our large‐scale coverage has allowed us to map the spatial structure of avian nocturnal migration pathways through Europe, the migration intensity and migratory directions that define a part of the European flyway, and show how the migration intensity at individual sites is affected by winds. In extension, these large‐scale findings will have many important practical applications, related to the flow of biomass (Hu et al ) at a continental scale, including the transport of nutrients, energy and pathogens (Bauer and Hoye ), the risk imposed by migrating birds to aircraft (van Gasteren et al ), potential implications for conservation of birds during cross‐country flight as they pass through tall anthropogenic structures (wind‐turbines, communication towers, etc.) (Hüppop et al 2006, 2019, Shamoun‐Baranes et al ) and on the ground while stopping to rest and refuel (Buler et al , et al Hüppop et al ).…”

“…In extension, these large‐scale findings will have many important practical applications, related to the flow of biomass (Hu et al ) at a continental scale, including the transport of nutrients, energy and pathogens (Bauer and Hoye ), the risk imposed by migrating birds to aircraft (van Gasteren et al ), potential implications for conservation of birds during cross‐country flight as they pass through tall anthropogenic structures (wind‐turbines, communication towers, etc.) (Hüppop et al 2006, 2019, Shamoun‐Baranes et al ) and on the ground while stopping to rest and refuel (Buler et al , et al Hüppop et al ). Importantly, our findings can serve as a benchmark and useful reference point for the large amounts of individual migration tracks that are being collected for some species (Tøttrup et al , Arlt et al , Åkesson et al ), and also to put other data, such as local bird counts or ringing recoveries, into a larger context.…”

“…Intensity of migration was expressed as migration traffic rate (MTR), defined as the number of birds that pass a theoretical 1‐km transect perpendicular to the direction of movement during one hour. MTR was calculated as the product of density (birds km –3 ), ground speed (km h –1 ) and altitude bin height (0.2 km), and was then summed over all altitude bins (Desmet and Nilsson , Dokter et al ). Nightly average MTR was calculated as the mean MTR from sunset to sunrise.…”