New maps use radar to predict bird migration

New maps use radar to predict bird migration

For the first time, the new maps use radar to predict night clouds for migratory birds and track their journeys in near real-time.

Scientists at the Cornell Lab of Ornithology and the University of Oxford in England have achieved this feat: processing weather radar data to produce maps visualizing migration on Cornell Lab's BirdCast website.

One map displays an animated visualization tracking migration in near real time. Adrian Docter, a postdoctoral fellow at Cornell Lab, designed an algorithm that quickly estimates the density and flight directions of migratory birds detected by a weather radar network. The system processes incoming radar data continuously and updates the moving map every 10 minutes.

“We are able to isolate bird data from atmospheric information because of the way weather radar works, a process called dual polarization,” Docter said. “This means that radar stations send and receive radio waves in both the vertical and horizontal directions. It provides a much clearer picture of the size, shape and direction of the targets it picks up. Thanks to the power of cloud computing, we can analyze all the radar data incredibly quickly.”

Another map predicts migration three days earlier. Color-coded displays combine forecast weather conditions with bird movements to show where and when the heaviest migrations are. Most songbirds migrate in the dark, usually when weather conditions are favourable. Tailwinds can produce huge migratory movements. Rain can stop flights completely.

“Knowing when and where a large group of migrants will pass through is useful for conservation purposes,” said Benjamin van Doren, a doctoral student at the University of Oxford. “Our forecasts could lead to temporary closures of wind turbines or large sources of light pollution along the migration route. Both measures could significantly reduce bird mortality.

“This is the most significant update since we first started using radar to study bird movements,” noted Kyle Horton, a postdoctoral fellow at Cornell Lab. “From a birdwatcher’s perspective, if you know where and when migratory birds will fly at night, you will have a better chance of seeing them.” , especially if the birds have stopped in your area.

Van Doren and Horton designed the system that generates migration forecast maps. They used machine learning models based on 23 years of radar and weather data to predict suitable conditions for the migration that occurs three hours after local sunset.

“These predictions and live migration maps, and the research they produced, represent an achievement that has been nearly 20 years in the making,” said Andrew Farnsworth, a migration researcher at Cornell Lab. “We hope these maps will provide a perspective for experts and novices alike on the incredible spectacle – and sheer scale – of the migration. Furthermore, we believe these maps will become powerful tools for conservation action to help reduce the impacts of human-caused hazards that birds encounter during their incredible journeys.”

This research was supported by funding from the National Science Foundation, the Leon Levy Foundation, and NASA. Additional funding was provided by an Edward W. Rose Postdoctoral Fellowship at the Cornell Laboratory of Ornithology, the UK Marshall Commission of Remembrance, and Amazon Web Services Cloud credits for the research.

BirdCast is a collaboration between the Cornell Laboratory of Ornithology, the University of Massachusetts Amherst, and Oregon State University, and was funded by grants from the National Science Foundation and the Leon Levy Foundation.

Pat Leonard is a staff writer at the Cornell Lab of Ornithology.

(Tags for translation)Ornithology Laboratory

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