Research Projects

Using NEXRAD weather surveillance network to forecast movements of migratory birds impacting safety at US airports

More than 14,000 wildlife strikes were reported to the Federal Aviation Administration in 2017. Globally, wildlife strikes have killed more than 287 people and destroyed over 263 aircraft from 1988 through November 2018 (Dolbeer and Begier. 2019). To warn pilots of potential wildlife hazards, airports often include generic language in the Automated Terminal Information System (ATIS) or Notices to Airmen (NOTAM) that does not provide useful or actionable information. Commonly these messages state, "use caution birds in the vicinity" and are not based on specifically observed or forecasted information. Some airports have integrated avian radar systems into their operations to detect local movements of birds; however, these systems are costly and have limitations making them impractical for the majority of airports. The existing infrastructure provided through the US weather surveillance radar network (NEXRAD) combined with recent advances in machine learning and computational power make it possible to study avian movements at large spatial and long temporal scales. Several studies have characterized bird migration with this sensor network and have related these characterizations to other data, such as weather and climatic patterns and artificial light pollution. Results from these research projects have been used to develop tools to track bird migration in near real-time ( These findings have yet to be related to wildlife hazards at airports but could provide more useful information to pilots, air traffic controllers, and airports.

Background (Describe the current situation or problem in the industry, and how your idea would address it.)

A peer-reviewed article recently published in Science by Van Doren and Horton (2018) developed a migration forecast model that was able to account for 81% of bird migration intensity across the United States at altitudes of 0 to 3000 meters. The performance of the model remained high in forecasting migration events 1 to 7 days in advance.

Unpublished research has found a high correlation between the number of bird strikes at John F. Kennedy International, Newark Liberty International, and LaGuardia Airports and the amount of bird movements registered by the NEXRAD weather surveillance network.

Objective (What is the desired product or result that will help the airport industry?)

Use historic NEXRAD data and the FAA Wildlife Strike Database to create and validate a regional/local model to predict periods of increased bird strike probability based on migratory activity detected by NEXRAD, weather, and other variables and recommend best management practices for identifying and communicating about periods of increased bird strike probability/severity.

Approach (Describe in general terms the steps you think are needed to achieve the objective.)

Survey airports to determine current methods used to detect elevated levels of bird activity that merits warnings to the airport community and document the the various ways in which this information is shared.

Conduct a literature review and identify existing tools, resources, and data streams that can be utilized to create and validate a regional/local model for predicting periods of increased bird strike probability.

Evaluate measures of severity that may be discernible from NEXRAD data (bird size/mass, flock density) and other ancillary information that may be helpful to provide to end users (altitude, etc.).

Create and validate a regional/local model that predicts periods of increased bird strike probability/severity based on migratory activity detected by NEXRAD, weather, and other information identified from the literature search.

Create an operational tool that can provide forecast information on migratory movements that may impact air safety at local, regional, and continental scales.

Determine coverage of the NEXRAD network for monitoring bird migration in airspace across the United States and describe any gaps in coverage or other factors that may impact the applicability of the model across US airspace.

Create a guidebook that described relevant research findings, model/tool development, limitations, and recommendations for best management practices for identifying and communicating about periods of increased bird strike probability/severity.

Develop and implement a dissemination plan to share the findings of this research at industry conferences and through relevant publications.

Cost Estimate and Backup (Provide a cost estimate and support for how you arrived at the estimate.)


In depth research is likely going to require post-doctoral level analyses as well a support from other subject matter experts. These funds should also include travel to industry conferences and meetings to present the findings from this research.

Related Research - List related ACRP and other industry research; describe gaps (see link to Research Roadmaps above), and describe how your idea would address these gaps. This is a critical element of a synthesis topic submission.

Several studies have characterized bird migration using the NEXRAD weather surveillance network; however, these findings have yet to be related to wildlife hazards at airports. Best management standards and practices have not been established to help airports communicate about periods of increased wildlife hazards.

ACRP Report 145 - Applying an SMS Approach to Wildlife Hazard Management
ACRP Report 32 - Guidebook for Addressing Aircraft/Wildlife Hazards at General Aviation Airports
ACRP Report 13 - Integrating Airport Information Systems.

FAA AC 150/5220-25 - Airport Avian Radar Systems

Dolbeer, Richard A, and Michael J Begier. 2019. "Wildlife Strikes to Civil Aircraft in the United States 1990-2017." Federal Aviation Administration National Wildlife Strike Database Serial Report Number 24.

Van Doren, B. M. & Horton, K. G. 2018. A continental system for forecasting bird migration. Science. 361, 1115–1118.

Dokter, A. M. et al. Seasonal abundance and survival of North America's migratory avifauna determined by weather radar. Nat. Ecol. Evol. 1 (2018).

Horton, Kyle G., Benjamin M. Van Doren, Frank A. La Sorte, Emily B. Cohen, Hannah L. Clipp, Jeffrey J. Buler, Daniel Fink, Jeffrey F. Kelly, and Andrew Farnsworth. 2019. "Holding Steady: Little Change in Intensity or Timing of Bird Migration over the Gulf of Mexico." Global Change Biology, no. In press.

Ansari, Steve, Stephen Del Greco, Edward Kearns, Otis Brown, Scott Wilkins, Mohan Ramamurthy, Jeff Weber, et al. 2018. "Unlocking the Potential of NEXRAD Data through NOAA's Big Data Partnership." Bulletin of the American Meteorological Society 99 (1): 189–204.

Dokter, Adriaan M., Peter Desmet, Jurriaan H. Spaaks, Stijn van Hoey, Lourens Veen, Liesbeth Verlinden, Cecilia Nilsson, et al. 2018. "BioRad: Biological Analysis and Visualization of Weather Radar Data." Ecography, November. doi:10.1111/ecog.04028.



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Idea No. 169