@misc{f57b2e3798ca4869888124e55fb6a892,
title = "Golden Eagle Behavioral Modeling Enabled by High-Fidelity Atmospheric Models",
abstract = "The DOE-funded Golden Eagle Behavioral Modeling project combines knowledge of eagle behavior, eagle telemetry data, high-fidelity atmospheric and wind power plant flow models, and machine learning to develop tools that predict behavior and risk around wind power plants. This presentation provides background on the project and modeling approaches, as well as recent modeling and validation results from the region around the Top of the World wind plant in Wyoming.",
keywords = "high-fidelity modeling, machine learning, mesoscale-to-microscale coupling, raptor behavior, wind-wildlife interaction",
author = "Eliot Quon and Rimple Sandhu and Regis Thedin and Paula Doubrawa and Caroline Draxl and Michael Lawson and Charles Tripp and Lindy Williams and Chris Farmer and Todd Katzner",
year = "2021",
language = "American English",
series = "Presented at the WREN Webinar, 23 March 2021",
type = "Other",
}