
WindNinja | US Forest Service Research and Development
WindNinja is a computer program that computes spatially varying wind fields for wildland fire and other applications requiring high resolution wind prediction in complex terrain.
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WindNinja is a computer program that computes spatially varying wind fields for wildland fire application.
WINDNINJA
Thanks to the U.S. Forest Service, that ‘something’ is now available to anyone with a computer or a smartphone. And it’s called ‘WindNinja.'" -- Michael Archer, Wildfire News of the Day.
GitHub - firelab/windninja: A diagnostic wind model developed …
A diagnostic wind model developed for use in wildland fire modeling. - firelab/windninja
WindNinja | Fire Research and Management Exchange System
WindNinja was developed to help fire managers predict these winds. It is a computer program that computes spatially-varying wind fields for wildland fire and other applications requiring high …
What is WindNinja? WindNinja is a computer program that computes spatially varying wind fields for wildland fire applications. It is specifically designed to simulate the effect of terrain on wind …
WindNinja Mobile - Apps on Google Play
Oct 31, 2023 · WindNinja is a computer program that computes spatially varying wind fields for wildland fire support. WindNinja Mobile is a mobile interface for initiating and viewing …
WindNinja update: Version 3.12.0 | US Forest Service Research …
Sep 22, 2025 · WindNinja is an established, open source high-resolution wind model developed for wildland fire applications. It is used on nearly every large fire incident in the United States.
WindNinja Overview | US Forest Service Research and Development
Dec 3, 2025 · WindNinja is a microscale wind model developed for use in wildland fire applications. It was developed to meet the specific needs of operational fire personnel, …
WindNinja - Overview
Jul 30, 2025 · WindNinja is a computer program that computes spatially-varying wind fields for wildland fire and other applications requiring high-resolution wind predictions in complex terrain.