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WindNinja

Abstract

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.

Overview and Applicability

WindNinja logoWind is one of the most influential environmental factors affecting wildland fire behavior. The complex terrain of fire-prone landscapes causes local changes in wind speed and direction that are not predicted well by standard weather models or expert judgment. WindNinja was developed to help fire managers predict these winds.

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. It was developed to be used by emergency responders within their typical operational constraints of fast simulation times (seconds), low CPU requirements (single processor laptops), and low technical expertise.

WindNinja can be run in three different modes depending on the application and available inputs. The first mode is a forecast, where WindNinja uses coarser resolution mesoscale weather model data from the US National Weather Service to forecast wind at future times. The second mode uses one or more surface wind measurements to build a wind field for the area. The third mode uses a user-specified average surface wind speed and direction.

Other required inputs for a WindNinja simulation include elevation data for the modeling area (which WindNinja can obtain from Internet sources), date and time, and dominant vegetation type. A diurnal slope flow model and non-neutral atmospheric stability model can be turned on or off. Outputs of the model are ASCII Raster grids of wind speed and direction (for use in spatial fire behavior models such as FARSITE and FlamMap), a GIS shapefile (for plotting wind vectors in GIS programs), and a .kmz file (for viewing in Google Earth).

WindNinja is typically run on domain sizes up to 50 kilometers by 50 kilometers and at resolutions of around 100 meters. WindNinja runs on 32- and 64-bit versions of Windows XP and later operating systems (installers can be accessed on the WindNinja Software page). WindNinja can also be run on versions of Linux, however building from source code is required (see Building WindNinja with CMake). 

Note: Software developers and researchers can visit the WindNinja Project Development website.

For incident support:

Inputs

NWS mesoscale weather model data; surface wind measurements; average surface wind speed and direction; elevation data for the modeling area (WindNinja can obtain from Internet sources); date and time; dominant vegetation type.

Outputs

ASCII Raster grids of wind speed and direction - for use in spatial fire behavior models such as FARSITE and FlamMap; a GIS shapefile - for plotting wind vectors in GIS programs; and a .kmz file - for viewing in Google Earth.

Publications

Wagenbrenner, NS, Lamb, BK, Forthofer, JM, Shannon, KS, Butler, BW. 2016. Downscaling surface wind predictions from numerical weather prediction models in complex terrain with a mass-consistent wind model. Atmospheric Physics and Chemistry 16:5229-5241.

Forthofer, Jason M.; Butler, Bret W.; Wagenbrenner, Natalie S. 2014. A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management: Part I. Model formulation and comparison against measurements. International Journal of Wildland Fire. doi: http://dx.doi.org/10.1071/WF12089.

Forthofer, Jason M.; Butler, Bret W.; McHugh, Charles W.; Finney, Mark A.; Bradshaw, Larry S.; Stratton, Richard D.; Shannon, Kyle S.; Wagenbrenner, Natalie S. 2014. A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management. Part II. An exploratory study of the effect of simulated winds on fire growth simulations. International Journal of Wildland Fire. 23: 982-994.

Forthofer, J.; Shannon, K.; Butler, B. 2010. Initialization of high resolution surface wind simulations using NWS gridded data. In: Wade, Dale D.; Robinson, Mikel L., eds. Proceedings of 3rd Fire Behavior and Fuels Conference; 25-29 October 2010; Spokane, WA. Birmingham, AL: International Association of Wildland Fire. 5 p.

Forthofer, J.; Shannon, K.; and Butler, B. 2009. Simulating diurnally driven slope winds with WindNinja. In: Proceedings of 8th Symposium on Fire and Forest Meteorological Society; 2009 October 13-15; Kalispell, MT. 13 p.

Forthofer, Jason; Butler, Bret 2007. Differences in simulated fire spread over Askervein Hill using two advanced wind models and a traditional uniform wind field. In: Butler, Bret W.; Cook, Wayne, comps. The fire environment--innovations, management, and policy; conference proceedings. 26-30 March 2007; Destin, FL. Proceedings RMRS-P-46CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. CD-ROM. p. 123-127.

Forthofer, J. M. 2007. Modeling wind in complex terrain for use in fire spread prediction. Fort Collins, CO: Colorado State University, Thesis. 123 p.

Downloads & User Guides

Citation

Jason, F., B. Butler, and N. Wagenbrenner. WindNinja. Available online at https://www.firelab.org/project/windninja.



Research Topics: 
Fire
National Strategic Program Areas: 
Wildland Fire and Fuels
National Priority Research Areas: 
Forest Disturbances
RMRS Science Program Areas: 
Fire, Fuel and Smoke
RMRS Strategic Priorities: 
Fire Sciences
Geography: 
National