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WindNinja


WindNinja is a diagnostic wind model developed for use in wildland fire modeling and other applications requiring high resolution wind predictions in complex terrain. It is designed to simulate the mechanical (and some thermal) effects of the underlying terrain on the flow. It was developed to be used by emergency responders within their typical operational constraints of fast simulation times (seconds), low computational requirements (e.g., laptop computers), and low technical expertise.

WindNinja has two solver options: 1. conservation of mass; 2. conservation of mass and momentum. The conservation of mass solver (developed in-house) minimizes the change in an initial wind field while conserving mass over the computational domain. The conservation of mass solver runs very quickly (seconds) on basic hardware and has been shown to improve wind predictions on the windward side of terrain obstacles (Forthofer et al., 2014; Wagenbrenner et al., 2016). The conservation of mass and momentum option is based on OpenFOAM libraries and uses a RANS approach with k-epsilon turbulence closure. The conservation of mass and momentum solver requires more computational time (minutes to hours, depending on available computational resources), but is expected to give more accurate predictions on the lee side of terrain obstacles (Forthofer et al., 2014).

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. Diurnal slope flow (Forthofer et al., 2009) and non-neutral atmospheric stability parameterizations can be turned on or off. Outputs of the model are ASCII Raster grids of wind speed and direction (for use in GIS programs), a 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.


Example WindNinja output viewed in Google Earth.

WindNinja runs on versions of Linux and also on 64-bit versions of Windows XP and later operating systems.

Building from source code is required when running on Linux.

Windows installers are available, or there is an option to build from source code.

Source code is also available at https://zenodo.org/record/55153#.V2joau1VKlN.

References:

Forthofer J.M., Butler B.W., Wagenbrenner N.S., 2014, A comparison of three approaches for simulating fine-scale surface winds in support of windland fire management. Part I. Model formulation and comparison against measurements, Int. J. Wildland Fire. 23:969-931

Forthofer J.M., Shannon K.S, Butler B.W., 2009, Simulating diurnally driven slope winds with WindNinja, 8th Symposium on Fire and Forest Meteorological Society proceedings, October 2009

Wagenbrenner N.S., Forthofer J.M., Lamb B.K., Shannon K.S., Butler B.W., 2016, Downscaling surface wind predictions from numerical weather prediction models in complex terrain with WindNinja, Atmos. Chem. Phys. 16:5229-5241

Publications & Products:

Wagenbrenner, NS, Forthofer, JM, Lamb, BK, Shannon, KS, Butler, BW, (2016) Downscaling surface wind predictions from numerical weather prediction models in complex terrain with WindNinja. Atmos. Chem. Phys. 16:5229-5241, doi:10.5194/acp-16-5229-2016.

Butler, BW, Wagenbrenner, NS, Forthofer, JM, Lamb, BK, Shannon, KS, Finn, D, Eckman, RM, Clawson, K, Bradshaw, L, Sopko, P, Beard, S, Jimenez, D, Wold, C, Vosburgh, M, (2015) High-resolution observations of the near-surface wind field over an isolated mountain and in a steep river canyon. Atmospheric Chemistry and Physics. 15: 3785-3801.

Forthofer, JM, Butler, BW, Wagenbrenner, NS, (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. Int. J. Wildland Fire, 23:969-931. doi:10.1071/WF12089.

Forthofer, JM, Butler, BW, McHugh, CW, Finney, MA, Bradshaw, LS, Stratton, RD, Shannon, KS, Wagenbrenner, NS, (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. Int. J. Wildland Fire. 23:982-994. doi:10.1071/WF12090.

Forthofer, JM, Shannon, KS, Butler, BW (2011) Initialization of high resolution surface wind simulations using National Weather Service (NWS) gridded data. In '11th International Wildland Fire Safety Summit. Missoula, MT', April 4-8, 2011. (International Association of Wildland Fire)

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 (2,037 KB; 13 pages)

Forthofer, J. M. 2007. Modeling wind in complex terrain for use in fire spread prediction. Fort Collins, CO: Colorado State University, Thesis. (528 KB; 123 pages)

Forthofer, J.; Butler, B. 2007. Differences in simulated fire spread over Askervein Hill using two advanced wind models and a traditional uniform wind field. In: Butler, B. W.; Cook, W. comps. The fire environment--innovations, management, and policy; conference proceedings; 2007 26-30 March: Destin, FL. Proceedings RMRS-P-46CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station: 123-127. (581 KB; 5 pages)



Latest version

WindNinja 3.0.1

Submitted by Natalie Wagenbrenner on June 20, 2016 - 12:18pm
Main hypothesis

WindNinja is a diagnostic wind model developed for use in wildland fire modeling and other applications requiring high resolution wind predictions in complex terrain.

Software
Solver
WindNinja, OpenFOAM
License
Regime
Turbulence
Turbulence closure
Turbulence model

k-epsilon

Atmospheric boundary layer
Range
Coriolis
No
Atmospheric Stability
Atmospheric Stability
Yes
Canopy
Forest canopy
No
Wind farm
Wind turbine
No
Remarks
WindNinja is under continuous development by the Missoula Fire Sciences Laboratory. Interested developers can visit github.com/firelab/windninja to browse the source code, submit a feature request, or file a bug report.

Content Visibility

Public

Versions