Evaluating the Ability of FARSITE to Simulate Wildfires Influenced by Extreme, Downslope Winds in Santa Barbara, California

Extreme, downslope mountain winds often generate dangerous wildfire conditions. We used the wildfire spread model Fire Area Simulator (FARSITE) to simulate two wildfires influenced by strong wind events in Santa Barbara, CA. High spatial-resolution imagery for fuel maps and hourly wind downscaled to 100 m were used as model inputs, and sensitivity tests were performed to evaluate the effects of ignition timing and location on fire spread. Additionally, burn area rasters from FARSITE simulations were compared to minimum travel time rasters from FlamMap simulations, a wildfire model similar to FARSITE that holds environmental variables constant. Utilization of two case studies during strong winds revealed that FARSITE was able to successfully reconstruct the spread rate and size of wildfires when spotting was minimal. However, in situations when spotting was an important factor in rapid downslope wildfire spread, both FARSITE and FlamMap were unable to simulate realistic fire perimeters. We show that this is due to inherent limitations in the models themselves, related to the slope-orientation relative to the simulated fire spread, and the dependence of ember launch and land locations. This finding has widespread implications, given the role of spotting in fire progression during extreme wind events.

[1]  J. Corcoran,et al.  Contemporary Applications For Spatially Integrated Social Science , 2021, Applied Spatial Analysis and Policy.

[2]  Alan T. Murray,et al.  Coastal Vulnerability under Extreme Weather , 2020, Applied Spatial Analysis and Policy.

[3]  C. Jones,et al.  The Sundowner Winds Experiment (SWEX) Pilot Study: Understanding Downslope Windstorms in the Santa Ynez Mountains, Santa Barbara, California , 2020, Monthly Weather Review.

[4]  Paul D. Gader,et al.  Classifying California plant species temporally using airborne hyperspectral imagery , 2019, Remote Sensing of Environment.

[5]  R. Fovell,et al.  Simulating Sundowner Winds in Coastal Santa Barbara: Model Validation and Sensitivity , 2019, Atmosphere.

[6]  R. Fovell,et al.  Winds and Gusts during the Thomas Fire , 2018, Fire.

[7]  R. Fovell,et al.  Downslope Windstorms of San Diego County. Part II: Physics Ensemble Analyses and Gust Forecasting , 2018 .

[8]  B. Hatchett,et al.  Characteristics of Sundowner Winds near Santa Barbara, California, from a Dynamically Downscaled Climatology: Environment and Effects near the Surface , 2017 .

[9]  R. Rothermel A Mathematical Model for Predicting Fire Spread in Wildland Fuels , 2017 .

[10]  R. Rothermel,et al.  How to Predict the Spread and Intensity of Forest and Range Fires , 2017 .

[11]  C. Jones,et al.  WRF simulation of downslope wind events in coastal Santa Barbara County , 2017 .

[12]  Fermín J. Alcasena,et al.  Predicting wildfire spread and behaviour in Mediterranean landscapes , 2016 .

[13]  A. P. Williams,et al.  Impact of anthropogenic climate change on wildfire across western US forests , 2016, Proceedings of the National Academy of Sciences.

[14]  Joe H. Scott,et al.  Standard Fire Behavior Fuel Models: A Comprehensive Set for Use with Rothermel?s Surface Fire Spread Model , 2015 .

[15]  N. Diffenbaugh,et al.  Anthropogenic warming has increased drought risk in California , 2015, Proceedings of the National Academy of Sciences.

[16]  A. Syphard,et al.  Location, timing and extent of wildfire vary by cause of ignition , 2015 .

[17]  Dar A. Roberts,et al.  Using HFire for Spatial Modeling of Fire in Shrublands , 2015 .

[18]  Bret W. Butler,et al.  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 , 2014 .

[19]  Charles W. McHugh,et al.  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 , 2014 .

[20]  Nicolas Faivre,et al.  Controls on the spatial pattern of wildfire ignitions in Southern California , 2014 .

[21]  Mir Abolfazl Mostafavi,et al.  Wind effect on wildfire and simulation of its spread (case study: Siahkal forest in northern Iran). , 2014 .

[22]  Joseph W. Mitchell Power line failures and catastrophic wildfires under extreme weather conditions , 2013 .

[23]  Alan A. Ager,et al.  Assessing exposure of human and ecological values to wildfire in Sardinia, Italy , 2013 .

[24]  John Michalakes,et al.  WRF-Fire: Coupled Weather–Wildland Fire Modeling with the Weather Research and Forecasting Model , 2013 .

[25]  D. Roberts,et al.  Comparing endmember selection techniques for accurate mapping of plant species and land cover using imaging spectrometer data , 2012 .

[26]  Mario Parise,et al.  Wildfire impacts on the processes that generate debris flows in burned watersheds , 2012, Natural Hazards.

[27]  Jonathan D. Beezley,et al.  Real time simulation of 2007 Santa Ana fires , 2012, 1202.3209.

[28]  Alex Hall,et al.  Spatial variation in extreme winds predicts large wildfire locations in chaparral ecosystems , 2010 .

[29]  J. Franklin,et al.  The 2007 Southern California Wildfires: Lessons in Complexity , 2009, Journal of Forestry.

[30]  Scott L. Stephens,et al.  Measuring the Rate of Spread of Chaparral Prescribed fires in Northern California , 2008 .

[31]  Alexandra D. Syphard,et al.  Predicting spatial patterns of fire on a southern California landscape , 2008 .

[32]  William C. Skamarock,et al.  A time-split nonhydrostatic atmospheric model for weather research and forecasting applications , 2008, J. Comput. Phys..

[33]  M. Dettinger,et al.  Climate change scenarios for the California region , 2008 .

[34]  Pierpaolo Duce,et al.  Evaluation of FARSITE simulator in Mediterranean maquis , 2007 .

[35]  Patricia L. Andrews,et al.  BehavePlus fire modeling system: Past, present, and future , 2007 .

[36]  John Radke,et al.  Applying fire spread simulation over two study sites in California lessons learned and future plans , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[37]  David A. Seal,et al.  The Shuttle Radar Topography Mission , 2007 .

[38]  Alexandra D. Syphard,et al.  Simulating fire frequency and urban growth in southern California coastal shrublands, USA , 2007, Landscape Ecology.

[39]  Charles W. McHugh,et al.  The impact of high resolution wind field simulations on the accuracy of fire growth predictions , 2006 .

[40]  T. Swetnam,et al.  Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity , 2006, Science.

[41]  Timothy J. Brown,et al.  Climate, Santa Ana Winds and Autumn Wildfires in Southern California , 2004 .

[42]  Max A. Moritz,et al.  SPATIOTEMPORAL ANALYSIS OF CONTROLS ON SHRUBLAND FIRE REGIMES: AGE DEPENDENCY AND FIRE HAZARD , 2003 .

[43]  D. A. Stow,et al.  Using multiple image endmember spectral mixture analysis to study chaparral regrowth in southern California , 2003 .

[44]  J. Horel,et al.  MESOWEST: COOPERATIVE MESONETS IN THE WESTERN UNITED STATES , 2002 .

[45]  Ian Owens,et al.  A GIS-supported model for the simulation of the spatial structure of wildland fire, Cass Basin, New Zealand , 1999 .

[46]  W. Blier The Sundowner Winds of Santa Barbara, California , 1998 .

[47]  C. E. Van Wagner,et al.  Conditions for the start and spread of crown fire , 1977 .

[48]  R. Rothermel,et al.  Predicting changes in chaparral flammability , 1973 .

[49]  Ted L. Hanes Ecological Studies on Two Closely Related Chaparral Shrubs in Southern California , 1965 .

[50]  G. Ellis,et al.  The Santa Ana Winds of Southern California , 1962 .

[51]  John B. Loomis,et al.  The hidden cost of wildfires: Economic valuation of health effects of wildfire smoke exposure in Southern California , 2012 .

[52]  S. Peterson Fire risk in California , 2011 .

[53]  B. Butler,et al.  4.4 Simulating Diurnally Driven Slope Winds with WindNinja , 2009 .

[54]  Richard D. Stratton Guidebook on LANDFIRE fuels data acquisition, critique, modification, maintenance, and model calibration , 2009 .

[55]  D. Durran Downslope Winds ∗ , 2008 .

[56]  Joe H. Scott Comparison of crown fire modeling systems used in three fire management applications , 2006 .

[57]  M. Finney Efforts at Comparing Simulated and Observed Fire Growth Patterns , 2004 .

[58]  M. Finney FARSITE : Fire Area Simulator : model development and evaluation , 1998 .

[59]  G. Ryan Downslope winds of Santa Barbara, California , 1996 .

[60]  David J. Murray-Smith,et al.  Real-Time Simulation , 1995 .

[61]  M. Finney,et al.  Use of the FARSITE fire growth model for fire prediction in the US national parks , 1995 .

[62]  H. Anderson Aids to Determining Fuel Models for Estimating Fire Behavior , 1982 .

[63]  Fotini-Niovi Pavlidou,et al.  This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE SYSTEMS JOURNAL 1 A Comparative Review on Wildfire Simulators , 2022 .