Determining and Applying the Relationship Between FWI and FRP In Predicting Fire Change


  • ARUSHI DESAI Cupertino High School, Cupertino, CA
  • SOPHIA TANG Del Norte High School, San Diego, CA
  • Yunyao Li Center for Spatial Information Science and Systems (CSISS), George Mason University



Fire Weather Index (FWI) analyzes how fire-prone an area is through considering the Initial Spread Index, or the wind and moisture levels in the area, and Buildup Index, or the amount of fuel available for combustion. An understanding of the relationship between FWI and changes in Fire Radiative Power (FRP), or the amount of energy released by fires, has been sought after in order to better fire management/prevention efforts. While FWI can analyze how susceptible an area is to fires, we lack an understanding of how FWI can be applied to predict fire change. Using 2020’s fire data, we analyzed fire duration and FWI distribution through scatterplots and histograms. Using this analysis, we performed statistical normalization to create a CDF of normalized FWI values on a 0 to 1 scale, removing the bottom and top 10% of FWI data in order to truncate out any extreme outliers. Our method involved normalizing a day’s FWI value, finding its corresponding value in the CDF, and multiplying this newfound value by a day’s FRP to find the next day’s FRP. This method was used to perform both 7-day and next-day forecasts, comparing predicted FRP to actual FRP. I focused on the specific region of the August Complex Fire, where my predictions proved to have a lower error than assuming a 25% decrease in FRP or persistent FRP, with the error only decreasing as the forecasts grew longer. The implications therein remain that FWI predicts FRP change more accurately than assuming no change or assuming a constant change.





College of Science: Department of Atmospheric, Oceanic & Earth Sciences