Statistics on Wind Speed and Other Fire-Weather Indices Relative to Terrain using 5 Years of the High-Resolution Rapid Refresh Model Output

The risk of wildland fire continues to grow, both as wildland urban interface regions expand and climate change enhances the probability of conditions that lead to wildland fire occurring. In particular, high wind speeds make containing wildland fire more challenging, and conditions that are hot and dry are correlated with increased fire initiations. Having better knowledge of the distribution of high winds, especially as they correlate with hot-and-dry conditions, in complex terrain will provide decision makers with the information they need to prepare for future potential wildland fires.

The High-Resolution Rapid Refresh (HRRR) numerical weather prediction model is run operationally by the National Weather Service, providing hourly updated forecasts across the country. This model uses a 3-km horizontal grid, and has been regularly updated to improve its data assimilation, physical parameterizations, and diagnostic output. Here, we use 5 years of version 4 of the HRRR, from August 2019 to July 2024, to derive statistics on the 80-m above ground level wind speeds, as well as statistics on fire-weather indices at the surface. We show spatial maps of the mean, standard deviation, and skewness of these variables, and how these results vary across seasons. The results provide insights into how synoptic and mesoscale variability interact with terrain features to modulate potentially hazardous wildland fire conditions over the annual cycle.