Diagnosing Santa Ana Winds in Southern California with Synoptic-Scale Analysis

Abstract

anta Ana winds (SAW) are among the most notorious fire-weather conditions in the United States and are implicated in wildfire and wind hazards in Southern California. This study employs large-scale reanalysis data to diagnose SAW through synoptic-scale dynamic and thermodynamic factors using mean sea level pressure gradient and lower-tropospheric temperature advection, respectively. A two-parameter threshold model of these factors exhibits skill in identifying surface-based characteristics of SAW featuring strong offshore winds and extreme fire weather as viewed through the Fosberg fire weather index across Remote Automated Weather Stations in southwestern California. These results suggest that a strong northeastward gradient in mean sea level pressure aligned with strong cold-air advection in the lower troposphere provide a simple, yet effective, means of diagnosing SAW from synoptic-scale reanalysis. This objective method may be useful for medium- to extended-range forecasting when mesoscale model output may not be available, as well as being readily applied retrospectively to better understand connections between SAW and wildfires in Southern California.