The Role of Lee-Slope Jets and Hydraulic Jumps in Wildfire Behavior: Insights from Observations and Modeling

Wildfire spread in complex terrain is strongly modulated by fine-scale atmospheric processes that remain poorly represented in operational models. Downslope windstorms are among the most critical drivers of extreme fire behavior, producing hot, dry, and gusty conditions that can rapidly accelerate fire spread. However, their inherently transient and spatially heterogeneous structure poses a major challenge for wildfire prediction systems, particularly in coastal environments where interactions with marine boundary layers further complicate the flow.

This study leverages observations from the Sundowner Winds EXperiment (SWEX, April–May 2022), conducted in Santa Barbara, California, together with high-resolution numerical simulations to investigate the variability of lee-slope jets and hydraulic jumps during wildfire-prone downslope windstorms in Southern California. SWEX provides a unique dataset of in-situ and remote sensing observations, including Doppler lidars and dropsondes, capturing boundary-layer structure and mountain wave dynamics during multiple downslope windstorm events. We focus on a representative event (IOP10) characterized by non-stationary mountain waves and strong spatial variability in downslope winds.

We evaluate the ability of the Weather Research and Forecasting (WRF) model to represent these processes at kilometer-scale resolution and at sub-kilometer Large-Eddy Simulation (LES) scales. While both configurations reproduce key features of lee-slope jets over the mountain slopes, the kilometer-scale simulation overestimates the spatial extent and persistence of strong winds farther downslope. In contrast, sub-kilometer simulations resolve transient mountain wave behavior and associated hydraulic jump variability, more closely resembling the observations. These differences highlight the importance of resolving unsteady wave dynamics and boundary-layer interactions, including coupling with the shallow, stably stratified marine layer. We then use the WRF-FIRE model to understand how hydraulic jump dynamics influence simulated wildfire spread.

Our results demonstrate that wildfire-relevant wind fields are highly sensitive to model resolution and terrain representation. The inability of coarser models to capture transient flow features can lead to systematic biases in near-surface winds that are critical for fire spread prediction. Simplified fire spread models often rely on static or parameterized surface wind inputs and cannot capture the dynamic atmosphere-fire interactions that occur during downslope windstorms. These findings underscore the need to integrate high-resolution modeling, targeted observations, and improved physical parameterizations into wildfire forecasting frameworks.