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In this study, we focus on the effects of fuel bed representation and fire heat and smoke distribution in a coupled fire-atmosphere simulation platform for two landscape-scale fires: the 2018 Camp Fire and the 2021 Caldor Fire. The fuel bed representation in the coupled fire-atmosphere simulation platform WRF-Fire currently includes only surface fuels. Thus, we enhance the model by adding canopy fuel characteristics and heat release, for which a method to calculate the heat generated from canopy fuel consumption is developed and implemented in WRF-Fire. Furthermore, the current WRF-Fire heat and smoke distribution in the atmosphere is replaced with a heat-conserving Truncated Gaussian (TG) function and its effects are evaluated. The simulated fire perimeters of case studies are validated against semi-continuous, high-resolution fire perimeters derived from NEXRAD radar observations. Furthermore, simulated plumes of the two fire cases are compared to NEXRAD radar reflectivity observations, followed by buoyancy analysis using simulated temperature and vertical velocity fields. The results show that while the improved fuel bed and the TG heat release scheme have small effects on the simulated fire perimeters of the wind-driven Camp Fire, they affect the propagation direction of the plume-driven Caldor Fire, leading to better-matching fire perimeters with the observations. However, the improved fuel bed representation, together with the TG heat smoke release scheme, leads to a more realistic plume structure in comparison to the observations in both fires. The buoyancy analysis also depicts more realistic fire-induced temperature anomalies and atmospheric circulation when the fuel bed is improved. 

Background Accurate simulation of wildfires can benefit pre-ignition mitigation and preparedness, and post-ignition emergency response management. Aims We evaluated the performance of Weather Research and Forecast-Fire (WRF-Fire), a coupled fire-atmosphere wildland fire simulation platform, in simulating a large historic fire (2018 Camp Fire). Methods A baseline model based on a setup typically used for WRF-Fire operational applications is utilised to simulate Camp Fire. Simulation results are compared to high-temporal-resolution fire perimeters derived from NEXRAD observations. The sensitivity of the model to a series of modelling parameters and assumptions governing the simulated wind field are then investigated. Results of WRF-Fire for Camp Fire are compared to FARSITE. Key results Baseline case shows non-negligible discrepancies between the simulated fire and the observations on rate of spread (ROS) and spread direction. Sensitivity analysis results show that refining the atmospheric grid of Camp Fire’s complex terrain improves fire prediction capabilities. Conclusions Sensitivity studies show the importance of refined atmosphere modelling for wildland fire simulation using WRF-Fire in complex terrains. Compared to FARSITE, WRF-Fire agrees better with the observations in terms of fire propagation rate and direction. Implications The findings suggest the need for further investigation of other possible sources of wildfire modelling uncertainties and errors. 

Abstract Coupled fire‐atmosphere models often struggle to simulate important fire processes like fire generated flows, deep flaming fronts, extreme updrafts, and stratospheric smoke injection during large wildfires. This study uses the coupled fire‐atmosphere model, WRF‐Fire, to examine the sensitivities of some of these phenomena to the modeled total fuel load and its consumption. Specifically, the 2020 Bear Fire and 2021 Caldor Fire in California's Sierra Nevada are simulated using three fuel loading scenarios (1X, 4X, and 8X LANDFIRE derived surface fuel), while controlling the fire rate of spread using observations. This approach helps isolate the fuel loading and consumption needed to produce fire‐generated winds and plume rise comparable to radar observations of these events. Increasing fuel loads and corresponding fire residence time in WRF‐Fire leads to deep plumes in excess of 10 km, strong vertical velocities of 40–45 m s⁻¹, and combustion fronts several kilometers in width (in the along wind direction). These results indicate that LANDFIRE‐based surface fuel loads in WRF‐Fire likely under‐represent fuel loading, having significant implications for simulating landscape‐scale wildfire processes, associated impacts on spread, and fire‐atmosphere feedbacks. 

Abstract Fire-generated tornadic vortices (FGTVs) linked to deep pyroconvection, including pyrocumulonimbi (pyroCbs), are a potentially deadly, yet poorly understood, wildfire hazard. In this study we use radar and satellite observations to examine three FGTV cases during high-impact wildfires during the 2020 fire season in California. We establish that these FGTVs each exhibit tornado-strength anticyclonic rotation, with rotational velocity as strong as 30 m s −1 (60 kt), vortex depths of up to 4.9 km AGL, and pyroCb plume tops as high as 16 km MSL. These data suggest similarities to EF2+ strength tornadoes. Volumetric renderings of vortex and plume morphology reveal two types of vortices: embedded vortices anchored to the fire and residing within high-reflectivity convective columns and shedding vortices that detach from the fire and move downstream. Time-averaged radar data further show that each case exhibits fire-generated mesoscale flow perturbations characterized by flow splitting around the fire’s updraft and pronounced flow reversal in the updraft’s lee. All the FGTVs occur during deep pyroconvection, including pyroCb, suggesting an important role of both fire and cloud processes. The commonalities in plume and vortex morphology provide the basis for a conceptual model describing when, where, and why these FGTVs form. 

Abstract There is a need for nowcasting tools to provide timely and accurate updates on the location and rate of spread (ROS) of large wildfires, especially those impacting communities in the wildland urban interface. In this study, we demonstrate how fixed‐site weather radars can be used to fill this gap. Specifically, we develop and test a radar‐based fire‐perimeter tracking tool that leverages the tendency for local maxima in the radar reflectivity to be collocated with active fire perimeters. Reflectivity maxima are located using search radials from points inside a fire polygon, and perimeters are updated at intervals of ∼10 min. The algorithm is tested using publicly available Next Generation Weather Radar radar data for two large and destructive wildfires, the Camp and Bear Fires, both occurring in northern California, USA. The radar‐based fire perimeters are compared with available, albeit limited, satellite and airborne infrared observations, showing good agreement with conventional fire‐tracking tools. The radar data also provide insights into fire ROS, revealing the importance of long‐range spotting in generating ROS that exceeds conventional estimates. One limitation of this study is that high‐resolution fire perimeter validation data are sparsely available, precluding detailed error quantification for the radar estimates drawn from samples spanning a range of environmental conditions and radar configurations. Nevertheless, the radar tracking approach provides the basis for improved situational awareness during high‐impact fires.