This article was jointly written between the Earth Prediction Innovation Center (EPIC) and NSF NCAR.
The increase in the frequency of drought and hot-dry-windy conditions over the last several decades, combined with the continued expansion into the wildfire-urban interface region, has led to a marked increase in the number of acres burned by hazardous wildfires. The number of wildfires and the acres burned are projected to increase, with profound changes to certain ecosystems. Wildfires threaten forest and grasslands, housing and communities, crops, aquatic and soil ecosystems, and air quality both near to and far from the fires, and ultimately cost the nation billions of dollars per year when accounting for the damage to buildings, communities, and the impacts on human health associated with smoke and poor air quality. Some of the adverse impacts can be mitigated with accurate predictions of the fire progression.
A range of models is available to perform simulations of the fire spread. From an operational perspective, coupled fire-atmosphere models provide a balance between the representation of physical processes and the computational resources required to run the model. These models have the ability to resolve winds in complex terrain and model fire induced phenomena in the atmosphere.
Coupled fire-atmosphere models have been developed during the last few decades. For example, the NSF NCAR-based Weather Research and Forecasting (WRF, Skamarock et al. 2021) model includes a fire behavior component known as WRF-Fire (Mandel, et al. 2011; Coen et al. 2013). The model simulates the propagation of the fire front based on its interactions with the lower atmosphere (e.g., winds) and surface (e.g., terrain and fuels). As the fire front advances, surface fire fuels burn releasing heat and moisture into the atmosphere, completing the coupling mechanism. As fuels burn, smoke is produced and transported by atmospheric flow.
While smoke, dust, and air quality had been included in previous versions of the Unified Forecast System (UFS), i.e., SRW-SD and SRW-AQM, the UFS lacked this capability of predicting fire behaviors before the SRW 3.0 release. To overcome this limitation, we have implemented a fire behavior model in UFS. The model, referred to as the Community Fire Behavior Model (CFBM, Jimenez y Munoz et al., 2024) closely follows WRF-Fire methods in its current implementation (v0.2.0). This allowed us to check for consistency between the widely used WRF-Fire and UFS coupling with the CFBM.
The coupled model will allow NOAA to forecast the propagation of existing fires. We know the location of active fires from satellite retrievals; this information, together with the new UFS capability (SRW v3.0.0), gives NOAA the opportunity to provide timely and accurate forecasts of fire weather, fire behavior, and smoke forecast guidance to safeguard lives and property and manage downstream air quality impacts.
The implementation of the Community Fire Behavior Model (CFBM) in the UFS is a groundbreaking step toward improving weather forecasts and quantifying the large-scale effect of concurrent fires during an active fire season. Wildfires are an integral part of the Earth system. They affect local circulation, generating eddies and inducing convection, producing smoke that interferes with cloud formation and precipitation, impacting weather and air quality downstream. As a result, fire and weather cannot be modeled as independent phenomena. The vision for this fire simulation component in the UFS is to improve weather forecasts and advance the tools that enable scientists to understand the compound effect of fires in the Earth system.
The integration of the CFBM into the UFS SRW v3.0.0 is a successful and significant collaboration between NSF NCAR and NOAA, highlighting the importance of the recently signed NSF NCAR-NOAA MOU.
References
Coen, J. L., M. Cameron, J. Michalakes, E. G. Patton, P. J. Riggan and K. M. Yedinak, 2013: WRF-Fire: Coupled weather-wildland fire modeling with the Weather Research and Forecasting model. J. Appl., Meteor. Climatol., 52, 16-38.
Jimenez y Munoz, P. A., Frediani, M., Eghdami, M., Rosen, D., Kavulich, M., and Juliano, T. W.: The Community Fire Behavior Model for coupled fire-atmosphere modeling: Implementation in the Unified Forecast System, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2024-124, in review, 2024.
Mandel, J., J. D. Beezley, A. K. Kochanski, 2011: Coupled atmosphere-wildland fire modeling with WRF 3.3 and SFIRE. Geosci. Model Dev., 4, 591-610.
Skamarock, B. C., J. B. Klemp, J. Dudhia, D. O. Gill, Z. Liu, J. Berner, W. Wang, J. G. Powers, M. G. Duda, D. M. Baker, X.-Y. Huang, 2021: A description of the advanced research WRF model version 4; Technical Report NCAR/TN-556-STR; NCAR: Boulder, CO, USA.
