Abstract
Abstract. Coupled atmosphere–fire models can now generate forecasts in real time, owing to recent advances in computational capabilities. WRF–SFIRE consists of the Weather Research and Forecasting (WRF) model coupled with the fire-spread model SFIRE. This paper presents new developments, which were introduced as a response to the needs of the community interested in operational testing of WRF–SFIRE. These developments include a fuel-moisture model and a fuel-moisture-data-assimilation system based on the Remote Automated Weather Stations (RAWS) observations, allowing for fire simulations across landscapes and time scales of varying fuel-moisture conditions. The paper also describes the implementation of a coupling with the atmospheric chemistry and aerosol schemes in WRF–Chem, which allows for a simulation of smoke dispersion and effects of fires on air quality. There is also a data-assimilation method, which provides the capability of starting the fire simulations from an observed fire perimeter, instead of an ignition point. Finally, an example of operational deployment in Israel, utilizing some of the new visualization and data-management tools, is presented.
Highlights
Wildland fire is a complicated multiscale process
The fire behavior is affected by very small-scale thermal degradation processes occurring well before the flames appear at the molecular scale (Sullivan and Ball, 2012)
9 Summary and conclusions ing building the model with Weather Research and Forecasting (WRF)–Chem, allows the study fire and smoke emission and dispersion, and an WRF–SFIRE system has significantly evolved since its orig- investigation of the effects of smoke on atmospheric cheminal description was published in Mandel et al
Summary
Wildland fire is a complicated multiscale process. The fire behavior is affected by very small-scale thermal degradation processes occurring well before the flames appear at the molecular scale (Sullivan and Ball, 2012). Large-scale weather patterns induce changes in temperature and humidity, which affect fuel moisture, affecting the fire behavior as well. Coupling a weather model with a fire-spread model and a time-lag fuel-moisture model captures these interactions, without explicitly resolving the small-scale combustion and water adsorption processes, in a computationally inexpensive way. WRF–SFIRE is a two-way coupled fire–atmosphere model, so the heat fluxes from the fire component provide forcing to the atmosphere, which influences winds, which in turn modify the fire spread. Validation studies of WRF–SFIRE are available for a large-scale wildfire (Kochanski et al, 2013b), as well as for a microscale simulation of a grass-burn experiment (Kochanski et al, 2013c), fuel-moisture data assimilation (Vejmelka et al, 2014a), and coupling with WRF–Chem (Kochanski et al, 2014b). We do not describe the basic principles, operation, or history of the core of WRF–SFIRE here, and refer to Mandel et al (2011) and the User’s Guide (OpenWFM, 2013) instead
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