P67     WRF-XPY: Numerical modeling framework for operational coupled fire-atmosphere-fuel moisture forecasting.

Kochanski, Adam, Derek V. Mallia, University of Utah, Jan Mandel, Angel Farguell Caus, University of Colorado Denver, Martin Vejmelka, AVAST, and Sher Schranz, NOAA/CIRA

Here, we present an integrated wildland fire modeling framework (WRF-SFIRE), which couples a high resolution, multi-scale weather forecasting model, with a semi-empirical fire spread model (SFIRE) and a prognostic dead fuel moisture model. New functionality has been added to the WRF-SFIRE modeling framework so that it can be executed in an operational setting using a set of software modules (WRF-XPY). These python-based modules can manipulate, WRF, WPS and fire runtime options, dynamically configure modeling domains, download meteorological input files, execute WRF-related executables, monitor real-time WRF performance, assimilate fuel moisture from RAWS observations, postprocess netCDF output files, and assemble WRFXP simulation outputs to be displayed, visually. All fire-simulation related settings can be initialized using a web-based control system, which allows the user to define a fire as well as basic simulation properties such as simulation length, type of meteorological forcing and resolution, anywhere in CONUS and any time meteorological products are available to initialize the weather model. Outputs generated from WRF-SFIRE are then displayed on an interactive web portal, which updates in real-time.
Fires can also impact local meteorology as a result of heat and moisture being released into the atmosphere by the fire. As a result, WRF-SIFRE has been coupled with a fuel moisture model, which is driven by the atmospheric component of the system in order to render the diurnal and spatial fuel moisture variability.