Assimilation of Perimeter Data and Coupling with Fuel Moisture in a Wildland Fire - Atmosphere DDDAS

TL;DR

This paper introduces a data assimilation methodology for the WRF-Fire coupled model that updates fire perimeters and fuel moisture in real-time, improving fire-atmosphere interaction simulations.

Contribution

It extends existing fire modeling techniques by incorporating perimeter data assimilation and dynamic fuel moisture coupling within the WRF-Fire framework.

Findings

The method allows real-time fire perimeter updates during simulations.

It improves the atmospheric response by replaying fire history with proper heat fluxes.

The coupled model is publicly available and extends WRF-Fire capabilities.

Abstract

We present a methodology to change the state of the Weather Research Forecasting (WRF) model coupled with the fire spread code SFIRE, based on Rothermel's formula and the level set method, and with a fuel moisture model. The fire perimeter in the model changes in response to data while the model is running. However, the atmosphere state takes time to develop in response to the forcing by the heat flux from the fire. Therefore, an artificial fire history is created from an earlier fire perimeter to the new perimeter, and replayed with the proper heat fluxes to allow the atmosphere state to adjust. The method is an extension of an earlier method to start the coupled fire model from a developed fire perimeter rather than an ignition point. The level set method is also used to identify parameters of the simulation, such as the spread rate and the fuel moisture. The coupled model is available from openwfm.org, and it extends the WRF-Fire code in WRF release.