55 research outputs found
Coupled atmosphere-wildland fire modeling with WRF-Fire
We describe the physical model, numerical algorithms, and software structure
of WRF-Fire. WRF-Fire consists of a fire-spread model, implemented by the
level-set method, coupled with the Weather Research and Forecasting model. In
every time step, the fire model inputs the surface wind, which drives the fire,
and outputs the heat flux from the fire into the atmosphere, which in turn
influences the atmosphere. The level-set method allows submesh representation
of the burning region and flexible implementation of various ignition modes.
WRF-Fire is distributed as a part of WRF and it uses the WRF parallel
infrastructure for parallel computing.Comment: Version 3.3, 41 pages, 2 tables, 12 figures. As published in
Discussions, under review for Geoscientific Model Developmen
Data Driven Computing by the Morphing Fast Fourier Transform Ensemble Kalman Filter in Epidemic Spread Simulations
The FFT EnKF data assimilation method is proposed and applied to a stochastic
cell simulation of an epidemic, based on the S-I-R spread model. The FFT EnKF
combines spatial statistics and ensemble filtering methodologies into a
localized and computationally inexpensive version of EnKF with a very small
ensemble, and it is further combined with the morphing EnKF to assimilate
changes in the position of the epidemic.Comment: 11 pages, 3 figures. Submitted to ICCS 201
Data management and analysis with WRF and SFIRE
pre-printWe introduce several useful utilities in development for the creation and analysis of real wildland fire simulations using WRF and SFIRE. These utilities exist as standalone programs and scripts as well as extensions to other well known software. Python web scrapers automate the process of downloading and preprocessing atmospheric and surface data from common sources. Other scripts simplify the domain setup by creating parameter files automatically. Integration with Google Earth allows users to explore the simulation in a 3D environment along with real surface imagery. Postprocessing scripts provide the user with a number of output data formats compatible with many commonly used visualization suites allowing for the creation of high quality 3D renderings. As a whole, these improvements build toward a unified web application that brings a sophisticated wildland fire modeling environment to scientists and users alike
Assimilation of Perimeter Data and Coupling with Fuel Moisture in a Wildland Fire - Atmosphere DDDAS
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.Comment: ICCS 2012, 10 pages; corrected some DOI typesetting in the reference
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