Natural Hazards

, Volume 77, Issue 2, pp 1013–1035 | Cite as

Coupled fire–atmosphere modeling of wildland fire spread using DEVS-FIRE and ARPS

  • Nathan DahlEmail author
  • Haidong Xue
  • Xiaolin Hu
  • Ming Xue
Original Paper


This article introduces a new wildland fire spread prediction system consisting of the raster-based Discrete Event System Specification Fire model (DEVS-FIRE) and the Advanced Regional Prediction System atmospheric model (ARPS). Fire–atmosphere feedbacks are represented by transferring heat from DEVS-FIRE to ARPS as an externally forced set of surface fluxes and mapping the resulting changes in near-surface wind from ARPS to DEVS-FIRE. A preliminary evaluation of the performance of this coupled model is performed through idealized tests and an examination of the September 2000 Moore Branch Fire; the results conform well with those of other coupled models and are superior to those produced by the uncoupled DEVS-FIRE model, motivating further investigation.


Discrete event specification Moore Branch Fire 



This work was accomplished under NSF Grants CNS-0941432, CNS-0941491, and CNS-0940134 and made extensive use of the Gordon, Sooner, and Kraken supercomputing clusters. The authors wish to thank the San Diego Supercomputing Center, the OU Supercomputing Center for Education and Research at the University of Oklahoma, the National Institute for Computational Sciences at the University of Tennessee, and the Oak Ridge National Laboratory for making those resources available and providing technical support. We also express our appreciation to Thomas Spencer and Curt Stripling of the US Texas Forest Service for providing the GIS data related to the Moore Branch Fire, the National Climatic Data Center for providing the necessary background weather data for our tests, and the reviewers whose feedback greatly improved the quality of this manuscript.


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Copyright information

© US Government 2015

Authors and Affiliations

  • Nathan Dahl
    • 1
    Email author
  • Haidong Xue
    • 2
  • Xiaolin Hu
    • 2
  • Ming Xue
    • 3
  1. 1.Rosenstiel School of Marine and Atmospheric ScienceUniversity of MiamiMiamiUSA
  2. 2.Department of Computer ScienceGeorgia State UniversityAtlantaUSA
  3. 3.Center for Analysis and Prediction of StormsNormanUSA

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