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    Author(s): Michael T. Kiefer; Warren E. Heilman; Shiyuan Zhong; Joseph J. CharneyXindi BianNicholas S. Skowronski; John L. Hom; Kenneth L. ClarkMatthew PattersonMichael R. Gallagher
    Date: 2014
    Source: Journal of Applied Meteorology and Climatology. 53: 793-812.
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (4.28 MB)


    Smoke prediction products are one of the tools used by land management personnel for decision making regarding prescribed fires. This study documents the application to a prescribed fire of a smoke prediction system that employs ARPS-CANOPY, a modified version of the Advanced Regional Prediction System (ARPS) model containing a canopy submodel, as the meteorological driver. In this paper, the performance of ARPS-CANOPY in simulating meteorological fields in the vicinity of a low-intensity fire is assessed using flux-tower data collected prior to and during a low-intensity prescribed fire in the New Jersey Pine Barrens in March 2011. A three-dimensional high-resolution plant area density dataset is utilized to define the characteristics of the canopy, and the fire is represented in ARPS-CANOPY as a heat flux to the atmosphere. The standard ARPS model is compared with reanalysis and upper-air data to establish that the model can simulate the observed synoptic-mesoscale and planetary boundary layer features that are salient to this study. ARPS-CANOPY profiles of mean turbulent kinetic energy, wind speed/direction, and temperature exhibit patterns that appear in the flux-tower observations during both the preburn phase of the experiment and the period of time the flux tower experienced perturbed atmospheric conditions due to the impinging fire. Last, the character and source of turbulence in and around the fire line are examined. These results are encouraging for smoke prediction efforts since transport of smoke from low-intensity fires is highly sensitive to the near-surface meteorological conditions and, in particular, turbulent flows.

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    Kiefer, Michael T.; Heilman, Warren E.; Zhong, Shiyuan; Charney, Joseph J.; Bian, Xindi; Skowronski, Nicholas S.; Hom, John L.; Clark, Kenneth L.; Patterson, Matthew; Gallagher, Michael R. 2014. Multiscale simulation of a prescribed fire event in the New Jersey Pine Barrens using ARPS-CANOPY. Journal of Applied Meteorology and Climatology. 53: 793-812.


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