Abstract
With the increase in commercially available small unmanned aircraft systems (UAS), new observations in extreme environments are becoming more obtainable. One such application is the fire environment, wherein measuring both fire and atmospheric properties are challenging. The Fire and Smoke Model Evaluation Experiment offered the unique opportunity of a large controlled wildfire, which allowed measurements that cannot generally be taken during an active wildfire. Fire–atmosphere interactions have typically been measured from stationary instrumented towers and by remote sensing systems such as lidar. Advances in UAS and compact meteorological instrumentation have allowed for small moving weather stations that can move with the fire front while sampling. This study highlights the use of DJI Matrice 200, which was equipped with a TriSonica Mini Wind and Weather station sonic anemometer weather station in order to sample the fire environment in an experimental and controlled setting. The weather station was mounted on to a carbon fiber pole extending off the side of the platform. The system was tested against an RM-Young 81,000 sonic anemometer, mounted at 6 and 2 m above ground levelto assess any bias in the UAS platform. Preliminary data show that this system can be useful for taking vertical profiles of atmospheric variables, in addition to being used in place of meteorological tower measurements when suitable.
Highlights
It is well known that the atmosphere influences many aspects of wildfire behavior, and that the fire itself influences the atmosphere
There are several indices and metrics for quantifying risk related to large fires or extreme fire behavior based on atmospheric parameters
The Hot–Dry–Windy index (HDW) index combines the maximum of the vapor pressure deficit (VPD), a function of temperature and relative humidity (RH), and wind speed in the lowest 500 m of the atmosphere to create an output that can be used to predict extreme fire weather [7]
Summary
It is well known that the atmosphere influences many aspects of wildfire behavior, and that the fire itself influences the atmosphere. The HDW index combines the maximum of the vapor pressure deficit (VPD), a function of temperature and RH, and wind speed in the lowest 500 m of the atmosphere to create an output that can be used to predict extreme fire weather [7] Each of these indices attempts to quantify how specific sets of atmospheric variables affect wildfire growth, behavior or ignition. Controlled wildland fire experiments, such as FASMEE, help to alleviate this restriction by coordinating flights and maintaining close communication between manned and UAS pilots [13,16,24,25] The purpose of this proof of concept study is to demonstrate the utility of UAS platforms, that can be used at a controlled wildland fire to sample the vertical wind profile of 3-dimensional (3D) winds measured by multiple sonic anemometers for fire weather observations
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