Multi-scale analyses of wildland fire combustion processes: Large-scale field experiments – FireTracker
The United States Department of Defense (DoD) Strategic Environmental Research and Development Program (SERDP) funded project: Multi-scale Analyses of Wildland Fire Combustion Processes in Open-canopied Forests using Coupled and Iteratively Informed Laboratory-, Field-, and Model-based Approaches (RC-2641) conducted a large-scale (management-scale) field experiment during an operational prescribed burn to quantify how atmospheric dynamics across a wide range of spatial and temporal scales affect fire propagation, energy exchange, and fuel consumption. This experiment also provided an opportunity to fully examine how combustion related processes transfer across scales of particles and simple fuel beds in the laboratory, wind tunnel, small-scale, and operational prescribed burns as instrumentation used in small-scale field experiments was embedded in this experiment. In addition, the large-scale experiment also provides data necessary for simulation and model testing of coupled atmosphere-fire behavior prediction systems (e.g., WRF-SFire, WFDS, QUIC-Fire, FIRETEC) and coupled atmosphere-canopy-smoke dispersion prediction systems (e.g., ARPS-Canopy/FLEXPART). The large-scale field experiment includes data from a heavily instrumented ~12.1 hectare (ha) management-scale fire conducted at the Silas Little Experimental Forest in the Pinelands National Reserve (PNR) on March 13, 2019. This data publication represents an array of 67 FireTracker sensors installed at ground level throughout the burn unit in a grid with approximately 35 meter spacing between sensors. The sensors consisted of 1.5 millimeter diameter K-type thermocouples (405-001, TC Direct) attached to Arduino Feather® data loggers (2796, Adafruit, New York, NY, USA) with thermocouple amplifiers which provided a resolution of 0.25 °C (degrees Celsius) (269, Adafruit). A GPS module (746, Adafruit) was used for time stamps and geolocation. Power was provided with 1200 mAh (milliampere/hour) lithium-ion batteries (258, Adafruit). FireTrackers were buried such that the tip of the thermocouple protruded through the surface fuels. FireTracker components were assembled prior to the experiment and a program to record the data, written in C++, was uploaded to the flash memory using the Arduino IDE. All FireTracker data were logged at a frequency of 2 hertz (Hz). The FireTracker data is used to spatially characterize the spread of the prescribed fire through the burn area.<br>Many DoD facilities utilize low intensity prescribed fire to manage hazardous fuels, restore ecological function and historic fire regimes, and encourage the recovery of threatened and endangered species in the forests they manage. Current predictive models used to simulate fire behavior during low-intensity prescribed fires (and wildfires) are empirically based, simplistic, and fail to adequately predict fire outcomes because they do not account for variability in fuel characteristics and interactions with important meteorological variables. This study used a suite of measurements at the fuel particle, fuel bed, field plot, and stand scales to quantify how variability in fuel characteristics and key meteorological factors interact to drive fire behavior during low intensity prescribed burns. These experiments were designed to inform the development and evaluation of mechanistic, physics-based models that explicitly account for combustion, turbulent transfer, and energy exchange by coupling and scaling individual component processes. These datasets provide measurements to improve the understanding of, and ability to accurately predict, fire behavior under a wide range of management scenarios.<br>A summary of the SERDP Project RC-2641 can be found at the RC-2641 Project Overview (serdp-estcp.org): https://www.serdp-estcp.org/projects/details/a4a4642d-f2be-4e52-b678-454fe06afbc2/rc-2641-project-overview. Please reference the burn layout and documentation data publication (Gallagher et al. 2023, https://doi.org/10.2737/RDS-2022-0089) as these data provide the sensor locations of each burn, a detailed description of data collected and a summary of the conditions during the burn periods.
| Main Authors: | , , , , , , , , , , |
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| Format: | Dataset biblioteca |
| Published: |
2023
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| Subjects: | Environmental sciences, combustion, computational fluid dynamics, environment, Fire suppression, pre-suppression, aerodynamic drag, fire spread, prescribed fire, Wildland/urban interface, climatologyMeteorologyAtmosphere, Prescribed fire, Smoke, Fire, fuel structure and loading, prescribed burn, biota, temperature, heat flux, fire behavior, |
| Online Access: | https://figshare.com/articles/dataset/Multi-scale_analyses_of_wildland_fire_combustion_processes_Large-scale_field_experiments_FireTracker/27010405 |
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