the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Mar 2026
A field dataset from replicated prescribed fire experiments on wildland fire behaviour and fire–atmosphere interactions
Abstract. We present a spatially and temporally resolved dataset characterizing combustion dynamics, fire behaviour, and associated environmental variables from thirty-five replicated prescribed fire experiments conducted between March 2018 and May 2019 on 10 m × 10 m burn plots at the U.S. Forest Service Silas Little Experimental Forest in the New Jersey Pinelands, USA. The experiments were designed to quantify the physical processes driving combustion, flame propagation, and energy exchange, bridging the gap between small-scale laboratory studies and large-scale prescribed fires. The dataset provides synchronized, multi-instrument observations of high frequency three-dimensional wind, temperature, pressure, fire radiative power, gas concentrations, fuel moisture, and mass loss, along with pre- and post-burn terrestrial LiDAR scans of fuel structure. These data capture key interactions among fuels, atmosphere, and combustion processes at a scale relevant to wildland fire behaviour. The dataset supports development and validation of coupled fire–atmosphere and combustion models, as well as analyses of radiative energy transfer and fuel consumption dynamics. All data are publicly available through the U.S. Forest Service Research Data Archive as an open-access benchmark resource for advancing process-level understanding and model evaluation in wildland fire science.
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Status: open (extended)
- RC1: 'Comment on essd-2026-11', Anonymous Referee #1, 18 May 2026 reply
Data sets
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – Transportable Analyzer for Calorimetry Outside (TACO) Z. J. Campbell-Lochrie et al. https://doi.org/10.2737/RDS-2022-0082
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments - three-dimensional wind and temperature K. L. Clark et al. https://doi.org/10.2737/RDS-2022-0081
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments - temperature profile K. L. Clark et al. https://doi.org/10.2737/RDS-2022-0083
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – plot layout and documentation M. R. Gallagher et al. https://doi.org/10.2737/RDS-2022-0079
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments - atmospheric pressure W. E. Heilman et al. https://doi.org/10.2737/RDS-2022-0080
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – fire radiative power R. L. Kremens et al. https://doi.org/10.2737/RDS-2022-0077
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – terrestrial laser scans. N. S. Skowronski et al. https://doi.org/10.2737/RDS-2022-0084
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – infrared data. N. S. Skowronski et al. https://doi.org/10.2737/RDS-2022-0076
Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – fuel loading and consumption C. Walker-Ravena et al. https://doi.org/10.2737/RDS-2022-0078
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- 1
The manuscript presents a valuable and comprehensive dataset from highly instrumented prescribed fire experiments conducted at an intermediate scale between laboratory and operational field burns. Such datasets are particularly important for wildfire research because they help bridge the gap between controlled laboratory studies and complex real-scale fires. The detailed measurements make this dataset especially relevant for the development and validation of physics-based wildfire models. I nevertheless have several major comments and suggestions that should help clarify the dataset description and make the data easier to interpret and use by the community.
1) The horizontal positions of the sensors are not sufficiently defined in the current manuscript, although this information is essential for proper interpretation of the dataset and for detailed comparison with numerical simulations. In addition to the current Fig. 3, I strongly recommend adding a clear top-view schematic of the experimental setup using one corner of the plot as the coordinate origin. The figure should explicitly report:
- the positions of the trusses and the sensor nodes along each truss,
- the ignition line,
- the positions of the fuel-loss load cells,
- the position of the central tower,
- the position of the TACO system,
- the north direction to properly define wind orientation.
Such a figure would significantly improve the clarity and usability of the dataset.
2) The instrumentation layout and sensor configuration vary significantly between the different burns. For example, the sonic anemometers were installed at 2.5 m for Burns 1-22 and at 3.0 m for Burns 23-35; Burns 7 and 8 included an alternative two-level configuration (1.5 m and 3.5 m); the number of thermocouple arrays changed after Burn 6; and the number and location of load cells also evolved throughout the campaign. These changes are currently described throughout the manuscript, making it difficult for the reader to know exactly the experimental configurations associated with each burn.
I strongly recommend centralizing this information in a dedicated table or subsection summarizing any modifications relative to the standard configuration. This would considerably improve the readability of the manuscript and facilitate the use of the dataset for comparative analyses and model validation.
3) For wildfire-model validation and comparison purposes, fire intensity is one of the most important integrated fire-behavior parameters. However, the manuscript does not clearly explain how fire intensity can be derived from the dataset. Since the data include measurements of the fire spread and fuel consumption, it should be possible to estimate fire intensity.
I strongly recommend adding a dedicated subsection explaining how users can estimate fire intensity from the available measurements and which variables should be used for that purpose. In particular, it is unclear whether the heat of combustion and the fraction of truly consumed fuel are available or can be reasonably estimated from the dataset.
Fire intensity is also a key parameter for estimating Byram’s convective number, which helps characterize the fire regime and determine whether a burn is primarily wind-driven or plume-dominated.
In addition to the comments above, I also have some minor comments and requests for clarification that should help improve the readability of the manuscript.
4) The manuscript states that five burns produced incomplete or weak fire-spread datasets due to low intensity or wet fuelbeds (line 311). These burns should be explicitly identified in the text.
5) The quality and resolution of Figure 3 are not sufficient. The labels and instrumentation details are difficult to read. A clearer and higher-resolution version should be provided.
6) Line 170: the capacity of the spring scale is provided, but its accuracy would be more relevant since it directly affects the uncertainty of the fuel-load values. The authors should provide the scale accuracy and, if possible, reflect this uncertainty in the reported fuel loads.
7) Line 236: the manuscript mentions the existence of diagnostic files reporting missing and suspect data. Please indicate, at least roughly, the typical percentages of missing and suspicious data across all measurements and burns. This information is important for assessing the overall reliability, completeness, and usability of the dataset.
8) Was the turbulence intensity of the ambient flow recorded, or can it be derived from the available measurements? This may influence fire spread.
9) The data archive link provided in the manuscript (https://www.fs.usda.gov/rds/archive/) does not appear to be working on my end. The authors should verify the URL and ensure that the dataset is directly accessible to readers and reviewers.