Eulerian modelling of spotting using a coupled Fire-Atmosphere approach

Alonso-Pinar, Alberto; Filippi, Jean-Baptiste; Guyot, Adrien; McCarthy, Nicholas; Tulet, Pierre; Filkov, Alexander

doi:10.5194/egusphere-2025-4855

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https://doi.org/10.5194/egusphere-2025-4855

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17 Dec 2025

| 17 Dec 2025

Status: this preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).

Eulerian modelling of spotting using a coupled Fire-Atmosphere approach

Alberto Alonso-Pinar, Jean-Baptiste Filippi, Adrien Guyot, Nicholas McCarthy, Pierre Tulet, and Alexander Filkov

Abstract. Spotting, the process by which burning firebrands are lifted by convection and transported downwind igniting secondary fires. Spotting can become a critical driver of rapid wildfire spread and presents major challenges for prediction and suppression. Coupled fire–atmosphere models, which simulate the two-way interaction between fire behaviour and local atmospheric dynamics, offer a promising avenue to capture such complex processes. In this study, we introduce a computationally efficient Eulerian formulation for firebrand transport and spotting, implemented within the coupled MesoNH–ForeFire modelling framework. Two case studies were analysed: an idealized scenario over flat and hilly terrain to assess wind influence, and a realistic simulation of the 2016 Mt Bolton wildfire in southeastern Australia. The model captured key spotting dynamics and fire spread patterns, producing realistic downwind distances with spot fire timing that slightly preceded observations. A full 8-hour forecast, including spotting, simulates in just less than 3 hours, without optimization. Results demonstrate that this simplified approach provides a credible and time-efficient spotting forecast, supporting its potential for operational wildfire modelling and decision-making.

Received: 01 Oct 2025 – Discussion started: 17 Dec 2025

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Alberto Alonso-Pinar, Jean-Baptiste Filippi, Adrien Guyot, Nicholas McCarthy, Pierre Tulet, and Alexander Filkov

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RC1:
'Comment on egusphere-2025-4855', Akli Benali, 24 Feb 2026 reply
The paper shows the implementation of simplified Eulerian-based spotting model over two distinct cases: 1) "synthetic" case studies 2) real case study. The paper needs substancial reviews to ensure it provides a solid contribution. At this stage there is some confusion and the objetives and associated workflow need to be clarified.
Main Comments
Fuel description. L66: “Four main fuel classes were identified: grassland, forest, artificial surfaces and constructions, and water bodies”, these are not fuel classes, these are land cover classes. I don’t understand why this was used, instead of Corine Land Cover. Shrubs are missing. Moreover, I don’t understand why the authors need fuel data from EU land cover considering that they are running idealized cases (you can simply assign a fuel class) and a fire in Australia that one would expect to have detailed fuel data. Which fuel models were used?

L98 “We acknowledge that the Rothermel model was developed for, and is typically applied to, Northern Hemisphere coniferous forests, but our analysis focuses on ForeFire’s performance in spotting transport rather than firebrand generation or forward rate of spread”. This should be in the discussion section under the limitations of the fire spread simulation.

Simulation setup (section 2.3) would benefit from having a clearer separation between the idealized simulations vs. the real case simulation.

L194-195: Rate of spread is expressed in m/min, not ha/min. Please correct.

“Verification of the model” (section 2.5). This section encapsulates two main concerns:
It looks like the authors did a “model comparison” where they compare the results of this new model with another model. It is not clear (from the beginning) why this was done and what kind of added-value this brings to paper. The model comparison should ideally be stated in the objectives of the paper. Reading the paper further, it looks like one of the objectives is to compare computational costs…

It is stated in the objetives that the model will be validated against the extensive observations of Mt Bolton fire. Reading the Methods section there is no reference to “validation” and Figure 3 does not show spotfire landing location. Moreover, “verification”, “model intercomparison” and “validation” are separate things that should be distinguished.

Please revise both aspects so that it is clear to the reader what is intended in each step of the analysis. Verify is not the best term. Use evaluate\assess in the first case, validate in the second.
There are some Methods missing, regarding how the assessment and validation were done. One example: first paragraph of section 3.2.3 refers to Methods and not Results.

Figure 1: where are the “orange contours”? Where is the ignition? What do these range values mean? (this is never mentioned in the paper)

I do not understand why the authors compare surface progressions nor surface rate of spread (section 3.2.1) if the objective of the work is to implement and evaluate a spotting model. This is stated in the objectives (Section 1) but also on the sentence “but our analysis focuses on ForeFire’s performance in spotting transport rather than firebrand generation or forward rate of spread” (section 2.1). Additionally, it doesn’t seem to make much sense to evaluate the progressions considering that “the available combustible fuel was limited to the burn area of the observed fire".

Figure 10: if plume measurements were done on the field, shouldn’t they be displayed here?

Why didn’t you compare the spotting simulations vs. observations considering the two models (Eulerian and LAgrangian)? This would allow a more complete analysis of the quality of the model you propose, besides the gains in computation time.

“it is likely that the ERA5 re-analysis has a time shift with respect to the actual wind behaviour, leading to a time difference in terms of fire progression.” No weather station data available for comparison?

A 30min difference between alert and ignition is quite large. What background information did you use to support this?

Regarding the quality and usefulness of the Method implement to represent spotting: I believe the paper would benefit from a quantitative assessment of the distribution of the estimated accumalated mass over the observed spot fires. Is the distribution over the observed spot fires significantly different than the distribution over "non-spot" locations?

Minor Comments:
- Check Reference formatting. Example (L34): “offered by (Sullivan, 2009))” as opposed to “offered by Sullivan (2009),”.
- What do you mean by “all six degrees of freedom”? L55
- L56…references…
- L70: it does not make sense to say that it spans from grassland to very large fires. Maybe grassland and shrub-forest fires or small to very large fires. Grassland fires can be large fires.
- Methods described what “was” done (L104). Change the remaning text accordingly.
- Equation 1: not all terms are described. Correct “C_i” to match the equation.
- L174: kW.m-2
- L178: looks like this sentence is repeated.
- Don’t understand this sentence “The Mt Bolton namefiles are published accompanying the MesoNH-ForeFire repository as an open-source dataset.”
- L194: “During this phase, the fuel supported intense short range (less than 1 km) spotting”, to avoid discussions around the importance of fuel, I suggest you simply state that intense short range spotting occurred.
- Suggest moving the paragraph in L200 to the top.
- L210: what was the extent (in ha) of the Mt Bolton fire? Move this paragraph upwards, it is generic information about the fire which contrasts with specific information, for example, regarding plume measurements.
- L216-17: repeated.
- Figure 2 shows before it is mentioned
- L307: “had already shifted”
- Figure 4: larger numbers on the axis. What is “Wind Y”? Never mentioned before. What are the units?
- L185: rephrase the last sentence to make it clearer.
- First 2 paragraphs of 3.2.4: Methods. Also part of the 3^rd paragraph
- L452: do you mean “slope”?
- L454: I don’t think your results allow you to state “including the topography in a spotting model would enhance its overall accuracy.” You could do that, if you run Mt Bolton Fire without topography, compared the results and concluded that accuracy was higher when topography was used.
- L455: Make it clear that you are making the transition from the idealized cases to the Mt Bolton fire.
- L458-460: also short distance spotting can be rapidly absorbed by the fire front without being detected. In the first hours your highest “mass deposition” values are close to the fire front.
- L499: I believe the term is “new ignitions” and not “reignition”
- L539: “radar”
- L542: rewrite sentence “consistent advection field in which to embed firebrand transport”
- L544 “with observations”

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Citation: https://doi.org/10.5194/egusphere-2025-4855-RC1

Alberto Alonso-Pinar, Jean-Baptiste Filippi, Adrien Guyot, Nicholas McCarthy, Pierre Tulet, and Alexander Filkov

Data sets

Simulation files for Eulerian modelling of spotting using a coupled Fire-Atmosphere approach Alberto Alonso-Pinar et al. https://doi.org/10.5281/zenodo.17241970

Alberto Alonso-Pinar, Jean-Baptiste Filippi, Adrien Guyot, Nicholas McCarthy, Pierre Tulet, and Alexander Filkov

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Short summary

Wildfires can spread quickly when firebrands are carried by wind to ignite new fires, a process known as spotting. Predicting this process is vital for safety and firefighting, but it is difficult to model. This paper introduces a new, faster way to simulate spotting using a coupled fire–atmosphere model. Tested on real and ideal cases, our approach reproduced realistic fire spread and timing, showing promise for faster, more reliable forecasts to support wildfire management and decision-making.


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