Subgrid-scale fire front reconstruction for ensemble coupled atmosphere-fire simulations of the FireFlux I experiment

Costes, Aurélien; Rochoux, Mélanie C.; Lac, Christine; Masson, Valéry

doi:10.1016/j.firesaf.2021.103475

Cited by 12 publications

(30 citation statements)

References 46 publications

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“…In this study, we consider Balbi's ROS parameterization adapted for landscape-scale wildland fires (Santoni et al 2011) and already implemented in the Meso-NH/BLAZE coupled model. It was, for instance, used for the coupled model evaluation against the FireFlux I grass experimental data (Costes et al 2021). The change made by Santoni et al (2011) compared to Balbi et al (2009) is the consideration of the different properties of live and dead fuels, and their impacts on the ROS.…”

Section: Sensitivity Analysis Application To Rate-of-spread (Ros) Par...mentioning

confidence: 99%

“…The change made by Santoni et al (2011) compared to Balbi et al (2009) is the consideration of the different properties of live and dead fuels, and their impacts on the ROS. Following previous work by Costes et al (2021), we consider here the conditions of a grass fire experiment, without slope, to carry out the sensitivity analysis. The slope parameter is therefore not among the perturbed input parameters.…”

Section: Sensitivity Analysis Application To Rate-of-spread (Ros) Par...mentioning

confidence: 99%

“…Without further information, they are perturbed according to a uniform statistical distribution, which is characterized by a variation interval. The center of this interval corresponds to a so-called standard value, which corresponds to a tall grass fuel typical of the FireFlux I experiment that was simulated in Costes et al (2021) using the Meso-NH/BLAZE coupled model configured with the Balbi's ROS parameterization. We consider here a large variation interval to study how the ROS changes for a wide set of environmental conditions, and to identify which are the most influential input parameters that could then be used to generate ensemble coupled model simulations and study the coupled model response in a variety of situations.…”

Section: Sobol'-saltelli Estimation Approach and Experimental Designmentioning

confidence: 99%

“…Coupled atmosphere/fire models (Kochanski et al 2013;Filippi et al 2018;Costes et al 2021) provide an efficient but representative way to simulate wildland fire behavior at landscape-to-meteorological scales. They predict the propagation of the fire front at the land surface, the dynamics of the fire plume, and their mutual interactions.…”

Section: Introductionmentioning

confidence: 99%

“…Ribeiro (Ed. ) Chapter 1 -Decision Support Systems and Tools run ensembles of the coupled atmosphere/fire model to represent the range of possible wildland fire behavior over a given time window (Costes et al 2021).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Identifying the most influential parameters in experimental grass fire spread modeling using global sensitivity analysis

Roubelat¹,

Costes²,

Antolin³

et al. 2022

Advances in Forest Fire Research 2022

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Coupled atmosphere/fire models are recognized as an efficient and representative way to simulate wildland fire behavior at geographical-to-meteorological scales by representing the two-way interactions between the fire front propagation and the surrounding atmosphere. They rely on a rate-of-spread (ROS) parameterization to represent the fire front propagation speed with respect to environmental factors characterizing biomass fuel properties and moisture content, near-surface wind conditions and terrain slope. In actual wildfire events, these input parameters are only partially known and induce significant uncertainties in the coupled model predictions. To estimate the envelope of plausible wildland fire behavior for a given event, we aim at designing a perturbed-physics ensemble prediction capability based on a coupled atmosphere/fire model. To make the approach feasible, it is essential to identify the relevant subset of parameters to perturb to generate an ensemble of fire front positions and shapes. In the present study, we perform a global sensitivity analysis based on Sobolâ€™ indices to rank the environmental factors by order of influence on the Balbiâ€™s ROS parameterization, and thereby identify the parameters that contribute most to the variability of ROS. Results show the predominance of the near-surface wind speed on the ROS variability, followed by the leaf area index LAI, the ignition temperature T_i, the dead fuel moisture content M_d, the dead fuel particle mass density ho_d, and the fuel layer height e. Results also indicate that the sensitivity of each fuel parameter to the ROS is not constant with respect to the near-surface wind speed, and that the most influential input parameters differ between the head and the back of a fire. This indicates the importance of exploring the spatial and temporal dependencies of coupled model sensitivities in future work.

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Section: Sensitivity Analysis Application To Rate-of-spread (Ros) Par...mentioning

confidence: 99%

Section: Sensitivity Analysis Application To Rate-of-spread (Ros) Par...mentioning

confidence: 99%

Section: Sobol'-saltelli Estimation Approach and Experimental Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Identifying the most influential parameters in experimental grass fire spread modeling using global sensitivity analysis

Roubelat¹,

Costes²,

Antolin³

et al. 2022

Advances in Forest Fire Research 2022

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The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models

Lean,

Theeuwes,

Baldauf

et al. 2024

Quart J Royal Meteoro Soc

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For a number of years research has been carried out in several centres which has demonstrated the potential benefits of 100‐m scale models for a range of meteorological phenomena. More recently, some meteorological services have started to consider seriously the operational implementation of practical hectometric models. Many, but by no means all, of the applications are likely to relate to urban areas, where the enhanced resolution has obvious benefits. This article is concerned with the issues that need to be addressed to bridge the gap between research at 100‐m scales and practical models. We highlight a number of key issues that need to be addressed, with suggestions of important avenues for future development. An overarching issue is the high computational cost of these models. Although some ideas to reduce this are presented, it will always be a serious constraint. This means that the benefits of these models over lower resolution ones, or other techniques for generating high‐resolution forecasts, will need to be clearly understood, as will the trade‐offs with resolution. We discuss issues with model dynamical cores and physics–dynamics coupling. There are a number of challenges around model parameterisations, where some of the traditional problems (e.g., convection) become easier but a number of new challenges (e.g., around surface parameterisations) appear. Observational data at these scales present a challenge and novel types of observations will need to be considered. Data assimilation will be needed for short‐range forecasts, but there is currently little knowledge of this, although some of the likely issues are clear. An ensemble approach will be essential in many cases (e.g., convection), but research is needed into ensembles at these scales and significant work on post‐processing systems is required to make the best use of models at these grid lengths.

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Assessing the Internal Variability of Large-Eddy Simulations for Microscale Pollutant Dispersion Prediction in an Idealized Urban Environment

Lumet,

Jaravel,

Rochoux

et al. 2024

Boundary-Layer Meteorol

Self Cite

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This study aims at estimating the inherent variability of microscale boundarylayer flows and its impact on the air pollutant dispersion in urban environment. For this purpose, we present a methodology combining a high-fidelity Large-Eddy Simulation (LES) model and a stationary bootstrap algorithm, to estimate the internal variability of time-averaged quantities over a given analysis period thanks to sub-averages samples. A detailed validation of a LES microscale air pollutant dispersion model in the framework of the Mock Urban Setting Test (MUST) field-scale experiment is performed. We show that the LES results are in overall good agreement with the experimental measurements of wind velocity and tracer concentration, especially in terms of fluctuations and peaks of concentrations. We also show that both LES estimates and the MUST experimental measurements are subject to a significant internal variability, which is therefore essential to take it into account in the model validation exercise. Moreover, we demonstrate that the LES model is able to accurately reproduce the observed internal variability. This study only accounts for the microscale wind fluctuations, and is therefore a first step in measuring the complete effect of the atmospheric boundary-layer (ABL) internal variability on pollutant dispersion.

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Subgrid-scale fire front reconstruction for ensemble coupled atmosphere-fire simulations of the FireFlux I experiment

Cited by 12 publications

References 46 publications

Identifying the most influential parameters in experimental grass fire spread modeling using global sensitivity analysis

Identifying the most influential parameters in experimental grass fire spread modeling using global sensitivity analysis

The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models

Assessing the Internal Variability of Large-Eddy Simulations for Microscale Pollutant Dispersion Prediction in an Idealized Urban Environment

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