diff --git a/paper/paper.bib b/paper/paper.bib index 2b6b5a6..6587c2f 100644 --- a/paper/paper.bib +++ b/paper/paper.bib @@ -8,7 +8,7 @@ @article{lautenberger2013 publisher = {Elsevier BV}, author = {Lautenberger, Chris}, year = {2013}, - month = nov, + month = Nov, pages = {289–298} } @techreport{finney1998, @@ -74,7 +74,7 @@ @article{kamilaris2023 publisher = {Elsevier BV}, author = {Kamilaris, A. and Filippi, J.B. and Padubidri, C. and Koole, R. and Karatsiolis, S.}, year = {2023}, - month = apr, + month = Apr, pages = {103747} } @@ -90,7 +90,7 @@ @article{linn2005 publisher = {American Geophysical Union (AGU)}, author = {Linn, Rodman R. and Cunningham, Philip}, year = {2005}, - month = jul + month = Jul } @article{allaire2022, title = {Simulation-based high-resolution fire danger mapping using deep learning}, @@ -103,7 +103,7 @@ @article{allaire2022 publisher = {CSIRO Publishing}, author = {Allaire, Frédéric and Filippi, Jean-Baptiste and Mallet, Vivien and Vaysse, Florence}, year = {2022}, - month = apr, + month = Apr, pages = {379–394} } @article{allaire2021, @@ -144,7 +144,7 @@ @article{filippi2014 publisher = {Copernicus GmbH}, author = {Filippi, Jean-Baptiste and Mallet, Vivien and Nader, Bahaa}, year = {2014}, - month = nov, + month = Nov, pages = {3077–3091} } @@ -176,7 +176,7 @@ @article{filippi2009 publisher = {SAGE Publications}, author = {Filippi, Jean-Baptiste and Morandini, Frédéric and Balbi, Jacques Henri and Hill, David RC}, year = {2009}, - month = aug, + month = Aug, pages = {629–646} } @@ -192,7 +192,7 @@ @article{santoni2011 author = {Santoni, Paul-Antoine and Filippi, Jean-Baptiste and Balbi, Jacques-Henri and Bosseur, Frédéric}, editor = {Morvan, D}, year = {2011}, - month = jan + month = Jan } @article{balbi2009, author = {Balbi, Jacques-Henri and Morandini, Frédéric and Silvani, Xavier and Filippi, Jean-Baptiste and Rinieri, Frédéric}, @@ -223,7 +223,7 @@ @article{garcia2008 publisher = {Wiley}, author = {Garcia, Tanya and Braun, John and Bryce, Robert and Tymstra, Cordy}, year = {2008}, - month = feb, + month = Feb, pages = {836–848} } @article{pais2021, @@ -249,7 +249,7 @@ @article{mandel2011 publisher = {Copernicus GmbH}, author = {Mandel, J. and Beezley, J. D. and Kochanski, A. K.}, year = {2011}, - month = jul, + month = Jul, pages = {591–610} } @@ -263,7 +263,7 @@ @article{campos2023 publisher = {Elsevier BV}, author = {Campos, Cátia and Couto, Flavio Tiago and Filippi, Jean-Baptiste and Baggio, Roberta and Salgado, Rui}, year = {2023}, - month = jul, + month = Jul, pages = {106776} } @article{couto2024, @@ -276,7 +276,7 @@ @article{couto2024 publisher = {Elsevier BV}, author = {Couto, Flavio Tiago and Filippi, Jean-Baptiste and Baggio, Roberta and Campos, Cátia and Salgado, Rui}, year = {2024}, - month = apr, + month = Apr, pages = {107223} } @article{baggio2022, @@ -289,7 +289,7 @@ @article{baggio2022 publisher = {Elsevier BV}, author = {Baggio, Roberta and Filippi, Jean-Baptiste and Truchot, Benjamin and Couto, Flavio T.}, year = {2022}, - month = dec, + month = Dec, pages = {103699} } @Article{filippi2021, @@ -329,7 +329,7 @@ @article{strada2012 publisher = {Elsevier BV}, author = {Strada, S. and Mari, C. and Filippi, Jean-Baptiste. and Bosseur, F.}, year = {2012}, - month = may, + month = May, pages = {234–249} } @article{filippi2018, @@ -343,7 +343,7 @@ @article{filippi2018 publisher = {MDPI AG}, author = {Filippi, Jean-Baptiste and Bosseur, Frédéric and Mari, Céline and Lac, Christine}, year = {2018}, - month = jun, + month = Jun, pages = {218} } @article{alonsopinar2025, @@ -356,6 +356,6 @@ @article{alonsopinar2025 publisher = {Elsevier BV}, author = {Alonso-Pinar, Alberto and Filippi, Jean-Baptiste and Filkov, Alexander}, year = {2025}, - month = may, + month = May, pages = {104348} } diff --git a/paper/paper.md b/paper/paper.md index 0f49092..68daf2d 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -100,8 +100,8 @@ ForeFire was developed as a community tool to fill the gap between highly comple ## Rapid prototyping of new models ForeFire implements several standard fire flux and spread rate models, such as Rothermel [@andrews2018] and Balbi [@balbi2009], and makes it trivial to switch, extend, or add to this base with a single `.cpp` file using any existing model file as a template. -Internally, data is handled as *layers* that can come from a NumPy array, be read from NetCDF, or be generated on the fly by ForeFire (e.g., slope derived from the elevation layer, fuel loaded as an index map with tabulated fuel — with standards fuel tables [@Scott2005] already available). -Developing a Rate Of Spread wildfire model was the original purpose of this simulation code and helped to iterate versions of the Balbi Rate Of Spread formulation on case studies [@balbi2009;@santoni2011]. It also served to implement various heat and chemical species flux models used for volcanic eruption [@filippi2021], plume chemistry [@strada2012], or industrial fires [@baggio2022]. In addition, the code includes a generic `ANNPropagationModel` that implements a feedforward artificial neural network (ANN) and expects a pre-trained graph file. +Internally, data is handled as *layers* that can come from a NumPy array, be read from NetCDF, or be generated on the fly by ForeFire (e.g., slope derived from the elevation layer, fuel loaded as an index map with tabulated fuel — with standard fuel tables [@Scott2005] already available). +Developing a Rate Of Spread wildfire model was the original purpose of this simulation code and helped to iterate versions of the Balbi Rate Of Spread formulation on case studies [@balbi2009; @santoni2011]. It also served to implement various heat and chemical species flux models used for volcanic eruption [@filippi2021], plume chemistry [@strada2012], or industrial fires [@baggio2022]. In addition, the code includes a generic `ANNPropagationModel` that implements a feedforward artificial neural network (ANN) and expects a pre-trained graph file. ## Batch simulations with the ForeFire scripting Custom FF language allows users to easily generate multiple scenarios, including fire-fighting strategies, model evaluation [@filippi2014], ensemble forecasts [@allaire2020], or generate a deep learning database [@allaire2021]. A FF script is a set of scheduled instructions that are interpreted in real-time, advancing the simulation clock with a `step[dt=]` or a `goTo[t=]` command. @@ -113,11 +113,11 @@ By utilizing pre-compiled datasets over extensive regions, this approach support ### Two-way coupling with the MesoNH atmospheric model -The same scripts can be executed in coupled mode with the Open-Source atmospheric model [MesoNH](https://mesonh.cnrs.fr/) [@lac2018] with fire propagating using surface fields (wind) from MesoNH and forcing heat and other flux fields into the atmosphere. An idealized coupled simulation can be run on a laptop at field scale [@filippi2013], but also on a supercomputer to forecast fire-induced winds of large wildfires [@filippi2018], fire-induced convection [@couto2024;@campos2023], or even to estimate wildfire spotting [@alonsopinar2025]. +The same scripts can be executed in coupled mode with the Open-Source atmospheric model [MesoNH](https://mesonh.cnrs.fr/) [@lac2018] with fire propagating using surface fields (wind) from MesoNH and forcing heat and other flux fields into the atmosphere. An idealized coupled simulation can be run on a laptop at field scale [@filippi2013], but also on a supercomputer to forecast fire-induced winds of large wildfires [@filippi2018], fire-induced convection [@couto2024; @campos2023], or even to estimate wildfire spotting [@alonsopinar2025]. Coupled simulations generate gigabytes of 3D data that can be converted to VTK/VTU files using Python helper scripts to visualize in the open-source tool ParaView, as shown in \autoref{fig:coupled}. -![Coupled simulation of the Pedrogao Grande wildfire [@couto2024] (Paraview rendering). On the ground, the burned area is in orange, while among atmospheric variables, downbursts are highlighted in red and pyro-cumulonimbus clouds in blue.\label{fig:coupled}](coupled.jpg) +![Coupled simulation of the Pedrogao Grande wildfire [@couto2024] (ParaView rendering). On the ground, the burned area is in orange, while among atmospheric variables, downbursts are highlighted in red and pyro-cumulonimbus clouds in blue.\label{fig:coupled}](coupled.jpg) # Acknowledgements This work has been supported by the Centre National de la Recherche Scientifique and French National Research Agency under grants **ANR-09-COSI-006-01 (IDEA)** and **ANR-16-CE04-0006 (FIRECASTER)**. The authors thank all contributors and collaborators who have assisted in the development and testing of the ForeFire software.