Software paper comments

[xiazeyu]

1. In Line 29, please add a more recent reference for Flammap.

2. In Line 35, please expand little more about how ForeFire is adaptable and high-performing. E.g., why it's adaptable, and what features enables it to be high-performing.

3. After Line 35, please mention your relation compared with other works, as well as ForeFire's underlying fire spreading models (list few well-known supported models).

4. After Line 35, please mention who the target audience is.

5. Please state how ForeFire compares with other commonly-used packages.

6. Please cite any dataset that has been pre-compiled into ForeFire.

7. Please consider citing the following works:

   a. https://doi.org/10.3390/fire3030026

   b. https://doi.org/10.1016/j.envsoft.2025.106401

   c. https://doi.org/10.1175/JAMC-D-12-023.1

   d. https://doi.org/10.1016/j.envsoft.2019.104616

Ref openjournals/joss-reviews#8680

[filippi]

Hi @xiazeyu thanks for comments,
I'll try to do most of it, the thing is that it was there in a previous version but we have strong issues with paper length to pass. I was more thinking of CELL2FIRE and ELMFIRE that are both used operationally and open sourced, you package PyTorchFire is great, but not yet used in operation, I can mention "other ai codes [your ref]" if you want.
Anyway.. to make all these additions, I would have to remove other parts. Which one are the most important for you ?

[xiazeyu]

Hello @filippi,

1, 3, 4, 7 are most important to me.

Please try to cite some commonly used simulators for operational use, and some more experimental models like PyTorchFire. One sentence comparison for each will be enough to show why people may use your simulator.

Please also mention the target audience. It's a requirement for JOSS.

[filippi]

In Line 29, please add a more recent reference for Flammap.

done

In Line 35, please expand little more about how ForeFire is adaptable and high-performing. E.g., why it's adaptable, and what features enables it to be high-performing. I added some lines on that.. sorry not much space left.

ForeFire was developed as a community tool to fill the gap between highly complex customizable models and more rigid operational tools: a unified wildfire simulator that is both adaptable (highly scriptable with multiple bindings) and high-performing (discrete‑event‑driven simulation with dynamic mesh allows to concentrate computation at meter resolution only on the active part of the front).

After Line 35, please mention your relation compared with other works, as well as ForeFire's underlying fire spreading models (list few well-known supported models).

relations are to be found just over line 35 now,i cite more packages (including yours)

After Line 35, please mention who the target audience is.

Added: It is inteded to serve both as a research platform and a tool for operational forecasting.

Please state how ForeFire compares with other commonly-used packages.

I did it already, in a condensed way.. Scripting language, ROS solver... No space to write more

Please cite any dataset that has been pre-compiled into ForeFire.

added: with part of [@Scott2005] fuel table already available)

Please consider citing the following works:

As for your work/paper, I added the citation as an example of AI, compared to all others, it is not used yet operationally by any fire agency.
b. https://doi.org/10.1016/j.envsoft.2025.106401

There is already a citation of WRF/SFire, WRF/Fire is not very far off...
c. https://doi.org/10.1175/JAMC-D-12-023.1

As of those, there are either not free or closed source, great, but neither open or free.. so we may add all commercial software too
a. https://doi.org/10.3390/fire3030026
d. https://doi.org/10.1016/j.envsoft.2019.104616

[filippi]

Last compiled paper :
joss.08680/10.21105.joss.08680.pdf

Thank again for comments

[xiazeyu]

LGTM. Thanks to your efforts.