For this paper as a stand-alone paper, I don't have much to recommend for revisions; as noted in the section 1 (Introduction), this paper is intended itself as a preliminary introduction to a number of papers, some of which are already written and available online. I did not review those other papers in support of providing these comments, so I don't know if any changes are warranted, to address my questions below.

The paper is written as if by a team ("we"), but there is only one author listed. Perhaps it should be clarified up-front that this author is writing on behalf of a larger team? The language is at times informal, not consistent with how scientific papers are normally written ("Do remember, though,..."). There's an uncapitalized sentence fragment in line 56, and an underlined sentence in lines 59-60. Lines 51-54 have two back-to-back single-sentence paragraphs.

My biggest questions pertain to the credibility of the projections coming from the model. However, this specific introductory paper is probably not the place to address this concern, and to provide the comparisons between FRIDA and the existing body of projections to 2100. Similarly I am wondering about the key data inputs to the model. Is it trained purely on statistical and historical data? How many of the equations used for projections were pulled from the literature or other models, as opposed to developed by this team? Are the parameterization designed with reference to existing projections from other models?

Within the paper, the only results shown are in Figure 7, where the figure is too small/blurry to interpret; the purpose of the figure seems primarily to show that results can be produced. Still, for a paper documenting the existence of a new model, it seems pretty basic that some projections of common scenarios ought to be run and compared with the existing published body of scenarios (e.g., AR6). Again, if this is done in subsequent papers then there is no issue here.

On a similar note, the author continually stresses the very high portion of endogenous variables in the model, i.e. that there are very few exogenous variable specified. This seems a worthy aspiration in general, but care should be taken to ensure that making a variable endogenous actually improves the quality of the projected outcomes. In the current generation of IA models, the major exogenous assumptions (e.g., population, GDP, techno-economic characteristics of energy technologies) can act as guardrails on future modeled outcomes. Some acknowledgment of this fact seems warranted, along with discussion of whether constraints on variables were applied, whether exogenously or simply within the equations used for projecting.

This paper acts as an overview of a collection of papers for the FRIDA model. As such it is not an original research article, but rather a high-level overview of the FRIDA model, with more details provided in relevant paper. As such my comments do not focus on the scientific aspects of FRIDA, but rather on the clarity of this manuscript as such an overview.

While the paper does indeed cover most of the aspects one would expect from an overview, I feel that the current structure of document is not helpful in order to convey a clear message. It seems to me that information is not given in a clear order, and some sections seems bit out of place. Section 3 doesn’t seem to have a clear purpose and gives snippets of information with no clear reasoning. Furthermore, section 5 provides a deep dive on the drivers of climate change, which seems a bit superfluous and not necessary for this paper.

I would propose the author considers revising the paper in order to provide a clearer structure. While reading the paper I felt that something along the lines of my below proposal (with relevant sub-sections) might make sense. I am not suggesting the author takes on my suggestion as is, but I think they should seriously consider how information is communicated to the reader, and the below can perhaps be a guide. If the Authors think the current structure has merit, I am also OK with that, but then a lot of the wording would have to improve to make this clear. My proposed structure has 6 sections, each with a specific goal, and in the sub-bullets I indicate how the sections of the current draft may fit in this revised structure.

1. Knowledge gap FRIDA aims to cover, including the shortcomings of existing models/scenarios
   1. Current section 1
2. Design and requirements of FRIDA
   1. Current introduction to section 2, and first paragraph of section 2.1
3. Structure of the model
   1. Section 4
   2. First two paragraphs of section 3
   3. Short sub-sections for each of the systems shown in figure 3. These sub-sections can include a lot of what is currently in section 6 (for the climate module) and perhaps figures 4 and 5)
4. Running, validation, and calibration
   1. Section 7
   2. Second paragraph of section 2.1
   3. 3^rd paragraph of section 3 (with more detail)
5. Using FRIDA
   1. 4^th paragraph of section 3
   2. Current sections 8 and 9
   3. Part of my motivation of combining section 8 and 9 is that given the low geographic resolution of FRIDA, as well as its highly stylized design, giving precise policy advice is limited. However FRIDA is extremely powerful as an educational tool
6. How FRIDA complements existing models/scenarios
   1. What has Frida brought to the table that was missing? Snippets of this information is provided throughout the current draft, but it would be useful to bring is all together in one clear place.
   2. Most of section 10
   3. Current lines: 207-211, 224, 259, 271,

Finally, as this paper acts as an introduction to a collection of papers, it would be really nice if at the end there was a paragraph highlighting what is available in the collection. Perhaps one sentence per paper, indicating what the reader can find within the collection.

Detailed comments:

• Lines 29-30: Please provide a reference for the “already observed” dangerous climate change impacts
• In figure 2 it is mentioned that the model is “calibrated with observations from the period 1980 to 2023”. More information on calibration would be very useful so readers can understand the purpose of the model better. What are the main inputs/outputs that are calibrated? What are the datasets? Is any specific processing done during calibration?
• Lines 134-135: Validation is mentioned, but not elaborated upon. As mentioned, I understand that calibration, validation and uncertainty are described in Schoenberg et al (2025), but it would be useful in this overview paper to have a very brief overview of these aspects. Just a few sentences would be enough to convey the message, and readers interested in more details can consult the specific paper.