In their study, the authors investigated the uncertainties in carbon emissions from land use and land cover change in Indonesia. They analyzed spatiotemporal differences in cropland from several LULCC datasets. The authors run multiple simulations to disentangle the impact of  different LULCC datasets on the carbon emissions. They also compared the results of different LULCC data-driven JULES-ES models and the results of MB1-driven TRENDYv12 simulations, as well as comparing their estimates with other models/products such as the National Greenhouse Gas Inventory of Indonesia (NGHGI). Overall, testing the sensitivity of the model to the LULCC changes is of great interest, especially for some important regional carbon emission assessments, and the manuscript is decently written.

However, I have some concerns as follows: (1) In the Introduction, the authors use a lot of paragraphs to describe the importance of Indonesia in the global carbon cycle, which is very important background knowledge, but this part should be streamlined. Even, the authors spend a lot of space on the introduction of some commonly used data, such as LUH2. It is unnecessary to introduce these too much, because it can appear in the data description section. Particularly, there is no review of similar studies and comparison with previous studies. Moreover, too much speculation appears in the Discussions and Conclusions, while there are no results to support them. Some results need to be explained better. (2) The innovativeness of the present version can not be observed and was not highlighted in the Introduction. (3) I am very concerned about the evaluation of the model as it directly determines the reliability of this study. However, the authors did not provide details on model parameter and their settings, which modules were used, and how carbon emissions were calculated. It is unclear. In particular, the authors used 0.5° resolution land use data (resampling 30 m Mapbiomas data to 0.5 degrees), only about 760 pixels in Indonesia, to run the model and analyze the spatial and temporal variability of the LULCC and investigate their impact on carbon emissions, which will lead to a great deal of uncertainty, and this make me and the readers very sceptical about the reliability of the study. (4) It seems that this study only focuses on cropland changes, while the title suggests that the authors are concerned about the impact of LULCC changes on uncertainties in carbon emission. Moreover, it should be noted that LULCC not only includes changes in the internal planting structure of a specific land use type (e.g., the area of cropland remaining unchanged, but its planting type can change, thereby affecting carbon emissions), but also includes the mutual transformation between different land use types (e.g., the conversion between cropland and forests). However, this study seems to primarily focus on changes in the area of different land use types.

Further detailed comments follow below.

Abstract:

Line 39:  Please keep the expression of 0.24 [0.22-0.25] Pg C/yr consistent with that of 0.23 ± 0.05 Pg C/yr. Make them comparable.

Line 44: Change the “,” to “.”.

Introduction

Line 47: I suggest adding the relevant references to support this statement.

Line 55: What does MHa mean? Is it Mha?

Line 65: Delete “(Emissions of Land Used Change)” as already mentioned above.

Lines 80-82: Add the references.

Methods:

Line 105: It appears that only cropland was considered in this study, but not grazing land. This is confusing.

Line 107: Which method have you used to reduce the grazing land fraction? Please describe the method in detail and add one or two sentences here.

Line 131: We could not get some detailed information about these data from Table 1, and I suggest adding some basic parameters about these data, etc.

Line 145: I am not an expert on the JULES-ES model. For a reader who may not know the JULES-ES model. Please add some important information on this model to the Supplementary, for example, adding the important parameters used in your study and their settings for different plant functional types (PFT), and the equations for the main modules (e.g., how do you calculate carbon emissions?) that used in your study, etc., making it so much easier to understand the scope of the model quickly and be able to interpret your study.

Line 190: But there is a big difference in the definitions of agriculture and cropland. In particular, they may have different parameter settings in the model. Generally, “cropland” is commonly used in the models (e.g., JULES-ES model). Are pulpwood or palm oil plantations croplands? These may affect your results and conclusions.

Line 200: We know that Indonesia is mainly composed of islands, and with such a coarse resolution (0.5 degrees) used in this region, it would introduce very large uncertainties. The 0.5-degree resolution is commonly used in global-scale simulations.

Line 221: How to calculate the ELUC trend, magnitude, and pattern with or without peat emission? It's not clear.

Results:

Line 227: Replace “million hectares” with the same unit, Mha.

Lines 237-238: This sentence “This aligns with other research…” seems to belong in the Discussion section. I suggest moving it to that section.

Line 241: In Fig. 2, are the results of spatial and temporal variations in cropland all based on 0.5 degrees? I'm curious how the cropland areas of MB1 and MB2 change at their original resolution? The same or different? This may affect the reliability of all the results. Besides, the scale bar is missing in Figure 2.

How are Figure 2e, 2h, and 2k calculated? 2018 minus 2000 or 2000 minus 2018? Please explain in the figure caption.

Lines 250-256: Part of the discussion?

Line 294: “0.12 ± 0.02 PgC/yr and 0.12 ± 0.02 PgC/yr respectively”? Please check these data carefully. They are not the same in Fig 4a.

Discussion:

Lines 308-309: It seems that you are not comparing it to the FAO data. I checked the entire results section and found no comparisons to the FAO data. Why? But you mentioned that data in above text and conclusions. Please add relevant results.

Line 314: JULES or JULES-ES?

Line 328: Don't repeat what you've already mentioned above (see Line 105).

Lines 333-334: There are no results to support this, it's plain speculation. Similar speculation comes up too many times in your research.

Lines 337-338: I doubt that it is correct to classify palm oil as cropland? Would the simulation results change if it was classified as forest or other land cover types? This leads to a great deal of uncertainty in your results. Please show the results of these differences.

Lines 360-361: It's a very interesting result, but you don't have any more explanations. Can you discuss it in depth?

Conclusion

Lines 372-373: Didn't find your results to support that conclusion. Suggest removing it from the text.

Additionally, the model's reliability is further questioned due to the lack of site-level validation, particularly for the region having different land types, site validation against all those types should be conducted. Before applying the model at a regional scale, validation against observational data is essential to ensure accuracy.

I suggest the following improvements:

1. Provide a more detailed explanation of the model mechanisms either in the method section, particularly the module responsible for calculating carbon cycles, to help readers better understand how the model functions.
2. Include site-level validation against observational data to demonstrate the model's ability to capture carbon emission trends. If such validation has been conducted previously, please cite the relevant publications and incorporate a figure or table to present the validation results.

Specific comments: