This manuscript analyzes the regional responses to Asian black carbon perturbations using a reduced complexity climate model, SyRAP-FORTE2. The authors find a regional response of surface cooling, low-level warming, and precipitation reduction in all seasons. They apply the atmospheric energy budget analysis to explain the mechanisms behind summer precipitation responses. The analysis links the regional precipitation reduction to atmospheric warming induced by BC shortwave absorption, while changes in dry static energy flux divergence partly offset the responses. 

The topic is well within the scope of the journal. I think the detailed investigation of the seasonality and the mechanistic insights in this study would be of interest to the relevant communities. I believe this study could be accepted for publication after addressing the following issues.

General comments

The Introduction needs to be better organized. In its current form, the authors list a large number of relevant literature (L61–126) in a somewhat scattered manner. I think more efforts should be made to structure these references logically and to concisely highlight the most pertinent findings. This will help clarify the gap the study aims to fill. On a related note, the Conclusion and Discussion section should better articulate why a reduced-complexity model approach is valuable in this context and how it complements existing work using GCMs or other modeling frameworks. What does the reduced complexity model allow us to see that might be more difficult to isolate in fully coupled GCMs?

In the atmospheric energy budget analysis, the DSE flux divergence is decomposed to mean and eddy terms. However, the eddy component is not discussed in the main text. If the eddy component is negligible, please clarify and justify why it is omitted. Otherwise, consider analyzing how eddies influence the results.

The description of the model and experiments needs some clarification. I’m confused by which aerosol effects are included in the simulations. L178 indicates the model includes the semi-direct effect of BC, while L207 seems to suggest otherwise. This should be further discussed in the Conclusion and Discussion. It will help readers gauge how directly they can compare your results with those from more comprehensive aerosol-forcing experiments. Additionally, from my reading, the simulations only use BC, why mention the parameterization of aerosol-cloud interactions for scattering aerosol (L174)?  

L509–511: I don’t find these results very convincing. Indian precipitation response in CESM1 and NorESM1 exhibits opposite sign compared to that in FORTE2. GISS and MIROC show evident precipitation decreases over Southeast Asia, while FORTE2 shows large increases.

I think it would be helpful to show the spatial pattern and vertical cross-section of the BC forcing in the supplementary. It might help to understand the seasonality of the BC effects.

Careful proofreading is required. There are a number of grammatical and clarity issues throughout the text (e.g., L124, 136, 235, 245, etc.).

Individual comments

L88: clarify what is “enhanced upper-level atmospheric temperature”

L149: referring to “emissions” may be misleading when BC AOD is prescribed in the models.

L170: do you mean to state that FORTE2 has good skills?

L204: what are “different background climate states”?  

L238: It does not seem right.

L367: please be explicit about what vertical temperature differences reduce SH and how heating reduces LH.

L547: precipitation increases in Southeast Asia.

Figure 12: suggest to cinldue the FORTE2 results to facilitate a direct comparison.

The authors investigate the response of Asian monsoon regions to South and East Asian BC perturbations using a simplified climate model. They analyze the seasonal response to BC forcing, with a focus on summertime for the energy budget analysis. This study compares the relative effects of local versus remote forcing, as well as their combined impact. The work underscores the importance of the spatial location of aerosol forcing in determining regional climate responses. I have several concerns that I would like the authors to address.

1. The Introduction could be better structured to more clearly articulate the motivation for using a simplified climate model to investigate the impacts of regional aerosol emissions. Given the extensive body of literature on aerosol-driven responses in the Asian monsoon region, the referenced studies cloud be organized to highlight the value of using a simplified model and specifically using observed AOD over the past two decades as forcing. However, the aerosol forcing used requires further clarification (see point 2 below).
2. The description of experimental design is confusing. Some information needs clarification. 
   • The method of “adding” a single aerosol species is not well explained. Is the prescribed AOD distribution from reanalysis data considered the “added” aerosol forcing? Is monthly mean AOD from reanalysis repeated each year in the experiment? Is there a seasonal cycle of AOD in the experiments that could influence the seasonal response to BC? A clearer description of the regional AOD used, along with a figure showing its spatial distribution and trends, would be helpful.
   • Lines 180–187 mention aerosol-radiation interactions (ARI) versus aerosol-cloud interactions (ACI), while line 171 refers to the inclusion of the semi-direct radiative effect. Which of these radiative effects are actually included in the experiments in this work? Moreover, described experiments aren’t directly analyzed or discussed in this work.
   • The parameterization discussed in lines 173–178 and does not appear to be applied in the current study. If this is the case, why is it included?
3. There are substantial differences between the response and patterns in the energy analysis based on SyRAP-FORTE2 BC_CHI+IND simulations and those in PDRMIP models. In PDRMIP, aerosol emissions are artificially amplified, however, responses in SyRAP-FORTE2 have a similar magnitude to those from PDRMIP experiments, for example, δQ in GISS-E2-R. Additionally, the radiative effects included across PDRMIP models vary.  Given these discrepancies in forcing magnitude, model configuration, and included radiative effects, I question the robustness of the conclusion that “the results of these models are overall consistent qualitatively".