This manuscript investigates the drivers of recent seasonal precipitation increases over Central Asia, focusing on differences between winter and summer. By combining PDRMIP idealised single-forcing experiments with CMIP6 historical and future simulations, the authors argue that greenhouse gases dominate winter precipitation increases via thermodynamic moisture enhancement, while anthropogenic aerosols, especially Asian sulfate, dominate summer wetting through circulation adjustments.

The topic is relevant to ACP as it sits at the interface of aerosol forcing, circulation dynamics, and hydroclimate change. The manuscript is generally well written, clearly structured, and supported by a substantial body of previous literature. The use of PDRMIP sensitivity experiments is appropriate and it is useful to isolate mechanisms, while the link to CMIP6 past and future experiments improve the context and perspectives.

However, several conceptual and methodological limitations weaken the conclusions. I recommend acceptance after satisfactorily addressing these comments.

• The Interpretation of PDRMIP aerosol perturbations and relevance to real world trends is somewhat overstated. The PDRMIP experiments are intentionally idealised, but the manuscript at times over-interprets these sensitivity experiments as direct analogues of historical forcing and what shown in Fig 1 in terms of observational changes.

For example, the relative importance of sulfate versus BC in recent decades depends strongly on regional emission trends, which have evolved non-uniformly (e.g., post-2010 reductions over China and increases over South Asia). Although the authors acknowledge these limitations briefly in the discussion, the main text and conclusions should be more explicit that PDRMIP results indicate sensitivities rather than quantitative attribution, and that the inferred role of aerosol forcing does not imply a one-to-one explanation of the observed trend. Along these lines, I wonder whether the authors should first show the analysis of CMIP historical experiments, and then use PDRMIP to corroborate the CMIP6 results.

I am also wondering: other regions, Europe in particular, may also play a role. I suggest the authors to consider also the 5x global sulfate experiment, and possibly also the European emissions only.

• The manuscript attributes much of the observed precipitation increase to anthropogenic forcing, supported by DAMIP hist-aer simulations. However, studies examining for example broad-scale Asian precipitation changes have shown that it is strongly influenced by internal variability (e.g., Atlantic multidecadal variability). In this regard, the relatively short period (1979–2014) poses some challenges to separate forced signals from low-frequency internal variability, and thus to attribute observed trends with marked certainty. Also, CMIP6 multi-model means are known to underestimate internal variability, which the authors note, but the implications are not fully explored. Finally, no explicit attempt is made to quantify how much of the observed trend could plausibly arise from internal variability alone.
• The proposed circulation mechanisms—southward or northward shifts of the westerly jet and associated changes in moisture transport—are physically plausible. However, in several places the manuscript relies on qualitative inference rather than quantitative diagnosis. For example, moisture transport pathways (e.g., from the Atlantic versus Indian Ocean) are discussed, but moisture budget or convergence are not presented.
• The winter precipitation increase is attributed almost entirely to thermodynamic moisture enhancement under global-scale forcing. While this is reasonable, the analysis risks being overly simplistic and based on limited diagnostics.
• The projected decline in summer precipitation under SSP scenarios is attributed primarily to reductions in Asian aerosol emissions. While this is plausible, it rests on assumptions that deserve clearer qualification and is somewhat speculative. SSP aerosol trajectories are known to underestimate recent emission reductions in China and may not capture future policy shifts accurately. Also, the relationship between aerosol reductions and circulation changes, concurrently with GHG changes, may be nonlinear. In view of this and similar considerations, it is hard to support the dominant role of aerosol changes in driving future precipitation variations
• The observational analysis would be much stronger if it were to incorporate a few other observational datasets (perhaps station-based) as well as some dynamical analyses, for example, based on ERA5.
• When comparing models across different experiments, the authors make use of different model ensembles across experiments. A recurring methodological issue in the manuscript is the use of different sets and numbers of models for different components of the analysis, including PDRMIP sensitivity experiments, CMIP6 historical simulations, DAMIP single-forcing runs, and future SSP projections. For example, differences between aerosol- and GHG-driven responses may partly reflect differences in model composition, not just differences in forcing. While the models used in PDRMIP are necessarily different from those in DAMIP, I recommend at least using the same models across different experiments of the same type (e.g., across the PDRMIP experiments, and within DAMIP) to avoid potential inconsistencies.
• The manuscript focuses primarily on the period 1979–2014 to diagnose and attribute seasonal precipitation changes over Central Asia. While this choice is understandable given data availability, the analysis is not sufficiently placed in the context of longer time series, which limits confidence in the attribution of observed trends. Regional precipitation trends over Central Asia are known to be highly sensitive to the start and end years, owing to strong decadal variability. The manuscript does not demonstrate whether the diagnosed trends are robust across alternative periods (e.g., 1950–2014, 1979–2020, or sliding windows), or whether the selected period coincides with a particular phase of internal variability. Without this context, it is difficult to assess whether the observed increase represents a real long-term forced signal or a transient (internal) fluctuation. There is also some inconsistency in the interpretation between historical and future changes as future trends are diagnosed over a longer period. I recommend for example to show time series extending back to the mid-20th century.
• A key result of the manuscript is the agreement between observations and model-simulated precipitation changes within the defined Central Asia analysis box, particularly in summer. However, this agreement appears to weaken substantially in the surrounding regions in some plots, raising concerns about the spatial robustness of the signal. The proposed mechanisms involve large-scale circulation adjustments (e.g., jet shifts and moisture transport changes), which should manifest as spatially coherent precipitation anomalies extending beyond the analysis box. While obviously we cannot expect models to capture the precipitation pattern across the entire Asian domain perfectly, the lack of consistent signals in neighbouring regions makes it difficult to reconcile the spatial pattern with the proposed dynamics. This also when accounting for the fact that the signal is not generated by local forcing but somewhat remote to the domain (South or East Asian aerosols). Strong claims that aerosols “dominate” summer precipitation changes may not be fully justified if the signal lacks broader spatial coherence.

Minor comments

The manuscript is generally clear but somewhat long; some repetition could be reduced, particularly in Sections 3.2 and 4.

Statistical significance is assessed mostly using a comparison with the standard deviation. It is not clear whether this is a standard t-test or the standard deviation refers to something else.

L27: “these sensitivity results that GHG forcing”. Something is not correct here.

Review’s comments for the manuscript egusphere-2025-5729, entitled “Distinct drivers of recent seasonal precipitation increase over Central Asia: roles of anthropogenic aerosols and greenhouse gases"

General comments

By using single-forcing experiments from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), this study investigates drivers and physical mechanisms of wetting trend over Central Asia in recent decades. Results show that greenhouse gas (GHG) forcing mainly increases winter precipitation by enhancing atmospheric moisture content through warming. In contrast, in summer, Asian sulfate aerosols enhance precipitation by modulating the westerly jet, which strengthens atmospheric moisture transport into the region. These conclusions are supported by CMIP6 model simulations. Future CMIP6 projections suggest that under moderate- to high-emission scenarios, winter precipitation will continue to rise due to increasing GHG concentrations, while summer precipitation may decline across much of Central Asia as a result of reduced aerosol emissions following Asian clean air policies. Results are interesting and they are well presented in the study. However, the paper needs some clarifications by addressing the following specific comments. Therefore, the paper is acceptable for publication after minor revisions.

Specific comments

1. Lines 63. “a meridional shift of the Asian subtropical westerly jet”. This is aerosol induced change in summer. Please clarify that it is in summer.
2. Lines 136-137. Please see my comment on Fig. 1b. It is not clear how authors construct the PDF.
3. 1b caption is clear. Please add more information to understand it.
4. 2 caption. Clarify what bars represent. Are they multimodel means?
5. 3. The reviewer thinks that various panels show the multimodel mean changes. Please state in the figure caption.
6. 5. Please add the zonal wind climatology in panels (b, c, e, and f) for readers to better understand wind changes.
7. 6. The reviewer thinks that bars in various simulations show multimodel mean trends. Please add clarification.
8. 9 caption. Please add more information in figure caption to help reader to understand it (e.g., full lines in panel a-c and e-f, vertical lines in panel d and h).

This work uses PDRMIP to investigate the impact of individual forcers on Central Asia (CA) precipitation. The authors found that greenhouse gases (GHGs) were the dominant driver of the wintertime precipitation response, while the summertime precipitation response was attributed to anthropogenic aerosols (AAs). AAs led to a regional northward shift of the westerly jet, resulting in a net increase of moisture inflow into CA. CMIP6 DAMIP simulations were then used to evaluate the cause of historical CA precipitation changes, and the corresponding conclusions were consistent with results obtained from PDRMIP. This work is clear and well-presented. However, I recommend the authors address the following questions:

1. This work would benefit from discussing the nonlinearity between different forcers, since the authors intend to attribute historical CA precipitation. PDRMIP simulations are an idealized tool that allows for a clean assessment of mechanisms, but previous work (e.g., Deng et al., 2020; Herbert et al., 2021) has shown the impact of nonlinearity among different forcers on regional precipitation.
2. In Section 3.3, the SSP scenarios include projected GHG and AA emissions. The response should be the result of the impact from both GHGs and AAs. The authors should be careful when stating the mechanism, such as in lines 285-290: “... the magnitude of these increasing trends is strongly dependent on the GHG emission levels...”.
3. The curves and dots in Figure 6 would benefit from an explanation of the estimation method. The authors did not discuss these results in detail.

Herbert, R., Wilcox, L. J., Joshi, M., Highwood, E., & Frame, D. (2021). Nonlinear response of Asian summer monsoon precipitation to emission reductions in South and East Asia. Environmental Research Letters, 17(1), 014005. https://doi.org/10.1088/1748-9326/ac3b19.

Deng, J., Dai, A., & Xu, H. (2020). Nonlinear climate responses to increasing CO2 and anthropogenic aerosols simulated by CESM1. Journal of Climate, 33(1), 281–301. https://doi.org/10.1175/JCLI-D-19-0195.1.