This study performs cloud feedback experiments using the fully coupled CESM2.1.3 model. By enhancing the sensitivity of low clouds to SST perturbations in the eastern Pacific subsidence regions and comparing them to control simulations, the authors isolate the effects of local low cloud-SST feedbacks in simulations of climate variability and change. The main findings are that the enhanced regional low cloud feedback strength results in: (i) increased SST variability in the eastern tropical and subtropical Pacific, (ii) slightly higher climate sensitivity, and (iii) a weakened east-west tropical Pacific SST gradient and Walker Circulation under 4xCO2.

The study is of high scientific quality, and the paper is generally well written. The most novel and impactful findings relate to tropical SST pattern and atmospheric circulation changes in the future climate, particularly the significant weakening of the Walker Circulation (finding iii). Findings (i) and (ii), while interesting, align with prior studies (e.g., Bellomo et al. 2014, 2015; Brown et al. 2016; Burgman et al. 2017; Loeb et al. 2018; Middlemas et al. 2019; Miyamoto et al. 2023; Myers et al. 2018a,b, 2021; Yang et al. 2023; Zhu et al. 2020). Given this, the authors could strengthen the paper by further contextualizing these results within previous work and clarifying how their experimental setup offers new insights. One distinguishing feature is the separation of fast and slow responses, which the authors might emphasize more. Additionally, a deeper analysis of finding (iii) would be valuable, given the uncertainty surrounding future tropical SST patterns and circulation changes. Implementing these suggestions, along with the specific points below, would improve the paper’s clarity and impact.

Specific Comments:

1. Introduction: The claim that cloud feedback has been studied primarily in terms of its impact on global-mean temperature change (lines 15–17) is somewhat misleading. While global implications have been extensively analyzed, many studies have also investigated regional climate impacts, particularly in the context of internal variability. A broader discussion of previous work in this area would provide better context.

2. Data and Methods: While the low cloud sensitivity to SST anomalies is computed following Ceppi’s approach, additional explanation in the paper would improve clarity. Moreover, since a low cloud cover anomaly proportional to the instantaneous SST anomaly is applied at every radiation time step, this will likely influence sensitivities to other cloud-controlling factors correlated with SST, as seen in Fig. A2a. While these changes appear minor, explicitly noting this effect in the paper would be beneficial.

3. Section 3.2: The paragraph beginning on line 113 discussing cloud feedbacks is somewhat unclear. Explicitly quantifying cloud feedback values in different experiments would allow for more precise comparisons. Additionally, the CRE anomalies with temperature in Fig. A4b are difficult to interpret. Given that CESM2 has a large positive cloud feedback (as quantified by Zelinka et al. 2020 and others), shouldn’t the dCRE/dT slopes be positive overall, not just for the slow responses? Including spatial maps of cloud feedback and low cloud changes would greatly enhance the analysis, making it easier to interpret the influence of enhanced cloud-SST sensitivity on future climate changes.

4. Walker Circulation Slowdown: The amplified Walker Circulation weakening in the 4xCO2 experiments is particularly interesting and warrants further investigation. Why is the change so large? Beyond the enhanced warming in the eastern tropical Pacific, could a reduction in LW radiative cooling at the cloud tops (as stratocumulus clouds decrease) contribute to the decreased SLP in that region? A deeper exploration of this and other possible mechanisms would strengthen the analysis.

5. Section 3.3 - Cloud Feedback Decomposition: The proposed decomposition is an interesting approach, but it lacks a quantification of which cloud-controlling factors drive future cloud changes. Why was this not included? In equation (7), what is the relative contribution of changes in cloud-controlling factors other than SST to the pattern-mediated response? Additionally, equation (4) may need adjustment: since the additional 3% reduction in low cloud cover per unit SST increase modifies dC/dYi for other factors correlated with SST, equation (4) should instead use (dC/dYi)_mod. Writing this as dC/dYi + δi, where δi represents the difference between modified and original sensitivities, would ensure accuracy in the derivations.

Specific Questions and Technical Notes:

a) Lines 43-44: Provide a reference or additional justification for the statement regarding CESM sensitivities.

b) Lines 124-126: The discussion on remote "pattern effects" could be clarified with more explicit details.

c) Line 175: Explain explicitly how this quantity is obtained as an output from the model runs.

d) Lines 189-190: Are these ratios to be interpreted as the fraction of the total response driven purely by pattern-mediated changes?  Please provide an explanation of the 0.37 and 0.16 values provided.

e) Lines 216-217: The difference in bias between low cloud cover and CRE sensitivities might also have a contribution from low cloud optical depth. A discussion of this possibility would improve interpretation.

f) Line 229: Do the authors mean strong cooling in those outlier models?  There could be a sign error here.

Conclusion:

Overall, this paper presents a well-executed set of experiments that offer valuable insights into cloud feedbacks and climate variability. To strengthen the impact of their findings, the authors should emphasize the novel aspects of their approach (e.g., separation of fast and slow responses) and provide additional discussion on key mechanisms, particularly for Walker Circulation weakening. Clarifying the cloud feedback decomposition and further contextualizing findings (i) and (ii) within existing literature will make the study more compelling. With these revisions, the paper would be a strong contribution to the field.

References (not already cited)

Bellomo, K., Clement, A. C., Mauritsen, T., Rädel, G., & Stevens, B. (2015). The influence of cloud feedbacks on equatorial Atlantic variability. Journal of Climate, 28(7), 2725-2744.

Burgman, R. J., Kirtman, B. P., Clement, A. C., & Vazquez, H. (2017). Model evidence for low‐level cloud feedback driving persistent changes in atmospheric circulation and regional hydroclimate. Geophysical Research Letters, 44(1), 428-437.

Loeb, N. G., Thorsen, T. J., Norris, J. R., Wang, H., & Su, W. (2018). Changes in Earth’s energy budget during and after the “pause” in global warming: An observational perspective. Climate, 6(3), 62.

Middlemas, E., Clement, A., & Medeiros, B. (2019). Contributions of atmospheric and oceanic feedbacks to subtropical northeastern sea surface temperature variability. Climate Dynamics, 53(11), 6877-6890.

Miyamoto, A., Nakamura, H., Xie, S. P., Miyasaka, T., & Kosaka, Y. (2023). Radiative impacts of Californian marine low clouds on North Pacific climate in a global climate model. Journal of Climate, 36(24), 8443-8459.

Myers, T. A., Mechoso, C. R., & DeFlorio, M. J. (2018a). Coupling between marine boundary layer clouds and summer-to-summer sea surface temperature variability over the North Atlantic and Pacific. Climate Dynamics, 50, 955-969.

Myers, T. A., Mechoso, C. R., Cesana, G. V., DeFlorio, M. J., & Waliser, D. E. (2018b). Cloud feedback key to marine heatwave off Baja California. Geophysical Research Letters, 45(9), 4345-4352.

Yang, L., Xie, S. P., Shen, S. S., Liu, J. W., & Hwang, Y. T. (2023). Low cloud–SST feedback over the subtropical northeast Pacific and the remote effect on ENSO variability. Journal of Climate, 36(2), 441-452.

Zhu, J., & Poulsen, C. J. (2020). On the increase of climate sensitivity and cloud feedback with warming in the community atmosphere models. Geophysical Research Letters, 47(18), e2020GL089143.

Rädel, Gaby, et al. "Amplification of El Niño by cloud longwave coupling to atmospheric circulation." Nature Geoscience 9.2 (2016): 106-110.