The authors present a comprehensive analysis of regional climate signals in the overshoot scenarios SSP5-34OS and SSP1-19. The study provides valuable insights about overshoot implications and is surely of interest for a wider audience. The scope of the presented study is very similar with Pfleiderer et al. 2024 and, as the authors write in their discussion, many of the findings are consistent. Due to different methodological choices, the results of this study are still very relevant and definitely worth publishing. It would, however, be useful to discuss the methodological differences between the two studies and implications in more detail.

The study is well written and I would suggest publication after some clarifications and potential changes in the framing.

The authors have chosen to work with ensemble means which is a common approach but has some subtle implications when studying overshoot scenarios. Most importantly, different climate models reach peak warming in different years (fig A1) and in the same way, the periods when GMT stabilizes and the respective period before peak warming differs between climate models. Therefore, some of the signal seen in fig 5, 6 (...) might be influenced by considerably different GMT levels. Example: UK-model is considerably warmer in 2090 as compared to 2030 (see fig A1.). The meaning and interpretation of "ensemble mean" becomes a bit complicated in this case as many different effects (regional hysteresis, differences in GMT trajectories, ...) will be merged in one number. It would be important to discuss these effects and if possible estimate how important they are in comparison.

Besides these technical implications of focusing on the ensemble mean, it is questionable whether ensemble mean differences are useful to inform potential risks. As Pfleiderer et al. 2024 shows (also visible in the appendix of the manuscript) the regional response differs considerably between climate models. Going into the details of model differences might be beyond the scope of this paper, but the authors could consider to show one exemplary regional difference between two models to highlight uncertainty when it comes to overshoot scenarios. In my opinion the uncertainty of climate projections in a cooling climate deserve some special attention as there is no observational data with a forced cooling trend to compare with.

Last comment on the ensemble mean: is there a reason you don't use the ensemble median? I would find the ensemble median more appropriate as it does not give additional weight to single models with strong reactions. I would suggest to check the sensitivity to the choice of ensemble mean / ensemble median and briefly discuss this.

The authors do not mention potential effects of aerosol reductions. On a regional level, changes in aerosol emissions can considerably influence precipitation and temperature. In SSP5-34OS and SSP1-19, besides changes in GHG, aerosol emissions change and some of the regional changes around peak warming might be influenced by aerosols. The authors should at least discuss this caveat/feature of the analyzed scenarios and it's implications on the findings. 

Specific comments:

Stippling in all figures: Is this a test performed on the ensemble mean? If yes, it would also be interesting to show model agreement. 

L72-73: Pfleiderer et al. 2024 focuses on exactly that question.

Fig 1: Why is there no brown line in the bottom of panel a & c?

L95-102: Just out of interest: do you have these extreme indices for all the models and runs listed in table 1? From my experience, daily data that is required for the computation of these indices is not (easily?) available for all simulations for which monthly tas and pr exists.

L103-107: I would expect that all the results would be quite sensitive to the choice of this period. Therefore, some sensitivity testing and some more discussion of the implications of different GMT levels between pre-overshoot period and the stabilization period would be helpful.  

L141-149: For the comparison of the two scenarios, it would be useful to merge fig. 2 and fig. 3. Since the GMT trajectory differs between the two scenarios, it is a bit unclear what conclusions can be drawn from the comparison of the two scenarios when fixed periods are used (as you also show in fig 4).

Fig 4: "obtained as the year after the maximum in which temperature reaches the same value as in the period 2290-2300" -> what is the tolerance for the temperature differences? And are you comparing 20-year periods with the 10-year period at the end (2290-2300)? I think that for this comparison, the period should have the same length. Similar question for e) and f): are you comparing single years, or 20-year periods?

L175-177: How do you interpret that the ITCZ shift is lower in SSP1-19 but precipitation differences are higher?

L193-195: Does the word "being" belong here?

L199-201: Although the slope looks similar, there is a different TXx - GMT relationship after the overshoot. At the same GMT level after the overshoot one would expect a lower TXx value in EN, right?

L251-253: Again, I'm not sure if I would agree. Isn't this statement contradicting L234-236?

The paper analyzes the response of surface air temperature and precipitation under two CMIP6 overshoot scenarios. The authors focus on mean and extreme changes of them. It would be a very interesting contribution to understanding how the climate system changes under the overshooting scenarios. I support publication, but some parts should be revised to publish in ESD. Please find the comments below:

Comments:

- Title: The current title is vague and does not effectively convey the actual content of the result. First of all, ‘asymmetries’ can have dual meanings without knowing the actual content of the paper. It can mean either asymmetry between global warming and cooling periods or between the Northern and Southern Hemisphere. Therefore, somehow, the title must be changed. The ‘..linked to large-scale temperature asymmetries’ part emphasizes the mechanistic part of the result, but I suggest removing it because the paper does not deeply dive into the mechanistic analysis (roughly done though) and not the major novel part. My suggestions are, for example:

‘Hysteresis of mean and extreme surface temperature and precipitation in the CMIP6 overshoot scenario’, ‘Response of mean and extreme surface temperature and precipitation in the CMIP6 overshoot scenario’, ‘Regional irreversibility of mean and extreme surface temperature and precipitation in the CMIP6 overshoot scenario’.

- Differentiate hysteresis and reversibility & Clear definition of reversibility: The author clearly defines what hysteresis is in the introduction part of the paper. I appreciate it. However, the irreversibility should be clearly defined as quantitative as possible. For example, how the reference period is set when we say the climate variable is irreversible? Putting a clear definition of it would be very helpful.

- The term ‘non-reversibility’: The author uses ‘non-reversibility’ not ‘irreversibility’ throughout the paper. English-wise sense both make sense, but the later one is much more used in the literature and much more standard term than the first one. I am wondering why the authors decided to choose this unpopular term. Is there any specific reason for it? I suggest changing the term to ‘irreversibility’ if there is no specific reason for it.

- There are multiple simulations within the same model with the same model forcing scenario. For example, Table 1 shows that CanESM5 has 50 simulations for the SSP1-1.9 scenario. I assume that they’re an ensemble with different initial conditions, but not sure and puzzling. Please clarify this information. The paper must include which ensemble member is used for the analysis.

- Additional analysis for ITCZ and AMOC: An additional time series plot for ITCZ position (i.e., plot for ITCZ position-time) would be very helpful for understanding the results. I also suggest performing additional analysis for AMOC strength which has a very important role in shaping hysteresis.

- To calculate the extreme indices (e.g., Rx1day), a baseline climatology value should be chosen. Under the changing climate, the way of defining this baseline climatology is very important (this is a reference for the Marine Heatwave case, but relevant to this case: https://www.nature.com/articles/d41586-023-00924-2). How did the author set the baseline climatology value for the extreme indices? This is very important for interpreting results, but not clearly explained.

- For the spatial pattern analysis (e.g., Figure 2 and 3), the author chose to do analysis within the continuously moving time frame with a 20-years period length, and not compared with the anomaly from the fixed preindustrial period as shown in Fig. 1. This hinders consistent comparison between the spatially averaged results and spatially-resolved results. Is there any specific reason to take such an analysis scheme?

- Abstract & Conclusion: The paper contains a lot of results with a large number of figures. Therefore, it is important to concisely & systematically organize the result in the paper, in particular in the abstract and conclusion section The current abstract and conclusion part requires heavy revision in this sense. I suggest reframing the abstract and conclusion part following the structure below:

‘How the global mean/extreme surface air temperature and precipitation change’

‘How do the regional mean/extreme surface air temperature and precipitation change, in particular, which part of the region shows the strong and weak reversibility under the overshooting scenario?’

‘Mechanistic insights into why such changes happen – role of ITCZ (and AMOC; optionally).’

‘Discussion on decoupling between regional and global average response’.

- More systematic analysis: The paper mainly merits showing the response of two key climate variables, surface temperature and precipitation under the overshooting scenarios. Mechanistic analysis part is not as novel as the main results. It is really good and would be very helpful for the community and also for the general public. However, the current analysis of the paper lacks the systematic. The ideal arrangement of the paper is:

1. Changes in mean surface temperature (global-average & regional pattern)
2. Changes in extreme surface temperature (global average & regional pattern)
3. Changes in mean precipitation (global-average & regional pattern)
4. Changes in extreme precipitation (global-average & regional pattern)

Providing this information systematically would be ‘very’ beneficial. Some parts are missing and require additional analysis. Also, the paper requires some rearrangement of the result sections (for example, figure B1, B2, B3 are very useful and can be placed in the main figure). I assume that the author intended to emphasize some specific point of their main results, but plainly providing the above information is already okay and novel. I strongly suggest considering this suggestion.