Dear Editor of Climate ot the Past,

I went through the manuscript by Cauquoin et al. titled "Effects of LGM sea surface temperature and sea ice extent on the isotope-temperature slope at polar ice core sites". The study investigates how SST and sea ice cover have an impact on the spatio-temporal variability of the δ¹⁸O vs T slope for Greenland and Antarctica precipitation between LGM and preindustrial climate. The authors used the ECHAM6-wiso model forced with different buondary conditions to test the impact of reconstructed and modeled SST/sea ice cover on simulation output. The key result of the work is that δ¹⁸O vs T slope is modulated by combination of both forcing (SST and sea ice, plus AMOC for Greenland) with different weights that depend on geographical location. The authors also highlight the importance of using reconstructed sea surface boundary conditions instead of using coupled models output and specifically the needing of sea ice cover reconstruction for LGM period.

General comment

This work provides an important piece of information to the isotope - glaciology community, because it shows that (1) SST and sea ice conditions over source regions of precipitation have an impact on the reconstructed temperatures using stable isotopes in ice cores and (2) the impact on the isotope-temperature temporal slope is location-dependent over the two continens. In this context, Figure 11 clearly show where such driving forces affect more the slope and  the δ¹⁸O of precipitation. In my opinion, the manuscript is highly relevant for CP audience, is well written, and is easy to read. Therefore, I strongly support the manuscript for publication and I have only minor-technical comments reported hereafter:

L225-227 and Figure 4. A  metric to evaluate the agreement could be useful (e.g. correlatation or RMSE), similar to the metrics reported in table 3 for the slope.

L235 This sentence is a bit vague. Are the authors referring to the spatial-temporal distribution of $\Delta_{LGM}-PI\delta^{18}O_{P}$ ? Or is this a "general" sentence? In that case, I would replace the word distribution with fractionation.

L363 The scientific question guiding section 4 is very clear and it should be also posed in the introduction.

Cauquoin et al. present a series of LGM simulations using the ECHAM6-wiso isotope-enabled atmosphere GCM, and use these to investigate the influence of SST, sea ice extent, and AMOC on the LGM isotopic depletion and isotope-temperature slopes in Greenland and Antarctica. While the work appears to be free from major technical errors, the reader unfortunately does not learn much from the lengthy study beyond what is known from earlier work – other than perhaps the fact that isotopic slopes are complicated. This is mostly due to an experimental design that is not ideal to discern the effects that the authors seek to study. Another problem is the interpretation of the, data that focuses mostly on lengthy anecdotal descriptions of the simulation outcomes rather than an analysis of underlying dynamics.

Since it is too late to adjust the experimental design, it seems the paper should probably be published. However, I would request the authors consider the changes suggested below.

Major comments:

First I want to share my concerns with the experimental design. This design does not allow for easy or straightforward assessments of impacts of SST and SIC. The various forcing files used are pulled from independent sources, and therefore have strong spatial (and presumably seasonal) differences between them that complicate the interpretation. For example, the effect of SST is mostly found by comparing GLOMAP, Tierney et al., and MIROC. The differences between them have strong spatial patterns such that some parts of the Southern Ocean are colder in one, and other parts colder in the other. This makes the interpretation of the SST influence very complicated. It would have been much simpler had the authors decided for example to simply subtract or add 1 degree to the entire GLOMAP SST anomaly – or perhaps scale the anomaly by a constant value. The same holds for the sea ice concentrations, where simply applying SIC anomalies would have been much more insightful. Another downside of their approach is that the reader has to do a lot of work to understand the manuscript, which is dense with acronyms. Is the GLOMAP SST colder than the MIROC_4m_strong_AMOC, and in which parts of the ocean? Which of the three SIC files is most extensive? The manuscript shows and explains this, but the average reader will not be able to keep all these facts straight in their minds while reading the manuscript and interpreting the figures. I found myself having to go back and forth all the time to understand what is being discussed which adds a lot of reading time to already (unnecessarily) long paper.

The authors use an incorrect metric of temperature in all their slope analyses. They use the precipitation-weighted T2m temperature (line 367). The long-standing standard in the literature is to use the annual mean temperature in estimating isotope slopes, in part because the precipitation-weighted temperature is never known in observational situations. For example, the spatial slope of 0.8 permil/K that the authors cite and compare to is based on mean-annual temperatures (Masson-Delmotte et al., 2008). It is widely understood that the small temporal isotope slopes in Greenland of around 0.3-0.4 permil/K are due to a change in precipitation seasonality, which is not expected in Antarctica. The metric by the authors would not reflect this difference. The temporal slopes the authors present can therefore not be meaningfully compared to values found elsewhere in the literature. While others have used precipitation-weighted temperature (besides mean annual) as part of an analysis to understand isotope dynamics, it should not be used as the only estimate.

The manuscript is much too long, I believe. While CP does not have page limits, the readers (and reviewers!) would appreciate a much more concise manuscript. The lengthy descriptions of observations can be shortened, as the readers can glean the same from the figures.  

The authors should perform more meaningful model-data comparison. Currently they only compare the change in d18O. For both Greenland and Antarctica empirical temperature reconstructions exist from e.g. borehole reconstructions, which give direct estimates of past temperatures and the temporal isotopic slope. A model-data comparison of change in T and of temporal isotope slopes would be very insightful, and allow the reader to judge whether the model has skill. For the d18O model comparison the model appears to underestimate the d18O changes – this would imply that the simulated isotopic slopes are likely biased toward too small values, but this is not discussed or shown. Figure 10 shows no significant differences between isotopic temporal slopes in Greenland and Antarctica, while it is a well-established observational fact that temporal slopes in Greenland are smaller.

The authors seek to capture the influence of SIC and SST on isotopes at the various sites in their Fig. 11, but do not provide any insight into why the patterns are the way they are. Why does SIC impact coastal but not inland sites? Modern isotope-enabled models have a suite of tools to address such questions, such as for example moisture tagging. Can you provide more insight? Noone and Simmonds (2004) already provided a very thorough interpretation on the SIC impact on d18O, and I would expect a follow-up study to provide more or deeper insight - which is lacking here. There is no meaningful attempt to understand or analyze the atmospheric dynamics or moisture transport.

I think providing the reader with more understanding of the moisture sources of the various stations would be helpful for their understanding. It has long been known that low elevation/coastal cores derive more of their moisture form local nearby sources, whereas high-elevation cores receive their moisture from long-ranged transport (Sodemann & Stohl, 2009). Since sea ice impacts the regional waters around Antarctica, I would expect Antarctic sea ice to impact coastal stations and not inland ones, as the authors indeed find.

The authors state several times that the PMIP3 ice sheet would improve the d18O simulations relative to the GLAC-1D ice sheet. However, most glaciologists would agree that PMIP3 is not the most realistic ice sheet (its elevation is much too high in the interior), and instead prefer GLAC-1D or ICE-6G. The PMIP3 ice sheet would lead to stronger Antarctic cooling via the higher elevation, and thereby deplete the isotopes and improve the ECHAM6-wiso fit to d18O observations. Do you think the PMIP3 ice sheet improves realism, or simply compensates for a model bias through anomalously high interior elevation? Please elaborate on your thinking.

Figure 8: Why is there such strong spatial variability in the isotopic slopes on such small spatial scales? Is this a model artifact? Would this go away with averaging over longer timescales? The ice core d18O observations are very consistent between cores, and temperature is likely to be homogeneous also.

It is unclear what the implications of the work are for others working in the field. Do the authors have any recommendations for the future interpretation of water isotopes?

Line-by-line comments:

Line 22: what are “mixed effects”?

Section 2: somewhere you should explain what AMIP is.

Section 2.2: Can you also specify the PI conditions you use?

Line 123: These simulations with different AMOC values are therefore not in equilibrium, correct?

Line 127: What does this mean: “selected in the middle of the AMOC peak”?

Line 155: Can you use SST and SIC reconstructions that are not self-consistent? Are there risks, such as warm temps under sea ice or freezing SST conditions without sea ice?

Table 1: It would be more clear in the last column to state “Less SST cooling” and “more SST cooling”

Figure 3: why not add the South Pole ice core? Data are publicly available.

Line 246: You could consider removing the LGM-PI subscript. You compare the same periods throughout the paper, so it’s unnecessary to specify all the time. It would improve readability.

 Table 2: could you add the simulated range of d18O?

Line 221-222: “due to lower temperatures”. Is this cause something you assume to be true, or tested somehow? Please specify

Fig 4b: instead of plotting the change in P, would it make sense to plot the ratio (P_LGM/P_PI)?

Fig. 4d: all data are in the upper left half. Do you have thoughts why?

Line 243: “strong cooling” – is this global, or just Arctic?

Line 270: Why do you think this improves the data? Is the ice more realistic, or does it compensate a model bias? I would suspect the latter

Line 340: I am surprised about the weak influence of the AMOC on Greenland climate. During DO events, Greenland warms by around 10 degrees during AMOC strengthening.

Line 367: You should not use precip-weighted temperatures. Almost the entire literature in this field reports mean annual.

Line 373: The 0.8 permil/K is regressed against mean annual temperatures, so you cannot compare to your valus

Line 384: these values (slope around 0.25 permil/K) suggest a bias in the model, no? If real, this would correspond to 24K of LGM cooling at EDC.

Fig. 8: Why are these maps so patchy?

Line 426: in *the* Greenland sea

Line 436: lead*s* to mixed results

Line 483-484: The lower… in this region. I don’t understand how you conclude this. I don’t see this from the analyses. Is this speculation or conclusion?

Line 498-499: What is meant by the middle of the AMOC peak? I don’t understand what is meant here.

Line 506: This comparison to other slopes is not meaningful, as you don’t evaluate mean annual temperatures and those studies do

References

Masson-Delmotte, V., Hou, S., Ekaykin, A., Jouzel, J., Aristarain, A., Bernardo, R. T., et al. (2008). A Review of Antarctic Surface Snow Isotopic Composition: Observations, Atmospheric Circulation, and Isotopic Modeling. Journal of Climate, 21(13), 3359-3387. http://dx.doi.org/10.1175/2007JCLI2139.1

Noone, D., & Simmonds, I. (2004). Sea ice control of water isotope transport to Antarctica and implications for ice core interpretation. Journal of Geophysical Research: Atmospheres, 109(D7), D07105.

Sodemann, H., & Stohl, A. (2009). Asymmetries in the moisture origin of Antarctic precipitation. Geophysical Research Letters, 36(22), L22803. http://dx.doi.org/10.1029/2009GL040242