General comment

The paper of Extier et al. presents the implementation of ¹H²H¹⁶O and H₂¹⁷O in the intermediate complexity model iLOVECLIM. Until now, only δ¹⁸O values could be simulated by this model. A simulation under preindustrial (or present-day) conditions has been performed for 5000 model years. The modeled δ²H, δ¹⁷O, d-excess, and ¹⁷O-excess in precipitation and in ocean water are evaluated against different data compilations. Their seasonal variability is also (quickly) evaluated.

One of the problems with complex fully coupled Earth System Models (ESMs) is the computing cost and the required time to perform proper paleoclimate simulations. This is all the more true when it comes to simulating water isotopes and considering transient simulation like the Holocene for example or the last deglaciation for example. So, I think this paper is important because iLOVECLIM can be used for a large range of (snapshot or transient) paleoclimate periods, and now on a greater range of isotopic species (i.e., not only δ¹⁸O) used to reconstruct the past variations of climate.

I have however several major points that need to be addressed, related to the evaluation of the simulation, the ¹⁷O-excess results, and the introduction. After preparing my comments for the paper, I noticed that they were similar to those of the first reviewer.

Major comments

• As I said in the introduction, one major problem of the complex ESMs is the computing time. From this perspective, iLOVECLIM is very useful for paleoclimate simulations. The drawback of this model is the rough spatial and time (?) resolutions. I think this aspect of iLOVECLIM should be more emphasized in the introduction. Still for the introduction, this is in my knowledge the first time that ¹⁷O-excess is modeled in a coupled atmosphere-ocean model. Until now, only the atmospheric model LMDZ-iso was able to simulate the H₂¹⁷O isotopologue (Risi et al., 2013). This should be clearly stated in the abstract and the introduction.
• Still for the introduction, for which kind of paleoclimate applications ¹⁷O-excess is useful? More generally, a paragraph of the introduction should be a review of the paleoclimate studies (recent if possible) using of d-excess or ¹⁷O-excess. For d-excess, such recent studies exist like Landais et al. (2021). For ¹⁷O-excess, I do not see to be honest as the measurements can be challenging. However, the author should try to explain how the ¹⁷O-excess can be used, not only by just saying that it is proxy of the relative humidity over the ocean. This kind of context information is necessary because simulating d-excess and ¹⁷O-excess is very challenging.
• I expect to use this kind of models for diverse paleoclimate applications. But which ones are really possible with a reasonable confidence? Before really reading the paper, I thought it would have been great to not only simulate pre-industrial conditions but also another climate period further in the past. As it is not the case, I recommend to the authors to do a deeper evaluation of their simulation against present-day observations with more skill metrics like r² and root mean square errors, and a comparison of these metrics with the ones from other general circulation models (GCMs) when available. Moreover, the authors should show more clearly if the well-known isotope continental effect and the amount effect are well represented in iLOVECLIM, in comparison to observations and other isotope enabled GCMs (like they did for the latitudinal effect). Last but not least, the disagreement between model results and observations is explained by uncertainties in the latter several times in the manuscript (e.g., l. 264-265, 289-291, 272-273, 310, 320-321, 443-445). I think these are not very honest statements. Instead, I would formulate a more quantitative model-data comparison, which would help the readers to know for which paleoclimate applications and isotope effects iLOVECLIM can be used. In this regard, the figures 4, 5, 6 and maybe 7 need to be changed or adapted.
• As already reported by the first reviewer, the fractionation for evapotranspiration is not supposed be at the equilibrium. Or there is no fractionation, like in MPI-ESM-wiso, or a fractionation using a bulk formula is used for the bare soil evaporation (i.e., kinetic, see the equation 6 from Haese et al., 2013). The simplest way is to perform another simulation without such fractionation in order to see the impact of your equation 10 and hopefully to improve the modeled results. Just an extension of a couple of hundred simulations should be enough, I guess.
• Before reading in detail the paper, I have been astonished by the very high and low values of ¹⁷O-excess, as well as their variations from one grid cell to another, in Figure 1. This is especially the case in Antarctica. As these are averages of several years, I guess these jumps are even worse from one year to another or at monthly scale. Honestly, I am worried by these huge variations. It is completely fine to not be able to represent very well the ¹⁷O-excess in such models because it is an extremely hard task. If the authors cannot fix this issue, I would expect honest suppositions on the causes of the failure of iLOVECLIM in simulating ¹⁷O-excess, instead of pseudo-explanations related to the uncertainties of the observations only. In addition, I suggest deleting all references and plots related to δ¹⁷O. δ¹⁷O is not really used in the literature and does not bring any new information compared to δ²H (the spatial characteristics are similar for example). The important proxy here is ¹⁷O-excess.

Minor comments

• Title: I would change the title a little bit because the novelty here is to model ¹H²H¹⁶O and H₂¹⁷O, not the ¹⁸O. Moreover, iLOVECLIM models the isotopologues (i.e., molecules), not the atoms of hydrogen and oxygen.
• l. 14-15: is the simulation really under preindustrial conditions as the orbital year considered is 1950 and not 1850?
• l. 24: “Stable water isotopologues (H₂¹⁶O, H₂¹⁸O, ¹H²H¹⁶O, H₂¹⁷O), expressed hereafter in the usual d notation with respect to V-SMOW scale (Dansgaard, 1964), are important…”
• l. 29: The term “however” sounds strange here.
• l. 53: not so new method.
• l. 61: same as above, the studies are not so recent. So, remove the term “More recently”.
• l. 65: A paragraph could be written about the use of d-excess and ¹⁷O-excess for paleoclimate studies. See major comment.
• l. 99-100: the authors say they present the equations for deuterium only, but then the equations of ¹⁷O are shown latter in the manuscript (equations 7 and 9). I would say instead that you introduce the equations for the heavy/light isotope ratios.
• Equation 4 is from Craig and Gorgon (1965).
• Section 2.3: please add the time steps of the atmosphere and ocean modules. Also, do all the results come from the 100-years simulation starting from the 5000-year spin-up simulation?
• Section 2.4: I would also mention the results from other isotope enabled GCMs here or in a new subsection just after. In the former case, please rename the section appropriately.
• l. 177 and many others: I do not understand the reference IAEA, 2006. All GNIP data should be mentioned with the reference IAEA, 2023.
• l. 181-182: why the authors did choose these stations, and not others like Vienna? What are the requirements (e.g., number of consecutive years with data)? How did they make the composite (I mean on which period or on how many years)?
• l. 190-191: You already said in the data section which dataset you will use for the evaluation of your results. You do not need to repeat here again.
• l. 193: Please rephrase “Differences with the observations are observed for specific regions.”.
• l. 204-205: I suppose these model results are from SWING2 database. Please add the reference (Risi et al., 2012) and state it clearly.
• l. 206: such as strong depletions over Antarctica?
• l. 208- 209: “Similarly to other GCMs, iLOVECLIM shows a small decrease of d2Hprecipitation and is in the higher range of the observed δ²H_{precipitation} values.”
• Sentence at l. 209-210: I do not understand this sentence and it should be removed.
• Figure 1 and all the other concerned figures: remove the δ¹⁷O, it’s not useful, I think.
• l. 231-232: please precise what could be these complex processes.
• Figure 3: is it really useful? I think this figure can be removed.
• l. 246-247: same comment as for l. 190-191.
• l. 253: you say that the model calculates mostly negative values with values ranging from -10 to 10 permil. It sounds a little bit strange, no?
• l. 264-265: see my main comment about a fair evaluation of your model results.
• l. 272-273: same comment.
• l. 289-291: same comment as for l. 190-191. Please explain the possible causes in terms of model biases.
• l. 307: H₂¹⁷O instead of ¹⁷O.
• l. 311-313: see major comment about a fair evaluation of the model.
• l. 320-321: same comment.
• Section 3.1.4: Why these stations in particular? I know that ¹⁷O-excess is not available in GNIP data (and it should be stated). Is there any data of ¹⁷O-excess in precipitation or in water vapor at seasonal resolution (at least) to evaluate iLOVECLIM? Moreover, the evaluation should be done in a fairer way (again). The uncertainties of the data alone do not explain the model-data disagreements.
• Section 3.2 should be re-organized a little bit for clarification. For example:

3.2 Isotopes in ocean water

3.2.1 Surface seawater

3.2.2 Vertical profiles

You can also make separate sub-sections for d-excess and ¹⁷O-excess. Moreover, even if there are no observations ¹⁷O-excess in deep ocean, I would expect to see the results from iLOVECLIM because this is one novelty of this model.

• l. 361-362: you should say that in the observation data section.
• l. 370-371: it should be in data section.
• l. 371 and 372: replace MPI-ESM by MPI-ESM-wiso. Do it also in the legend of the concerned figures.
• l. 387-388: It’s one explanation. Usually, very depleted δ¹⁸O or δ²H values in seawater in Artic area are explained by the very depleted river discharges. What about iLOVECLIM? If it is not modelled, it is one very plausible explanation for this bias.
• l. 406: I would say instead that model d2H values are lower than the observations by several permil.
• Section 3.2.3: Related to my comment for the section 3.2, the ¹⁷O-excess is very short.
• l. 434: “we presented the implementation of the ¹H²H¹⁶O and H₂¹⁷O isotopologues in the …”
• End of line 435: remove “also”.
• l. 439-440 and 443-445: see main comment about the evaluation of iLOVECLIM results.
• Figure A1: it should be in the main text.

References

Haese, B., Werner, M., and Lohmann, G.: Stable water isotopes in the coupled atmosphere–land surface model ECHAM5-JSBACH, Geosci. Model Dev., 6, 1463–1480, https://doi.org/10.5194/gmd-6-1463-2013, 2013.

Craig, H. and Gordon, L. I.: Deuterium and oxygen 18 variation in the ocean and marine atmosphere, in: Stable Isotopes in Oceanographic Studies and Paleotemperatures, edited by: Tongiogi, E., Consiglio nazionale delle richerche, Laboratorio de geologia nucleare, Spoleto, Italy, 9–130, 1965.

Dansgaard, W.: Stable isotopes in precipitation, Tellus, 16, 436– 468, https://doi.org/10.3402/tellusa.v16i4.8993, 1964.

Landais, A., Stenni, B., Masson-Delmotte, V. et al. Interglacial Antarctic–Southern Ocean climate decoupling due to moisture source area shifts. Nat. Geosci. 14, 918–923, https://doi.org/10.1038/s41561-021-00856-4, 2021.

Risi, C., Noone, D., Worden, J., Frankenberg, C., Stiller, G., Kiefer, M., Funke, B., Walker, K., Bernath, P., Schneider, M., Wunch, D., Sherlock, V., Deutscher, N., Griffith, D., Wennberg, P.O., Strong, K., Smale, D., Mahieu, E., Barthlott, S., Hase, F., García, O., Notholt, J., Wameke, T., Toon, G., Sayres, D., Bony, S., Lee, J., Brown, D., Uemura, R., and Sturm, C.: Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopologues: 1. Comparison between models and observations, J. Geophys. Res., 117, D05303, https://doi.org/10.1029/2011JD016621, 2012.

Risi, C., Landais, A., Winkler, R., and Vimeux, F.: Can we determine what controls the spatio-temporal distribution of d-excess and ¹⁷O-excess in precipitation using the LMDZ general circulation model?, Clim. Past, 9, 2173–2193, https://doi.org/10.5194/cp-9-2173-2013, 2013.