CO<sub>2</sub>- and orbitally- driven oxygen isotope variability in the Early Eocene

Campbell, Julia; Poulsen, Christopher J.; Zhu, Jiang; Tierney, Jessica E.; Keeler, Jeremy

doi:https://doi.org/10.5194/cp-2023-37

Preprints

https://doi.org/10.5194/cp-2023-37

Preprints

31 May 2023

| 31 May 2023

Status: this preprint is currently under review for the journal CP.

CO₂- and orbitally- driven oxygen isotope variability in the Early Eocene

Julia Campbell, Christopher J. Poulsen, Jiang Zhu, Jessica E. Tierney, and Jeremy Keeler

Abstract. Paleoclimate reconstructions of the Early Eocene provide important data constraints on the climate and hydrologic cycle under extreme warm conditions. Available terrestrial water isotope records have been primarily interpreted to signal an enhanced hydrologic cycle in the Early Eocene associated with large-scale warming induced by high atmospheric CO₂. However, orbital-scale variations in these isotope records have been difficult to quantify and largely overlooked, even though orbitally driven changes in solar irradiance can impact temperature and the hydrologic cycle. In this study, we fill this gap using water isotope-climate simulations to investigate the orbital sensitivity of Earth’s hydrologic cycle under different CO₂ background states. We analyze the relative difference between climatic changes resulting from CO₂ and orbital changes and find that the seasonal climate responses to orbital changes are larger than CO₂-driven changes in several regions. Using terrestrial δ¹⁸O and δD records from the Paleocene-Eocene Thermal Maximum (PETM), we compare our modeled isotopic seasonal range to fossil evidence and find agreement between empirical and simulated isotopic compositions. Our conclusions consider systematic impacts on the proxy records, including the preservation state of the proxy, analytical uncertainty, and the relationship between δ¹⁸O or δD and environmental context, as well as illustrate the utility of fully coupled, isotope-enabled climate models when interpreting proxy records in times of extreme warmth.

Received: 26 May 2023 – Discussion started: 31 May 2023

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Julia Campbell et al.

Status: final response (author comments only)

RC1:
'Comment on cp-2023-37', Gordon Inglis, 11 Jul 2023

In this paper, Campbell and co-authors explore how changes in seasonality and CO2 influence water isotopes during the PETM. To achieve this, they employ iCESM1.2 – this model is the ideal choice because it is able to closely replicate other key climate metrics during the early Eocene/PETM, including global temperatures, climate sensitivity, and the hydrological cycle (i.e., MAP, P/E – see Cramwinckel et al., 2023). The authors find that orbital variability may exert a greater control on water isotopes than a doubling of CO2. This is a really important finding. They also compare model output alongside d18O and d2H proxy indicators for the PETM – they find that del18O proxies (esp. siderites) are typically summer biased. The data-model agreement for leaf wax d2H is more variable with values typically similar or higher than annual values.
This is a useful and important contribution to the paleoclimate community. It also has relevance to both the proxy and modeling community,. The findings are likely to have major implications for future work, especially during other (longer) climate intervals (e,g, the Eocene).
As such, I have relatively few comments – my suggestions are instead focused on improving the clarity of text/figures, adding additional literature, and exploring some of the implications for other climate intervals moving forward.
Major comment: It is interesting that changes in orbit have a reduced impact at higher CO2 (Page 11, L269) – does this mean that studies from the EECO or Cretaceous are less likely to be influenced by orbital controls. instead, CO2 is the key driver? Conversely, for relatively cold climates (e.g,. Oligocene, Pliocene), are orbital controls more important than CO2? Would be good to discuss this a bit more at the end of the paper. Will be useful for future work!
Other comments:
Page 2, Line 32 – in addition to citing Rae 2021, probably good to cite original studies (i.e., Anagnostou et al., 2020) and give the range of proxy values.
Page 2, Line 35 – see also Inglis et al., 2020 for an independent approach (…that arrives at a similar conclusion)
Page 2, Line 50 – see also Piedrahita et al., 2022 EPSL for insights into orbital variability during PETM
Page 2, Line 58 – would probably use d2H rather than dD (as recommended by IUPAC)
Page 4, Line 115 – CESM is also in close agreement with hydrological precipitation proxies from the PETM and early Eocene in Cramwinckel et al., 2023 Figure 12 (this was only just published, so I am aware why you could not include this paper!).
Page 5 – note that the carbon preference index is quite low (<1.5) at Mar2X, perhaps suggesting a diagenetic control (see nice review by Alex Sessions in org. geochem for more on this…)
Page 9, L213 – 13’c global warming between 6x and 3x CO2 simulations seems like a LOT and much higher than inferred in proxy synthesis (e.g, Tierney 2022, Inglis 2020 etc). I also don’t remember such high values in Zhu 2019 either – it was more like 5-7 degrees, right? Can you clarify the 13c value?
Page 10, L226 – this is a comment that applies throughout the manuscript – you need to be a little more specific with your language when describing changes in data. For example, “the colder subpolar region does not experience much of an increase…” – but how much of an increase? …and then later “…contributed to the slight increase in relative humidity” – how much did it increase? Another later example is on Page 17, L402 = “one record is closer…”, but what record do you mean? Please add this detail in where appropriate througout,
Page 10, L228-229: re: narrowing and strengthening of ITCZ during PETM, Cramwinckel et al, 2023 also shows that “…the width of the ITCZ decreases with increased CO2 in five (CESM, COSMOS, HadCM3B, HadCM3BL and MIROC) of the six [DeepMIP] models that provided the meridional wind field variable required to perform ITCZ width calculation” but that… “an ITCZ narrowing signal is not clearly evident within the proxy [MAP] data”.
Page 17, L405-410: as mentioned above, can also be other controls on leaf wax del2H during PETM – e.g., diagenesis. Although a seasonal bias might be important, is this likely to be visible in marine sediments that record a catchment-integrated signal? or will it all be smoothed out?
Page 17, L410 – you are right that fractionation factor a big unknown – one way this could be addressed is to apply a pollen corrected fractionation factor (see Feakins 2013 for first applicaiton, and Inglis et al,. 2022 Paleoceanography & Paleoclimatology for an early Eocene example). This can change absolute values substantially – for example, when applied to sediments from the East Antarctic margin during the early Eocene, the “...pollen-corrected fractionation factor ranges between −107 and −113‰ and is higher than assumed in some Eocene studies (−130‰) (Handley et al., 2012; Pagani et al., 2006). I would therefore try and emphasise how important the fractionation factor could be when undertaking a data-model comparison! Could shift values by 20-30 permil potentially.
Also, note that there is also quite a lot variability in the Inglis 2022 leaf wax de2H record (-30-40 permil) – given your findings, perhaps this could be attributed to orbital variability?
Figure 9/10 – I found it hard to figure out what the top and bottom dashed lines were – could you give these a different colour and/or add these to the key? There are also no error bars on the leaf wax del2H values - can these be added?
Appendix A: please add site names to this table.

Gordon Inglis

Citation: https://doi.org/10.5194/cp-2023-37-RC1
- AC1: 'Reply on RC1', Julia Campbell, 03 Aug 2023
  
  The authors greatly appreciate the helpful comments. Each one was addressed in the new revisions. We especially appreciate the additional literature that was suggested - these papers were relevant to the paper and a positive addition.
  Major comment - This is an important note; the authors added a few sentences on how these findings (specifically the impact of orbit at a higher or lower CO2) may impact studies on colder or warmer climates. In short, orbit may exert more control on the seasonal hydrological cycle in colder climates. As such, it is especially important to incorporate the influence of orbital variability on cold climate studies.
  Comments that included additional literature to reference - These comments were very useful for finding more relevant literature to enrich the manuscript. I added them all where appropriate.
  Page 2, Line 58 - I changed every instance of dD to d2H in regards to the IUPAC standards.
  Page 9, L213 - This line was too confusing and what I meant to get across wasn’t received, so I changed this sentence to be clearer.
  Page 10, L226 - I added more detail in several sentences that were too vague.
  Page 17, L405-410 - I emphasized diagenesis in another place as a possible factor in bias, but did not address marine sediments as all proxies are terrestrial.
  Page 17, L410 - I put more effort into emphasizing how much a different fractionation factor (and that the one we are using is just an estimate!) can impact the end results. I also addressed the Inglis 2022 leaf wax record in regards to orbital variability.
  Fig 9/10 - I added in more places what the top and bottom lines represented and added error bars to the leaf wax records (though the error I have is small).
  Appendix A - I added site names to this table.
  
  Citation: https://doi.org/10.5194/cp-2023-37-AC1
RC2:
'Comment on cp-2023-37', Anonymous Referee #2, 03 Aug 2023
General comments:

The aim of the paper is to demonstrate the importance of the insolation variations’ impact during early Eocene. More specifically, the manuscript presents the results of a series of simulations using the CESM water isotope-enabled version for 2 levels of pCO2 (3 and 6 PAL), which mimic the transient evolution of pCO2 during LPTM. Moreover, they compute the impact of different insolation contexts on water cycle to investigate seasonal response and compare it to the water isotopic records. They attribute the large variation of recorded seasonal water isotope values to insolation changes, which are much larger for weak CO2 values.
The paper is interesting but, unfortunately, globally not convincing on many important points:

The simulations are performed in a LPTM context that is largely a transient event (100 Kyears). Therefore, the eccentricity and obliquity may vary. The way the authors intend to capture this variation is done through sensitivity simulations, which are supposed to mimic the envelope of this event. This may be a serious limitation of the exercise, both for the modeling process and for the comparison to data to be sure that the comparison is meaningful.

All these aspects are not seriously discussed at this stage.

The isotopic response interpretation in this paper is very limited. There are many reasons to record variations in water isotope (dynamics of the atmosphere: transport of air masses, dynamics of the ocean: origin of evaporation of water...). All these processes are well described in many papers, including C. Risi for example. The authors’ references are interesting from an historical point of view (Craig), but certainly a bit short compared to the large literature and more importantly to the complexity of the water isotope response. Indeed, the authors only evoked temperature and precipitation impact (essentially through amount effects) on water isotope changes. Whereas there are much more processes involved in water isotope changes that are not seriously discussed.

The comparison with different proxies recording water isotopes is unclear to me. The authors did claim LPTM only last 100 kyr, but this duration corresponds to a whole eccentricity cycle and to several obliquity and precession cycles. Moreover, the PCO2 increases from two different values that are here fixed to 3 and 6 Pal; therefore, there are two different issues:

First, do we compare water isotope records to 2 different equilibrated climate simulations, which only represents an envelope of the transient LPTM event?
Then, what are the meaning of the isotopic record in terms of model age and duration to be compared with sensitivity model results?
Another important issue that the author avoids completely here is the vegetation impact on water isotope fractionation, especially through evapotranspiration. During LPTM, there is a large change of temperature and hydrologic cycle and therefore, an adaptation on the terrestrial biosphere that has to be accounted for or at least discussed.

For these main reasons, I am not in favor of publishing this manuscript at this stage in Climate of the Past. However, the study is interesting in many aspects, the authors should answer my major and minor comments below, before publication.

Detailed comments:

Abstract:
The limitations of the manuscript should be clarified as far as the point is to compare to LPTM proxies, the equilibrated snapshot simulation using different values of pco2 and insolation is not fully appropriate.
The model / data comparison is also limited, as described above.
Moreover, the proxies used are not easy to interpret and there is no real validation of these proxies in a more constrained context, to be sure that the model data comparison is valid.
The LPTM is a transient event which lasted, as the authors claims, 100 00 yrs. The approximation of this transient event with the difference between two snapshots simulations is therefore not straightforward. It is important to clarify for both modeling and proxy data. From a modeling point of view, it is certainly important to use a water-isotope enabled model to directly compare with data, but what are recording these data during the LPTM transient event?

Introduction:
Early Eocene is maybe less appropriate than MMCO concerning the concentration atmospheric CO2 of the end of this century, because the paleogeography is closer for the MMCO. Moreover, the absence of cryosphere for Eocene considerably modified the earth response to the perturbation.
The reference to Berger for the role of insolation at LGM on the hydrologic cycle is maybe inappropriate.
On the same note, the reference to Ruddiman for the ice sheet is not obvious; Ruddiman mostly depicts the role of orography on climate. The impact of insolation of ice sheet growth for Antarctica or Greenland are better described by Ladant et al., Paleoceanography and Paleoclimatology, 2014, or Tan et al., Nature Communications, 2018 respectively, or by De Conto and Pollard, Nature, 2008, for the transient climate evolution.
Craig is certainly a pioneer reference, but here, the author used a coupled model.
Is the water isotope also simulated in the ocean model?
Anyway, there are much more than the temperature effect and the amount effect to account for, such as the changes of water mass transports due to atmospheric dynamics change, or the origin of the evaporated water from ocean associated to the ocean thermal response, as well as the ocean dynamics.

Terrestrial data are difficult to interpret for many reasons:
Age models are often very large and spread over several orbital cycle, which make them not very well constrained.

The processes involved in water isotopes variations and records are sometimes a bit ambiguous and not unimodal; those isotope records may hide many different physical processes, not only the increased temperature and amount effects. Moreover, the isotope enabled models analyses clearly demonstrated - in a series of paleoclimate studies for different climate changes from mid Holocene to Eocene - that the complexity to associate the water isotope variations to climate changes (see for instance Joussaume, Nature, 1984, for a pioneering study or Camille Risi et al., Reviews of Geophysics, 2016, and Werner, Geoscience, 2016, for more recent studies)

The o18 enable coupled models include a bunch of mechanisms which allow a disentangling of the different processes responsible of the O18 changes. These processes may be associated with thermal, hydrology effects but also dynamics of atmosphere and ocean.
Indeed, there is a crucial role played by the vegetation in the water isotope variations, superimposed to pCO2 levels and astronomical forcing. The evapotranspiration is certainly an important process to account for. The author should stress this point in the introduction.
In summary, there are many issues in this introduction that need clarifications both in the text and references.

2/ Method:
Because the author uses a previous simulation (Tierney 2022), she gave a minimum of information; even the number of vertical levels in atmosphere and ocean are not specified.
Moreover, we expect to have some information of strength and weaknesses on the LPTM simulation.
More importantly, depending on the scientific question, the insolation simulations may be different. Here, the hypotheses derived from Lunt et al. 2017, but for LPTM, it is possible to compute the exact value of astronomical parameters from Laskar, Astronomy & Astrophysics, 2004, and therefore, to get the min and max insolations for a latitude or the separated values of each orbital parameter.
In this paper, the aim is water cycle, so the question is what is the most appropriate insolation? A discussion is lacking on this important point.
It is very classical to prescribe the PI value for methane, concentration, but it is worth to specify that methane could be higher in a warmer and wetter climate.
The problem concerning the use of terrestrial data is the model age, this data encompasses several astronomical cycles. Therefore, it is not easy to have something else than a large envelope.

3/ Results:
This section is interesting, the analysis of the series of simulations are well described in section 3.1 to 3.3 and compared to data in section 3.4, which is less convincing for me.

3.1/ Response to orbit:
The authors refer most of the time to Berger; no problem with that for Quaternary, because Berger and Laskar are similar, but for the Eocene, it may be interesting to compare both values for orbital parameters.
The interpretation of o18 is not restricted to thermal and hydrological effects. Indeed, the atmosphere dynamics and also ocean dynamics, especially for the Eocene paleogeography, play an important role.
The changes of origin of atmospheric air mass or the changes of evaporation area due to SST changes may drastically impact coastal region, for instance. The same is true for the tropics, where the Hadley cell is modified, and in such regions, the atmospheric dynamics are changed, so the isotopes may change only for dynamic reasons.

3.2/ Response to CO2 and 3.3/ Orbital sensitivity under different CO2 background state:
No major comment, the analyses are interesting but there are two severe limitations:
A major limitation in this manuscript: there is no impact of vegetation changes, and during LPTM, when the earth experienced such a change, a major modification / adaptation of the biosphere occurred, which will drastically modify the evapotranspiration and the water cycle. This should be discussed in much more details.

A minor one: the CO2 increase may be associated to a methane increase; this will also modify the temperature pattern and therefore, the hydrological cycle. Such a possibility should be at least discussed.

3.4/ Comparison with data:
The authors focused on LPTM because more data are available.
Could the authors explain how exactly they account for the “Calendar” effect? (See reference from Barthlein et al. for Quaternary, and it is possible to use Laskar or Berger results, because they are similar). What about the LPTM? I don’t understand neither what the authors mean by microclimate, and the point they raised concerning its duration.

4/ Discussion:
The comparison of model/data for Holocene is not really comparable to the LPTM one for many reasons. The first sentence of the discussion is very general and too vague to be appropriate in this context.
There are indeed caveats and limitation in comparing model and data, especially when this comparison deals with a transient event, the onset of the LPTM, and especially when the target is to quantify, which may be the effect of orbital forcing through a seasonal behavior.
The sensitivity to orbital forcing is higher than the one of CO2 in o18.
Is it a real surprise, there are many papers, especially from the Bristol group, which depict that the effect of CO2 on monsoon for different time scales - geologic or glacial interglacial - is very weak.
Another important issue, which is not only for the proxy used here, is what seasonal temperature it represents; if it represents the warmer season, then it is interesting to account for the effect of insolation.
It is only in the discussion section that there is some reference to the bias of CESM o18 limitation; clearly, this is an important point to be discussed in the model description section 2 but also more in details in the discussion section.
The author assesses at the end of the paper that the low resolution is not appropriate for regional analyses, which is a bit strange when compared to their previous sentence on microclimate.

Cited references :
Ladant, J.-B., Donnadieu, Y., Lefebvre, V., and Dumas, C. (2014), The respective role of atmospheric carbon dioxide and orbital parameters on ice sheet evolution at the Eocene-Oligocene transition, Paleoceanography, 29, 810–823, doi:10.1002/2013PA002593.
Tan, N., Ladant, JB., Ramstein, G. et al. Dynamic Greenland ice sheet driven by pCO₂ variations across the Pliocene Pleistocene transition. Nat Commun 9, 4755 (2018). https://doi.org/10.1038/s41467-018-07206-w
DeConto, R., Pollard, D., Wilson, P. et al. Thresholds for Cenozoic bipolar glaciation. Nature 455, 652–656 (2008). https://doi.org/10.1038/nature07337
Joussaume, S., Sadourny, R. & Jouzel, J. A general circulation model of water isotope cycles in the atmosphere. Nature 311, 24–29 (1984). https://doi.org/10.1038/311024a0
Galewsky, J., Steen-Larsen, H. C., Field, R. D., Worden, J., Risi, C., and Schneider, M. (2016), Stable isotopes in atmospheric water vapor and applications to the hydrologic cycle, Rev. Geophys., 54, 809–865, doi:10.1002/2015RG000512.
Werner, M., Haese, B., Xu, X., Zhang, X., Butzin, M., and Lohmann, G.: Glacial–interglacial changes in H₂¹⁸O, HDO and deuterium excess – results from the fully coupled ECHAM5/MPI-OM Earth system model, Geosci. Model Dev., 9, 647–670, https://doi.org/10.5194/gmd-9-647-2016, 2016.
Laskar, P. Robutel, F. Joutel, M. Gastineau, A. C. M. Correia and B. Levrard, A&A,428 1 (2004) 261-285, A long-term numerical solution for the insolation quantities of the Earth, DOI: https://doi.org/10.1051/0004-6361:20041335
Citation: https://doi.org/10.5194/cp-2023-37-RC2
- AC2: 'Reply on RC2', Julia Campbell, 11 Aug 2023
  
  General Comments -
  The authors greatly appreciate the helpful comments and concerns. They will be addressed in the new revisions, and I will specify how they will be addressed below. Many of these comments raised a concern regarding the accuracy of the simulations in representing the Early Eocene (and PETM) and the validity of the model-data comparison. These comments were very helpful in emphasizing a main point of confusion. These are sensitivity experiments - the purpose of this paper is not to perfectly represent the Early Eocene with these simulations, or to boast an extremely reliable model-data comparison; the purpose of this paper is to use the Early Eocene (the most recent time period with extreme warmth and elevated CO2 levels) as the background in order to study the climatic changes (specifically in the hydrological cycle) as a result of manipulation of CO2 levels and orbits. Therefore, the first three sections of the results regarding the manipulation of CO2 and orbit are the main results, while the model-data comparison serves to judge whether or not the simulated isotope behavior is in the ballpark of available data - and specifically to see if the seasonal range of simulated water isotope values are able to capture water isotope data from the PETM. The data used are not tied to a specific orbit as their timing is not that exactly known, which is why we compare these data to all orbital simulations at an estimated PETM CO2 level and to all seasons in order to determine if the range captures most data. The simulations mostly envelope the data, but not fully, which triggers the reader to consider the many limitations and uncertainties in model-data comparisons with isotope-enabled simulations. We draw on those limitations in the discussion section, but we will add more on that in the introduction section at the request of this reviewer.
  The resolution of the simulations are rather coarse - so these simulations are best used for global matters, rather than regional or local matters. Therefore, the main figures used represent temperature and precipitation as those likely have the greatest impact on the water isotopes on a global and large-scale. However, the supporting figures in the appendix (addressed in the results sections) include relative humidity, specific humidity, and cloud cover. Although we speak on the effects of topography, ocean temperature and dynamics at the Indo-Pacific warm pool, and air mass transport in the results section when discussing Figures 4 and 7, I agree that we could speak to it a bit more. The authors will add more context for the water isotope signals we see in these figures, specifically regarding the origin of evaporation, air mass transport, and topographic effects at mountain ranges.
  We initially compare the water isotope records to the 6x PI CO2 simulations only, as there is more available data for the PETM and that CO2 level is the better estimate for the PETM. I also want to clarify that the simulations used in this study were not initially at 3x PI CO2 and then increased to 6x PI CO2 - the 3x PI CO2 simulations were fully spun up, and the 6x PI CO2 simulations were fully spun up, independently from one another. The data are not tied to specific orbits, so we compare them to all four simulated orbits. In the last results section, we decide to compare the data to all simulations (both CO2 levels and all four orbits) to determine if any sort of pattern exists. If there had been a clear pattern, that could have been indicative of data recording more strongly during a certain orbit. However, we did not find a clear pattern, so we don’t attempt to make this conclusion, rather the only pattern seen is that the data (representative of sometime in the PETM) match with the 6x PI CO2 simulations better than the 3x PI CO2 simulations, which we expected.
  The different proxies likely record different seasons and durations, which are discussed in the methods and discussion sections. The paleosol carbonates and siderite record the soil water they form in over an interval of hundreds to thousands of years, and may be more likely to form during the warmer months. The leaf waxes record the soil water over an interval of weeks to months and are also more likely to form over the warmer months. None of the records can be pinpointed to an exact moment in time, so we compare them to all the orbits at the appropriate CO2 level for the PETM (6x PI). Since they may form more rapidly during different times of the year, we find the simulated range of water isotope values (main figures use monthly max and min, supporting figures in appendix use summer and winter means incase that’s of interest) and overlay the data to determine if most of the data is captured by the simulations. We use a proxy system model for all proxies in order to compare them to the simulated values as accurately as possible. However, there are limitations and uncertainties that exist for this comparison, which we detail in the discussion section but will add to the introduction as well. As for the final results section with the root mean square deviation table, we compare the data even more specifically to the simulations by using the proxy system models and determining the quantitative comparison at the approximate location in the model where the data formed on Earth. Many limitations exist for this as well, but the purpose of this table was to determine if a clear pattern would emerge. The imperfections in the model-data comparison also prompt a discussion on what model-data comparison can and cannot accomplish, especially in regards to simulations that are coarser in resolution. These simulations are global, fully coupled, and isotope-enabled, so unfortunately a higher resolution model would have been too computationally expensive at this time.
  The only differences between the simulation inputs are CO2 and orbit, as the purpose of this paper is to address climatic changes resulting from one or both of these factors. Therefore, the vegetation used for the 3x and 6x PI CO2 simulations must be the same, the authors do not want any climatic changes resulting from the vegetation to be a factor here. However, there were changes in the vegetation during the PETM which would have affected the climate in reality, so we will address this in the introduction. The authors do mention the importance of the fractionation factor in the proxy system model for the leaf wax records, which changes depending on vegetation and is unknown for this time period, but we will emphasize this further in the methods and discussion sections.
  Detailed Comments -
  Abstract:
  The authors will add a mention to the limitations surrounding the simulations and model-data comparison in the abstract in response to these comments. Details are provided in the main text of the paper.
  Final comment on abstract: The authors want to clarify that we are not using the difference between any simulations to approximate the PETM. We first find the hydrological differences between orbits and then the hydrological differences between CO2 levels, not to try and represent the PETM, but to assess the impact of orbital variations and CO2 variations on water isotopes. We then assess the difference of the impact of orbital variation at each CO2 level to determine if orbit has a relatively stronger effect on water isotopes at a lower or higher CO2 background state, in which we find orbit seems to have a stronger effect at a lower CO2 background state.
  Introduction:
  The authors chose to simulate the Early Eocene, a geologically recent time period with extreme CO2 levels, in order to study hydrological changes at a high CO2 background state. This study is not meant to represent the end of this century, but the beginning of the introduction does mention that the CO2 levels during the Early Eocene were as high as CO2 may get by the end of this century following a higher future emissions pathway. This was added as another reason the Early Eocene was chosen, but the authors will stress further that this time period and model do not represent the end of this century and should not be mistaken as such. The mention of the lack of cryosphere is helpful, the authors will add a sentence in the introduction on the significance of the lack of cryosphere during this time period.
  The reference to Berger was regarding the influence of orbit on climate, and the ice ages were added as an example. However, I agree that this is a confusing reference here - I am going to remove the ice age example (as I will have a sentence previous to this one regarding the comment above about the lack of cryosphere) and replace Berger with a more appropriate reference on the influence of orbit on warm climates. The Ruddiman reference was also regarding the role of orbit on climate, and the ice sheets were added as an example at the end of the sentence. I’m going to remove the ice sheet example here (same reason above), and will include one of the references you list after my new sentence on the lack of cryosphere in the Eocene (mentioned above). Craig is referenced when briefly explaining water isotope physics for any reader that may not be well-read in that field. I believe it is important to include this reference as we are not speaking about the model here, but I will add another reference on the use of water isotopes in fully coupled CESM simulations as well for the second half of that paragraph where we do begin to mention models.
  The water isotope is also simulated in the ocean model, I will clarify this in the introduction.
  I agree with the comment on factors in water isotopes. The authors do mention these other factors when speaking on certain regions in the results section, but not in depth, therefore we will add more context for the water isotope signals in Figures 4 and 7 regarding these other factors, especially for the regions of interest. We will also mention these factors in the introduction so the reader considers them sooner.
  It is true that the terrestrial data is not well constrained to a time or orbit, the authors use this to our advantage by comparing the data to all orbits and seasonal ranges to determine if the water isotope signal is largely captured by the model or not (on large-scale, coarse resolution) rather than comparing to only one orbit or season. We will emphasize this further in the introduction. The physical processes involved in water isotope signals are complex and many. On a global scale, it is likely that temperature and amount effects have the greatest influence on large-mass, coarse isotope signals. However, many physical processes come into play and the authors will clarify the other major factors (SST, evaporation, air mass transport, humidity, orography) in the introduction so the readers are aware that it is not so cut and dry. The specifics of how these factors are involved are discussed (and will be discussed further) in the results and discussion sections.
  We thank the reviewer for the comment on the biosphere; we had not focused on vegetation as that factor is not manipulated in the simulations (in order to constrain changes to CO2 or orbital variability), but in reality, vegetation would have changed throughout the Early Eocene. Therefore, the authors will add a bit in the introduction in regards to the importance of the biosphere on water isotope signals and the reason vegetation was built the same in all simulations.
  Methods:
  The authors will add more on the specifics of the model, including the vertical levels in the atmosphere and ocean. The authors also hope readers who are interested in a deeper understanding of these specific simulations will turn to previous publications on them.
  Strengths and weaknesses of these simulations are addressed throughout the paper, especially in the discussion section, but we will clarify the main strengths and weaknesses in the modeling methodology section as well.
  We thank the reviewer for the orbital insight. The scientific question is in regards to climatic changes resulting from varying orbits (we specifically focus on two orbits in this paper with very strong differences in insolation given precession differences). We are not attempting to perfectly represent the PETM or the various orbits during the PETM; this paper uses the entirety of the Early Eocene as a background time interval, not just the PETM. Additionally, we study how drastically water isotope signals can change when influenced by the most dramatically different seasonal insolation patterns. In this case, the most dramatically different seasonal insolation patterns stem from the difference between OrbMaxN and OrbMaxS - the orbits with high eccentricity and high obliquity but at opposite points in the precessional cycle. The timing of the PETM is also not perfectly known, so although several papers (referenced in this paper) found that data collected around the onset of the PETM best match orbits with high eccentricity and obliquity, it is not confidently understood what the exact orbital parameters were during the entirety of the PETM, given the uncertainty in timing.
  I believe the reviewer is asking what the most appropriate insolation for the PETM is, which would have changed throughout the PETM and is not exactly known (see above response). Previous publications on this question are referenced in the discussion section.
  The authors appreciate the comment on methane - I agree this is an important factor in climate that, in reality, may have increased during the Early Eocene. The authors will add a sentence regarding methane in this section.
  On the comment concerning terrestrial data: Yes exactly, we will clarify this in the methods section so there is no confusion.
  Results:
  Response to orbit:
  Comment on Laskar: This is interesting. The authors will mention Laskar if it does not disturb the flow of the paper - possibly in the discussion section instead.
  Comment on o18 interpretation: Agreed, the authors will emphasize this further so it is clear.
  Comment on water isotope signals: As said above, the authors will speak a bit further on these factors. We appreciate the reviewer’s examples here, and we speak a bit on the ITCZ differences in the discussion section already but could also mention in the results section.
  Response to CO2 and Orbital sensitivity under different CO2 background state:
  We understand the reviewer’s concerns with these limitations. The authors will clarify why we chose not to include the impact of vegetation changes in this study, and mention that if we had, there would have been major impacts on the water cycle as a result. Although this is an interesting scientific question, it would best be explored in a different study to not overwhelm the experiments discussed in this paper, which focus on hydrological changes influenced from CO2 and orbit only. As for the minor limitation, as responded to above, we appreciate the reviewer’s mention of methane and will be sure to mention it in the methods section.
  Comparison with data:
  Following the mention of the paleo-calendar effect, the authors will add a sentence on how we account for that in the simulations. We are grateful for the example references here.
  The authors also appreciate the comment on micro-climates, we have decided the mention of micro-climates is unnecessary, pulls from the focus of the section, and disturbs the flow. We have removed this sentence.
  Discussion:
  I believe the reviewer is referencing the Burns citation here - this comment is a valid point and the Burns citation has been removed. The first sentence of the discussion is meant to be a general, introductory sentence for the section to reflect the details we discuss in this section. We can replace some of the vague terms with more specific ones so it feels more appropriate.
  On the CESM bias comment: This is discussed, but the authors will mention this in the methods section as well, and can expand on it in the discussion section.
  On the low resolution comment: We agree with this comment and have deleted the sentence on micro-climate.
  The authors thank this reviewer for their comments and concerns. We hope this response clears up any points of confusion with this publication. We will clarify the purpose of the paper, what this paper accomplishes (and what it does not accomplish - perfectly representing the PETM), and the limitations in the introduction, which we believe resolves most of the comments. We will address the detailed comments as described above.
  
  Citation: https://doi.org/10.5194/cp-2023-37-AC2

Julia Campbell et al.

Data sets

CESM1.2 simulation data for "CO2 and orbitally driven oxygen isotope variability in the Early Eocene" Julia Campbell https://doi.org/10.5281/zenodo.7971738

Julia Campbell et al.

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Short summary

In this study, we use climate modeling to investigate the relative impact of CO₂ and orbit on Early Eocene (~55 million years ago) climate, as well as compare our modeled results to fossil records to determine the context for the Paleocene-Eocene Thermal Maximum, the most extreme hyperthermal in the Cenozoic. Our conclusions consider limitations and illustrate the importance of climate models when interpreting paleoclimate records in times of extreme warmth.


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CO2- and orbitally- driven oxygen isotope variability in the Early Eocene

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CO₂- and orbitally- driven oxygen isotope variability in the Early Eocene