the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Feb 2026
Simulation of climate during the Miocene Climatic Optimum under different CO2 forcings
Abstract. The Miocene Climatic Optimum (MCO; 17 – 14 Ma), characterized by global mean surface temperatures ~7 °C higher than preindustrial (PI), offers a target for validating models for warmer-than-present climate states. Here, we use a water isotope tracer enabled version of the Community Earth System Model to simulate the MCO under 1x (MCO1x), 2x (MCO2x), and 4x (MCO4x) PI CO2. Our simulations show significant warming due to MCO boundary conditions as well as a small increase in equilibrium climate sensitivity with higher CO2. All simulations exhibit a decreased mean equator-to-pole temperature gradient relative to PI. However, the spatial patterns of warming are distinct between simulations with relatively greater high latitude warming between MCO1x and MCO2x and relatively greater low latitude warming between MCO2x and MCO4x. Warming is associated with enhanced precipitation and enriched precipitation δ¹⁸O (δ¹⁸Op) globally.
We compare the MCO model outputs with proxy of surface temperature, precipitation, and δ¹⁸Op. Like many other MCO modeling studies, our simulations underestimate the reduced latitudinal temperature gradient reconstructed with proxies. We find better model-proxy agreement for terrestrial and marine temperature records in the MCO1x and MCO4x experiments, respectively. Precipitation and δ¹⁸Op records show the best agreement with the MCO2x and MCO1x experiments, respectively, but there are large uncertainties due to limited proxy data and large reconstruction uncertainties. The MCO2x simulation is warmer than the projected 2080–2100 climate under RCP8.5, highlighting the importance of both boundary conditions and equilibrium versus transient climate system response to increased CO2.
Competing interests: I declare that neither I nor my co-authors have any competing interests.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-899', Anonymous Referee #1, 07 Mar 2026
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RC2: 'Comment on egusphere-2026-899', Anonymous Referee #2, 13 Apr 2026
This manuscript presents Miocene Climatic Optimum simulations using the water-isotope-enabled CESM under 1x, 2x, and 4x preindustrial CO2, and compares the simulations with proxy constraints on temperature, precipitation, and precipitation isotopes. The topic is important, and the isotope-enabled framework is potentially a valuable addition to Miocene climate research. However, I do not think the current manuscript yet fully capitalizes on the main scientific opportunity provided by this modeling framework, and several of the broader comparative conclusions are presently stronger than the available analysis can support. I therefore recommend major revision.
Major comments
1. The isotope-enabled aspect of the study is the clearest distinguishing feature, but the isotope results are not yet interpreted deeply enough. To me, the main added value of this paper relative to prior Miocene CESM-style studies is the inclusion of water isotopes. However, the manuscript currently presents the isotope results more as an additional diagnostic than as a central scientific contribution. In particular, the paper would be much stronger if it more explicitly discussed the relative roles of temperature effects, precipitation amount effects, moisture source changes, transport pathway shifts, circulation changes, and seasonality in shaping the simulated isotope response. Without this deeper interpretation, the isotope-enabled framework remains underused, despite being one of the manuscript’s main distinguishing features.
2. The comparison with future climate can be informative in a qualitative sense, but the conclusions should be framed more cautiously. I think this comparison can be useful as a broad conceptual contrast, but only if its limitations are made fully explicit. The Miocene and the late 21st century differ fundamentally in paleogeography, land–sea distribution, gateways, vegetation, cryosphere state, and equilibration timescale. These differences strongly limit direct comparison. I therefore encourage the authors to retain this section only as a qualitative discussion and to avoid overly absolute conclusions that might imply stronger comparability than is actually justified.
3. The ranking of different CO2 experiments based mainly on RMSE is not, by itself, the most informative way to interpret the model–proxy comparison. According to the study, terrestrial temperatures agree best with one experiment, marine temperatures with another, precipitation with another, and δ18Op with another, while the manuscript also acknowledges limited data availability and substantial uncertainty. This is an interesting result, but I do not think the main scientific takeaway should simply be that different proxy classes “prefer” different CO2 concentrations based on RMSE. A more meaningful discussion would examine regional pattern agreement and, more importantly, what the mismatches imply about the limitations of the model, the proxy compilations, and the experimental design.
Minor comments
- The current Introduction lacks a clear statement elaborating the novelty and motivation of this study.
- Lines 62–66: The review of previous modeling work is too brief and lacks key references (Herold et al., 2011; Krapp & Jungclaus, 2011; Goldner et al., 2014; Burls et al., 2021 MioMIP1; Acosta et al., 2024; Sun et al., 2024; Liu et al., 2024; Lee et al., 2025; Hutchinson et al., 2025; Tan et al., 2026). It would be valuable to compare different MCO modeling studies and pinpoint the current weaknesses as well as the gap between model results and proxy records.
- The authors mention the climate sensitivity of GCMs but do not elaborate on why it is important for MCO simulations, nor do they discuss the climate sensitivity of the model used in this study.
- Line 90: What is the exact elevation change applied in this study?
- Lines 96–103: What initial conditions (ocean temperature and salinity) were used for the MCO2x simulation? What are the background oxygen isotope values prescribed for each ocean basin, and are they inherited from the PI condition?
- It would be helpful to add the PI results to Figure 1 and Figure 7 for direct comparison.
- Schouten is cited as 2002 in the main text but appears as 2013 in the reference list. The CenCO₂PIP / Hönisch reference is listed twice (Line 630 and Line 633). Only Haywood 2020 is cited in the main text (Line 36), others are not cited but appear in the reference list. Kürschner et al. 2008 is in the reference list but not cited in the main text. Please cross-check all references.
- I would encourage the authors to deposit their data in a public repository rather than making them available only upon request.
Citation: https://doi.org/10.5194/egusphere-2026-899-RC2
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- 1
This manuscript presents new Miocene climate simulations using the water isotope-enabled Community Earth System Model (iCESM 1.2). The authors examine large-scale climate features, including temperature, precipitation, precipitation δ¹⁸O, and meridional heat transport, and provide an energy-balance interpretation of the simulated temperatures. Model results are compared against available proxy records for evaluation.
Overall, the manuscript is clearly written and well structured. The scope of the study aligns well with the readership of Climate of the Past. However, I found it challenging to identify the key novel elements and the specific advances relative to prior Miocene simulations. I encourage the authors to articulate more clearly what is new or distinctive in this work and why those aspects are significant for advancing Miocene modeling. Below are several detailed comments and suggestions.
Major comments
1. Please clarify what is genuinely new about this set of Miocene iCESM1.2 simulations relative to prior studies using the same model (e.g., Acosta et al., Paleoceanogr. Paleoclimatol., e2021PA004383; Liu et al., Geophys. Res. Lett., e2024GL109159). As presented, the primary differences seem to be in the paleogeography, vegetation, and ice-sheet boundary conditions. If so, state this explicitly and explain why these choices are critical for the simulated climate response—for instance, how altered topography or gateways influence circulation patterns, or how vegetation/ice changes affect albedo and feedbacks.
I recommend a concise table (or bulleted summary) comparing your boundary conditions to standard datasets like Herold et al. (2008), covering: land–sea mask/topography, ocean gateways/bathymetry, prescribed vegetation/land surface, ice-sheet extent/height, CO₂ and other greenhouse gases, aerosols, and orbital parameters. This would enable readers to attribute climate differences (e.g., in heat transport or precipitation) to boundary conditions versus intrinsic model behavior.
Importantly, for any differences in these simulation results compared with previous iCESM1.2 simulations (e.g., temperatures, hydroclimate, or δ¹⁸O), provide mechanistic explanations. Link these to physical processes such as changes in boundary / initial conditions where possible.
2. From a MioMIP perspective, please situate your iCESM1.2 ensemble relative to other MioMIP model results available at https://www.deepmip.org/data-miocene/. Are the large-scale Miocene patterns (e.g., polar amplification, tropical SST gradients, monsoon intensity, zonal mean precipitation shifts, sea-ice extent) broadly consistent, and where does iCESM deviate? Identify explicitly what this study adds beyond existing MioMIP findings—such as new water-isotope diagnostics, refined boundary conditions, a unique climate mechanism, or improved process attribution (e.g., via energy balance, heat transport, or cloud feedbacks).
3. The current Results section reads primarily as descriptive documentation. The manuscript would be much stronger if the authors emphasized the most exciting outcomes—those that either revise our understanding of Miocene climate or demonstrate new model insights. Identify explicitly which findings are novel and discuss their broader implications.
4. Consider merging Section 3.4.1 (“Comparison with preindustrial climate”) and Figure 10 with Section 3.1 and the earlier figures. Since the preindustrial (PI) reference curves already appear in Figure 1, integrating the full PI comparison earlier would make the narrative more cohesive and help readers interpret Miocene–PI anomalies throughout the paper.
5. Including an Atlantic Meridional Overturning Circulation (AMOC) diagnostic would enhance the discussion of oceanic heat transport. A figure showing the maximum Atlantic overturning stream function (and, if possible, a depth–latitude structure) would connect directly to the meridional heat flux analysis in Figure 7. A concise global overturning depiction could also help link the ocean circulation to the modeled heat transport and energy balance frameworks.
Minor comments
1. In Tables 1 and 2, the listed values appear overly precise for the intended context. Rounding to single-digit precision (or justifying the current precision) would improve readability and consistency.