the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Shaping the mid-Miocene warmth: a sensitivity study on paleogeography, CO2 and model physics
Abstract. The mid-Miocene (15.98 to 13.82 Ma) was a period characterized by substantially warmer temperatures than today and atmospheric CO2 concentrations comparable to near-future projections. Climate models have generally struggled to reproduce proxy-based reconstructions from this interval, particularly at high latitudes where model temperatures are consistently too low. Here, we present new mid-Miocene simulations using an unpublished geography and evaluate the climate's sensitivity to several key components: paleogeography (including land-sea distribution, topography and ice sheets), atmospheric CO2 concentration, atmospheric model choice, and solar forcing. Our baseline mid-Miocene climate yields a global mean surface temperature (GMST) of 19.8 °C. GMST varies by up to 3.2 °C between simulations with CO2 concentrations of two and four times pre-industrial values, which is consistent with estimates for the mid-Miocene. Removal of the Antarctic ice-sheet leads to expected local warming, but nevertheless records an overall global cooling of 1.3 C. Solar forcing and subtle changes of land-sea mask each impact GMST by around 0.2 °C. The choice of atmospheric model substantially affects the simulated mid-Miocene climate through modified feedback mechanisms. We estimate an equilibrium climate sensitivity (ECS) of 2.9 °C for the mid-Miocene, similar to modern-based estimates from our model, indicating the potential for the Miocene to contribute to constraining equilibrium ECS. Global precipitation is tightly coupled to GMST across all our simulation. As with previous studies, all our simulations, regardless of specific configuration, underestimate high-latitude proxy-reconstructed temperatures. This highlights the need to improve our understanding on polar amplification and the need to use high concentrations of CO2 to compensate for a cold modeled Miocene climate.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-5078', Lauren Burton, 11 Nov 2025
- AC1: 'Reply on RC1', Martin Renoult, 16 Feb 2026
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RC2: 'Comment on egusphere-2025-5078', Anonymous Referee #2, 02 Dec 2025
Comments to the Author:
This manuscript presents a comprehensive sensitivity study of the mid-Miocene climate using the CESM1.2 model. The study aims to understand why climate models systematically underestimate high-latitude warmth during the Mid-Miocene Climatic Optimum and to quantify equilibrium climate sensitivity (ECS) from this warm paleoclimate. The study explores the roles of paleogeography, CO₂ concentration, atmospheric model physics, solar forcing, and Antarctic ice sheet. The topic is highly relevant, given the mid-Miocene's potential as an analog for near-future warm climates and the persistent model-data mismatch, especially at high latitudes. Here, I give some comments.
Major Comments:
Paleogeographic Reconstruction:
The study relies on an unpublished paleogeography from Getech Plc., which is compared with the Burls et al. (2021) reconstruction. While this offers a valuable comparison, the manuscript provides insufficient details on the paleogeographic reconstructions, and does not compare with several recent published mid-Miocene paleogeographic reconstructions. As the paleogeography is the important boundary condition that fundamentally shapes the simulated climate.
Model-Data Mismatch:
The manuscript highlights the persistent cold bias in high latitudes. It is advisable to consider adding a discussion on "seasonal deviation" of the proxy. And the discussion could be strengthened by linking this to broader challenges in paleoclimate modeling (e.g., cloud feedbacks, ocean heat transport, vegetation-atmosphere interactions).
Addition, a key concern is that the model might be over-reliant on CO₂ forcing to achieve a warmer climate, potentially at the expense of other, less constrained factors that are known to be important for warm paleoclimates, such as the role of ocean–ice interactions and their dependence on model dynamics.
The simulated AMOC:
The model simulation suggests a collapse of the Atlantic Meridional Overturning Circulation (AMOC) during the middle Miocene. However, the available geological evidence does not support a complete shutdown of the AMOC at that time.
Antarctic Ice Sheet Impact:
The finding that the inclusion of an Antarctic ice sheet leads to global warming is intriguing and counterintuitive. While the authors briefly discuss this, the mechanism remains speculative. Provide the relative contribution percentages of each feedback item (cloud, water vapor, albedo, temperature) to the 1.4 °C increase. This could be a significant contribution if better explained.
Citation: https://doi.org/10.5194/egusphere-2025-5078-RC2 - AC2: 'Reply on RC2', Martin Renoult, 16 Feb 2026
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This is an important and timely piece of work, particularly considering the next phase of MioMIP. The methodology is sound and is generally well described. I would like to see a number of minor comments addressed before publication and attach a PDF which details these. Many comments relate to rephrasing or editorial-style changes that will enhance the paper for the reader.
Generally, the paper would benefit from more discussion around the implications of the findings. As there is no specific 'Discussion' section, I would like to see this weaved into all other results sections. I have pointed out some specific instances in the PDF.
I would also like to see some more nuance when it comes to comparing the model results to the proxy reconstructions. As it stands, the text largely reads that proxy data are correct and the error must all come from the models, when it is very likely a combination of both model error and proxy bias. We need to better understand both sources of error, and we shouldn't be adapting the model CO2 to potentially unlikely/unevidenced levels just to better represent the proxy values. Again, I have pointed out some specific instances in the PDF.
Figures are generally very good quality, but some would benefit from subplot labels (a, b, c etc.) so that they can be clearly identified in the caption and the main text.
Please also check for the consistency in subscripting CO2.