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Simulating Miocene Warmth: Insights From an Opportunistic Multi‐Model Ensemble (MioMIP1)

Insights From an Opportunistic Multi-Model Ensemble (MioMIP1)
Authors: Natalie J Burls; Catherine Bradshaw; Agatha Margaretha De Boer; Nicholas Herold; Matthew Huber; Matthew Pound; Yannick Donnadieu; +17 Authors

Simulating Miocene Warmth: Insights From an Opportunistic Multi‐Model Ensemble (MioMIP1)

Abstract

AbstractThe Miocene epoch, spanning 23.03–5.33 Ma, was a dynamic climate of sustained, polar amplified warmth. Miocene atmospheric CO2 concentrations are typically reconstructed between 300 and 600 ppm and were potentially higher during the Miocene Climatic Optimum (16.75–14.5 Ma). With surface temperature reconstructions pointing to substantial midlatitude and polar warmth, it is unclear what processes maintained the much weaker‐than‐modern equator‐to‐pole temperature difference. Here, we synthesize several Miocene climate modeling efforts together with available terrestrial and ocean surface temperature reconstructions. We evaluate the range of model‐data agreement, highlight robust mechanisms operating across Miocene modeling efforts and regions where differences across experiments result in a large spread in warming responses. Prescribed CO2 is the primary factor controlling global warming across the ensemble. On average, elements other than CO2, such as Miocene paleogeography and ice sheets, raise global mean temperature by ∼2°C, with the spread in warming under a given CO2 concentration (due to a combination of the spread in imposed boundary conditions and climate feedback strengths) equivalent to ∼1.2 times a CO2 doubling. This study uses an ensemble of opportunity: models, boundary conditions, and reference data sets represent the state‐of‐art for the Miocene, but are inhomogeneous and not ideal for a formal intermodel comparison effort. Acknowledging this caveat, this study is nevertheless the first Miocene multi‐model, multi‐proxy comparison attempted so far. This study serves to take stock of the current progress toward simulating Miocene warmth while isolating remaining challenges that may be well served by community‐led efforts to coordinate modeling and data activities within a common analytical framework.

Countries
France, Netherlands, France, France, France, United Kingdom, United Kingdom
Keywords

Atmospheric Science, 550, Palaeontology, Paleoclimate Modelling, Miocene, 551, Oceanography, [SDU.STU.OC] Sciences of the Universe [physics]/Earth Sciences/Oceanography, Miocene surface temperature synthesis, [SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology, model intercomparison, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Model Intercomparision, paleoclimate, SDG 13 - Climate Action, polar amplification, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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