Quick overview

In this project, I try to understand how much the Earth warms as carbon dioxide, which traps heat in the atmosphere, increases. Scientists still disagree on how much warming to expect in the future, which makes planning and decision-making difficult.

Modern measurements only show recent climate conditions. To understand a wider range of possibilities, I studied several periods in Earth’s past when carbon dioxide levels were higher, making the planet warmer and changing how much snow and ice covered it. Together, these periods help show how Earth may respond as human-caused warming continues.

To estimate how warm the planet was during these periods, I used natural evidence preserved in ocean mud and fossils. I then combined these estimates with results from many climate model experiments. I found that carbon dioxide caused more warming during cooler periods, when large ice sheets were present. This suggests that future warming could be especially strong during times when ice sheets are present and vulnerable to melting, meaning even small changes in future warming could have large consequences.

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Scientific abstract

Equilibrium climate sensitivity (ECS) quantifies the amount of warming resulting from a doubling of the atmospheric CO2 forcing. Despite recent advancements in climate simulation capabilities and global observations, there remains large uncertainty on the degree of future warming. To help alleviate this uncertainty, past climates provide a valuable insight into how the Earth will respond to elevated atmospheric CO2. However, there is evidence to suggest that ECS is dependent on background climate warmth, which may interfere with the direct utilization of paleo-ECS to understand present-day ECS. Thus, it is important that a range of different climate states are considered to better understand the factors modulating the relationship between CO2 and temperature. In this study, we focus on three time intervals: the mid-Pliocene Warm Period (3.3 – 3.0 Ma), the mid-Miocene (20 – 11.6 Ma), and the early Eocene (~50 Ma), in order to sample ECS from Cenozoic coolhouse to hothouse climates (see image above). Here, we combine a linear framework of constraining the ECS and its uncertainty with several published methods to estimate the global mean surface temperature (GMST) from sparse proxy records. This framework utilizes an emergent constraint between the simulated GMST changes and climate sensitivities across the model ensemble. For each time interval, we employ a combination of parametric and non-parametric functions, coupled with a probabilistic approach to derive a refined estimate. Preliminary results for the Pliocene indicate a GMST reconstruction of approximately 19.3°C, which is higher than previous estimates that were derived using only marine records. Using this estimate, we calculate an ECS that is also higher than previously published values, especially due to the inclusion of high-latitude terrestrial temperature records into our estimates. Intriguingly, using the consistent methodology, our calculated ECS for the early Eocene and the mid-Miocene are lower than that of the mid-Pliocene. This result does not support an amplified ECS in hothouse climate, and points to a potentially important role of ice albedo feedback in amplifying the ECS in coolhouse climate. Ongoing work will conduct sensitivity testing and further investigate the source for the estimated ECS state dependency between these climate intervals.