Gaskell, DE; Huber, M; O'Brien, CL; Inglis, GN; Acosta, RP; Poulsen, CJ; Hull, PM; (2022) The latitudinal temperature gradient and its climate dependence as inferred from foraminiferal δ18O over the past 95 million years. Proceedings of the National Academy of Sciences of the United States of America , 119 (11) , Article e2111332119. 10.1073/pnas.2111332119.

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Abstract

The latitudinal temperature gradient is a fundamental state parameter of the climate system tied to the dynamics of heat transport and radiative transfer. Thus, it is a primary target for temperature proxy reconstructions and global climate models. However, reconstructing the latitudinal temperature gradient in past climates remains challenging due to the scarcity of appropriate proxy records and large proxy–model disagreements. Here, we develop methods leveraging an extensive compilation of planktonic foraminifera δ18O to reconstruct a continuous record of the latitudinal sea-surface temperature (SST) gradient over the last 95 million years (My). We find that latitudinal SST gradients ranged from 26.5 to 15.3 °C over a mean global SST range of 15.3 to 32.5 °C, with the highest gradients during the coldest intervals of time. From this relationship, we calculate a polar amplification factor (PAF; the ratio of change in >60° S SST to change in global mean SST) of 1.44 ± 0.15. Our results are closer to model predictions than previous proxy-based estimates, primarily because δ18O-based high-latitude SST estimates more closely track benthic temperatures, yielding higher gradients. The consistent covariance of δ18O values in low- and high-latitude planktonic foraminifera and in benthic foraminifera, across numerous climate states, suggests a fundamental constraint on multiple aspects of the climate system, linking deep-sea temperatures, the latitudinal SST gradient, and global mean SSTs across large changes in atmospheric CO2, continental configuration, oceanic gateways, and the extent of continental ice sheets. This implies an important underlying, internally driven predictability of the climate system in vastly different background states.

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