Search for: All records

Abstract PremiseThe Aptian–Albian (121.4–100.5 Ma) was a greenhouse period with global temperatures estimated as 10–15°C warmer than pre‐industrial conditions, so it is surprising that the most reliable CO₂estimates from this time are <1400 ppm. This low CO₂during a warm period implies a very high Earth‐system sensitivity in the range of 6 to 9°C per CO₂doubling between the Aptian‐Albian and today. MethodsWe applied a well‐vetted paleo‐CO₂proxy based on leaf gas‐exchange principles (Franks model) to twoPseudotorelliaspecies from three stratigraphically similar samples at the Tevshiin Govi lignite mine in central Mongolia (~119.7–100.5 Ma). ResultsOur median estimated CO₂concentration from the three respective samples was 2132, 2405, and 2770 ppm. The primary reason for the high estimated CO₂but with relatively large uncertainties is the very low stomatal density in both species, where small variations propagate to large changes in estimated CO₂. Indeed, we found that at least 15 leaves are required before the aggregate estimated CO₂approaches that of the full data set. ConclusionsOur three CO₂estimates all exceeded 2000 ppm, translating to an Earth‐system sensitivity (~3–5°C/CO₂doubling) that is more in keeping with the current understanding of the long‐term climate system. Because of our large sample size, the directly measured inputs did not contribute much to the overall uncertainty in estimated CO₂; instead, the inferred inputs were responsible for most of the overall uncertainty and thus should be scrutinized for their value choices. 

Paleo-CO2 reconstructions are integral to understanding the evolution of Earth system processes and their interactions given that atmospheric-CO2 concentrations are intrinsically linked to planetary function. In this talk, we use several case studies, spanning the 3 Phanerozoic Eras, to illustrate the potential of paleo-CO2 records to constrain the magnitude and state-dependency of equilibrium climate sensitivity, to advance our understanding of global biogeochemical cycles, to test the sensitivity of Earth System modeled atmospheric and oceanic circulation to PCO2 over a range of climate states, and to interrogate ecosystem—CO2—climate linkages and physiological responses to CO2. Further advances in these areas, however, are dependent on how well we ‘know’ paleo-CO2 estimates. CO2 estimates exist for much of the past half-billion years, but the degree to which the accuracy and precision of these estimates are constrained is quite variable, leading to substantial uncertainty and inconsistency in paleo-CO2 estimates. Potential sources of this uncertainty and inconsistency include an incomplete understanding of how environmental and ecophysiological conditions and processes imprint the CO2 proxy signals we measure, of the sensitivity of the CO2 estimates to this uncertainty, and differences in approaches to assigning uncertainties to CO2 estimates, among other factors. Application of newly established screening criteria, defined as part of an effort to improve our understanding of how atmospheric CO2 has varied through the Cenozoic, illustrates how the majority of pre-Cenozoic estimates are unreliable in their current form. To address these issues and to advance paleo-CO2 reconstruction, we introduce CO2PIP, a new community-scale project that takes a two-step approach to building the next generation Phanerozoic-CO2 record. Collective efforts are modernizing existing terrestrial-based CO2 estimates through additional analyses, measurements and proxy system modeling to constrain critical parameters used to estimate paleo-CO2. A set of forward proxy system models being developed in collaboration with the CO2 community, will provide a quantified representation of proxy sensitivities to environmental and ecophysiological conditions and processes that govern the CO2 signals. Ultimately, statistical inversion analysis of the simulated and modernized proxy datasets will be used to revise individual CO2 records and to build a new integrated model-data-constrained CO2 record for the Phanerozoic. 

The geological record encodes the relationship between climate and atmospheric carbon dioxide (CO₂) over long and short timescales, as well as potential drivers of evolutionary transitions. However, reconstructing CO₂beyond direct measurements requires the use of paleoproxies and herein lies the challenge, as proxies differ in their assumptions, degree of understanding, and even reconstructed values. In this study, we critically evaluated, categorized, and integrated available proxies to create a high-fidelity and transparently constructed atmospheric CO₂record spanning the past 66 million years. This newly constructed record provides clearer evidence for higher Earth system sensitivity in the past and for the role of CO₂thresholds in biological and cryosphere evolution. 

A variety of proxies have been developed to reconstruct paleo‐CO₂from fossil leaves. These proxies rely on some combination of stomatal morphology, leafδ¹³C, and leaf gas exchange. A common conceptual framework for evaluating these proxies is lacking, which has hampered efforts for inter‐comparison. Here we develop such a framework, based on the underlying physics and biochemistry. From this conceptual framework, we find that the more extensively parameterised proxies, such as the optimisation model, are likely to be the most robust. The simpler proxies, such as the stomatal ratio model, tend to under‐predict CO₂, especially in warm (>15^°C) and moist (>50%humidity) environments. This identification of a structural under‐prediction may help to explain the common observation that the simpler proxies often produce estimates of paleo‐CO₂that are lower than those from the more complex proxies and other, non‐leaf‐based CO₂proxies. The use of extensively parameterised models is not always possible, depending on the preservation state of the fossils and the state of knowledge about the fossil's nearest living relative. With this caveat in mind, our analysis highlights the value of using the most complex leaf‐based model as possible.