T237 Insights from Microfossils and Their Modern Analogs: From Traditional and Emerging Approaches, to Critical Re-Evaluations (Posters)

Wednesday, 18 October 2023
8:00 AM - 5:30 PM
Hall B

MODELING HIGH-RESOLUTION VARIATION IN CENOZOIC DEEP-SEA PALEOTEMPERATURE AND BARYSTATIC SEA LEVEL FROM BENTHIC FORAMINIFERAL δ18O AND MG/CA DATA

Paper number: T237-7
Program: Technical Sessions
Time: 8:00 AM – 5:30 PM

Authors

Abstract

Determining high-resolution variations in Cenozoic δ18O of seawater (δ18O sw) and barystatic sea level (BSL) from benthic foraminiferal δ18O (δ18Ob) represents a challenge considering complexities in separating the isotopic signatures of deep-sea temperature changes and ice volume fluctuations. Comprehensively considering recent advances in methods and new data that can be applied to identify these signals, we have created a numerical model that facilitates the estimation of paleotemperature and BSL variations through the Cenozoic. The model primarily relies on Pacific δ18Ob measurements and global deep-sea foraminiferal Mg/Ca data. The global Mg/Ca data is transformed to a Pacific basin deep-sea paleotemperature estimate using Bayesian hierarchical modeling with Gaussian process priors. A modeled calculation of BSL begins with a given initial temperature and proceeds using a set of equations that parameterize the proportion of δ18Ob changes that reflect alterations in paleotemperature over time. A benthic foraminiferal paleotemperature equation can then be used to generate estimates of δ18O sw and paleotemperature at each timestep. BSL is then determined from the modeled δ18O sw values using an ice-sheet model that accounts for temporal variability in the relationship between δ18O sw and BSL variations. A Markov chain Monte Carlo algorithm is used to identify model parameters that produce: 1) an estimate of BSL change that correlates closely with stable-isotope independent estimates of BSL variation derived from the stratigraphic record; and 2) paleotemperature variation implied by differences in measured Pacific δ18Ob and modeled δ18O sw that corresponds with Pacific deep-sea paleotemperature estimates derived from the Gaussian process regression applied to the Mg/Ca data. The model resolution is limited only by data sampling rate of δ18Ob, and uncertainties are quantified using the Bayesian optimization framework. The model reveals Milankovitch-scale sea-level variations increased from ~5-10m in the Eocene, to ~25m through the Oligocene and Early Miocene, and to 30-40m in the Late Miocene, with a 50m sea level fall during event Oi-1. The ice-sheet model suggests early northern hemisphere glaciation post-Oi-1, and a consistent Greenland ice sheet presence in the time since, excluding the mid-Miocene climate optimum.

Geological Society of America Abstracts with Programs. Vol. 55, No. 6

doi: 10.1130/abs/2023AM-395719

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