Bayesian Data Analysis for Revealing Causes of the Middle Pleistocene Transition.

ABSTRACT: Currently, causes of the middle Pleistocene transition (MPT) - the onset of large-amplitude glacial variability with 100 kyr time scale instead of regular 41 kyr cycles before - are a challenging puzzle in Paleoclimatology. Here we show how a Bayesian data analysis based on machine learning approaches can help to reveal the main mechanisms underlying the Pleistocene variability, which most likely explain proxy records and can be used for testing existing theories. We construct a Bayesian data-driven model from benthic δ¹⁸O records (LR04 stack) accounting for the main factors which may potentially impact climate of the Pleistocene: internal climate dynamics, gradual trends, variations of insolation, and millennial variability. In contrast to some theories, we uncover that under l

SUBMITTER: Mukhin D 

PROVIDER: S-EPMC6513842 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature