Abstract. Constructing accurate age models for Pleistocene marine sediments is crucial for our understanding of glacial-interglacial cycles and other climatic processes. Benthic foraminiferal δ18O stacks, a proxy for ice sheet and climate evolution, are often used for stratigraphic alignment and chronology development in deep-sea sedimentary records, in combination with biostratigraphy, paleomagnetism, and radioisotopic constraints. Selection of an appropriate benthic δ18O alignment target influences the derived chronology at a given site, and divergent regional trends in benthic δ18O highlight the need for ocean-specific benthic δ18O stacks. The specific scientific question to be addressed by a study may also influence whether the alignment target should include astronomical tuning. Here, we introduce three benthic δ18O stacks – Atlantic, Pacific, and global – with three distinct chronologies for the global stack that incorporate astronomical forcing constraints to various degrees. The new global stack utilizes data from 221 cores and includes 45 % more data than the previous “ProbStack” (Ahn et al., 2017). Hand-tuned regional and global stacks, intended as updates to the “LR04” stack (Lisiecki and Raymo, 2005), incorporate chronologies transferred from absolutely dated archives during 0–654 thousand years ago (ka) and an astronomically forced ice sheet model during 654–2700 ka. Due to the heterogeneous nature of the age constraints used for these stacks, we call them BIGSTACKmixed, BIGSTACKmixedA, and BIGSTACKmixedP. For applications where astronomical tuning should be minimized, we present a global stack primarily constrained by geomagnetic reversal age estimates, BIGSTACKmagrev. We also develop a third age model, BIGSTACKauto, which uses an automated optimization algorithm to “minimally tune” the stack to the pervasive ∼ 41 kyr obliquity cycle, while avoiding assumptions about astronomical phase relationships. This suite of stacks offers flexibility in choosing δ18O stratigraphic alignment targets, to allow a wide range of applications in paleoceanographic hypothesis testing.
Zhou et al. (2026) studied this question.