Past Ocean Circulation and Climate Change

This webinar is part of a special series celebrating 20 years of Climate of the Past.

Please find the video on the EGU YouTube channel.

Mon, 24 Nov 2025, 24:00 CEST

Conveners: Lorraine Liesicki & Laurie Menviel

This webinar will explore the relationship between ocean circulation and climate change. The invited talks will provide new evidence of changes in deep water formation, or changes in surface circulation and how they impacted global climate and the carbon cycle. The session will emphasize the importance of understanding ocean dynamics in projecting the effects of climate change.

Guest speakers:

  • Helen Bostock (The University of Queensland, Australia)
  • Sam Sheriff-Tadano (University of the Ryukyus, Japan)

Carbon isotopes in planktic foraminifera – an under-utilized resource in paleoceanography

Helen Bostock

Planktic foraminifera have been analyzed from hundreds of cores globally. Planktic oxygen isotopes have been used to develop age models, and when corrected for temperature, used as a salinity indicator. The carbon isotopes from these planktic foraminifera are rarely analyzed as they are often noisy, and are influenced by several different factors which are difficult to entangle. Here, I would like to present how carbon isotopes from planktic foraminifera can provide information about paleo-ocean circulation.

Isolating Feedback Mechanisms to Unravel Glacial climate variability

Sam Sheriff-Tadano

Complex coupled climate models have successfully reproduced intrinsic atmosphere-sea ice-ocean variabilities that resemble Dansgaard-Oeschger cycles. However, the driving mechanisms of these cycles remain debated due to the interactions within the climate system. Here, we use a complex climate model to quantitatively assess the role of individual feedback mechanisms by deactivating some key processes. Our results provide a novel understanding of how specific feedbacks control climate variability and offer new insights for interpreting differences across various climate models.