Date, Time, Location: July 12th at 9am in Ford ES&T room L1114, https://bit.ly/3NQIvkP

Committee Member names: Jean Lynch-Stieglitz, Emanuele di Lorenzo, Annalisa Bracco, Heather Ford, Takamitsu Ito

Thesis title: Utilizing Subsurface-Dwelling Foraminifera for Quantitative Paleoclimate Reconstructions

Thesis abstract: Foraminifera are useful tools for paleoclimatology (how the climate was different in the past) with many proxies for key ocean variables in their shells. Subsurface-dwelling foraminifera have been underutilized in paleoclimate due to their inherent habitat uncertainty; much research with these species has been qualitative in the past. I outline a methodology for using these species quantitatively for paleoclimate reconstruction and apply it to the Last Glacial Maximum (LGM). Firstly, I compile a database of foraminiferal data to quantitively estimate the error in their habitats. Using these uncertainty estimates, I describe a regression method to estimate an ocean profile that can reconstruct important features in the ocean such as the thermocline. Using five species of foraminifera that live in the surface, subsurface, and bottom of the ocean, this method recreates large scale features in the thermocline across the Tropical Pacific as well as changes between the Holocene and LGM at published core sites. Finally, I apply this method to a dataset of LGM foraminiferal data for sites across the Tropical Pacific. After filling in the data gaps for these sites, I find that there were heterogenous changes in the Tropical Pacific thermocline, with no change in the Western Pacific thermocline and a deepening at some sites in the Eastern Pacific. Looking along a transect in the Western Pacific, I find that there are structural differences between the profiles estimated from LGM data and the Holocene climatology, suggesting a change in atmospheric circulation during the past. By improving the ability to utilize these recorders of subsurface ocean conditions, we can better understand how climate was different in the past and how well climate models can recreate those differences.