Understanding the causes and rates of climate change in the past requires accurate age models; however, age estimates for many climate records from ocean sediment cores are based on stratigraphic alignment of benthic G18O (a proxy for global ice volume and deep ocean temperature), which produces age uncertainties of several thousand years. This project focuses on creating more accurate benthic G18O age models with smaller uncertainties for the last glacial cycle (0-150,000 yr ago), a time period which includes the Last Glacial Maximum, the previous interglacial, two rapid deglaciations, and large amplitude millennial-scale variability. Over this time period, a major source of uncertainty for G18O alignments is that the timing of benthic G18O change can differ by 4000 years between different parts of the ocean. These differences have been observed during the last deglaciation at a few core sites with very accurate radiocarbon (14C) age models, but overall little is known about how benthic G18O signal propagation may have varied throughout the last glacial cycle. Specifically, this research will characterize benthic G18O lags and improve alignment age models using a three-pronged approach that incorporates ocean circulation models, analysis of paleoclimate data (benthic G18O and 14C) from ~100 globally distributed cores, and statistical inference. The final products of the project will be (1) probabilistic stacks (averages) describing regional and global patterns of benthic G18O variability, (2) probabilistic algorithms for multiproxy core alignments and for generating Bayesian inferences of lags, (3) a database of age models for ~300 cores with benthic G18O data, and (4) estimates of ocean circulation changes based on comparing benthic G18O data with different ocean model scenarios.
Paleoclimate studies rely on age models when identifying cause-and-effect (lead/lag) relationships, creating snapshots of the climate state at a specific point in time, or characterizing the magnitude of natural variability on different timescales. Such information is crucial for testing the effectiveness of climate models and improving confidence in their ability to simulate potential future climate changes. Compilations of marine sediment core data are also used to estimate past changes in global mean surface temperature and in deep ocean carbon storage. To maximize the spatial coverage of such datasets, they often include cores with indirect age estimates, such as benthic G18O alignment, that have large, poorly constrained uncertainties. This project will improve age and uncertainty estimates for benthic G18O alignments and allow for more informed selection of which data to include in compilations and overall better accuracy. Data-model comparison will also better constrain ocean circulation changes (e.g., mixing pathways and rates) and the surface climate signals which propagate to the deep ocean (e.g., distinguishing signals which originate from the North Atlantic versus Southern Ocean). These results may help describe the causal chain of events for past climate changes and identify isolated ocean reservoirs that may have sequestered carbon from the atmosphere during glaciations.
This project may benefit society by improving paleoclimate reconstructions used to validate the climate models that forecast future climate change. Its impact will be enhanced by incorporating results into community data compilation efforts. This research also bridges the gap between paleoclimate and the mathematical sciences and will provide interdisciplinary training to two graduate students. Research methods and findings will be incorporated into undergraduate and graduate classes through the development and dissemination of two course modules that include interactive computer lab activities. PI Lisiecki has a strong record of mentoring female and under-represented minority students; she also organizes bimonthly meetings for female Earth Science graduate students and post docs to discuss articles about overcoming the challenges faced by women in science and academia.