Collaborative Research: Targeted resampling of deep polar ice cores using information theory

Ice cores contain detailed accounts of Earth's climate history. The collection of an ice core can be logistically challenging, and extraction of data from the core can be time-consuming as well as susceptible to both human and machine error. Furthermore, locked in measurements from ice cores is information that scientists have not yet found ways to recover. This project will apply techniques from information theory to ice-core data to unlock that information. The primary goal is to demonstrate that information theory can (a) identify regions of a specific ice-core record that are in need of further analysis and (b) provide some specific guidance for that analysis. A secondary goal is to demonstrate that information theory has practical and scientific utility for studies of past climate. This project aims to use information theory in two distinct ways: first, to identify regions of a core where information appears to be damaged or missing, perhaps due to human and/or machine error. In the segment of the West Antarctic Ice Sheet Divide core that is 5000-8000 years old, for instance, information-theoretic methods reveal significant levels of noise, probably due to a laboratory instrument, and something that was not visible in the raw data. This is a particularly important segment of the record, as it contains valuable clues about climatic shifts and the onset of the Holocene. Targeted re-sampling of this segment of the core and reanalysis with newer laboratory apparatus could resolve the data issues. The second way in which information theory can potentially aid in ice-core analysis is by extracting climate signals from the data--such as the accumulation rate at the core site over the period of its formation. This quantity usually requires significant time and effort to produce, but information theory could help to streamline that process.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.