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Cambridge NERC Doctoral Training Partnerships

Graduate Research Opportunities
 
Brief summary: 
This project aims at developing a new quantitative method for synchronization of ice core records that will enable generating improved reconstructions of volcanism and solar forcing of the past 60,000 years.
Importance of the area of research concerned: 
The stratigraphic correlation of ice-core records plays a central role in palaeoclimate research as it iused to develop mutually consistent timescales that allow quantifying how rapidly climate change propagates across the globe, as well as reconstructing volcanism and solar activity histories. To present, most stratigraphic correlations are performed manually using common tie points observed in records of atmospheric gas concentrations (Buizert et al., 2015), volcanic signatures of large eruptions (Svensson et al., 2020), and cosmogenic radionuclide proxies of solar irradiance (Raisbeck et al., 2017). However, this synchronization method often hinges on a limited number of tie points, is inherently subjective, and does not provide a quantification of the confidence of the correlation. Alignment algorithms based on Bayesian probability theory can help us address these limitations. In particular, they have an enormous and, as of yet, underexploited potential for automating the correlation of ice-core records, replacing subjectivity with reproducibility, ensuring a truly continuous synchronization, and deriving confidence bands associated with the syncronization procedure.
Project summary : 
This project aims at developing a Bayesian algorithm for automated and continuous synchronization of ice cores. The approach will leverage machine learning techniques to identify the correlation probabilities between records of global volcanisms, and cosmogenic radionuclide data of solar variability. The method will consider correlations based on multiple reconstructions in each ice core and incorporate independent chrono-stratigraphic information. The algorithm will provide an essential tool to construct robust ice-core timescales and will bring a new degree of accuracy and precision to the use of synchronization in ice-core chronologies. More importantly, the methodology will be applied to derive new reconstructions of volcanism and solar activity for the past 60,000 years, which will provide fundamental knowledge on the sensitivity of the climate system to external forcing.
What will the student do?: 
The successful applicant will apply machine learning methods to develop an automated synchronization algorithm that models alignments of ice cores based on the signal registered in volcanic and solar activity sequences from Greenlandic and Antarctic ice cores. High-resolution records of sulfur, sulfate, chloride, and electrical conductivity measurements of the ice will be employed as indicators of volcanic signals, whereas records of cosmogenic isotopes such as 10Be and 36Cl will be used to infer changes in solar variability. The new algorithm will be employed to establish precise and quantitative synchronizations of Greenland and Antarctic ice cores, as well as to generate climate forcing reconstructions of volcanic emission strength and solar irradiance.
References - references should provide further reading about the project: 
Buizert, C., K. M. Cuffey, J. P. Severinghaus, D. Baggenstos, T. J. Fudge, E. J. Steig, B. R. Markle et al. "The WAIS Divide deep ice core WD2014 chronology–Part 1: Methane synchronization (68–31 ka BP) and the gas age–ice age difference." Climate of the Past 11, no. 2 (2015): 153-173.
Svensson, Anders, Dorthe Dahl-Jensen, Jørgen Peder Steffensen, Thomas Blunier, Sune O. Rasmussen, Bo M. Vinther, Paul Vallelonga et al. "Bipolar volcanic synchronization of abrupt climate change in Greenland and Antarctic ice cores during the last glacial period." Climate of the Past 16, no. 4 (2020): 1565-1580.
Raisbeck, Grant M., Alexandre Cauquoin, Jean Jouzel, Amaelle Landais, Jean-Robert Petit, Vladimir Y. Lipenkov, Juerg Beer et al. "An improved north–south synchronization of ice core records around the 41 kyr 10 Be peak." Climate of the Past 13, no. 3 (2017): 217-229.
Applying
You can find out about applying for this project on the Department of Geography page.
Dr Francesco Muschitiello
Department of Geography Graduate Administrator