Kalman Filtering and Smoothing of Sediment Records from the Atlantic Ocean over the last 20 KYRS

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Paleoclimatology is a rapidly evolving field, with a sustained production of records with improved accuracy and chronology. As the number of such records increases, the question of how to interpret them in the presence of a dynamical model has emerged. This work, led by a researcher at the Woods Hole Oceanographic Institution in Massachusetts, develops an inverse method for assimilating long time series of sea surface temperature and other oceanic properties, such as those generated from the analysis of sediment cores, into three-dimensional models of ocean circulation. The computational challenge posed by data assimilation over geologic time scales will be addressed by relying on a model with simplified dynamics and on a partitioned Kalman filter & smoother. The filter & smoother will be applied to drive the model with a collection of sediment records over the last 20,000 years from the North Atlantic Ocean. The movements of large-scale hydrographic fronts and the attendant circulation changes over this time interval will be estimated in a manner that is consistent with both sediment data and ocean dynamics, thereby allowing various paleoceanographic hypotheses to be tested. By estimating the time-dependent state of the North Atlantic Ocean over the last 20,000 years, the project will provide a perspective on ongoing changes in ocean circulation that are postulated from instrumental records. This project brings together an ocean modeler, a paleoceanographer, and two physical oceanographers to ensure a robust approach to the various aspects of the project. These participants include two collaborators from French institutions. Funding supports a graduate student and a post-doctoral scholar at the Woods Hole Oceanographic Institution.