title: Deriving dynamical models from paleoclimatic records: application to glacial millennial-scale climate variability.
abstract: A method for systematically deriving simple nonlinear dynamical models from ice-core data is proposed. It offers a tool to integrate models and theories with paleoclimatic data. The method is based on the unscented Kalman filter, a nonlinear extension of the conventional Kalman filter. Here, we adopt the abstract conceptual model of stochastically driven motion in a potential that allows for two distinctly different states. The parameters of the model-the shape of the potential and the noise level-are estimated from a North Greenland ice-core record. For the glacial period from 70 to 20 ky before present, a potential is derived that is asymmetric and almost degenerate. There is a deep well corresponding to a cold stadial state and a very shallow well corresponding to a warm interstadial state.
authors.affiliation: School of Engineering, Mathematics and Physical Sciences, University of Exeter, North Park Road, Exeter, United Kingdom. f.kwasniok@exeter.ac.uk
authors.forename: Frank
authors.initials: F
authors.lastname: Kwasniok
authors.forename: Gerrit
authors.initials: G
authors.lastname: Lohmann
mesh_terms: D000465:Algorithms; D002980:Climate; D003080:Cold Temperature; D003198:Computer Simulation; D006116:Greenland; D007053:Ice; D008962:Models, Theoretical; D010163:Paleontology / Q000379:methods; D015203:Reproducibility of Results; D013269:Stochastic Processes; D013696:Temperature; D013997:Time Factors
chemical_list: D007053:Ice