Deriving dynamical models from paleoclimatic records: Application to glacial millennial-scale climate variability

被引:44
作者
Kwasniok, Frank [1 ]
Lohmann, Gerrit [2 ]
机构
[1] Univ Exeter, Sch Engn Math & Phys Sci, Exeter EX4 4QF, Devon, England
[2] Alfred Wegener Inst Polar & Marine Res, D-27570 Bremerhaven, Germany
来源
PHYSICAL REVIEW E | 2009年 / 80卷 / 06期
关键词
glaciology; Kalman filters; noise; proxy records (geophysical); stochastic processes; STOCHASTIC RESONANCE; OSCILLATIONS; TIMESCALES;
D O I
10.1103/PhysRevE.80.066104
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
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.
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页数:9
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