论文标题
随机古气候学：建模Epica Ice Core气候记录
Stochastic Paleoclimatology: Modeling the EPICA Ice Core Climate Records
论文作者
论文摘要
我们分析和建模古气候时间序列的随机行为，并评估对更新世冰川周期期间气候变量偶联的影响。我们检查了800公里的二氧化碳，甲烷，一氧化二氮和温度代理数据，来自Epica Dome-C冰核，其特征是100〜Kyr冰川周期在广泛的时间范围内的波动覆盖。我们通过多重时间加权的下降波动分析来量化这种行为，该分别在所有记录中分别区分了100〜Kyr冰川周期的红色噪声和白噪声行为。这使我们能够将每个时间序列建模为一维的周期性非自主随机动力学系统，并评估物理过程的稳定性和模型模拟时间序列的忠诚度。我们将这种方法扩展到具有线性耦合术语的四变量模型，我们根据时间序列之间的相互关系来解释。发现甲烷和一氧化二氮具有明显的不稳定影响，而二氧化碳和温度的稳定影响较小。我们得出关于冰川过渡中因果关系以及可能促进这些耦合的气候过程的结论，并突出了进一步开发随机建模方法的机会。
We analyze and model the stochastic behavior of paleoclimate time series and assess the implications for the coupling of climate variables during the Pleistocene glacial cycles. We examine 800 kyr of carbon dioxide, methane, nitrous oxide, and temperature proxy data from the EPICA Dome-C ice core, which are characterized by 100~kyr glacial cycles overlain by fluctuations across a wide range of time scales. We quantify this behavior through multifractal time-weighted detrended fluctuation analysis, which distinguishes near red-noise and white-noise behavior below and above the 100~kyr glacial cycle respectively in all records. This allows us to model each time series as a one-dimensional periodic non-autonomous stochastic dynamical system, and assess the stability of physical processes and the fidelity of model-simulated time series. We extend this approach to a four-variable model with linear coupling terms, which we interpret in terms of the interrelationships between the time series. Methane and nitrous oxide are found to have significant destabilizing influences, while carbon dioxide and temperature have smaller stabilizing influences. We draw conclusions about causal relationships in glacial transitions and the climate processes that may have facilitated these couplings, and highlight opportunities to further develop stochastic modeling approaches.
