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Stochastic parameterisation schemes based on rigorous limit theorems.

机译：基于严格极限定理的随机参数化方案。

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摘要

In this study, theorem-based, generally applicable stochastic parameterisation schemes are developed and applied to a quasi-geostrophic model of extratropical atmospheric low-frequency variability (LFV). Hasselmann's method is developed from limiting theorems for slow-fast systems of ordinary differential equations (ODEs) and applied to this high-dimensional model of intermediate complexity comprised of partial differential equations with complicated boundary conditions. Seamless, efficient algorithms for integrating the parameterised models are developed, which require only minimal changes to the full model algorithm. These algorithms may be readily adapted to a range of climate models of greater complexity in parameterising the effects of fast, sub-grid scale processes on the resolved scales. For comparison, the Majda-Timofeyev-Vanden-Eijnden (MTV) parameterisation method is applied to this model.;The low-dimensional Hasselmann stochastic models perform well in simulating the statistics of the planetary-scale modes. In particular, a model with only one resolved (planetary-scale) mode captures the multiple regime behaviour of the full model. Although a fast-evolving synoptic-scale mode is of primary importance to the multiple regime behaviour, deterministic averaged forcing and not multiplicative noise is responsible for the regime behaviour in this model. The MTV models generate non-Gaussian statistics, but generally do not perform as well in capturing the climate statistics.;The seamless algorithms are first adapted to probe the multiple regime behaviour that characterises the full model LFV. In contrast to the conclusions of a previous study, it is found that the multiple regime behaviour is not the result of a nonlinear interaction between the leading two planetary-scale modes, but rather is the result of interactions among these two modes and the leading synoptic-scale mode.
机译：在这项研究中，开发了基于定理的，普遍适用的随机参数化方案，并将其应用于温带大气低频变率（LFV）的准地转模型。 Hasselmann的方法是从常微分方程（ODE）的慢速系统的极限定理发展而来，并应用于具有复杂边界条件的偏微分方程组成的这种中等复杂度的高维模型。开发了用于集成参数化模型的无缝高效算法，该算法仅需对完整模型算法进行最小的更改。这些算法可以很容易地适应一系列复杂度更高的气候模型，从而在参数化快速，次网格规模过程对已分解规模的影响方面进行参数化。为了进行比较，将Majda-Timofeyev-Vanden-Eijnden（MTV）参数化方法应用于该模型。;低维Hasselmann随机模型在模拟行星尺度模式的统计量方面表现良好。特别是，只有一个解析（行星尺度）模式的模型会捕获整个模型的多态行为。尽管快速发展的天气尺度模式对多模式行为至关重要，但在此模式中，确定性的平均强迫而非乘性噪声是该模式行为的原因。 MTV模型生成非高斯统计数据，但通常在捕获气候统计数据方面表现不佳。;首先，对无缝算法进行调整以探查表征完整模型LFV的多态行为。与以前的研究结论相反，发现多态行为不是前两种行星尺度模式之间非线性相互作用的结果，而是这两种模式与前天气现象之间相互作用的结果。比例模式。

著录项

  • 作者

    Culina, Joel David.;

  • 作者单位

    University of Victoria (Canada).;

  • 授予单位 University of Victoria (Canada).;
  • 学科 Atmospheric Sciences.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 188 p.
  • 总页数 188
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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