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Emulation and interpretation of high-dimensional climate model outputs

机译：高维气候模型输出的仿真和解释

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摘要

Running complex computer models can be expensive in computer time, while learning about the relationships between input and output variables can be difficult. An emulator is a fast approximation to a computationally expensive model that can be used as a surrogate for the model, to quantify uncertainty or to improve process understanding. Here, we examine emulators based on singular value decompositions (SVDs) and use them to emulate global climate and vegetation fields, examining how these fields are affected by changes in the Earth's orbit. The vegetation field may be emulated directly from the orbital variables, but an appealing alternative is to relate it to emulations of the climate fields, which involves high-dimensional input and output. The SVDs radically reduce the dimensionality of the input and output spaces and are shown to clarify the relationships between them. The method could potentially be useful for any complex process with correlated, high-dimensional inputs and/or outputs.
机译：运行复杂的计算机模型可能会花费大量的计算机时间，而了解输入和输出变量之间的关系可能会很困难。仿真器是计算成本高昂的模型的快速近似，可以用作模型的替代品，以量化不确定性或改善过程理解。在这里，我们研究基于奇异值分解（SVD）的仿真器，并使用它们来仿真全球气候和植被场，并研究这些场如何受到地球轨道变化的影响。植被场可以直接从轨道变量进行模拟，但是一种有吸引力的替代方法是将其与气候场的模拟相关联，这涉及高维度的输入和输出。 SVD从根本上减少了输入和输出空间的维数，并显示为阐明它们之间的关系。该方法对于具有相关的高维输入和/或输出的任何复杂过程都可能有用。

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