ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction
ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction
复制标题
当前气候模型中的 ENSO 动力学：使用非线性降维的研究
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
Stephen Wiggins
中科院分区：
文献类型：
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作者：
I. Ross;P. Valdes;Stephen Wiggins
抽象。线性降维技术，特别是主成分分析，被广泛用于气候数据分析，作为一种手段，以帮助解释高维数据集。这些线性方法可能不适合于分析气候系统中发生的非线性过程所产生的数据。近年来，非线性降维技术的发展为识别非线性动力学引起的气候数据中的低维流形提供了一个潜在的有用工具。在这里，我们应用Isomap，这样的技术之一，厄尔尼诺/南方涛动变化的热带太平洋海面温度的研究，比较观测数据与模拟从一些目前耦合的大气-海洋环流模型。我们使用Isomap来检查不同数据集中的厄尔尼诺变化，并评估Isomap方法对气候数据分析的适用性。我们的结论是，对于这里提出的应用程序，使用Isomap的分析不提供额外的信息以外，已经提供了主成分分析。
Abstract. Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality. These linear methods may not be appropriate for the analysis of data arising from nonlinear processes occurring in the climate system. Numerous techniques for nonlinear dimensionality reduction have been developed recently that may provide a potentially useful tool for the identification of low-dimensional manifolds in climate data sets arising from nonlinear dynamics. Here, we apply Isomap, one such technique, to the study of El Nino/Southern Oscillation variability in tropical Pacific sea surface temperatures, comparing observational data with simulations from a number of current coupled atmosphere-ocean general circulation models. We use Isomap to examine El Nino variability in the different datasets and assess the suitability of the Isomap approach for climate data analysis. We conclude that, for the application presented here, analysis using Isomap does not provide additional information beyond that already provided by principal component analysis.