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Visual Exploration of Climate Variability Changes Using Wavelet Analysis

机译:利用小波分析对气候变异性进行可视化探索

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Due to its nonlinear nature, the climate system shows quite high natural variability on different time scales, including multiyear oscillations such as the El Ni˜no Southern Oscillation phenomenon. Beside a shift of the mean states and of extreme values of climate variables, climate change may also change the frequency or the spatial patterns of these natural climate variations. Wavelet analysis is a well established tool to investigate variability in the frequency domain. However, due to the size and complexity of the analysis results, only few time series are commonly analyzed concurrently. In this paper we will explore different techniques to visually assist the user in the analysis of variability and variability changes to allow for a holistic analysis of a global climate model data set consisting of several variables and extending over 250 years. Our new framework and data from the IPCC AR4 simulations with the coupled climate model ECHAM5/MPI-OM are used to explore the temporal evolution of El Ni˜no due to climate change.
机译:由于其非线性性质,气候系统在不同的时间尺度上表现出相当高的自然变异性,包括多年的振荡,例如厄尔尼诺〜南方涛动现象。除了平均状态和气候变量极端值的变化以外,气候变化还可能改变这些自然气候变化的频率或空间模式。小波分析是研究频域变异性的完善工具。但是,由于分析结果的大小和复杂性,通常很少会同时分析几个时间序列。在本文中,我们将探索不同的技术,以可视化的方式帮助用户分析变异性和变异性,从而对包含多个变量并持续250年的全球气候模型数据集进行整体分析。我们的新框架和来自IPCC AR4模拟以及耦合气候模型ECHAM5 / MPI-OM的数据被用于探索由于气候变化而导致的El Ni〜no的时间演变。

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