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A new early warning indicator of abrupt climate change based on the changing normalized dynamic range
International Journal of Climatology ( IF 3.5 ) Pub Date : 2021-01-11 , DOI: 10.1002/joc.7000
Qiong Wu 1, 2, 3 , Xiao‐qiang Xie 4 , Ying Mei 4 , Wen‐ping He 4
Affiliation  

An abrupt change will occur when the system is forced to across a critical threshold. This study presents a novel early warning indicator—the changing normalized dynamic range. We use a one‐variable climate model and three simple folding models to test the performance of the new early warning indicator. The results show that the present indicator exhibits a statistically significant increase or decrease in all of tests at a significance level of α = .05 before a dynamical system with a folding bifurcation approaches a tipping point. Comparing the well‐known autocorrelation coefficient with the normalized dynamic range, it is found that autocorrelation coefficient performs well in most of tests, which shows an almost monotonous increasing or decreasing trend for an upcoming abrupt change. However, autocorrelation coefficient exhibits a diametrically opposite trend for a noise‐induced abrupt change in a two‐dimensional vegetable model. The kurtosis coefficient can perform well in most of the tests used in this study, however, fails to give an early warning in a particular case. Moreover, the magnitude of change of the autocorrelation and kurtosis is much smaller than that of the normalized dynamic range before the four folding models approach its tipping point. Therefore, the performance of the new indicator for warning an abrupt change in advance is better than that of the autocorrelation coefficient as well as kurtosis coefficient, which can make up for the deficiency of the kurtosis coefficient and autocorrelation coefficient to some extent.

中文翻译:

基于变化的归一化动态范围的新的突然的气候变化预警指标

当系统被迫超过临界阈值时,将会发生突然的变化。这项研究提出了一种新颖的预警指标-不断变化的标准化动态范围。我们使用单变量气候模型和三个简单折叠模型来测试新的预警指示器的性能。结果表明,在显着性水平为α = .05时,本指标在所有测试中均显示出统计学上显着的增加或减少在具有折叠分叉的动力学系统达到临界点之前。将众所周知的自相关系数与归一化的动态范围进行比较,发现自相关系数在大多数测试中表现良好,对于即将到来的突然变化显示出几乎单调的上升或下降趋势。然而,在二维蔬菜模型中,自相关系数呈现出与噪声引起的突然变化截然相反的趋势。峰度系数在本研究中使用的大多数测试中都可以很好地执行,但是在特定情况下不能给出预警。此外,在四个折叠模型接近其临界点之前,自相关和峰度的变化幅度远小于归一化动态范围的变化幅度。所以,
更新日期:2021-01-11
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