An empirical model of decadal ENSO variability
An empirical model of decadal ENSO variability
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DOI：
10.1007/s00382-012-1424-y
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发表时间：
2012-07
期刊：
影响因子：
4.6
通讯作者：
S. Kravtsov
中科院分区：
文献类型：
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作者：
S. Kravtsov
本文利用ENSO指数的经验非线性随机模型构建并模拟了El Niño/南方涛动（ENSO）特征年代际变化的潜在可预测性。该模式将全球海表温度（SST）异常分解为年代际与次年代际海表温度方差比值最大的模态，以定义称为典型变量（cv）的低频预测因子。当对整个海温时间序列进行处理时，发现首个典型变量（CV-1）与区域平均海温时间序列具有良好的相关性，表现出非均匀的增温趋势，而后两个典型变量（CV-2和CV-3）描述的长期变率可能与大西洋多年代际涛动（AMO）和太平洋年代际涛动（PDO）信号的组合有关。相应的ENSO模型使用所有三个（cv 1-3）或仅使用AMO/ pdo相关（cv 2和3）预测因子，很好地捕获了观测到的ENSO自相关函数、概率密度函数、季节依赖性，以及最重要的是观测到的ENSO方差的年代际调制。后一种调制及其对cv的依赖，与多元线性逆模型模拟的ENSO随机年代际变化的零假设不一致。交叉验证的ENSO方差预测表明，在十年提前期有潜在的有用技能。因此，这些发现表明，ENSO变率的年代际变化是可以预测的，这取决于我们预测AMO/ pdo型气候模式的能力；后一种预测可能需要基于动态模型的模拟，而不是像本文中那样基于纯粹的统计方案。
This paper assesses potential predictability of decadal variations in the El Niño/Southern Oscillation (ENSO) characteristics by constructing and performing simulations using an empirical nonlinear stochastic model of an ENSO index. The model employs decomposition of global sea-surface temperature (SST) anomalies into the modes that maximize the ratio of interdecadal-to-subdecadal SST variance to define low-frequency predictors called the canonical variates (CVs). When the whole available SST time series is so processed, the leading canonical variate (CV-1) is found to be well correlated with the area-averaged SST time series which exhibits a non-uniform warming trend, while the next two (CV-2 and CV-3) describe secular variability arguably associated with a combination of Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO) signals. The corresponding ENSO model that uses either all three (CVs 1–3) or only AMO/PDO-related (CVs 2 and 3) predictors captures well the observed autocorrelation function, probability density function, seasonal dependence of ENSO, and, most importantly, the observed interdecadal modulation of ENSO variance. The latter modulation, and its dependence on CVs, is shown to be inconsistent with the null hypothesis of random decadal ENSO variations simulated by multivariate linear inverse models. Cross-validated hindcasts of ENSO variance suggest a potential useful skill at decadal lead times. These findings thus argue that decadal modulations of ENSO variability may be predictable subject to our ability to forecast AMO/PDO-type climate modes; the latter forecasts may need to be based on simulations of dynamical models, rather than on a purely statistical scheme as in the present paper.