Estimation of the SST Response to Anthropogenic and External Forcing and Its Impact on the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation
Estimation of the SST Response to Anthropogenic and External Forcing and Its Impact on the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation
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DOI：
10.1175/jcli-d-17-0009.1
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发表时间：
2017-12-01
影响因子：
4.9
通讯作者：
Kwon, Young-Oh
中科院分区：
文献类型：
--
作者：
Frankignoul, Claude;Gastineau, Guillaume;Kwon, Young-Oh
利用历史气候模拟的两个大型集合(LES)，比较了各种统计方法如何估计人为和其他外部强迫引起的海表面温度(SST)变化，以及它们的去除如何影响内部产生的大西洋年代际振荡(AMO)、太平洋年代际振荡(PDO)和大西洋经向翻转环流(AMOC)的SST足迹。通过减去全球平均SST(GM)或对其进行线性回归(REGR)来去除强迫SST信号会在太平洋产生很大的误差。多维集合经验模式分解(MEEMD)和二次去趋势法只能有效地去除一维空间中的强迫SST信号，不能将火山喷发的短期响应与SST的自然变化分开。去除线性趋势效果不佳。两种基于线性逆模型(LIM)的方法，一种是前导LIM模式表示强迫信号，另一种是使用最优摄动滤波器(LIMopt)，其效果一直很好。然而，前两个LIM模式有时需要表示强迫信号，因此建议使用更健壮的LIMopt。在这两个地区，自然的AMO变率似乎主要是由亚极地北大西洋的AMOC驱动的，而不是在副热带和热带地区，并且AMOC-AMO相关的散布在个体集合成员之间很大。在1900-2015年的三个观测海温重建中，线性和二次去趋势、MEEMD和GM产生的AMO行为略有不同，而REGR产生较小的PDO幅度。根据LIMopt，只有大约30%的AMO可变性是内部产生的，而PDO的可变性超过90%。讨论了自然海温变率对全球变暖间歇期的贡献。
Two large ensembles (LEs) of historical climate simulations are used to compare how various statistical methods estimate the sea surface temperature (SST) changes due to anthropogenic and other external forcing, and how their removal affects the internally generated Atlantic multidecadal oscillation (AMO), Pacific decadal oscillation (PDO), and the SST footprint of the Atlantic meridional overturning circulation (AMOC). Removing the forced SST signal by subtracting the global mean SST (GM) or a linear regression on it (REGR) leads to large errors in the Pacific. Multidimensional ensemble empirical mode decomposition (MEEMD) and quadratic detrending only efficiently remove the forced SST signal in one LE, and cannot separate the short-term response to volcanic eruptions from natural SST variations. Removing a linear trend works poorly. Two methods based on linear inverse modeling (LIM), one where the leading LIM mode represents the forced signal and another using an optimal perturbation filter (LIMopt), perform consistently well. However, the first two LIM modes are sometimes needed to represent the forced signal, so the more robust LIMopt is recommended. In both LEs, the natural AMO variability seems largely driven by the AMOC in the subpolar North Atlantic, but not in the subtropics and tropics, and the scatter in the AMOC-AMO correlation is large between individual ensemble members. In three observational SST reconstructions for 1900-2015, linear and quadratic detrending, MEEMD, and GM yield somewhat different AMO behavior, and REGR yields smaller PDO amplitudes. Based on LIMopt, only about 30% of the AMO variability is internally generated, as opposed to more than 90% for the PDO. The natural SST variability contribution to global warming hiatus is discussed.