Low-Pass Filtering, Heat Flux, and Atlantic Multidecadal Variability

Low-Pass Filtering, Heat Flux, and Atlantic Multidecadal Variability
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DOI:
10.1175/jcli-d-16-0810.1
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发表时间:
2017-09-01
期刊:
影响因子:
4.9
通讯作者:
Bellomo, Katinka
Bellomo, Katinka
中科院分区:
地球科学2区
文献类型:
--
作者:
Cane, Mark A.;Clement, Amy C.;Bellomo, Katinka

文献摘要

被引文献

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在这个模式的研究中,作者探讨了大西洋的多年代际振荡(AMO)的海表温度(SST)信号的内部组件是无法区分的大气和海洋的白色噪声强迫的响应的可能性。在这里,复杂的模式进行了比较,没有外部变化的强迫与一维噪声驱动模式的SST。一般的解析表达式,得到未经滤波和低通滤波的超前滞后相关。结果表明,这个简单的模型再现了许多模拟温度,温度变化率和表面热通量之间的超前滞后关系。它的结论是,发现在低频率的海洋失去热量的大气温度是温暖的,这已被解释为表明,海洋环流驱动AMO,是一个必要的后果的事实,即在很长一段时间内的净热通量(海洋加大气)是零到一个很好的近似。它不区分大气和海洋作为AMO的来源,是一致的假设,AMO是由白色噪声热通量驱动。结果表明,文献中的一些结果是低通滤波的伪影,当底层数据是白色或红色噪声时,它会产生虚假的低频信号。它的结论是,在没有外部强迫的AMO在大多数GCM是一致的被驱动的白色噪声,主要来自大气。
In this model study the authors explore the possibility that the internal component of the Atlantic multidecadal oscillation (AMO) sea surface temperature (SST) signal is indistinguishable from the response to white noise forcing from the atmosphere and ocean. Here, complex models are compared without externally varying forcing with a one-dimensional noise-driven model for SST. General analytic expressions are obtained for both unfiltered and low-pass filtered lead-lag correlations. It is shown that this simple model reproduces many of the simulated lead-lag relationships among temperature, rate of change of temperature, and surface heat flux. It is concluded that the finding that at low frequencies the ocean loses heat to the atmosphere when the temperature is warm, which has been interpreted as showing that the ocean circulation drives the AMO, is a necessary consequence of the fact that at long periods the net heat flux (ocean plus atmosphere) is zero to a good approximation. It does not distinguish between the atmosphere and ocean as the source of the AMO and is consistent with the hypothesis that the AMO is driven by white noise heat fluxes. It is shown that some results in the literature are artifacts of low-pass filtering, which creates spurious low-frequency signals when the underlying data are white or red noise. It is concluded that in the absence of external forcing the AMO in most GCMs is consistent with being driven by white noise, primarily from the atmosphere.