Stochastically-forced multidecadal variability in the North Atlantic: a model study
Stochastically-forced multidecadal variability in the North Atlantic: a model study
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DOI：
10.1007/s00382-013-1930-6
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发表时间：
2014-07
期刊：
影响因子：
4.6
通讯作者：
J. Mecking;N. Keenlyside;R. Greatbatch
中科院分区：
文献类型：
--
作者：
J. Mecking;N. Keenlyside;R. Greatbatch
观测显示，北大西洋出现了几十年的信号，但其时间尺度的潜在机制和原因仍不清楚。此前的研究表明，这可能是由北大西洋涛动(NAO)驱动的，北大西洋涛动是冬季大气变化的主要模式。为了进一步解决这个问题，全球海洋环流模型--欧洲海洋模型(NEMO)的核心--是由与NAO相关的2000年长的白噪声强迫驱动的。聚焦于关键的海洋环流型，我们发现大西洋子午线翻转环流(AMOC)和副极地涡旋(SPG)强度在低频都有增强的力量，但没有主导的时间尺度，因此没有提供仅限于海洋的振荡变率模式的证据。相反，这两个指数对NAO强迫的响应都是线性的，但响应时间不同。北纬30°AOC的变率在大于90年的时间尺度上明显增强，而SPG强度的变率在15a开始增加。通过构建简单的统计模型证实了不同的响应特征，表明AMOC和SPG的变率分别与前53和10个冬季的NAO变率有关。或者，可以分别使用七阶和五阶的自回归(AR)模型来重建AMOC和SPG强度。这两个统计模型都很好地重建了AMOC的年际和年代际变化，而另一方面，SPG强度的AR(5)重建只捕捉到了数十年的变化。使用这些方法重建海洋变量可以用于预测和模型的相互比较。
Observations show a multidecadal signal in the North Atlantic ocean, but the underlying mechanism and cause of its timescale remain unknown. Previous studies have suggested that it may be driven by the North Atlantic Oscillation (NAO), which is the dominant pattern of winter atmospheric variability. To further address this issue, the global ocean general circulation model, Nucleus for European Modelling of the Ocean (NEMO), is driven using a 2,000 years long white noise forcing associated with the NAO. Focusing on key ocean circulation patterns, we show that the Atlantic Meridional Overturning Circulation (AMOC) and Sub-polar gyre (SPG) strength both have enhanced power at low frequencies but no dominant timescale, and thus provide no evidence for a oscillatory ocean-only mode of variability. Instead, both indices respond linearly to the NAO forcing, but with different response times. The variability of the AMOC at 30°N is strongly enhanced on timescales longer than 90 years, while that of the SPG strength starts increasing at 15 years. The different response characteristics are confirmed by constructing simple statistical models that show AMOC and SPG variability can be related to the NAO variability of the previous 53 and 10 winters, respectively. Alternatively, the AMOC and the SPG strength can be reconstructed with Auto-regressive (AR) models of order seven and five, respectively. Both statistical models reconstruct interannual and multidecadal AMOC variability well, while on the other hand, the AR(5) reconstruction of the SPG strength only captures multidecadal variability. Using these methods to reconstruct ocean variables can be useful for prediction and model intercomparision.