Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems
Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems
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DOI：
10.1007/s00382-017-3969-2
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发表时间：
2018-08
期刊：
影响因子：
4.6
通讯作者：
F. Sévellec;H. Dijkstra;S. Drijfhout;Agathe Germe
中科院分区：
文献类型：
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作者：
F. Sévellec;H. Dijkstra;S. Drijfhout;Agathe Germe
在这项研究中，两种方法之间的关系，以评估海洋可预报性的年际到十年的时间尺度进行了研究。第一种实用的方法包括采样的初始条件的不确定性和评估的可预报性，通过这个合奏的时间的分歧。第二种方法提供了一个理论框架，以确定误差增长估计最佳线性增长模式。在线性化动力学和不确定性正态分布的假设下，可以从理论框架中确定系综的精确定量扩展。这种传播至少比实用方法给出的近似解便宜一个数量级。这一结果被应用到一个国家的最先进的海洋环流模式，以评估在北大西洋的四个典型的海洋指标的可预测性：大西洋经向翻转环流（AMOC）的强度，其热传输的强度，二维空间平均海表面温度（SST）在北大西洋，和三维空间平均温度在北大西洋。对于除SST外的所有检验指标，年际时间尺度上总不确定性的75%可归因于海洋初始条件的不确定性，而不是大气随机强迫。该理论方法还提供了对初始条件不确定性的敏感性模式，允许有针对性的测量，以提高预测的技能。有人建议，一个相对较小的船队的几个自主水下航行器可以减少70%的不确定性，在AMOC强度预测1-5年的提前期。
In this study, the relation between two approaches to assess the ocean predictability on interannual to decadal time scales is investigated. The first pragmatic approach consists of sampling the initial condition uncertainty and assess the predictability through the divergence of this ensemble in time. The second approach is provided by a theoretical framework to determine error growth by estimating optimal linear growing modes. In this paper, it is shown that under the assumption of linearized dynamics and normal distributions of the uncertainty, the exact quantitative spread of ensemble can be determined from the theoretical framework. This spread is at least an order of magnitude less expensive to compute than the approximate solution given by the pragmatic approach. This result is applied to a state-of-the-art Ocean General Circulation Model to assess the predictability in the North Atlantic of four typical oceanic metrics: the strength of the Atlantic Meridional Overturning Circulation (AMOC), the intensity of its heat transport, the two-dimensional spatially-averaged Sea Surface Temperature (SST) over the North Atlantic, and the three-dimensional spatially-averaged temperature in the North Atlantic. For all tested metrics, except for SST,75% of the total uncertainty on interannual time scales can be attributed to oceanic initial condition uncertainty rather than atmospheric stochastic forcing. The theoretical method also provide the sensitivity pattern to the initial condition uncertainty, allowing for targeted measurements to improve the skill of the prediction. It is suggested that a relatively small fleet of several autonomous underwater vehicles can reduce the uncertainty in AMOC strength prediction by 70% for 1–5 years lead times.