论文标题

上海上热含量的内在海洋际变异性

Intrinsic oceanic decadal variability of upper-ocean heat content

论文作者

Constantinou, Navid C., Hogg, Andrew McC.

论文摘要

大气和海洋通过空气相互作用耦合。大气条件会助长海洋循环及其变异性,但是在际际时间尺度上,海洋过程影响大气的程度尚不清楚。特别是,这种低频可变性很难从简短的观测记录中提取,这意味着气候模型是解决此问题的主要工具。在这里,我们评估了海洋的内在变异性如何导致际际时尺度变化的上洋热含量的模式。这些模式具有反馈大气的潜力,从而影响了可变性的气候模式,例如厄尔尼诺现象或十年中太平洋振荡。我们在三种不同的水平分辨率下使用全球海洋冰循环模型的输出,每种水平分辨率都由相同的大气再分析驱动。为了消除海洋对大气强迫的直接反应从内在的海洋动力学引起的可变性的可变性,我们比较模型与工会间强迫的驱动(1958-2018)和模型运行,并以重复年份强迫驱动。具有依赖涡流参数的粗分辨率的模型显示,(i)在十年时间尺度上显着降低了近代热含量的方差,并且(ii)与较高分辨率模型相比,低频变异性的空间模式的差异。气候预测通常是使用具有粗分辨率海洋组件的一般循环模型来完成的。因此,这些偏见会影响我们预测变异性际气候模式的能力,进而阻碍气候预测。我们的结果表明,为了改善气候预测,社区应朝着具有较高海洋分辨率的气候模型迈进。

Atmosphere and ocean are coupled via air-sea interactions. The atmospheric conditions fuel the ocean circulation and its variability, but the extent to which ocean processes can affect the atmosphere at decadal time scales remains unclear. In particular, such low-frequency variability is difficult to extract from the short observational record, meaning that climate models are the primary tools deployed to resolve this question. Here, we assess how the ocean's intrinsic variability leads to patterns of upper-ocean heat content that vary at decadal time scales. These patterns have the potential to feed back on the atmosphere and thereby affect climate modes of variability, such as El Niño or the Interdecadal Pacific Oscillation. We use the output from a global ocean-sea ice circulation model at three different horizontal resolutions, each driven by the same atmospheric reanalysis. To disentangle the variability of the ocean's direct response to atmospheric forcing from the variability due to intrinsic ocean dynamics, we compare model runs driven with inter-annually varying forcing (1958-2018) and model runs driven with repeat-year forcing. Models with coarse resolution that rely on eddy parameterizations, show (i) significantly reduced variance of the upper-ocean heat content at decadal time scales and (ii) differences in the spatial patterns of low-frequency variability compared with higher resolution models. Climate projections are typically done with general circulation models with coarse-resolution ocean components. Therefore, these biases affect our ability to predict decadal climate modes of variability and, in turn, hinder climate projections. Our results suggest that for improving climate projections, the community should move towards coupled climate models with higher oceanic resolution.

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