Collaborative Research: Understanding Atlantic Decadal-to-Multidecadal Variability and Predictability

该奖项下的研究将审查大西洋海洋表面温度(SSTs)的可变性和可预测性，特别侧重于“天气噪声”在产生十年和十年SST波动方面的作用。天气噪音是指天气模式的变化，它与海温无关，是由于空气运动的混乱性质而产生的。尽管持续时间较短，但天气系统通过海洋混合层的长热弛豫时间的增红效应，产生海-气热力通量，这可能是SST低频变化的一个重要来源。这项研究的一个关键工具是NCAR社区气候系统模型(CCSM)的修订版，称为互动集合CCSM(IE-CCSM)，该工具是在PIS之前就这一主题提供的NSF拨款期间开发的。IE-CCSM通过显著降低天气噪声来解决天气噪声的作用，从而可以有选择地启用或禁用天气噪声机制。IE-CCSM采用的步骤是对耦合气候模式的大气分量模式的多个副本进行积分，并使用所有副本的地表通量的平均值来强制海洋分量模式。每个大气分量模型会有不同的天气噪声，因此天气噪声将通过对所有副本进行平均来去除。海洋分量模型只与大气分量模型的平均值相互作用，因此不能“看到”天气噪声。利用IE-CCSM进行的实验将研究天气噪声对大西洋海温变率的四种主要模式的重要性：北大西洋北部与北大西洋涛动有关的三极海温模式，与大西洋数十年变率有关的北大西洋单极海温异常，可能与大西洋经向翻转环流变率有关的北大西洋单极海温异常，以及两种热带大西洋海温变率模式，一种类似于太平洋厄尔尼诺现象的纬向结构，以及一种以跨赤道海温梯度变化为特征的经向结构。这项研究还包括了解天气噪声对大西洋海温变率可预报性的影响的实验。这项工作通过支持三名研究生产生了更广泛的教育影响，这将有助于培养这一研究领域的下一代科学家。此外，这项研究可能有助于深入了解气候系统在很长一段时间内的可变性和可预测性，这将使关注气候可变性和变化影响的政策制定者和决策者感兴趣。

Research under this award will examine the variability and predictability of Atlantic sea surface temperatures (SSTs), with a particular focus on the role of "weather noise" in producing decadal and multidecadal SST fluctuations. Weather noise refers to the variability of weather patterns which is independent of SSTs and occurs owing to the chaotic nature of air movements. Despite their short duration, weather systems produce air-sea thermodynamic fluxes which can be a significant source of low-frequency SST variability, through the reddening effect of the long thermal relaxation time of the ocean mixed layer. A key tool in the research, developed during the PIs' previous NSF grant on this topic, is a modified version of the NCAR Community Climate System Model (CCSM) referred to as the Interactive Ensemble CCSM (IE-CCSM). The IE-CCSM addresses the role of weather noise by dramatically reducing it, so that the weather noise mechanism can be seletively enabled or disabled. The procedure used in IE-CCSM is to integrate multiple copies of the atmospheric component model of the coupled climate model, and use the average of the surface fluxes from all copies to force the ocean component model. Each atmospheric component model will have different weather noise, thus the weather noise will be removed by averaging over all the copies. The ocean component model interacts only with the average of the atmospheric component models, and thus does not "see" the weather noise. Experiments conducted with the IE-CCSM will examine the importance of weather noise for four major patterns of Atlantic SST variability: a tripole SST pattern in the northern North Atlantic which is associated with the North Atlantic Oscillation, a monopole SST anomaly in the North Atlantic associated with Atlantic multidecadal variability, and which may be related to variability of the Atlantic meridional overturning circuation, and two patterns of tropical Atlantic variability, a zonal structure resembling the Pacific El Nino phenomenon, and a meridional structure characterized by changes in the cross-equatorial SST gradient. The research also include experiments to understand the impact of weather noise on the predictability of Atlantic SST variability.The work has eduational broader impacts through its support for three graduate students, which will help to develop the next generation of scientists in this research area. In addition, the research may lead to insights into the variability and predictability of the climate system over long time periods, which would be of interest to policy and decision makers concerned with the impacts of climate variability and change.