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

合作研究：了解大西洋十年间到多十年间的变异性和可预测性

• 批准号: 1137911
• 负责人: Benjamin Kirtman
• 金额: $ 35.44万
• 依托单位: University of Miami
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1137911&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Atlantic; Decadal

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.

根据该奖项的研究将研究大西洋海面温度（SSTS）的可变性和可预测性，并特别关注“天气噪声”在产生年代十年和多年sST波动中的作用。 天气噪声是指与SST无关的天气模式的可变性，并且由于空气流动的混乱性而发生。 尽管持续时间很短，但天气系统会产生空气热力学通量，这可以通过长长的海洋混合层的长热松弛时间的红色效果来成为低频SST变异性的重要来源。 该研究期间开发的研究中的一个关键工具是该主题的NSF拨款，是NCAR社区气候系统模型（CCSM）的修改版本，称为交互式集合CCSM（IE-CCSM）。 IE-CCSM通过大大减少天气噪声的作用来解决天气噪声的作用，从而可以自由地启用或禁用天气噪声机制。 IE-CCSM中使用的过程是整合耦合气候模型的大气组件模型的多个副本，并使用所有副本的表面通量的平均值来迫使海洋组件模型。 每个大气组件模型都会有不同的天气噪声，因此将通过所有副本平均来消除天气噪声。 海洋组件模型仅与大气组件模型的平均值相互作用，因此不会“看到”天气噪声。 使用IE-CCSM进行的实验将研究天气噪声对大西洋SST可变性的四种主要模式的重要性：北大西洋北部北部的三核SST模式，与北大西洋的北大西大学相关，这是一种与北大西洋上的单极SST异常，与大西洋多级别的多年可变性相关的北大西洋和循环频率，该模式与大西洋多的循环范围相关，该模式与旋转的旋转典型性和循环系统相关。热带大西洋的变异性，类似于太平洋埃尔尼诺现象的区域结构，以及以跨备置SST梯度变化为特征的子午结构。 该研究还包括实验，以了解天气噪声对大西洋SST变异性可预测性的影响。这项工作通过对三名研究生的支持产生了更广泛的影响，这将有助于发展该研究领域的下一代科学家。 此外，该研究可能会导致对长期以来气候系统的可变性和可预测性的见解，这对与气候变异性和变化的影响有关的政策和决策者感兴趣。