Collaborative Research: Understanding Climate Processes with Causal Discovery and Graphs of Information Flow in the Coupled Atmosphere-Land-Ocean System

合作研究：通过大气-陆地-海洋耦合系统中的因果发现和信息流图来了解气候过程

• 批准号: 1445978
• 负责人: Imme Ebert-Uphoff
• 金额: $ 28.31万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-01-15 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1445978&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Climate; Processes

The goal of this project is to develop graphical models of causal discovery and apply them to topics the field of climate dynamics. In these models lagged correlations are used to identify pathways of causal influence among components of a coupled system, and the model is constructed by representing each component as one node of a directed graph. Edges between node are assigned values representing the extent to which one component is predictable given prior knowledge of another. A key issue in causal discovery is accounting for indirect effects, in which component A influences component B which in turn influences component C, as opposed to the case in which component A directly influences component C. In graphical terms the distinction is whether or not an edge exists between A and C, or whether A's connection to C is only through B. This evaluation is done through a statistical calculation of conditional probabilities. Previous work by the PIs applied causal discovery to identify relationships among four well-known teleconnection patterns, the Western Pacific and Eastern Pacific Oscillations (WPO and EPO), the North Atlantic Oscillation (NAO), and the Pacific/North America (PNA) pattern. In this case the method shows that the EPO can affect the NAO 18 days later, while the NAO can influence the PNA pattern three to six days later. Although the application to atmospheric science is novel, the method has been used successfully in other disciplines including economics, systems engineering, and bioinformatics.Work under the project will further develop the modeling technique, with a goal of increasing computational speed by a factor of 100 through improvements in parallelization and localization of memory access. Visualization tools will also be developed to display results. In addition to these development efforts, the PIs will apply the technique to address three topics in climate dynamics: the onset dynamics of the Asian summer monsoon, the subseasonal variation of the Northern Hemisphere annual mode (NAM), and changes in the characteristics of information flow in global warming simulations. Work on monsoon onset will focus on three questions: What are the critical processes responsible for the establishment of the cross-equatorial flow? How important is the mechanical and thermal forcing associated with the Tibetan Plateau for the onset compared to local air-sea interaction in the Bay of Bengal and South China Sea? Is the onset a direct manifestation of atmospheric instability? For subseasonal NAM variability, the research goal is to investigate the relative importance of tropospheric dynamics, stratosphere-troposphere coupling, and troposphere-surface coupling in determining the phase transition of the NAM. The work on global warming is based on a preliminary analysis of one simulation in which information flows in the Northern midlatitudes become weaker as the climate warms, suggesting a reduction in atmospheric predictability in the tropics and mid-latitudes.The work has broader impacts through the introduction of a methodology developed in one scientific discipline (economics) into another (climate dynamics). The PIs will promote the adoption of the modeling technique by making their algorithms and software available to the community of climate dynamics researchers through a web portal. They will also offer tutorials at scientific conferences including the annual meetings of the American Meteorological Society and the American Geophysical Union. Tutorial materials will also be made available online and through published papers. In addition, the project will support and train a graduate students and a postdoctoral fellow, thereby providing for the future workforce in this research area.

该项目的目标是开发因果发现的图形模型，并将其应用于气候动力学领域的主题。 在这些模型中，滞后的相关性被用来识别耦合系统的组件之间的因果影响的路径，并且该模型通过将每个组件表示为有向图的一个节点来构建。 节点之间的边被分配值，该值表示在给定另一个组件的先验知识的情况下一个组件可预测的程度。 因果发现的一个关键问题是解释间接效应，即A成分影响B成分，B成分又影响C成分，而不是A成分直接影响C成分。 用图形术语来说，区别在于A和C之间是否存在边，或者A和C的连接是否仅通过B。该评估通过条件概率的统计计算来完成。 PI先前的工作应用因果发现来确定四种著名的遥相关模式之间的关系，西太平洋和东太平洋振荡（WPO和EPO），北大西洋振荡（NAO）和太平洋/北美（PNA）模式。 在这种情况下，该方法显示EPO可以在18天后影响NAO，而NAO可以在3至6天后影响PNA模式。虽然应用于大气科学是新颖的，该方法已成功地用于其他学科，包括经济学，系统工程，和bioinformatics. Working下的项目将进一步发展的建模技术，通过并行化和本地化的内存访问的改进，提高计算速度的一个因素100的目标。 还将开发可视化工具以显示结果。 除了这些开发工作之外，PI将应用该技术解决气候动力学中的三个主题：亚洲夏季风的启动动力学，北方半球年度模式（NAM）的亚季节变化，以及全球变暖模拟中信息流特征的变化。 季风爆发的工作将集中在三个问题：什么是关键的过程负责建立跨赤道流？与孟加拉湾和南海的海气相互作用相比，青藏高原的机械和热力强迫对爆发的重要性有多大？它的出现是大气不稳定的直接表现吗？ 对于亚季节NAM变化，研究的目标是调查对流层动力学，平流层-对流层耦合，对流层-地面耦合在确定NAM的相变的相对重要性。 关于全球变暖的工作是基于对一个模拟的初步分析，在该模拟中，随着气候变暖，北方中纬度地区的信息流动变弱，表明热带和中纬度地区的大气可预测性降低。这项工作通过将一个科学学科（经济学）开发的方法引入另一个科学学科（气候动力学）而产生更广泛的影响。 研究所将通过一个门户网站向气候动力学研究人员社区提供其算法和软件，以促进采用建模技术。 他们还将在科学会议上提供指导，包括美国气象学会和美国地球物理联合会的年会。 还将在网上和通过已发表的论文提供宣传材料。 此外，该项目将支持和培训一名研究生和一名博士后研究员，从而为这一研究领域的未来劳动力提供支持。