Global S&T Development Trend Analysis Platform of Resources and Environment
项目编号 | 1445956 |
Collaborative Research: Understanding Climate Processes with Causal Discovery and Graphs of Information Flow in the Coupled Atmosphere-Land-Ocean System | |
Yi Deng | |
主持机构 | Georgia Tech Research Corporation |
项目开始年 | 2015 |
2015-01-15 | |
项目结束日期 | 2017-12-31 |
资助机构 | US-NSF |
项目类别 | Standard Grant |
项目经费 | 322463(USD) |
国家 | 美国 |
语种 | 英语 |
英文摘要 | 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. |
来源学科分类 | Geosciences - Atmospheric and Geospace Sciences |
文献类型 | 项目 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/67492 |
专题 | 环境与发展全球科技态势 |
推荐引用方式 GB/T 7714 | Yi Deng.Collaborative Research: Understanding Climate Processes with Causal Discovery and Graphs of Information Flow in the Coupled Atmosphere-Land-Ocean System.2015. |
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