Collaborative Research: Revisiting the Low-Frequency Variability of the Extratropical Circulation Using Non-Empirical Orthogonal Function (EOF) Modes and Linear Response Functions

两半球温带外对流层大气环流变化的一个主要模式是时间尺度大于10天的强弱西风急流之间的振荡。这种温带西风急流的低频变化称为环状模式。这种年模式影响着中高纬度地区的日常天气和极端事件，因此了解它是非常有意义的。冬半球的环状模式也影响平流层极涡，并受其影响。该项目寻求对控制环状模式的因素有更深入的了解。这项工作的结果可能会改变人们对中、高纬度地区急流变化和天气的理解。这一结果还可能导致可预报性的进步，超过目前约10天的天气预报障碍，并导致气候模型能力的提高。此外，新的量化框架将有助于解释综合气候模型预测的结果范围。这些成果有可能推动旨在为应对气候变化和与天气有关的极端情况做准备的国家和全球努力，从而产生重大的社会经济效益。该项目将支持两名博士生和一名博士后研究员的教育和培训，从而培养下一代大气动力学家和气候科学家。在这项工作中开发的一些工具将被PIS用于其本科生和研究生水平的教学，以帮助学生可视化和量化急流可变性的某些方面。此外，该项目将通过莱斯和斯坦福的几个STEM扩展项目，让K-12年级的学生参与与气候和计算机模拟相关的研究。在这个项目中，将开发新的分析方法，并将与计算机模型和观测数据一起使用，以更深入地了解急流的这种可变性。此外，还将制定一个新的框架，将当前的这种可变性与未来的可变性量化地联系起来。该框架将综合急流变化和极地涡旋对各种气候强迫的响应，例如温室气体增加或臭氧消耗。该项目的具体任务是：1)在观测和气候模型中检验正压和斜压环模之间的耦合；2)开发传播环模的涡旋反馈模式；3)通过数值实验了解平流层对两个半球的对流层环模的影响；4)研究气候模型模拟中的低频变化模式和波动-耗散关系，以更好地评估气候变化预测在这些模拟中的逼真度。这一奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

One dominant pattern of the atmospheric circulation variability in the extratropical troposphere of both hemispheres is the oscillation between stronger and weaker westerly jet streams with a time scale longer than 10 days. Such low-frequency variability of extratropical westerly jet streams is called the annular mode. The annual mode influences the day-to-day weather and extreme events in the middle and high latitude regions and is therefore of great interest to understand. The annular mode in winter hemisphere also influences, and is influenced by, the stratospheric polar vortex. This project seeks a deeper understanding of the factors that control the annular mode. The outcome of this work will potentially transform the understanding of jet stream variability and weather in the middle and high latitudes. The outcome could also lead to advances in predictability past the current weather prediction barrier of about 10 days, and lead to improvements in capabilities of climate models. Furthermore, the new quantitative framework will aid the interpretation of the range of outcomes predicted by comprehensive climate models. These outcomes have the potential to advance the national and global efforts aimed at preparing for climate change and weather-related extremes, resulting in significant socio-economic benefits. This project will support the education and training of two PhD students and a postdoctoral researcher, thus preparing the next generation of atmospheric dynamists and climate scientists. Some of the tools developed during this work will be used by the PIs in their undergraduate and graduate-level teaching to help the students with visualizing and quantifying some aspects of the jet stream variability. Also, the project will engage K-12 students in climate and computer modeling-related research through several STEM outreach programs at Rice and Stanford.In this project, novel analysis methods will be developed, and will be employed along with computer models and observational data to gain a deeper understanding of this variability of the jet streams. Furthermore, a new framework will be developed to quantitively link this variability in the present day to variability in the future. This framework will integrate the response of the jet stream variability and polar vortex to various climate forcings, such as greenhouse gas increase or ozone depletion. The specific tasks of this project are 1) examining the coupling between the barotropic and baroclinic annular modes in observations and in climate models; 2) developing an eddy feedback model for propagating annular modes; 3) understanding stratospheric influence on the tropospheric annular mode in both hemispheres using numerical experiments; 4) studying low-frequency variability modes and fluctuation-dissipation relationship in climate model simulations to better evaluate the fidelity of the climate change projections in these simulations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.