Atmospheric Blocking: Dynamics and Responses to Climate Change

大气阻塞事件是高影响极端天气事件的重要诱因。改进阻塞事件的预测，并评估此类事件的频率、严重性和位置可能如何随气候变化而变化，具有重要的社会意义。天气涡旋已被证明通过维持阻塞模式在大气阻塞事件的动力学中发挥关键作用，但目前对其作用的了解还不够全面和定量。拟议研究的目标是：1)通过发展对块体天气涡旋强迫的定量评估，提高对大气阻塞事件的动力学理解。2)利用这种动力学理解来研究阻塞事件将如何随气候变化而变化，以及如何在气候和天气模式中更好地模拟阻塞。这项研究将利用一系列大气环流模式、再分析资料和全物理大气环流模式的存档结果(如耦合模式比对计划模式)进行数值试验。本研究分为三个部分：第一部分是利用理想化的模拟实验对涡旋强迫机制进行研究，以分离和发展对这一机制的定量认识。同样理想化的框架将被用来研究急流的速度和纬度、不同的准静止行星波模式和湿度如何调制这一机制。第二个组成部分是使用再分析数据来检验这种理解，并进一步了解观察到的阻塞事件的动态。第三个组成部分是应用这一理解来检验全物理模型在模拟阻塞方面的性能，并对阻塞事件未来如何变化提供更可靠和更具说服力的预测。

Atmospheric blocking events are an important contributor to high impact extreme weather events. Improving the forecasts of blocking events and assessing how the frequency, severity, and location of such events may change with climate change are of substantial societal importance. Synoptic eddies have been shown to play a critical role in the dynamics of atmospheric blocking events by maintaining the blocking pattern but the understanding of their role is currently not sufficiently complete and quantitative. The goals of the proposed research are 1) to improve the dynamical understanding of atmospheric blocking events through developing a quantitative assessment of synoptic-eddy forcing of blocks. 2) to employ this dynamical understanding to investigate how blocking events will change with climate change and how blocks can be better simulated in climate and weather models. The proposed research will employ numerical experiments with a hierarchy of general circulation models, reanalysis data, and archived results of full-physics general circulation models such as Coupled Model Intercomparison Project models. The research has three components: the first is to study the eddy-forcing mechanism using idealized modeling experiments which to isolate and develop a quantitative understanding of this mechanism. The same idealized framework will be used to investigate how the speed and latitude of jet streams, different patterns of quasi-stationary planetary waves, and moisture modulate this mechanism. The second component is to test this understanding using the reanalysis data and to gain further insight into the dynamic of observed blocking events. The third component is to apply this understanding to examine the performance of full-physics models in simulating blocking, and to provide a more reliable and conclusive prediction on how blocking events will change in the future.