Solar and Quasi-decadal Modulation of the Stratospheric Circulation

这项研究将探索平流层的年代际变化，目的是增加我们对内部和太阳驱动的年际变化的影响以及这些信号如何在大气中传播的理解。已经确定了几个信号或强迫，这些信号或强迫可以解释平流层环流中许多年复一年的变化。这些信号包括热带平流层的准两年一次振荡、11年太阳周期、长期趋势（可能是由于全球气候变化）、厄尔尼诺/南方涛动和对流层信号，以及高频信号的低频调制。该方法将使用观测数据分析和数值模拟相结合的方法来探索平流层中十年尺度信号的存在、原因和传播。观测工作将利用网格大气数据集、火箭探空仪观测以及卫星和地面臭氧测量。相关、复合和经验正交函数等技术将用于识别数据中的年际信号。太阳辐射的变化对地球近期气候的影响还不为人所知。同样，除了太阳的影响外，地球-大气系统的年代际变化也知之甚少。了解平流层的年际变率是重要的，不仅因为它与对流层的联系，而且还因为可能确定长期全球气候趋势和太阳变率在确定全球气候方面的作用。＃

This research will explore the decadal-scale interannual variability of the stratosphere, with the goal of increasing our understanding of the effects of both internal and solar-driven interannual variability and how these signals propagate through the atmosphere. Several signals or forcings have been identified which may account for many of the year-to-year changes in the stratospheric circulation. These signals include the quasi-biennial oscillation of the tropical stratosphere, the 11-year solar cycle, secular trends (possibly due to global climate change), El Nino/Southern Oscillation and tropospheric signals, and low-frequency modulation of higher-frequency signals. The approach will be to use a combination of observational data analysis and numerical modeling to explore the existence, causes, and propagation of decadal-scale signals in the stratosphere. Observational work will exploit gridded atmospheric data sets, rocketsonde observations, and satellite- and ground- based ozone measurements. Techniques such as correlations, composites, and empirical orthogonal functions will be used to identify interannual signals in the data. The effect of changes in solar output on the earth's recent climate is not well known. Likewise, decadal variations of the earth-atmosphere system apart from solar influence are poorly understood. The understanding of the interannual variability of the stratosphere is important not only because of its links to the troposphere, but due to possible identification of secular global climate trends and the role of solar variability in determining the global climate. #