Low-Order Modeling of Low-Frequency Atmospheric Variability on a Sphere

本论文的研究项目旨在建立一个低频大气变率的低阶模式，并将高频分量准随机地参数化。一个两级谱原始方程模型构成了低阶模型的框架。未经过滤的菱形-15截断模拟的输出提供了选择低通截止频率和截断的行星尺度模式集以表征低阶模型所需的数据。将使用全球谱能量学和欧拉诊断对输出进行分析，以研究低频变率和高频涡旋强迫之间的关系。通量梯度和纯随机涡旋强迫参数化将通过对解析变量和涡旋强迫时间序列的统计分析来评估。将发展一种反映涡旋/平均流反馈显著特征的准随机参数化法。使用低阶模式的几组蒙特卡罗模拟将检验在低纬向指数状态和高纬向指数状态下以及在区域持续的低和高位势高度异常情况下季节内可预报性退化的时空特征。这项工作很重要，因为它将有助于描绘对低频行星运动有重大影响的高频天气尺度事件。因此，它应该有助于提高我们作出中期预测的能力。

This dissertation research project aims to develop a low- order model of low-frequency atmospheric variability with the high-frequency components parameterized quasi-stochastically. A two-level spectral primitive equations model constitutes the framework of the low-order model. Output from an unfiltered, rhomboidal-15 truncation simulation provides the data necessary to select a low-pass cutoff frequency and truncated set of planetary-scale modes to characterize the low-order model. The output will be analyzed using global spectral energetics and Eulerian diagnostics to study the relationship between the low- frequency variability and high-frequency eddy forcing. Flux- gradient and purely stochastic eddy forcing parameterizations will be evaluated by means of statistical analysis of the resolved variables and eddy forcing time series. A quasi- stochastic parameterization that reflects salient features of the eddy/mean flow feedback will be developed. Several sets of Monte-Carlo simulations using the low-order model will be run to examine spatial and temporal characteristics of the intraseasonal predictability degradation under low and high zonal index states, and under cases of regionally persistent low and high geopotential height anomalies. This work is important because it will help delineate the high frequency synoptic scale events that have significant influence on low frequency planetary motions. Hence, it should contribute to improving our capability to make medium range forecasts.