Noise-induced vortex-splitting stratospheric sudden warmings
Noise-induced vortex-splitting stratospheric sudden warmings
复制标题
噪声引起的涡旋分裂平流层突然变暖
DOI：
10.1002/qj.3443
复制
发表时间：
2019
影响因子：
8.9
通讯作者：
Esler J
中科院分区：
文献类型：
--
作者：
Esler J
观测到的南极平流层极涡的振荡经常类似于Kida的线性背景流中椭圆涡模型中的振荡。在这里，Kida的模型被用来研究“涡旋分裂”平流层突然变暖（SSW）的动力学，例如2002年的南极事件。SSW被确定为在模型的周期轨道的分支。“对流层宏观湍流”对涡的影响是通过允许的线性背景强迫流被驱动的随机过程，有限的去相关时间（一个Ornstein-Uhlenbeck过程）。结果表明，这种随机性产生了一个随机游走在状态空间的周期轨道，这将最终导致一个分叉点后，一个SSW将发生。在一定的渐近极限，预期的时间之前，SSW发生可以找到通过解决“第一次通过时间”问题的随机微分方程，允许的依赖性的预期时间到SSW的模型参数被阐明。用Kida的模式和单层准地转模式对结果进行了验证。结果指向冬季平流层的“噪声记忆”范例，根据该范例，强迫历史决定涡旋是否静止，是否经历大幅非线性振荡，或者在极端情况下，涡旋最终是否会分裂。
Observed oscillations of the Antarctic stratospheric polar vortex often resemble those in Kida's model of an elliptical vortex in a linear background flow. Here, Kida's model is used to investigate the dynamics of “vortex‐splitting” stratospheric sudden warmings (SSWs), such as the Antarctic event of 2002. SSWs are identified with a bifurcation in the periodic orbits of the model. The influence of “tropospheric macroturbulence” on the vortex is modelled by allowing the linear background forcing flow to be driven by a random process, with a finite decorrelation time (an Ornstein–Uhlenbeck process). It is shown that this stochasticity generates a random walk across the state‐space of periodic orbits, which will eventually lead to a bifurcation point after which an SSW will occur. In certain asymptotic limits, the expected time before an SSW occurs can be found by solving a “first passage time” problem for a stochastic differential equation, allowing the dependence of the expected time to an SSW on the model parameters to be elucidated. Results are verified using both Kida's model and single‐layer quasi‐geostrophic simulations. The results point towards a “noise‐memory” paradigm of the winter stratosphere, according to which the forcing history determines whether the vortex is quiescent, whether it undergoes large amplitude nonlinear oscillations or, in extreme cases, whether the vortex will eventually split.