What is the Intrinsic Predictability of Tornadic Supercell Thunderstorms?
What is the Intrinsic Predictability of Tornadic Supercell Thunderstorms?
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DOI：
10.1175/mwr-d-20-0076.1
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发表时间：
2020-08
影响因子：
3.2
通讯作者：
P. Markowski
中科院分区：
文献类型：
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作者：
P. Markowski
相对高分辨率（75米的水平网格间距）的合奏用于撕裂的超级电池风暴，以了解其固有的预测性在边界层中存在的温度驱动器在湍流中触发12小时，以在潮湿的环境中启动了一个准稳定状态。尽管统计上相同的环境，也可以将近距离旋转的风暴延伸到最低的模型水平。 OS差异只能通过最初的温暖气泡和/或风暴与湍流边界层结构相互作用的差异来解释。
A 25-member ensemble of relatively high-resolution (75-m horizontal grid spacing) numerical simulations of tornadic supercell storms is used to obtain insight on their intrinsic predictability. The storm environments contain large and directionally varying wind shear, particularly in the boundary layer, large convective available potential energy, and a low lifting condensation level. Thus, the environments are extremely favorable for tornadic supercells. Small random temperature perturbations present in the initial conditions trigger turbulence within the boundary layers. The turbulent boundary layers are given 12 h to evolve to a quasi–steady state before storms are initiated via the introduction of a warm bubble. The spatially averaged environments are identical within the ensemble; only the random number seed and/or warm bubble location is varied. All of the simulated storms are long-lived supercells with intense updrafts and strong mesocyclones extending to the lowest model level. Even the storms with the weakest near-surface rotation probably can be regarded as weakly tornadic. However, despite the statistically identical environments, there is considerable divergence in the finescale details of the simulated storms. The intensities of the tornado-like vortices that develop in the simulations range from EF0 to EF3, with large differences in formation time and duration also being exhibited. The simulation differences only can be explained by differences in how the initial warm bubbles and/or storms interact with turbulent boundary layer structures. The results suggest very limited intrinsic predictability with respect to predicting the formation time, duration, and intensity of tornadoes.