The kinetic energy spectrum in the atmospheric mesoscale has a - 5/3 slope, which suggests an energy cascade. But the underlying dynamics of this cascade is still not fully understood. Is it driven by inertia–gravity waves, vortices or something else? To answer these questions, it is necessary to decompose the spectrum into contributions from waves and vortices. Linear decompositions are straightforward, but can lead to ambiguous results. A recent paper by Wang & Buhler ( J. Fluid Mech. , vol. 882, 2020, A16) addresses this problem by presenting a nonlinear decomposition of the energy spectrum into waves and vortices using the omega equation. They adapt this method for one-dimensional aircraft data and apply it to two datasets. In the lower stratosphere, the results show a mesoscale spectrum dominated by waves. The situation in the upper troposphere is different: here vortices are just as important, or possibly more than important, as waves, although the limitations of the one-dimensional data preclude a definitive answer.

中文翻译：

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解开大气动能谱中的波和涡旋

大气中尺度的动能谱具有 - 5/3 的斜率，表明存在能量级联。但是这种级联的潜在动力仍未完全了解。它是由惯性——重力波、漩涡还是其他什么东西驱动的？要回答这些问题，有必要将频谱分解为波和涡旋的贡献。线性分解很简单，但可能会导致模棱两可的结果。Wang & Buhler 最近的一篇论文 (J. Fluid Mech., vol. 882, 2020, A16) 通过使用 omega 方程将能谱非线性分解为波和涡流来解决这个问题。他们将这种方法应用于一维飞机数据并将其应用于两个数据集。在平流层下部，结果显示出以波为主的中尺度光谱。