Atmospheric rivers and water fluxes in precipitating quasi‐geostrophic turbulence
Atmospheric rivers and water fluxes in precipitating quasi‐geostrophic turbulence
复制标题
准地转湍流中的大气河流和水通量
DOI：
10.1002/qj.3777
复制
发表时间：
2020
影响因子：
8.9
通讯作者：
Stechmann, Samuel N.
中科院分区：
文献类型：
--
作者：
Edwards, Thomas K.;Smith, Leslie M.;Stechmann, Samuel N.
大部分向极地的水输送可以通过被称为大气河流（ARs）的狭长走廊来解释。AR通常与对流层外气旋相关，对于干对流层外气旋，准地转（QG）动力学先前已经提供了理想化的原型。然而，很少有研究，调查AR在QG框架。这里，首要的问题是：理想化的AR是否出现在潮湿的QG动力学中？一个降水准地转（PQG）模式被探索作为一个可能的原型AR和相关的水传输。该设置使用数值模拟的地转湍流与降水，在一个单一的阶段。模拟显示出产生理想化的AR，并且对于这样一个简单的设置，它们具有合理的现实统计数据。例如，基于常用的AR识别算法，模型AR大致与自然界中一样频繁地发生。为了在这个模型中产生AR，发现需要两个关键成分超出干燥的QG框架：降水和非均匀的水分梯度。如果这两种成分中的任何一种太弱，则产生不太真实的AR。此外，对于一定范围的降水率，经向水分输送的很大一部分是由于AR造成的。
Most of the poleward transport of water can be accounted for by long narrow corridors known as Atmospheric Rivers (ARs). ARs are typically associated with extratropical cyclones and, for dry extratropical cyclones, an idealized prototype has previously been provided by quasi‐geostrophic (QG) dynamics. However, there are few if any studies that investigate ARs in a QG framework. Here, the overarching question is: do idealized ARs appear in moist QG dynamics? A precipitating quasi‐geostrophic (PQG) model is explored as a possible prototype for ARs and associated water transport. The set‐up uses numerical simulations of geostrophic turbulence with precipitation, in a single phase. The simulations are shown to produce idealized ARs, and they have reasonably realistic statistics for such a simple set‐up. For instance, the model ARs occur roughly as frequently as in nature, based on commonly used AR identification algorithms. To produce ARs in this model, it is found that two key ingredients are needed beyond the dry QG framework: precipitation and a meridional moisture gradient. If either of these two ingredients is too weak, then less realistic ARs are produced. In addition, for a range of precipitation rates, a large fraction of the meridional moisture transport is due to ARs.
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影响因子：
8
作者：
Dacre, H. F.;Clark, P. A.;Lavers, D. A.
通讯作者：
Lavers, D. A.
影响因子：
8.9
作者：
J. Monteiro;J. Sukhatme
通讯作者：
J. Sukhatme
影响因子：
5.2
作者：
M. Nayak;G. Villarini;D. Lavers
通讯作者：
M. Nayak;G. Villarini;D. Lavers
DOI：
--
发表时间：
--
期刊：
--
影响因子：
--
作者：
通讯作者：
--
影响因子：
3.2
作者：
Cordeira, Jason M.;Ralph, F. Martin;Moore, Benjamin J.
通讯作者：
Moore, Benjamin J.