The role of tributary valley outflows in the development of a nocturnal mountain boundary layer (TribuNAL)

在水平均匀和平坦的地形上，热量、动量、质量、气溶胶、灰尘和各种其他有害污染物的交换受大气边界层（对流层的最低部分）内湍流运动的支配。如果考虑一个非均匀的山区，在交换中所涉及的湍流运动的复杂性大大增加。特别令人感兴趣的是夜间，稳定的条件下，引起的现象和相互作用，只有山。所有这些现象通常集中在地势较低的地方，最常见的是在大多数人类活动所在的山谷。在夜间，污染物可能会被困在山谷表面附近的非常浅的层中，从而影响能见度，交通，最重要的是，生活在山谷中的人们的健康和安全。一个问题是，由于所涉及的时空尺度范围很广，如何对所讨论的相互作用进行充分抽样。因此，天气预报模型很难正确预测这种复杂地形地区的局部天气演变，因为它们的网格分辨率仍然太粗糙。目前的建议解决了在稳定的夜间条件下，在一个母谷与其支流山谷的流量汇合。尽管在过去的四十年里，激光雷达等遥感技术取得了进步，但到目前为止，夜间相互作用的这一方面很少受到关注。由于持续缺乏足够的观测，这种相互作用，我们的理解，并在数值天气预报模型的适当表示仍然是不完整的。该提案旨在产生几种类型的可交付成果，从高质量的后处理观测产品到对所涉及过程的物理理解的改进，这些过程可能会导致在数值模型中更好地表示夜间现象。

Over horizontally homogeneous and flat terrain, the exchange of heat, momentum, mass, aerosols, dust and various other harmful pollutants is governed by turbulent motions within the atmospheric boundary layer, the lowest part of the troposphere. If a heterogeneous mountainous area is considered instead, the turbulent motions involved in the exchange greatly increase in complexity. Of particular interest are nighttime, stable conditions, which give rise to phenomena and interactions specific only to mountains. All these phenomena typically converge in low points of the terrain, most often in valleys where the majority of human activities are located. During nighttime, pollutants may get trapped inside very shallow layers adjacent to the valley surface, therefore affecting visibility, traffic, and most important of all, health and safety of people living in valleys. One problem lies in adequately sampling the interactions in question, owing to the broad range of spatio-temporal scales involved. As a result, weather forecast models struggle to properly predict the evolution of local weather in such regions of complex terrain, since their grid resolution is still too coarse. The present proposal addresses the confluence of flows in a parent valley with its tributary valleys during stable nighttime conditions. This aspect of nighttime interactions has received little attention to date, despite the advancement of remote sensing technologies such as lidars over the past four decades. Due to an on-going lack of adequate observations of such interactions, both our understanding, and a proper representation in numerical weather prediction models remain incomplete. This proposal intends to produce several types of deliverables, ranging from high-quality post-processed observational products to improvements of the physical understanding of the involved processes that can potentially lead to a better representation of nighttime phenomena within numerical models.