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Horizontal diffusion by submeso motions in the stable boundary layer

机译:稳定边界层中亚中观运动引起的水平扩散

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Four networks of wind data are used to construct the first systematic estimates of the horizontal diffusivity from observations of submeso motions on scales often unresolved in numerical models. Currently, the horizontal diffusivity in numerical models is specified mainly for numerical reasons without observational support. The data analysis in this study emphasizes the stable boundary layer although results are briefly presented for the unstable boundary layer. The horizontal diffusivity is estimated from the horizontal gradient and the observed flux. Horizontal gradients of scalars are generally difficult to directly estimate from observations with sufficient accuracy for much of the data. As an alternative, simulated particles with conservative properties are introduced into the observed wind field in order to estimate the horizontal diffusivity for submeso motions. The sensitivity of the horizontal diffusivity to details of the method is examined. The horizontal diffusivity increases with the range of time and space scales that are included in the evaluation. The horizontal diffusivity is much larger with significant topography and may increase with wind speed, depending on the site location. The coarse station spacing or the small domain size is found to be a major limitation to the analysis.
机译:使用四个风数据网络,通过对通常在数值模型中未解决的尺度上的亚细观运动的观测来构建水平扩散率的第一个系统估计。目前,数值模型中的水平扩散率主要是由于数值原因而没有观测支持的。尽管简要介绍了不稳定边界层的结果,但本研究中的数据分析强调稳定边界层。根据水平梯度和观察到的通量估算水平扩散率。标量的水平梯度通常很难直接从观测数据中以足够的准确性直接估算出来,以用于许多数据。作为替代方案,将具有保守属性的模拟粒子引入到观察到的风场中,以估计次中观运动的水平扩散率。研究了水平扩散对方法细节的敏感性。水平扩散率随评估中所包含的时间和空间尺度的范围而增加。在重要的地形条件下,水平扩散率要大得多,并且可能会随风速而增加,具体取决于站点的位置。发现粗站间距或小域大小是分析的主要限制。

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