This paper reports analysis of eddy-covariance data collected during the WFIP2 field campaign in the complex-terrain of the US Pacific Northwest. A 31-day period representative of the region’s dry season was used to address the following questions: (1) To what extent does the Constant-Flux Layer (CFL) assumption hold? (2) What is the spatial variability of turbulent and momentum fluxes over km scales? and (3) How skilful are the surface-layer parameterizations of mesoscale models? These questions are directly relevant to subgrid parameterization studies of mesoscale models. Results show that the efficacy of the CFL concept and the spatial variability of turbulent and momentum fluxes are dependent on: (i) the turbulent parameter being analysed, (ii) the measurement’s location, (iii) the atmospheric stability regime (determined by the flow and vertical stratification), and (iv) the magnitude of the flux. Finally, the skill of the physics formulation of an often-used surface-layer parameterization scheme available in the Weather Research and Forecasting (WRF) model was also evaluated. Meteorological conditions associated with the highest and the lowest errors were identified. A metric to quantify (time-dependent) flow heterogeneity is proposed, which appears to be a good candidate to predict the skill of idealized surface-layer parameterization schemes in complex terrain.

本文报告了在美国太平洋西北部复杂地形的 WFIP2 野外活动期间收集的涡度协方差数据分析。该地区旱季的 31 天周期代表用于解决以下问题：(1) 恒定通量层 (CFL) 假设在多大程度上成立？(2) km 尺度上的湍流和动量通量的空间变异性是什么？(3) 中尺度模型的表层参数化有多熟练？这些问题与中尺度模型的亚网格参数化研究直接相关。结果表明，CFL 概念的有效性以及湍流和动量通量的空间变异性取决于：(i) 正在分析的湍流参数，(ii) 测量位置，(iii) 大气稳定性机制（由流动和垂直分层决定），以及 (iv) 通量的大小。最后，还评估了天气研究和预报 (WRF) 模型中可用的常用表面层参数化方案的物理公式技巧。确定了与最高和最低误差相关的气象条件。提出了一种量化（时间相关）流异质性的指标，这似乎是预测复杂地形中理想化表面层参数化方案技能的良好候选者。确定了与最高和最低误差相关的气象条件。提出了一种量化（时间相关）流异质性的指标，这似乎是预测复杂地形中理想化表面层参数化方案技能的良好候选者。确定了与最高和最低误差相关的气象条件。提出了一种量化（时间相关）流异质性的指标，这似乎是预测复杂地形中理想化表面层参数化方案技能的良好候选者。