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Assessment of Planetary-Boundary-Layer Schemes in the Weather Research and Forecasting Model Within and Above an Urban Canopy Layer

机译:城市遮篷层内和上方天气研究和预测模型中行星边界层方案的评估

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摘要

We tested several planetary-boundary-layer (PBL) schemes available in the Weather Research and Forecasting (WRF) model against measured wind speed and direction, temperature and turbulent kinetic energy (TKE) at three levels (5, 9, 25 m). The Urban Turbulence Project dataset, gathered from the outskirts of Turin, Italy and used for the comparison, provides measurements made by sonic anemometers for more than 1 year. In contrast to other similar studies, which have mainly focused on short-time periods, we considered 2 months of measurements (January and July) representing both the seasonal and the daily variabilities. To understand how the WRF-model PBL schemes perform in an urban environment, often characterized by low wind-speed conditions, we first compared six PBL schemes against observations taken by the highest anemometer located in the inertial sub-layer. The availability of the TKE measurements allows us to directly evaluate the performances of the model; results of the model evaluation are presented in terms of quantile versus quantile plots and statistical indices. Secondly, we considered WRF-model PBL schemes that can be coupled to the urban-surface exchange parametrizations and compared the simulation results with measurements from the two lower anemometers located inside the canopy layer. We find that the PBL schemes accounting for TKE are more accurate and the model representation of the roughness sub-layer improves when the urban model is coupled to each PBL scheme.
机译:我们在天气研究和预测(WRF)模型中测试了几种行星边界层(PBL)方案,以防止测量的风速和方向,温度和湍流动能(TKE),在三个水平(5,9,25米)。从意大利都灵的郊区收集的城市动荡项目数据集提供了由Sonic Diquometers进行的测量超过1年。与其他类似的研究相比,这主要专注于短时间内,我们考虑了2个月的测量(1月和7月)代表季节性和日常可变性。要了解WRF模型PBL方案如何在城市环境中表现,通常以低风速条件为特征,我们首先将六种PBL方案与位于惯性子层中的最高风速计进行的观察结果进行了比较。 TKE测量的可用性使我们能够直接评估模型的性能;模型评估的结果以分位数与分位数图和统计指标为呈现。其次,我们考虑了可以耦合到城市表面交换参数化的WRF模型PBL方案,并将模拟结果与位于顶层层内部的两个低级计测量值进行比较。我们发现,当城市模型耦合到每个PBL方案时,TKE的PBL计划是更准确的,并且粗糙度子层的模型表示提高了。

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