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Radiation Fog. Part II: Large-Eddy Simulations in Very Stable Conditions

机译:辐射雾。第二部分:非常稳定条件下的大涡模拟

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Despite the long interest in understanding fog processes and improving fog parametrization, numerical modelling of fog remains an important challenge in short-term forecasts, due to the diversity and scales of the mechanisms involved with fog parametrization. In this study, we focus on the key processes that govern performance in fog modelling in very stable conditions. Large-eddy simulations at very high resolution are tested against the observations from Cardington, UK, presented in Part I of thisstudy. The radiation fog forms in statically stable conditions. Five hours after its formation, the fog deepens rapidly and a significant cooling associated with the formation of positive curvature can be seen in the vertical profiles of potential temperature around 50 m. After roughly 8 h of development, a mixed layer has formed at the base of the fog, driven by surface instability. We show that the model captures well the change in static stability, but fails at capturing correctly the mechanisms associated with the deepening of the fog layer. Different possible mechanisms are discussed and tested with the model, such as additional drainage flow and cold air advection, which might result from local heterogeneity. The sensitivity of these results to different microphysical parametrizations is also briefly addressed.
机译:尽管人们对了解雾的过程和改善雾的参数化一直抱有浓厚的兴趣,但由于与雾参数化有关的机制的多样性和规模,雾的数值模型仍然是短期预测中的重要挑战。在这项研究中,我们重点研究了在非常稳定的条件下控制雾模型性能的关键过程。在本研究的第I部分中,针对英国Cardington的观测结果,对了高分辨率的大涡模拟进行了测试。辐射雾在静态稳定的条件下形成。雾形成五小时后,雾迅速加深,在约50 m的潜在温度的垂直剖面中可以看到与正曲率形成有关的明显冷却。显影约8小时后,由于表面不稳定性而在雾的底部形成了一个混合层。我们表明该模型很好地捕获了静态稳定性的变化,但未能正确捕获与雾层加深相关的机制。该模型讨论并测试了不同的可能机制,例如可能由局部异质性引起的额外排水流和冷空气对流。还简要介绍了这些结果对不同微物理参数的敏感性。

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