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Multi-Layer Arctic Mixed-Phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity Experiments

机译:云解析模型模拟的多层北极混合相云:与ARM观测和敏感性实验的比较

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摘要

A cloud-resolving model (CRM) is used to simulate the multiple-layer mixed-phase stratiform (MPS) clouds that occurred during a three-and-a-half day subperiod of the Department of Energy-Atmospheric Radiation Measurement Program s Mixed-Phase Arctic Cloud Experiment (M-PACE). The CRM is implemented with an advanced two-moment microphysics scheme, a state-of-the-art radiative transfer scheme, and a complicated third-order turbulence closure. Concurrent meteorological, aerosol, and ice nucleus measurements are used to initialize the CRM. The CRM is prescribed by time-varying large-scale advective tendencies of temperature and moisture and surface turbulent fluxes of sensible and latent heat. The CRM reproduces the occurrences of the single- and double-layer MPS clouds as revealed by the M-PACE observations. However, the simulated first cloud layer is lower and the second cloud layer thicker compared to observations. The magnitude of the simulated liquid water path agrees with that observed, but its temporal variation is more pronounced than that observed. As in an earlier study of single-layer cloud, the CRM also captures the major characteristics in the vertical distributions and temporal variations of liquid water content (LWC), total ice water content (IWC), droplet number concentration and ice crystal number concentration (nis) as suggested by the aircraft observations. However, the simulated mean values differ significantly from the observed. The magnitude of nis is especially underestimated by one order of magnitude. Sensitivity experiments suggest that the lower cloud layer is closely related to the surface fluxes of sensible and latent heat; the upper cloud layer is probably initialized by the large-scale advective cooling/moistening and maintained through the strong longwave (LW) radiative cooling near the cloud top which enhances the dynamical circulation; artificially turning off all ice-phase microphysical processes results in an increase in LWP by a factor of 3 due to interactions between the excessive LW radiative cooling and extra cloud water; heating caused by phase change of hydrometeors could affect the LWC and cloud top height by partially canceling out the LW radiative cooling. It is further shown that the resolved dynamical circulation appears to contribute more greatly to the evolution of the MPS cloud layers than the parameterized subgrid-scale circulation.
机译:使用云解析模型(CRM)来模拟在能源大气辐射测量计划部门混合半天的半天半子期间发生的多层混合相层状云(MPS)。阶段性北极云实验(M-PACE)。 CRM采用先进的两步微物理方案,最先进的辐射传递方案和复杂的三阶湍流闭塞实现。同时进行的气象,气溶胶和冰核测量可用于初始化CRM。 CRM由温度和湿度随时间变化的大规模对流趋势以及显热和潜热的表面湍流确定。 CRM再现了M-PACE观测所揭示的单层和双层MPS云的出现。但是,与观测值相比,模拟的第一云层较低,第二云层较厚。模拟的液态水路径的大小与观察到的一致,但是其时间变化比观察到的更为明显。与之前对单层云的研究一样,CRM还捕获了液态水含量(LWC),总冰水含量(IWC),液滴数浓度和冰晶数浓度的垂直分布和时间变化的主要特征( nis),如飞机观测所建议。但是,模拟的平均值与观察到的值明显不同。 nis的大小特别被低了一个数量级。敏感性实验表明,较低的云层与显热和潜热的表面通量密切相关。高层云层可能是由大规模对流冷却/增湿作用所初始化,并通过云顶附近的强长波辐射冷却来维持,从而增强了动力循环。人工关闭所有冰相微物理过程会导致LWP增加3倍,这是由于过量的LW辐射冷却与多余的云水之间的相互作用所致;由水凝物相变引起的热可通过部分抵消LW辐射冷却来影响LWC和云顶高度。进一步表明,与参数化亚网格规模环流相比,解析的动态环流似乎对MPS云层的演化贡献更大。

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