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Microphysical observations and mesoscale model simulation of a warm fog case during FRAM project

机译:FRAM工程中热雾情况的微观物理观察和中尺度模型模拟

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摘要

The objective of this work is to apply a new microphysical parameterization for fog visibility for potential use in numerical weather forecast simulations, and to compare the results with ground-based observations. The observations from the Fog Remote Sensing And Modeling (FRAM) field which took place during the winter of 2005-2006 over southern Ontario, Canada (Phase I) were used in the analysis. The liquid water content (LWC), droplet number concentration (N-d), and temperature (T) were obtained from the fog measuring device (FMD) spectra and Rosemount probe, correspondingly. The visibility (Vis) from a visibility meter, liquid water path from microwave radiometers (MWR), and inferred fog properties such as mean volume diameter, LWC, and N-d were also used in the analysis. The results showed that Vis is nonlinearly related to both LWC and N-d. Comparisons between newly derived parameterizations and the ones already in use as a function of LWC suggested that if models can predict the total N-d and LWC at each time step using a detailed microphysics parameterization, Vis can then be calculated for warm fog conditions. Using outputs from the Canadian Mesoscale Compressible Community (MC2) model, being tested with a new multi-moment bulk microphysical scheme, the new Vis parameterization resulted in more accurate Vis values where the correction reached up to 20-50%.
机译:这项工作的目的是为雾的能见度应用一种新的微物理参数化技术,以便将其用于数值天气预报模拟中,并将结果与​​地面观测结果进行比较。分析中使用了2005年至2006年冬季在加拿大安大略省南部(第一阶段)进行的雾遥感和建模(FRAM)领域的观测结果。分别从雾度测量仪(FMD)光谱和罗斯蒙特探头获得液态水含量(LWC),液滴数浓度(N-d)和温度(T)。分析中还使用了能见度仪的能见度(Vis),微波辐射计(MWR)的液态水路径以及推断的雾度,例如平均体积直径,LWC和N-d。结果表明,Vis与LWC和N-d都非线性相关。将新推导的参数化与已根据LWC使用的参数化进行比较表明,如果模型可以使用详细的微物理参数化来预测每个时间步的总N-d和LWC,则可以计算出暖雾条件下的Vis。使用来自加拿大中尺度可压缩社区(MC2)模型的输出,并通过新的多时刻整体微物理方案进行了测试,新的Vis参数化可实现更准确的Vis值,校正值可达到20-50%。

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