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On the forward modeling of radar Doppler spectrum width from LES: Implications for model evaluation

机译:LES对雷达多普勒频谱宽度的正演模拟:对模型评估的启示

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摘要

Large-eddy simulations of an observed single-layer Arctic mixed-phase cloud are analyzed to study the value of forward modeling of profiling millimeter-wave cloud radar Doppler spectral width for model evaluation. Individual broadening terms and their uncertainties are quantified for the observed spectral width and compared to modeled broadening terms. Modeled turbulent broadening is narrower than the observed values when the turbulent kinetic energy dissipation rate from the subgrid-scale model is used in the forward model. The total dissipation rates, estimated with the subgrid-scale dissipation rates and the numerical dissipation rates, agree much better with both the retrieved dissipation rates and those inferred from the power spectra of the simulated vertical air velocity. The comparison of the microphysical broadening provides another evaluative measure of the ice properties in the simulation. To accurately retrieve dissipation rates as well as each broadening term from the observations, we suggest a few modifications to previously presented techniques. First, we show that the inertial subrange spectra filtered with the radar sampling volume is a better underlying model than the unfiltered −5/3 law for the retrieval of the dissipation rate from the power spectra of the mean Doppler velocity. Second, we demonstrate that it is important to filter out turbulence and remove the layer-mean reflectivity-weighted mean fall speed from the observed mean Doppler velocity to avoid overestimation of shear broadening. Finally, we provide a method to quantify the uncertainty in the retrieved dissipation rates, which eventually propagates to the uncertainty in the microphysical broadening.
机译:分析了观察到的单层北极混合相云的大涡模拟,以研究毫米波云雷达多普勒谱宽剖面的正向建模对模型评估的价值。对观察到的光谱宽度量化各个扩展项及其不确定性,并将其与建模的扩展项进行比较。当在正向模型中使用子网格规模模型的湍动能耗散率时,建模的湍流展宽比观测值窄。总耗散率(用亚网格尺度耗散率和数值耗散率估算)与所取回的耗散率以及从模拟垂直空气速度的功率谱推断出的耗散率更加一致。微观物理展宽的比较为模拟中的冰性质提供了另一种评估方法。为了从观测值中准确获取耗散率以及每个扩展项,我们建议对先前介绍的技术进行一些修改。首先,我们表明,从平均多普勒速度功率谱中获取耗散率时,用雷达采样量滤波的惯性子范围谱比未滤波的-5/3定律更好。其次,我们证明了滤除湍流并从观测到的平均多普勒速度中去除层均反射率加权平均下降速度非常重要,以避免过高估计剪切展宽。最后,我们提供了一种量化获取的耗散率中不确定性的方法,该方法最终会传播到微物理展宽中的不确定性。

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