Turbulent entrainment-mixing processes profoundly influence the relationship between radar reflectivity factor and liquid water content (Z-LWC) of cloud droplets. However, quantification of the entrainment-mixing mechanisms based on the Z-LWC relationship is still lacking. To address this gap, 12,218 entrainment-mixing cases are simulated using the Explicit Mixing Parcel Model. We examine the variations of the parameters in the power-law relationship Z = aLWC^b, and the relationship between parameter b and homogeneous mixing degree (ψ), a measure quantifying entrainment-mixing processes. The results indicate that parameter b distributes within the range of 1–2, with a positive correlation between parameter b and ψ. The b-ψ relationship is fitted, which connects the Z-LWC relationship for various entrainment-mixing types. The results suggest the potential for employing a remote sensing approach to investigate the entrainment-mixing mechanisms of non-precipitating small cumulus/stratocumulus clouds, thereby overcoming the limitations of traditional observational studies that rely solely on aircraft observations.

中文翻译：

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基于云滴 z-LWC 关系的湍流夹带混合过程量化


湍流夹带混合过程深刻影响雷达反射率因子与云滴液态水含量 （Z-LWC） 之间的关系。然而，基于 Z-LWC 关系的夹带混合机制的量化仍然缺乏。为了解决这一差距，使用显式混合宗地模型模拟了 12,218 个夹带混合情况。我们研究了幂律关系 Z = aLWC ^b 中参数的变化，以及参数 b 与齐次混合度 （ψ） 之间的关系，齐次混合度 （） 是量化夹带混合过程的度量。结果表明，参数 b 分布在 1-2 的范围内，参数 b 和 ψ 之间呈正相关。拟合了 b-ψ 关系，该关系连接了各种夹带混合类型的 Z-LWC 关系。结果表明，采用遥感方法来研究非降水小积云/层积云的夹带混合机制的潜力，从而克服仅依赖飞机观测的传统观测研究的局限性。