COMPoSE: Characterization of phase partitioning in mixed-phase clouds

人们对混合相云的形成和生命周期知之甚少，因为对混合相云进行精确的观测仍然是一个挑战。在混合相云中，过冷液态水滴和固体冰晶共存。特别是对混合相云中过冷液层分布缺乏完整的垂直表征是目前广泛应用的观测方法的主要缺陷之一。提出的项目是由混合相云观测中存在的这一空白所驱动的，并提出了一系列新的方法和模型来解决这个复杂的问题。混合相云观测将采用最先进的高分辨率遥感仪器，如云多普勒雷达和多普勒偏振激光雷达。利用云雷达和激光雷达进行协同剖面测量以识别混合相云的液体成分，通常限于最大激光雷达观测高度，该高度由穿透光学深度约为3的完全信号衰减决定。相比之下，云雷达能够穿透多个液体层，因此，如果开发出适当的算法从雷达测量中识别液体层，则可以将整个垂直柱的垂直分辨云相位识别扩展到激光雷达测量范围之外。在提议的项目中，将分析完整的雷达多普勒频谱——它具有代表云微物理和动力学的独特特征——以确定激光雷达消光后整个垂直柱中混合相位云的相位划分。此外，雷达多普勒光谱将用于确定垂直空气运动，以深入了解云动力学。这个项目的重点将放在云尺度的过程研究上，特别是分析云热力学阶段的划分与温度和垂直空气运动的关系，以及随着时间的推移这种划分的发展，以深入了解混合阶段云的生命周期。在这种情况下，将根据气团的起源，通过反向轨迹分析、模式预报和气溶胶特性激光雷达测量，对观测到的混合相云进行分离，研究气溶胶对相划分的影响。拟议的工作超出了发展遥感技术的范围。使用一维微物理模型和雷达多普勒光谱向前模拟器将创建一个闭环，这将使我们能够评估我们对混合相云中发生的某些微物理过程的理解，例如环化。

The formation and life cycle of mixed-phase clouds - in which supercooled liquid water droplets and solid ice crystals coexist - are poorly understood because making accurate mixed-phase cloud observations remains a challenge. Especially, the lack of a full vertical characterization of the distribution of supercooled liquid layers in mixed-phase clouds is one of the major deficiencies in widely applied observational methods. The proposed project is motivated by this existing gap in mixed-phase cloud observations and proposes a series of novel methods and models to tackle this complex problem. Mixed-phase cloud observations will be made with state-of-the-art high-resolution measurements with remote-sensing instruments such as cloud Doppler radar and Doppler- and polarization lidar. Synergistic profiling measurements with cloud radars and lidars to identify the liquid component of mixed-phase clouds are usually limited to the maximum lidar observation height which is determined by the complete signal attenuation at a penetrated optical depth of about three.In contrast, cloud radars are able to penetrate multiple liquid layers and could thus be used to expand the vertically resolved cloud phase identification in the entire vertical column beyond the lidar measurement range if appropriate algorithms to identify the liquid layer from radar measurements are developed. In the proposed project the full radar Doppler spectrum - which has a unique signature representing cloud microphysics and dynamics - will be analyzed in order to determine the phase partitioning in mixed-phase clouds in the entire vertical column beyond lidar extinction. Additionally, the radar Doppler spectra will be used to determine the vertical air motion to gain insight on cloud dynamics. The focus of this project will be on process studies at cloud scale, in particular on the analysis of the partitioning of the cloud thermodynamic phase in relation to temperature and vertical air motion as well as the development of this partitioning over time to gain insight into the life cycle of mixed-phase clouds. In that context, the impact of aerosols on the phase partitioning will be studied by segregation of the observed mixed-phase clouds according to the origin of the air masses via backward trajectory analysis and model forecasts and lidar measurements of aerosol properties. The proposed work extends beyond the development of remote sensing techniques. The use of a 1D microphysical model and of a radar Doppler spectra forward simulator will create a closed-loop that will allow us to evaluate our understanding of certain microphysical processes - such as riming - occurring in mixed-phase clouds.