Cloud and precipitation studies using millimeter-wavelength radars

云通过辐射的反射、吸收和散发、热量和水分的垂直输送、降水的产生及其相关的潜热释放和蒸发，在地球气候中发挥着至关重要的作用。尽管计算能力和模型的复杂性不断提高，云过程的代表性仍然是气候和天气数值模拟中不确定性的主要来源之一。为了充分了解云的作用并改进其在数值模式中的参数化，需要对云的形成、演变和消散进行所有重要尺度的基础（过程）研究。观测数据集是这种研究的一个关键因素，因为许多云的过程，如降水的形成，云湍流，夹带和冰晶的演变，仍然没有得到充分的机械理解。 拟议的研究建立在PI的专业知识分析毫米波雷达观测和引进新的检索算法的微物理和动力学特性的云和降水。 利用云雷达作为云尺度过程的关键，并与其他光学或微波传感器协同，我们建议在三个主要研究领域开展工作：冰云中垂直速度场的表征及其与大尺度气象学和暖云中降水起始的关系 拟议的分析将使用最先进的观测和过程模型，以产生关于这两个问题的新信息，这两个问题对模拟云参数化至关重要。这些信息将提供更好地了解云尺度过程中涉及的降雨开始，夹带和卷云的形成，这种理解将提高我们的能力，更好地参数化这些过程中的大尺度模型。

Clouds play a critical role in Earth's climate through the reflection, absorption and emission of radiation, the vertical transport of heat and moisture, and the generation of precipitation and its associated latent heat release and evaporation. Despite ever increasing computational power and model sophistication, the poor representation of cloud processes continues to be one of the major sources of uncertainty in numerical simulations of climate and weather. In order to adequately understand the role of clouds and improve their parameterization in numerical models, fundamental (process) studies on all scales important to cloud formation, evolution and dissipation are required. Observational data sets are a crucial element of such studies because many cloud processes, such as precipitation formation, cloud turbulence, entrainment, and ice crystal evolution, remain insufficiently understood mechanistically. The proposed research builds upon the PI's expertise on the analysis of millimeter-wavelength radar observations and the introduction of novel retrieval algorithms of microphysical and dynamical properties in clouds and precipitation. Using cloud radars as a keyhole in cloud-scale processes and in synergy with other optical or microwave sensors, we propose to work on three main research areas: characterization of the vertical velocity field in ice clouds and its relationship to large-scale meteorology and precipitation initiation in warm clouds The proposed analysis will use state-of-the-art observations and process models to produce novel information on these two issues of crucial importance to model cloud parameterization. This information will provide better understanding of the cloud-scale processes involved in rain initiation, entrainment, and cirrus formation, and this understanding will improve our ability to better parameterize those processes in large-scale models.