Convective Cloud Dynamics and Turbulence Interactions with Microphysical Processes and the Atmospheric Environment (CLOUDY TIME)

本项目研究对流云动力学和湍流与微物理过程和大气环境的相互作用（多云时间）将：（i）利用亚千米级模型和大涡模拟层次提高对微观物理学-湍流相互作用的理解;（ii）评估亚千米和千米级模型中湿对流湍流的三维表示，测试湍流参数化方案，包括与微观物理学的耦合;（iii）提高对垂直廓线表示法引起的模式不确定性的理解;（iv）评估导致云组织的中尺度过程，为尺度感知对流参数化方案提供信息。英国夏季对流场活动WesCon计划进行新的测量和观测，旨在首次观测许多相关的湍流过程及其与环境的关系，从而提高对多云时间的理解和评估。对流导致危险天气，是全球大气环流的基础。对流风暴的建模是具有挑战性的，因为许多过程的相互作用，这些过程在很大的尺度上相互作用，从湍流和微物理学，包括降水的形成，到对流不稳定的释放和蒸发驱动的下沉气流和冷池。下一代全球天气和气候模式将在公里尺度网格长度上运行，并将明确表示对流风暴，但这些模式对次网格湍流参数化高度敏感，即使在网格长度小于1公里的更高分辨率下运行。这种敏感性导致风暴数量、强度和寿命的偏差，从而导致恶劣天气警报和大尺度环流的错误。相反，大尺度上的误差会影响对流的时间和性质，从而形成一个复杂的跨尺度相互作用网络。云时的目的是解开对流的控制从微尺度，由参数化，天气尺度，由数据同化和降尺度。

This project, studying Convective Cloud Dynamics and Turbulence Interactions with Microphysical Processes and the Atmospheric Environment (CLOUDY TIME) will: (i) improve understanding of microphysics-turbulence interactions using a hierarchy of sub-km models and large-eddy simulations; (ii) evaluate the 3D representation of moist convective turbulence in sub-km and km-scale models, testing turbulence parametrization schemes including coupling with microphysics; (iii) improve understanding of model uncertainty due to representation of vertical profiles; and (iv) evaluate mesoscale processes that lead to cloud organisation to inform scale-aware convection parametrization schemes. The improved understanding and evaluation in CLOUDY TIME will be informed by novel measurements and observations planned for the UK summertime convection field campaign WesCon, which aims to observe many of the relevant turbulent processes, and their relation to the environment, for the first time.Convection leads to hazardous weather and is fundamental to the global atmospheric circulation. Modelling of convective storms is challenging due to the interaction of many processes which interact over a wide range of scales, from turbulence and microphysics, including precipitation formation, to the release of convective instability and evaporatively driven downdraughts and cold pools. The next generation of global weather and climate models will be run at km-scale grid lengths and will explicitly represent convective storms, but these models are highly sensitive to the sub-grid turbulence parametrization, even when run at finer resolutions with grid lengths less than 1 km. This sensitivity leads to biases in storm number, intensity and lifetime, and hence to errors in severe weather warnings and in the large-scale circulation. Conversely, errors on the large scale affect the timing and nature of convection, creating a complex web of interactions across scales. CLOUDY TIME aims to disentangle the controls on convection from the microscale, governed by parametrization, to the synoptic scale, governed by data assimilation and downscaling.