Stereo Observations of Clouds for LES Validation and Sub-scale Cloud Parameterizations (SOCLES)

我们建议结合联合收割机高频云观测多个立体相机与大涡模拟（LES）在中纬度大陆气象supersite，以更好地了解和量化细尺度的空间和时间结构的浅积云人口。这些云场是高度不均匀的，并在广泛的尺度上迅速演变，这种行为使它们对用于天气预报和气候预测的数值模式中的大尺度流和能量收支的影响的表示复杂化。该项目将填补与细尺度云结构有关的信息空白，这阻碍了积云参数化的进展。随着超级计算的不断发展，这个问题变得更加紧迫，超级计算允许模拟越来越精细的分辨率，开始使现有积云参数化的概念基础失效。我们通过利用LES和立体相机测量之间的协同作用来解决这个问题。四维立体重建的高分辨率采样能力及其相当大的空间覆盖范围将使我们能够以前所未有的细节捕捉积云种群，这是垂直指向的仪器或卫星传感器无法实现的。这些将被用来验证LES模拟，并在平行测试和开发积云参数化。因此，精细尺度模型模拟补充了观测数据，但也允许用立体相机系统测试测量策略。假设使用开放的边界，多嵌套和详细的地形，以提高现实主义的模拟云超出理想化的常规LES在气象超级站点。测试这一假设是一个主要的研究目标，并涉及到模拟云的不规则性开始匹配立体相机观测的分辨率的确定，以及量化的不确定性的影响，在大尺度强迫。一个简单的立体摄像机模拟器LES的开发，以确保建模和测量数据之间的公平比较。数据分层和聚类技术将用于搜索和确定描述云的大小和不规则性以及环境条件的变量之间的参数关系。目标是使用这些数据来更好地约束天气和气候模式的对流和云重叠的参数化。

We propose to combine high-frequency cloud observations by multiple stereo cameras with Large-Eddy Simulation (LES) at a mid-latitude continental meteorological supersite to better understand and quantify fine-scale spatial and temporal structures of shallow cumulus cloud populations. These cloud fields are highly heterogeneous and quickly evolving on a broad range of scales, a behavior which has complicated the representation of their impact on the larger-scale flow and energy budget in numerical models used for weather prediction and climate projection. The project will fill the information gap related to fine-scale cloud structures, that has hampered progress in cumulus parameterization. This problem became more urgent with ongoing developments in supercomputing, which allow simulations for increasingly finer resolutions that start to invalidate the conceptual basis of existing cumulus parameterizations. We approach this problem by exploiting the synergy between LES and stereo camera measurements. The high-resolution sampling capability of stereo reconstruction in four dimensions and its considerable spatial coverage will allow us to capture cumulus populations in unprecedented detail, which cannot be achieved with vertically pointing instrumentation or satellite sensors. These will be used to validate LES simulations and in parallel to test and develop cumulus parameterizations. The fine-scale model simulations thus supplement the observational data but also allow for the testing of measurement strategies with the stereo camera system. The use of open boundaries, multiple nesting and detailed topography is hypothesized to improve the realism of the simulated clouds beyond that of idealized routine LES at meteorological supersites. Testing this hypothesis is a major research objective, and involves determination of the resolution at which simulated cloud irregularity starts to match the stereo camera observations, as well as quantification of the impact of uncertainties in the large-scale forcings. A simple stereo camera simulator for LES is developed to ensure a fair comparison between modelled and measured data. Data stratification and clustering techniques will be applied to search and identify parametric relations between variables describing cloud size and irregularity and environmental conditions. The objective is to use this data to better constrain parameterizations of convection and cloud overlap for weather and climate models.