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

用于 LES 验证和小尺度云参数化 (SOCLES) 的云立体观测

• 批准号: 430226822
• 负责人: Professor Dr. Roel Neggers
• 金额: --
• 依托单位: Institut für Geophysik und Meteorologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/430226822?language=en
• 关键词: Stereo; Observations; Clouds; LES; Validation

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.

为了更好地了解和量化浅层积云种群的精细尺度时空结构，我们建议在中纬度大陆气象超级站点将多台立体相机的高频云观测与大涡模拟（Large-Eddy Simulation， LES）相结合。这些云场是高度异质性的，并且在大尺度范围内迅速演变，这一行为使得它们在用于天气预报和气候预测的数值模式中对更大尺度流量和能量收支的影响的表示变得复杂。该项目将填补与精细尺度云结构相关的信息空白，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，这开始使现有的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获积云种群，这是垂直指向仪器或卫星传感器无法实现的。这些将用于验证LES模拟，并并行测试和开发积云参数化。因此，精细模型模拟补充了观测数据，但也允许使用立体相机系统测试测量策略。假设使用开放边界、多重嵌套和详细地形来提高模拟云的真实感，而不是在气象重叠站点使用理想的常规LES。验证这一假设是一个主要的研究目标，包括确定模拟云的不规则性开始与立体相机观测相匹配的分辨率，以及量化大尺度强迫中不确定性的影响。一个简单的立体相机模拟器为LES开发，以确保公平比较模型和测量数据。数据分层和聚类技术将应用于搜索和识别描述云大小、不规则性和环境条件的变量之间的参数关系。目的是利用这些数据更好地约束天气和气候模式对流和云重叠的参数化。