Estimation of Cloud Properties in Three-dimension (3D) from Cloud Resolving Data Assimilation

该项目将在中尺度上提供与空间和时间相关的云属性的准确估计。基于区域大气模式系统(RAMS)的四维变分(4DVAR)数据同化将被用于将高分辨率卫星辐射、卫星探空反演和DOE-ARM南大平原测量同化到云分辨模式中。将使用三种方法来量化空间/时间云特性的准确性：1)通过在模拟空间中进行统计误差分析，2)在观测空间中相对于同化的观测值进行统计误差分析，以及c)对照美国能源部ARM档案中的独立观测值进行验证。这项工作的更广泛影响将是在业务数值天气预报模式中同化卫星辐射测量的进展和随后对定量降水预报的预期改进。

This project will provide accurate estimates of space and time dependent cloud properties on the meso-scale. Four-dimensional variational (4DVAR) data assimilation, based on the Regional Atmospheric Modeling System (RAMS), will be used to assimilate high-resolution satellite radiances, satellite sounding retrievals, and DOE-ARM Southern Great Plains measurements into a cloud-resolving model. The accuracy of the space/time cloud properties will be quantified using three methods: 1) by statistical error analysis in the modeled space, 2) statistical error analysis in the observation space with respect to the observations that are assimilated, and c) verification against independent observations from the DOE-ARM archive.The broader impacts of this work will be in the progress made for the assimilation of satellite radiance measurements in operational numerical weather prediction models and the subsequent expected improvement in quantitative precipitation forecasts.