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

该项目将在中尺度上提供依赖于空间和时间的云特性的准确估计。基于区域大气模拟系统（RAMS）的四维变分（4DVAR）数据同化将用于将高分辨率卫星辐射、卫星探测检索和DOE-ARM南部大平原测量数据同化到云分辨模型中。时空云属性的准确性将通过三种方法进行量化：1)通过建模空间中的统计误差分析，2)观测空间中与同化观测数据相关的统计误差分析，以及c)对来自DOE-ARM存档的独立观测数据进行验证。这项工作的更广泛影响将是在实际数值天气预报模式同化卫星辐射测量方面取得的进展，以及随后预期的定量降水预报方面的改进。

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.