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

从云解析数据同化估计云的三维 (3D) 属性

• 批准号: 0514399
• 负责人: Katja Friedrich
• 金额: $ 36.67万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0514399&HistoricalAwards=false
• 关键词: Estimation; Cloud; Properties; Three; dimension

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.

该项目将对中尺度上的空间和时间依赖性云属性进行准确的估计。基于区域大气建模系统（RAMS）的四维变异（4DVAR）数据同化，将用于吸收高分辨率的卫星射线激光，卫星声音检索以及DOE ARM Southern Great Plains Great Plains Great Plains测量量。将使用三种方法来量化空间/时间云特性的准确性：1）通过统计误差分析在建模空间中，2）观察空间中相对于观察值的统计误差分析，以及c）对doe arm档案的独立观察的验证，从而实现了更广泛的范围。随后预期的定量降水预测改善。