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

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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.