Wei-Kuo Tao (PI)
NASA Goddard Space Flight Center
tao@agnes.gsfc.nasa.gov

Applications, Evaluation and Improvement of a Coupled, Global and Cloud-Resolving Modeling System

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. Such programs require a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) in order to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems.  The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization.  NASA satellite and field campaign cloud-related datasets can provide initial conditions as well as validation for both the MMF and CRMs.  The proposed research meets the requirements and addresses the scientific problems as stated in NN-H-04-Z-YS-008-N and particularly aims to the Cloud Modeling and Analysis Initiative (CMAI). Here we will utilize NASA's satellite data and field campaign observations to extend our understanding of clouds and also to provide realistic impacts of clouds in climate and weather models.  Cloud process models and a coupled global-cloud process modeling system can generate a cloud library and provide information on cloud and precipitation microphysical and dynamic processes as well as their interactions with radiation and aerosols.  A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities.  The major objectives of this proposal are:  (1) To evaluate and identify the CRM's capabilities with the focus on improving the CRM as it relates to the MMF,  (2) To use NASA satellite data and field campaign observations to validate and improve the CRM used in the MMF,  (3) To produce and provide multi-dimensional cloud data sets (i.e., a cloud data library) to the global modeling community to improve the representation and performance of moist processes in climate models and to improve our understanding of cloud processes globally (software tools needed to produce cloud statistics and to identify various types of clouds and cloud systems from both high-resolution satellite and model data will be developed jointly), and  (4) To enhance the computational performance of the MMF on NASA high performance super-computers. Computer scientists at NASA Ames will port, extend, and enhance the performance of the MMF and develop tools and methodologies, including visualization packages, to manage and display the immense data sets generated by the MMF. 

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