Utilizing Model Interoperability and High Performance Computing to Enhance Dust Storm Simulation

The simulations of dust storm and potential forecasting are of significant interest to public health, environment sciences, and global Earth observation system of systems (GEOSS). To support improved decision making of public health with higher resolution of dust storm forecasting. Model interoperability and high performance computing need to be leveraged to increase the resolution to the zip code level. This poses significant computational challenge for dust storm simulations. This presentation reports our research in utilizing interoperability technologies and high performance computing to enhance dust storm forecasting by facilitating model integration, data discovery, data access, and data utilization in a HPC (High performance computing) environment for a) reducing the computing time, b)lengthening the period of forecast, and c) ingesting large amount of geospatial datasets.DREAM-eta-8p and NMM-dust dust storm simulation models are utilized for the exploration of utilizing Model Interoperability and High Performance Computing to Enhance Dust Storm Forecasting. In our approach, the coarse model (DREAM-eta 8p) is used to identify hotspots of higher predicted dust concentration, and the output results are served as the input for the fine-grain model (NMM-dust) on the hotspot areas. After ingesting the DREAM-eta output the NMM-dust can start simulation. Experimental results demonstrates promising towards a forecasting system of dust storm forecasting. Acknowledgements: We would like to thank Drs. Karl Benedict, Bill Hudspeth of Univ. from New Mexico, Drs. William Sprigg, Goran Pejanovic, Slobodan Nickovic from UofArizona, and Dr. John D. Evans, and Ms. Myra J. Bambacus from NASA GSFC for the collaboration