Utilizing Cloud Computing to Support Scalable Atmospheric Modeling

Atmospheric modeling is an important method to generate physical and numerical measurements of climate parameters, quantify the spatiotemporal changes of atmospheric phenomena over space and time, and predict their occurrences. With simulated data sets from atmospheric models, scientists are able to examine the driving forces of atmospheric phenomena and perform advanced analysis. Due to the inherent complexity and computational intensity of atmospheric models, running such models requires considerable amounts of computing resources. Traditionally, high-performance supercomputers or clusters have been used to perform atmospheric modeling. Recently, cloud computing solutions are emerged as a cost-effective approach to provide on-demand computing resources, remove the technical barriers, and reduce the high costs for computing facility management and maintenance. This chapter presents the design and implementation of a cloud-based framework to facilitate atmospheric modeling. The framework consists of a web portal, cloud instances, and a cloud-based data repository. To evaluate the feasibility of the framework, we have customized and deployed the serial processing version of ModelE onto our framework. Upon the deployment, we conducted two sets of experiments to evaluate the readiness of cloud computing resources to support large-scale atmospheric modeling. Experimental results demonstrate the framework provides scalable and customizable computing resources that meet the computational needs of atmospheric modeling.