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Scientific applications have diverse data and computational needs that scale from desktop to supercomputers. Besides the nature of the application and the domain, the resource needs for the applications also vary over time—as the collaboration and the data collections expand, or when seasonal campaigns are undertaken. Cloud computing offers a scalable, economic, on-demand model well-matched to evolving eScience needs. We will present a suite of science applications that leverage the capabilities of Microsoft's Windows Azure cloud-computing platform. We will show tools and patterns we have developed to use the cloud effectively for solving problems in environmental science.
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