Adria H. Liszka
Due to an almost unmanageable size, atmospheric datasets necessitate the use a clear and logical analysis tool : visualization. With this tool, scientists can study complex data in the form of images, and develop hypotheses based on the patterns of data. This project concentrates on taking the first step towards a comprehensive and automated atmospheric visualization program. The data parameters within the sets, such as those from the European Center for Medium-Range Weather Forecasts (ECMWF), fall into one of four categories: two-dimensional scalars, three-dimensional scalars, two-dimensional vectors, and three-dimensional vectors. Since the two-dimensional scalar visualization task has already been tackled, the project focuses on adding data representation capability in the other categories. This goal is accomplished through the programs tempanim.net (three-dimensional scalar data temperature), surfacewindanim.net (two-dimensional vector data surface wind) and windanim.net (three-dimensional vector data wind) in IBM’s Data Explorer. These simplified programs render only one type of data because the overall goal of complete generalization is too complicated to achieve immediately. This paper focuses on the accomplishments of the three programs and discusses the next steps towards the ideal, complete data visualization program of the future.
Presentation: Visualization of an Atmospheric Dataset
The Global Change Education Program is funded by the