Abstract
Visualization is an essential tool for analysis of data and communication of findings in the sciences, and the Earth System Sciences (ESS) are no exception. However, within ESS, specialized visualization requirements and data models, particularly for those data arising from numerical models, often make general purpose visualization packages difficult, if not impossible, to use effectively. This paper presents VAPOR: a domain-specific visualization package that targets the specialized needs of ESS modelers, particularly those working in research settings where highly-interactive exploratory visualization is beneficial. We specifically describe VAPOR’s ability to handle ESS simulation data from a wide variety of numerical models, as well as a multi-resolution representation that enables interactive visualization on very large data while using only commodity computing resources. We also describe VAPOR’s visualization capabilities, paying particular attention to features for geo-referenced data and advanced rendering algorithms suitable for time-varying, 3D data. Finally, we illustrate VAPOR’s utility in the study of a numerically- simulated tornado. Our results demonstrate both ease-of-use and the rich capabilities of VAPOR in such a use case.
Highlights
In the past two to three decades, computational modeling has emerged as such an important approach for scientific discovery that numerical simulation is considered by many as a third pillar of science [1]
To further explore and quantify the benefits of the VAPOR Data Collection (VDC) data format, we report a few findings from an evaluation of VDC performance using a commodity computing platform and a relatively large dataset
Among the common Graphical User Interfaces (GUIs) components, the transfer function editor serves a critical role in data exploration and the creation of informative visualizations, so we describe it in detail
Summary
In the past two to three decades, computational modeling has emerged as such an important approach for scientific discovery that numerical simulation is considered by many as a third pillar of science [1]. Scientific visualization is an intuitive, yet powerful approach to explore, analyze, and present large and complex data and is considered to be critical to the understanding of simulation outputs [2]. Elementary visualization methods such as line plotting, contouring, color mapping, and scatter plots are fundamental to scientific workflows, and examples of such are found in nearly every scientific journal article. The most successful of these “advanced” techniques are often deployed in software packages either as stand-alone tools or as part of a menu of selectable visualization algorithms within an application Two representatives of such software packages are VisIt [3] and ParaView [4]. The scientific significance of this feature is reflected in the fact that an entire
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