Correlative visualization techniques for multidimensional data

Critical to the understanding of data is the ability to provide pictorial or visual representation of those data, particularly in support of correlative data analysis. Despite the advancement of visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are other computer science domains outside of computer graphics that are required to make visualization effective such as data management. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformation, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and Earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in data visualization system

Interactive archives of scientific data

A focus on qualitative methods of presenting data shows that visualization provides a mechanism for browsing independent of the source of data and is an effective alternative to traditional image-based browsing of image data. To be generally applicable, such visualization methods, however, must be based upon an underlying data model with support for a broad class of data types and structures. Interactive, near-real-time browsing for data sets of interesting size today requires a browse server of considerable power. A symmetric multi-processor with very high internal and external bandwidth demonstrates the feasibility of this concept. Although this technology is likely to be available on the desktop within a few years, the increase in the size and complexity of achieved data will continue to exceed the capacity of 'worksation' systems. Hence, a higher class of performance, especially in bandwidth, will generally be required for on-demand browsing. A few experiments with differing digital compression techniques indicates that a MPEG-1 implementation within the context of a high-performance browse server (i.e., parallized) is a practical method of converting a browse product to a form suitable for network or CD-ROM distribution

Animated computer graphics models of space and earth sciences data generated via the massively parallel processor

The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined

Thermoclinic Assessment Of A Preliminary Circulation Model For Lake George In The Jefferson Project

The Jefferson Project is a collaboration between the Rensselaer Polytechnic Institute, IBM, and the FUND for Lake George aimed at understanding and managing complex factors (road salt, storm water runoff, invasive species) threatening Lake George, New York. Lake George is located about 80 km north of Albany in upstate New York and is known internationally for its water clarity. Understanding the hydrodynamics of the lake is fundamental for creation and maintenance of a research and monitoring program for the early detection of and response to adverse environmental and biological change. In this work a 3D circulation model of the lake is developed to better understand the hydro-environmental conditions of the lake; forcing is by a combination of local public survey data for the water budget and atmospheric data from the NWS (NOAA National Weather Service). The model is validated by a combination of water chemistry data collected by Darrin Fresh Water Institute (DFWI) over the last three decades, and known empirical relationships of the lake\u27s structural profile. Numerical simulations run over several years to capture the seasonal progression of thermocline depth throughout the lake, the south to north salt and surface thermal gradients and the timing of the spring and fall overturn events. Validation is by comparison with physical and chemical measurements collected over the last three decades. The study presents a novel combination of observational data, numerical modelling and empirical relationships to better understand and predict the lake circulation, and consequently the natural ecosystem

INTERACTIVE, WEB-BASED THREE-DIMENSIONAL VISUALIZATIONS OF OPERATIONAL MESOSCALE WEATHER MODELS

Visualization is critical to the effective analysis and assessment of data generated by numerical weather prediction. In that regard, our previous work has discussed methods of appropriate mapping of user goals to the design of pictoria

Coupling of Mesoscale Weather Models to Business Operations Utilizing Visual Data Fusion

In many industries weather conditions are a critical factor in planning business operations and making effective decisions. Typically, what optimization that is applied to these processes to enable proactive efforts utilize either historica