Acquisition and Display of Real-Time Atmospheric Data on Terrain

This paper investigates the integrated acquisition, organization, and display of data from disparate sources, including the display of data acquired in real-time. In this case real-time acquisition and display refers to the capture and visualization of data as they are being produced. The particular application investigated is 3D dynamic atmospheric data on terrain, but key elements presented here are applicable more generally to other types of real-time data. 3D Doppler radar data are acquired and visualized with global, high resolution terrain. This is the first time such data have been displayed together in a real-time environment and provides the potential for new vistas in forecasting and analysis. Associated data such as buildings and maps are displayed along with the weather data and the terrain. A global hierarchical structure makes these disparate data available for integrated visualization in real-time. Requirements for effective 3D visualization for decision-making are identified, and it is shown that the applications presented meet most of these requirements.

[1]  Philip C. Chen.  Climate and weather simulations and data visualization using a supercomputer, workstations, and microcomputers , 1996, Electronic Imaging.

[2]  Lloyd A. Treinish.  Task-specific visualization design: a case study in operational weather forecasting , 1998 .

[3]  David Ellsworth,et al.  Application-controlled demand paging for out-of-core visualization , 1997, Proceedings. Visualization '97 (Cat. No. 97CB36155).

[4]  Robert E. Mercer,et al.  Tracking severe weather storms in Doppler radar images , 1998, Int. J. Imaging Syst. Technol..

[5]  Arthur Witt,et al.  The National Severe Storms Laboratory Tornado Detection Algorithm , 1998 .

[6]  William Ribarsky,et al.  Efficient Ray Intersection for Visualization and Navigation of Global Terrain using Spheroidal Height-Augmented Quadtrees , 1999, VisSym.

[7]  William Ribarsky,et al.  Real-Time Global Data Model for the Digital Earth , 2000 .

[8]  William Ribarsky,et al.  Intent, perception, and out-of-core visualization applied to terrain , 1998, Proceedings Visualization '98 (Cat. No.98CB36276).

[9]  William Ribarsky,et al.  Real-time visualization of scalably large collections of heterogeneous objects (case study) , 1999, VIS '99.

[10]  Ben Shneiderman,et al.  Design and evaluation of incremental data structures and algorithms for dynamic query interfaces , 1997, Proceedings of VIZ '97: Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium.

[11]  Arthur Witt,et al.  The Storm Cell Identification and Tracking Algorithm: An Enhanced WSR-88D Algorithm , 1998 .

[12]  John Anderson,et al.  Exploring Coupled Atmosphere-Ocean Models Using Vis5D , 1996, Int. J. High Perform. Comput. Appl..

[13]  William Ribarsky,et al.  Real-time visualization of scalably large collections of heterogeneous objects , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[14]  Alex T. Pang,et al.  Visualizing gridded datasets with large number of missing values , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[15]  William Ribarsky,et al.  Third-person navigation of whole-planet terrain in a head-tracked stereoscopic environment , 1999, Proceedings IEEE Virtual Reality (Cat. No. 99CB36316).