This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Coupling Advanced Modeling and Visualization to Improve High-Impact Tropical Weather Prediction
September/October 2011 (vol. 13 no. 5)
pp. 56-67
Bo-Wen Shen, University of Maryland, College Park

To meet the goals of extreme weather event warning, this approach couples a modeling and visualization system that integrates existing NASA technologies and improves the modeling system's parallel scalability to take advantage of petascale supercomputers. It also streamlines the data flow for fast processing and 3D visualizations, and develops visualization modules to fuse NASA satellite data.

1. US National Research Council Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, The Nat'l Academies Press, 2007.
2. B.W. Shen et al., "Hurricane Forecasts with a Global Mesoscale-Resolving Model: Preliminary Results with Hurricane Katrina," Geophysical Research Letters, vol. 33, no. 15, 2006; doi:10.1029/2006GL026143.
3. B.W. Shen et al., "Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Hierarchical Multiscale Interactions During the Formation of Tropical Cyclone Nargis (2008)," J. Geophysical Research, vol. 115, 2010; doi:10.1029/2009JD013140.
4. R.A. Madden and P.R. Julian, "Detection of a 40–50 Day Oscillation in the Zonal Wind in the Tropical Pacific," J. Atmospheric Science, vol. 28, no. 5, 1971, pp. 702–708.
5. R. Biswas et al., "Petascale Computing: Impact on Future NASA Missions," Petascale Computing: Architectures and Algorithms, D. Bader ed., CRC Press, 2007, pp. 29–46.
6. W.K. Tao et al., "A Goddard Multi-Scale Modeling System with Unified Physics," , World Climate Research Programme/Global Energy and Water Cycle Experiment (WCRP/GEWEX) Newsletter, vol. 18, no. 1, 2008, pp. 6–8.
7. D.B. Ellsworth et al., "Concurrent Visualization in a Production Supercomputing Environment," IEEE Trans. Visualization and Computer Graphics, vol. 12, no. 5, 2006, pp. 997–1004.
8. B. Green, C. Henze, and B.-W. Shen, "Development of a Scalable Concurrent Visualization Approach for High Temporal- and Spatial-Resolution Models," Eos Trans. Am. Geophysical Union, vol. 91, no. 26, 2010; http://atmospheres.gsfc.nasa.gov/cloud_modeling/ docsGreen_Henze_Shen_2010.pdf.
9. S.J. Lin, "A 'Vertically Lagrangian' Finite-Volume Dynamical Core for Global Models," Monthly Weather Review, vol. 132, no. 10, 2004, pp. 2293–2307.
10. R. Atlas et al., "Hurricane Forecasting with the High-Resolution NASA Finite Volume General Circulation Model," Geophysical Research Letters, vol. 32, no. 3, 2005; doi:10.1029/2004GL021513.
11. W.K. Tao and J. Simpson, "The Goddard Cumulus Ensemble Model. Part I: Model Description," Terrestrial, Atmospheric and Oceanic Sciences, vol. 4, 1993, pp. 35–71.
12. J.-M. Juang et al., "Parallelization of NASA Goddard Cloud Ensemble Model for Massively Parallel Computing," Terrestrial, Atmospheric and Oceanic Science s, vol. 18, no. 3, 2007, pp. 593–622.
13. W. Putman, S.J. Lin, and B.W. Shen, "Cross-Platform Performance of a Portable Communication Module and the NASA Finite Volume General Circulation Model," Int'l J. High Performance Computing Applications, vol. 19, no. 3, 2005, pp. 213–223.
14. B.W. Shen et al., "Scalability Improvements in the NASA Goddard Multiscale Multicomponent Modeling Framework for Tropical Cyclone Climate Studies," Proc. Int'l Conf. High-Performance Computing in Asia-Pacific Region, 2009, pp. 249–256; http://atmospheres.gsfc.nasa.gov/cloud_modeling/ docsShen_HPC_ASIA_2009_Proceedings.pdf .
1. R. Biswas et al., "Petascale Computing: Impact on Future NASA Missions," Petascale Computing: Architectures and Algorithms, D. Bader ed., CRC Press, 2007, pp. 29–46.
2. D.B. Ellsworth et al., "Concurrent Visualization in a Production Supercomputing Environment," , IEEE Trans. Visualization and Computer Graphics, vol. 12, no. 5, 2006.
3. R. Atlas et al., "Hurricane Forecasting with the High-Resolution NASA Finite Volume General Circulation Model," Geophysical Research Letters, vol. 32, no. 3, 2005; doi:10.1029/2004GL021513.
4. B.W. Shen et al., "Hurricane Forecasts with a Global Mesoscale-Resolving Model: Preliminary Results with Hurricane Katrina," Geophysical Research Letters, vol. 33, no. 15, 2006; doi:10.1029/2006GL026143.
5. B.W. Shen et al., "Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Hierarchical Multiscale Interactions During the Formation of Tropical Cyclone Nargis (2008)," J. Geophysical Research, vol. 115, 2010; doi:10.1029/2009JD013140.
6. W.K. Tao and J. Simpson, "The Goddard Cumulus Ensemble Model. Part I: Model Description," Terrestrial, Atmospheric and Oceanic Sciences, vol. 4, 1993, pp. 35–71.
7. W.K. Tao et al., "A Goddard Multi-Scale Modeling System with Unified Physics," World Climate Research Programme/Global Energy and Water Cycle Experiment (WCRP/GEWEX) Newsletter, vol. 18, no. 1, 2008, pp. 6–8.

Index Terms:
Hurricane prediction, Global Multiscale Modeling, concurrent visualization, CAMVis, supercomputing, hyperwall, parallel computing, scientific computing and visualization
Citation:
Bo-Wen Shen, Wei-Kuo Tao, Bryan Green, "Coupling Advanced Modeling and Visualization to Improve High-Impact Tropical Weather Prediction," Computing in Science and Engineering, vol. 13, no. 5, pp. 56-67, Sept.-Oct. 2011, doi:10.1109/MCSE.2010.141
Usage of this product signifies your acceptance of the Terms of Use.