IEEE Visualization 2004 Contest
Data Set
The theme for the inaugural IEEE Visualization contest was visualization fusion. The goal was to provide a data set which will allow researchers to showcase their visualization techniques from a wide range of disciplines. Since the type of information being shown is so diverse, we hoped to encourage collaboration of researchers from all domains of scientific and information visualization.
The data set for this contest is a simulation of a hurricane from the National Center for Atmospheric Research in the United States. The data consists of several time-varying scalar and vector variables over large dynamic ranges. The sheer size of the data also presents a challenge for interactive exploration.
Data Format
A summary of the data can be found below:
- Dimensions: 500 x 500 x 100
- Physical Scale: 2139km (east-west) x 2004km (north-south) x 19.8km (vertical) Note: The east-west distance of 2139km is measured at the southern latitude; the distance is only 1741km at the northern latitude due to the curvature of the earth.
- Physical Location: Longitude (x): 83W to 62W; Latitude (y): 23.7N to 41.7N; Height (z): 0.035km to 19.835km
- Format: Brick-of-Floats
- Number of Variables: 13
- Number of Time Steps: 48 (1 simulated hour between time steps)
- Size per Time Step: ~95 MB uncompressed
Format
The data is in "Brick-of-Floats" format. It consists of a volume of data values at each position in space. The three-dimensional array of data consists of planes of x-y values in ascending z order; in the data, the x values vary fastest. Assuming the data was stored as a one-dimensional array, the index into that array for the point x, y, z would be:
where dim_x is the number of x values (500) and dim_y is the number of y values (500).
Variables
The following table described the variables in the data set. Each variable is contained in a separate data file, one for each time step. All data values are floating-point values.
| Variable | Description | Range |
|---|---|---|
| QCLOUD | Cloud moisture mixing ratio (kg water/kg dry air) | 0.00000/0.00332 |
| QGRAUP | Graupel mixing ratio (solid ice precipitation: hail, sleet, snow pellets) | 0.00000/0.01638 |
| QICE | Cloud ice mixing ratio | 0.00000/0.00099 |
| QSNOW | Snow mixing ratio | 0.00000/0.00135 |
| QVAPOR | Water vapor mixing ratio | 0.00000/0.02368 |
| CLOUD | Total cloud moisture mixing ratio (QCLOUD+QICE) | 0.00000/0.00332 |
| PRECIP | Total precipitation mixing ratio (QGRAUP+QRAIN+QSNOW) | 0.00000/0.01672 |
| P | Pressure (weight of atmosphere above a grid point) | -5471.85791/3225.42578 |
| TC | Temperature (Celsius) | -83.00402/31.51576 |
| U | X wind speed (positive means winds from west to east) | -79.47297/85.17703 |
| V | Y wind speed (positive means winds from south to north) | -76.03391/82.95293 |
| W | Z wind speed (positive means upward wind) | -9.06026/28.61434 |
Note that all data is stored in big-endian format and compressed via GNU zip (gzip) for storage. Each file is named VARfNN.bin.gz where VAR is the variable name and NN is the time step.
Physical Position
Since the data in question simulates an actual event (a hurricane), each computational data point (voxel) corresponds to an actual physical point. The surface topology (for the actual ground) is in a special 500x500x1 data file (HGTdata.bin.gz). In the other files, where there is ground, no data is recorded. The special value for this "no data" value is 1.0000000e+35.
Acquiring the Data
Data can be downloaded from following locations- NCAR Server : A README file with more information and a Python script to simplify downloading the data are also available.
- SDSC Cloud : You can easily download all data by using wget as follows % wget -r -nH --no-parent --cut-dirs=2 https://cloud.sdsc.edu/v1/AUTH_sciviscontest/2004/isabeldata
- Kitware Server
If you use the data set, please provide the following attribution:
The authors will like to thank Bill Kuo, Wei Wang, Cindy Bruyere, Tim Scheitlin, and Don Middleton of the U.S. National Center for Atmospheric Research (NCAR) and the U.S. National Science Foundation (NSF) for providing the Weather Research and Forecasting (WRF) Model simulation data of Hurricane Isabel.
A shorter attribution is:
Hurricane Isabel data produced by the Weather Research and Forecast (WRF) model, courtesy of NCAR and the U.S. National Science Foundation (NSF).
For More Information
For for information about hurricanes or the method used to generate the data, consult the following links.
- The hurricane modeled is Hurricane Isabel from September of 2003. It was a very strong hurricane in the west Atlantic region.
- Tropical Cyclones from the University of Wisconsin
- Tropical Cyclone Archive from the National Weather Service
- The Weather Research and Forecasting (WRF) Model was used to generate the data
Acknowledgments
The data set has kindly been provided by Wei Wang, Cindy Bruyere, Bill Kuo, and others at NCAR. Tim Scheitlin at NCAR converted the data into the Brick-of-Float format described above.