HR: 17:05h
AN: IN24A-04    [Abstracts]
TI: Frameworks for Geoscience Data Analysis and Visualization
AU: * Brown, D I
EM: dbrown@ucar.edu
AF: National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, CO 80305, United States
AU: Haley, M
EM: haley@ucar.edu
AF: National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, CO 80305, United States
AU: Clare, F
EM: fred@ucar.edu
AF: National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, CO 80305, United States
AU: Grubin, R
EM: grubin@ucar.edu
AF: National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, CO 80305, United States
AU: Shea, D
EM: shea@ucar.edu
AF: National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, CO 80305, United States
AB: We present a suite of tools developed at NCAR for analyzing and visualizing geoscientific data. NCL, a self- contained scripting language, provides robust file input and output for a number of commonly used scientific formats, including NetCDF, HDF, and GRIB, and most recently GRIB 2. It provides hundreds of analysis functions and has easily accessed 2D visualization capabilities that many consider to be world class. Its diverse and rapidly growing user base is spread among more than 70 countries around the world. Recently, in order to reach a wider scientific community, we have developed new Python interfaces to NCL's capabilities. PyNGL and PyNIO are Python modules that provide access to essentially the same visualization and data I/O functionality as NCL. The programming style is remarkably similar, allowing users to easily move between the NCL and Python languages. The online documentation has step-by-step tutorials for getting up to speed with PyNGL and PyNIO. There are also hundreds of examples showing how to ingest, analyze and visualize many varieties of data. This year we are releasing the complete suite of tools as OSI-compliant open source. The tools are under continuous development with active community input. Our current projects are porting the analysis functions to the Python environment and adding support for the NetCDF 4 and HDF 5 file formats.
UR: http:www.ncl.ucar.edu/
DE: 0520 Data analysis: algorithms and implementation
SC: Earth and Space Science Informatics [IN]
MN: 2007 Joint Assembly