Tuesday, 8 January 2013: 9:00 AM
Room 12B (Austin Convention Center)
VAPOR is a visualization and analysis tool developed at NCAR, targeted at interactive 3D visualization and analysis of massive earth-science datasets. We report here on the recent addition to VAPOR of an embedded Python/NumPy interpreter. The primary use of this interpreter is to support creation and visualize derived variables as required by users. VAPOR's Python capabilities complement VAPOR's efficient handling of massive datasets, so that the visualization of Python-derived variables is accelerated through the use of wavelet compression, region control and data caching. To limit the I/O overhead of visualizing these variables, the Python-derived variables are only evaluated as needed, and only entail accessing data at the user's required compression level and data sub-region. VAPOR supports a library of Python functions of particular use in analyzing NWP data, such as cloud-top height, potential vorticity, relative humidity, etc. This presentation will demonstrate the use of Python in VAPOR with several examples of interactive weather visualization using WRF and related models.
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