Visualization and animating of Pan European Climate Simulation with the WRF Model using ParaView Python-Scripting

Data

In this example, one data file containing 12 timesteps was given. The file is stored at /arch/software/grafprod/data/slts.fz-juelich.de/k.goergen/WRF_initial_example/wrf_rv025_r07_test.wrfout_3km.20100702130000-20100703000000.nc in netCDF format. As netCDF 3 is used, the file had to be converted to netCDF 4 (which is hdf5) via "nccopy -k 4 foo3.nc foo4c.h5".

Variables of Interest

3D Scalar Variables

The 3D variables are located on a grid of size 49x1552x1600. As for each variable all 12 timesteps are stored in one hdf5 array, the size of this array is 12x49x1552x1600, obviously. Here is a list of interesting scalar variables:

• CLDFRA: Cloud Fraction (values from 0 to 1)
• QNICE: Ice Number concentration (values from -1.1e-8 to 1.3e6, good value for visualisation: 10000)
• QNRAIN: Rain Number concentration (values from -3e-5 to 620000, good value for visualisation: 5000)
• QVAPOR: Water vapor mixing ratio (values from -0.0043 bis 0.0207, good value for visualisation: 0.005)

3D Vector Variables

The wind components are stored on a staggered grid. Please note, that therefore the array size of those components vary along one axis Vector Components:

• U: x-wind component (12 x 49 x 1552 x 1601)
• V: y-wind component (12 x 49 x 1553 x 1600)
• w: z-wind component (12 x 50 x 1552 x 1600)

2D Scalar Variables

There are also a couple of surface related 2D variables includes in the data, located on a grid of size 12x1552x1600. Some examples:

• HGT: Terrain Height
• LH: Latent Heat Flux at the Surface