Exercise #12




  • Problem #1 - Recompute the multiple meteorological data ensemble and determine whether decreasing the concentration grid size and increasing the particle number will improve the ensemble mean results.

  • Hint - Simply edit ens_data.{bat|sh} to double the resolution (0.125 deg and 20,000 particles). Perhaps also change the name of the binary concentration output file to avoid conflicts.

  • Solution - Most individual simulations showed only small differences, some worse, some better. The statistical results for the mean model (006) showed a slight improvement in most metrics compared to the original coarse resolution result.
  • 11 m 31 s

  • Problem #2 - Using the existing output files from the physics ensemble, compute the performance statistics for each member and the ensemble mean.

  • Hint - Using the binary file merge menu, compute the ensemble mean for the 15 members. Then using the ensemble statistics menu, create the file of the summary statistics.

  • Solution - In this example, the better performance of the ensemble mean is not evident. The scatter diagram of the physics ensemble mean is comparable to the scatter diagram of the meteorological ensemble mean calculated in a previous section. The best performance is indicated by member #8 (Beljaars turbulence), which is very similar to the ensemble mean results.

  • Problem #3 (for advanced users only) - If your computer has multiple processors, can you configure the standard CAPTEX simulation to run on two processors so the simulation completes in about half the time?

  • Hint - Use the KRAND=4 namelist option to run two simultaneous simulations, each with half the number of particles, and then add the results together.

  • Solution - CPU Monitor