Turbulence Ensemble - Random Variations

Another component of the uncertainty in the concentration calculation is the contribution of random motions by atmospheric turbulence. The model already computes this turbulence when computing particle dispersal. However, normally we would try to release a sufficiently large number of particles to insure that each simulation gives similar results. In the turbulence ensemble approach, we reduce the particle release number and run multiple simulations, each with a different random number seed, and then examine the variations between simulations. Start by retrieving the previously saved captex_control.txt and captex_setup.txt settings into the GUI menu.

1. After the Setup Run and the Advanced Configuration menus have been retrieved, open the Advanced / Menu #4 and change the particle release per cycle from 50000 to 2500. Although the turbulence ensemble can be composed of any number of members, to parallel the meteorological grid ensemble, 27 variations are also run in this case. The 2500 is determined by dividing 50000 by the number of members to maintain about the same total particle number when computing the mean concentration.


2. After saving the change, press the Special Runs / Ensemble / Turbulence menu tab. There are no data entry options, just a prompt menu to ask if you really want to continue with the ensemble turbulence calculation. The calculation will start and as each member calculation is completed, a message is added to the simulation log and finally a completion message when member 27 finishes.


3. Following the same procedure as previously with the meteorological ensemble, select the Display / Ensemble / View Map menu tab. This step is required to display probability maps or box plots because it invokes the pre-processor step that creates the probability files from the individual concentration simulations. Display any map and then open the box plot menu and enter the same position 42.25 -78.80, sampler 510 (Little Valley, NY), used in the previous section.


4. The resulting box plot with values every 3-h rather than every 6-h as in the previous example, shows that for two periods with the highest concentrations, the 90th percentile concentration uncertainty range (5th to 95th) is about a factor of four.

The approach shown here, using the model's random number generator, provides some guidance as to how much variability might be introduced by atmospheric turbulence. On your own, try two additional simulations, one with a greater particle release rate and another with an even smaller release rate, and view the effect on the concentration uncertainty at sampler 510.