MET Online Tutorial for METv8.0 | MODE > Run

Next, run MODE on the command line using the following command:

MODE is now performing the verification task we requested in the configuration file. It should take a minute or two to run. MODE's runtime is greatly influenced by the number of gridpoints in the domain, the convolution radius chosen, and the number of objects resolved. The more dense the domain, larger the convolution radius, and greater the number of objects, the more computations required.

When MODE is finished, it will have created four files: two ASCII statistics files, a NetCDF object file, and a PostScript summary plot. Open up the PostScript summary plot using the PostScript viewer of your choice, gv, or Ghostview, for example:

This PostScript summary plot contains 5 pages. The first page summarizes the application of MODE to this dataset. The second and third pages contain enlargements of the forecast and observation raw and object fields. The fourth page shows the forecast and observation object fields overlaid on top of each other. And the fifth page contains pair-wise differences for the matched clusters of objects. The PostScript summary plot will contain additional pages when additional merging methods are selected. Looking at the first page, note the following:

• The valid data in the forecast field extends much further than in the observation field leading to objects in the forecast field with no match (royal blue = unmatched) in the observation field.
• The forecast field contains 5 objects while the observation field contains 6.
• Two pairs of objects (colored red and green) are matched across these fields. Forecast object 4 matches observed object 5 (red). Forecast object 3 matches observed object 2 (green).

Now, let's modify the configuration file and rerun this case. Again, open up the $MET_TUTORIAL_DATA/config/MODEConfig_tutorial file and edit it as follows:

• In the fcst dictionary, set conv_radius = 2;
  To apply less smoothing before defining objects.
• Set mask_missing_flag = BOTH;
  To mask out the bad data in both fields with each other.

Now, rerun the MODE command listed above, and when it's finished, reload the PostScript plot. Reducing the convolution radius (amount of smoothing) while keeping the convolution threshold fixed should result in a greater number of smaller objects. On the first page of the PostScript plot, note the following:

• The valid data in the raw forecast and observation fields now match up nicely.
• The forecast field contains six objects and the observation field contains 17. These are called simple objects.
• Four sets of objects are now matched across the fields. They are colored red, green, magenta, blue, and light blue.
• Objects that are colored the same color within the same field are called merged. Objects that have the same color across fields are called matched.
• Each set of colored objects is referred to as a cluster object. A cluster object consists of one or more simple objects. For example, in the observation field, simple object numbers 11 and 13 (both colored green) are merged together and are members of the same cluster object. They match forecast object number 4 which is its own cluster object.

After completing the next page on MODE Output, users are welcome to return to this page, play around with settings in the configuration file, and rerun this case several times. Listed below are some configuration parameters you may want to try modifying:

• total_interest_thresh
• fcst_conv_radius and obs_conv_radius
• fcst_conv_thresh and obs_conv_thresh
• fcst_area_thresh and obs_area_thresh
• fcst_inten_thresh and obs_inten_thresh
• fcst_merge_thresh and obs_merge_thresh with fcst_merge_flag and obs_merge_flag both set to 1