Reconfigure

Point-Stat Tool: Reconfigure

Now we'll reconfigure and rerun Point-Stat.

Start by making a copy of the configuration file we just used:

cp PointStatConfig_tutorial_run1 PointStatConfig_tutorial_run2

This time, we'll use two dictionary entries to specify the forecast field in order to set different thresholds for each vertical level. Point-Stat may be configured to verify as many or as few model variables and vertical levels as you desire.

Edit the PointStatConfig_tutorial_run2 file as follows:

vi PointStatConfig_tutorial_run2

Set:

fcst = {
   field = [
    {
      name       = "TMP";
      level      = [ "Z2" ];
      cat_thresh = [ >273, >278, >283, >288 ];
},
    {
name       = "TMP";
      level      = [ "P750-850" ];
      cat_thresh = [ >278 ];
    }
];
}
obs = fcst;

to verify 2-meter temperature and temperature fields between 750hPa and 850hPa, using the thresholds specified.
Set:

message_type = ["ADPUPA","ADPSFC"];
sid_inc = [];
sid_exc = [];
obs_quality = [];
duplicate_flag = NONE;
obs_summary = NONE;
obs_perc_value = 50;

to include the Upper Air (UPA) and Surface (SFC) observations in the evaluation
Set:

mask = {
   grid = [ "G212" ];
   poly = [ "MET_BASE/poly/EAST.poly",
             "MET_BASE/poly/WEST.poly" ];
   sid   = [];
   llpnt = [];
}

to compute statistics over the NCEP Grid 212 region and over the Eastern and Western United States, as defined by the polylines specified.
Set:

interp = {
vld_thresh = 1.0;
shape       = SQUARE;
type = [
      {
         method = NEAREST;
         width = 1;
      },
      {
         method = DW_MEAN;
         width = 5;
      }
   ];
}

to indicate that the forecast values should be interpolated to the observation locations using the nearest neighbor method and by computing a distance-weighted average of the forecast values over the 5 by 5 box surrounding the observation location.
Set:

output_flag = {
   fho    = BOTH;
   ctc    = BOTH;
   cts    = BOTH;
   mctc   = NONE;
   mcts   = NONE;
   cnt    = BOTH;
   sl1l2 = BOTH;
   sal1l2 = NONE;
   vl1l2 = NONE;
   val1l2 = NONE;
   pct    = NONE;
   pstd   = NONE;
   pjc    = NONE;
   prc    = NONE;
   ecnt   = NONE;
   eclv   = BOTH;
   mpr    = BOTH;
}

to switch the SL1L2 and CTS output to BOTH and generate the optional ASCII output files for them.
Set:

output_prefix = "run2";

to customize the output file names for this run.

Let's look at our configuration selections and figure out the number of verification tasks Point-Stat will perform:

2 fields: TMP/Z2 and TMP/P750-850
2 observing message types: ADPUPA and ADPSFC
3 masking regions: G212, EAST.poly, and WEST.poly
2 interpolations: UW_MEAN width 1 (nearest-neighbor) and DW_MEAN width 5

Multiplying 2 * 2 * 3 * 2 = 24. So in this example, Point-Stat will accumulate matched forecast/observation pairs into 24 groups. However, some of these groups will result in 0 matched pairs being found. To each non-zero group, the specified threshold(s) will be applied to compute contingency tables.

Can you diagnose why some of these verification tasks resulted in zero matched pairs? (Hint: Reread the tip two pages back!)

cindyhg Tue, 06/25/2019 - 09:44