Point-Stat Tool: Reconfigure
Now we'll reconfigure and rerun Point-Stat.
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.
- 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.
- 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.