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# 27.1 Program CODAQ_AREA

CODAQ outputs the Q-values at midpoints between station and events. Using these values directly will often not show consistent results so some averring is needed. CODAQ_AREA reads this output and, at each frequency, average Q-values in user defined lat-lon bins. In each bin, provided there is enough data, the Q relation

Q =Q0*f**qalpha

is also calculated. If little data is available, Q0 can additionally be calculated for fixed qalpha given by the user. Results are also made for f=10 Hz, Q10, since this might show the differences between areas more clearly. The values in each bin is listed in an output file which can be displayed to get an approximate idea of the areal Q-distribution. In addition, a contoured map is made with EPIMAP of Q0 or Q10 and started from CODAQ_AREA. Optionally it can be deselected with parameter *Extrapolate', see below.

Input files: It is assumed that codaq.area and codaq1.out exist so these names are hardwired. Codaq1.out is used to get the frequencies available for the data set.

The interactive options are: Min no for grid average, min no of freq for Q0 calculation: Minimum number of values in a grid point for average to be calculated

Constant qalpha in Q=Q0*f**qalpha relation, 0 means do not use: Q0, can optional be calculated with a fixed qalpha. This can be useful when there is little data and it is expected that qalpha does not vary a lot over a region.

Print numbers of observations for each Q0: 1 else 0: When printing out the Q0, it is also possible to print out the total number of observations used for calculating Q0. This is all results for all frequencies.

Extrapolate q0 or q10 for plot, 0=no, 1=yes, -1= do no plot contours: When making the contours, it is possible to extrapolate the Q0 or Q10 values to bins with no data. This is done by averaging the values for the bins around. This process is done several times to fill the complete grid so in gridpoints more than 2 away from grids with data, all values will be constant.

Plot Q0 (0) or q10 (1): Plot Q0 or Q10

Latitude range and grid size: It can be a fraction of a degree but Q0 does not have resolutions better than one degree.

Longitude range and grid size: ----------------

The interactive options can be stored in a file called codaq_area.inp. If the file is present, input will be read from that file and no questions asked. An example of the file is:

Minimum number for grid average
3
Minimum number of frequencies for Q0 calculation
4
Constant qalpha in Q=Q0*f**qalpha relation, 0 means do not use
0.0
Print numbers of observations for each Q0 (1), else 0
0
Extrapolate q0 or q10 for plot, 0=not, 1=yes
1
Plot Q0 (0) or q10 (1)
0
Latitude range and delta
34 44 1
Longitude range and delta
-12,-2 1


The comments between the lines with numbers are just for information but there must be a line. This example file is also in DAT.

Example run with input from parameter file so no questions:

C:\>codaq_area
Frequencies    1.00    2.00    4.00    8.00   16.00
Min no for grid average, min no of freq for Q0 calculation           3           4
Constant in Q-relation, print number of observations   0.00000000               0
Extrapolate, plot Q0           0           0
Lat range and delta   34.0000000       44.0000000       1.00000000
Lon range and delta  -14.0000000      -2.00000000       1.00000000
Number of q-data in input file        4581
Number of q-data inside grid          4581

Range of Q values to plot    58.4   310.7
Writing codaq_area_epimap.inp
....
....   epimap output
....

File with area grid:    codaq_area.out
File with grid points: codaq_grid.out
File with epimap commands: codaq_area_epimap.inp


Example of the areal output file coda_area.out showing the lat-lon bins, note the midpoint of the bin is used:


freq=   1.00000000
-13.5 -12.5 -11.5 -10.5  -9.5  -8.5  -7.5  -6.5  -5.5  -4.5  -3.5  -2.5
43.5     0     0     0     0     0     0     0     0     0     0     0     0
42.5     0     0     0     0     0     0     0     0     0     0     0     0
41.5     0     0     0     0     0     0     0     0     0     0     0     0
40.5     0     0     0     0     0     0     0     0     0     0     0     0
39.5     0     0     0     0    81    93     0     0     0     0     0     0
38.5     0     0     0     0   136   114     0     0   196     0     0     0
37.5     0     0     0     0     0     0     0     0     0    88    94     0
36.5     0     0    97     0     0   141     0    83   124     0   103     0
35.5     0     0     0   134     0     0     0     0   107     0     0     0
34.5     0     0     0     0     0     0     0     0    89     0     0     0
freq=   2.00000000
-13.5 -12.5 -11.5 -10.5  -9.5  -8.5  -7.5  -6.5  -5.5  -4.5  -3.5  -2.5
43.5     0     0     0     0     0     0   256     0     0     0     0     0
42.5     0     0     0     0   323     0     0   227     0     0     0     0
41.5     0     0     0     0     0   394   150     0     0     0     0     0
40.5     0     0     0     0     0   112     0     0     0     0     0     0
39.5     0     0     0     0   221   227     0     0     0     0     0     0
38.5     0     0     0     0   256   338   303     0     0     0     0     0
37.5     0     0     0     0     0   245   273     0     0   126   125     0
36.5     0   219   141     0     0   156     0   133   155     0   135     0
35.5     0     0     0   155     0     0     0     0   155     0     0     0
34.5     0     0     0     0     0     0     0     0   128     0     0     0
freq=   4.00000000
-13.5 -12.5 -11.5 -10.5  -9.5  -8.5  -7.5  -6.5  -5.5  -4.5  -3.5  -2.5
43.5     0     0     0     0     0     0   487     0     0     0     0     0
42.5     0     0     0     0   619     0     0   411     0     0     0     0
41.5     0     0     0     0     0   640   485   565     0     0     0     0
40.5     0     0     0     0     0   502   546     0     0     0     0     0
39.5     0     0     0     0   556   531     0     0     0     0     0     0
38.5     0     0     0     0   503   560   540     0     0   623     0     0
37.5     0     0     0     0   319   500   505     0   265   235   207     0
36.5     0   287   210   384   280   303   287   196   211     0   204     0
35.5     0     0     0   273     0     0   207     0   233     0     0     0
34.5     0     0     0     0     0     0     0     0   209     0     0     0
freq=   8.00000000
-13.5 -12.5 -11.5 -10.5  -9.5  -8.5  -7.5  -6.5  -5.5  -4.5  -3.5  -2.5
43.5     0     0     0     0     0   790   803     0     0     0     0     0
42.5     0     0     0     0   921  1121     0   712     0     0     0     0
41.5     0     0     0     0     0   859   896   808     0     0     0     0
40.5     0     0     0     0     0   732   797     0     0     0     0     0
39.5     0     0     0     0   948   880   667     0     0     0   808     0
38.5     0     0     0     0   884   897   836     0  1002  1028     0     0
37.5     0     0     0     0   622   812   899   970   774   463   379     0
36.5     0   486   386   604   569   607   577     0     0     0   358     0
35.5     0     0     0   492     0     0     0     0   754     0     0     0
34.5     0     0     0     0     0     0     0     0   518     0     0     0
freq=   16.0000000
-13.5 -12.5 -11.5 -10.5  -9.5  -8.5  -7.5  -6.5  -5.5  -4.5  -3.5  -2.5
43.5     0     0     0     0     0  1238  1306  1342     0     0     0     0
42.5     0     0     0     0  1362  1574     0  1216     0     0     0     0
41.5     0     0     0     0     0     0  1499  1302     0     0     0     0
40.5     0     0     0     0     0     0  1451     0     0     0     0     0
39.5     0     0     0     0  1558  1376     0     0     0     0     0     0
38.5     0     0     0     0  1534  1375  1295  1442     0  1537     0     0
37.5     0     0     0     0  1413  1306  1366  1418     0   970   805     0
36.5     0     0     0     0  1007  1427     0     0     0     0     0     0
35.5     0     0     0  1188     0     0     0     0     0     0     0     0
34.5     0     0     0     0     0     0     0     0   989     0     0     0
Q0
-13.5 -12.5 -11.5 -10.5  -9.5  -8.5  -7.5  -6.5  -5.5  -4.5  -3.5  -2.5
43.5     0     0     0     0     0     0   160     0     0     0     0     0
42.5     0     0     0     0   226     0     0   133     0     0     0     0
41.5     0     0     0     0     0   256   129     0     0     0     0     0
40.5     0     0     0     0     0    58     0     0     0     0     0     0
39.5     0     0     0     0   103   126     0     0     0     0     0     0
38.5     0     0     0     0   142   162   193     0   196   266     0     0
37.5     0     0     0     0    69   169   166   310     0    85    77     0
36.5     0   114    83     0     0    87     0     0     0     0    83     0
35.5     0     0     0   118     0     0     0     0    93     0     0     0
34.5     0     0     0     0     0     0     0     0    72     0     0     0
Q10
-13.5 -12.5 -11.5 -10.5  -9.5  -8.5  -7.5  -6.5  -5.5  -4.5  -3.5  -2.5
43.5     0     0     0     0     0     0   923     0     0     0     0     0
42.5     0     0     0     0  1032     0     0   841     0     0     0     0
41.5     0     0     0     0     0  1115  1005     0     0     0     0     0
40.5     0     0     0     0     0  1468     0     0     0     0     0     0
39.5     0     0     0     0  1061   965     0     0     0     0     0     0
38.5     0     0     0     0  1035  1034   962     0  1193  1150     0     0
37.5     0     0     0     0   848   933  1006  1096     0   522   457     0
36.5     0   559   440     0     0   857     0     0     0     0   417     0
35.5     0     0     0   747     0     0     0     0   561     0     0     0
34.5     0     0     0     0     0     0     0     0   590     0     0     0
Qalpha
-13.5 -12.5 -11.5 -10.5  -9.5  -8.5  -7.5  -6.5  -5.5  -4.5  -3.5  -2.5
43.5  0.00  0.00  0.00  0.00  0.00  0.00  0.76  0.00  0.00  0.00  0.00  0.00
42.5  0.00  0.00  0.00  0.00  0.66  0.00  0.00  0.80  0.00  0.00  0.00  0.00
41.5  0.00  0.00  0.00  0.00  0.00  0.64  0.89  0.00  0.00  0.00  0.00  0.00
40.5  0.00  0.00  0.00  0.00  0.00  1.40  0.00  0.00  0.00  0.00  0.00  0.00
39.5  0.00  0.00  0.00  0.00  1.01  0.88  0.00  0.00  0.00  0.00  0.00  0.00
38.5  0.00  0.00  0.00  0.00  0.86  0.80  0.70  0.00  0.78  0.64  0.00  0.00
37.5  0.00  0.00  0.00  0.00  1.08  0.74  0.78  0.55  0.00  0.79  0.77  0.00
36.5  0.00  0.69  0.72  0.00  0.00  0.99  0.00  0.00  0.00  0.00  0.70  0.00
35.5  0.00  0.00  0.00  0.80  0.00  0.00  0.00  0.00  0.78  0.00  0.00  0.00
34.5  0.00  0.00  0.00  0.00  0.00  0.00  0.00  0.00  0.91  0.00  0.00  0.00


Output file codaq_grid.out contains details of the averages in each bin see part of file below:



freq=   1.00000000
34.500   -13.500       0.0       0.0         0
34.500   -12.500       0.0       0.0         0
34.500   -11.500       0.0       0.0         0
34.500   -10.500       0.0       0.0         0
34.500    -9.500       0.0       0.0         0
34.500    -8.500       0.0       0.0         0
34.500    -7.500       0.0       0.0         0
34.500    -6.500       0.0       0.0         2
34.500    -5.500      89.5      21.1        81
34.500    -4.500       0.0       0.0         0
34.500    -3.500       0.0       0.0         0
34.500    -2.500       0.0       0.0         0
35.500   -13.500       0.0       0.0         0
35.500   -12.500       0.0       0.0         0
35.500   -11.500       0.0       0.0         0
35.500   -10.500     134.9      13.7         3
35.500    -9.500       0.0       0.0         0
35.500    -8.500       0.0       0.0         0
35.500    -7.500       0.0       0.0         0
35.500    -6.500       0.0       0.0         0
35.500    -5.500     107.8      15.8         4
35.500    -4.500       0.0       0.0         0
35.500    -3.500       0.0       0.0         0
35.500    -2.500       0.0       0.0         0
36.500   -13.500       0.0       0.0         0
36.500   -12.500       0.0       0.0         1
36.500   -11.500      97.4      49.9         5
36.500   -10.500       0.0       0.0         0
36.500    -9.500       0.0       0.0         0
36.500    -8.500     141.6      66.4         6
36.500    -7.500       0.0       0.0         0
36.500    -6.500      83.0      19.4        15
36.500    -5.500     124.6       9.9         3
36.500    -4.500       0.0       0.0         0
36.500    -3.500     103.4      24.0         3
36.500    -2.500       0.0       0.0         0
37.500   -13.500       0.0       0.0         0
37.500   -12.500       0.0       0.0         0
37.500   -11.500       0.0       0.0         0
37.500   -10.500       0.0       0.0         0
37.500    -9.500       0.0       0.0         0
37.500    -8.500       0.0       0.0         2
37.500    -7.500       0.0       0.0         0
37.500    -6.500       0.0       0.0         0
37.500    -5.500       0.0       0.0         0
37.500    -4.500      88.6      13.9        15
37.500    -3.500      94.8      19.9        21
37.500    -2.500       0.0       0.0         0
38.500   -13.500       0.0       0.0         0
38.500   -12.500       0.0       0.0         0
38.500   -11.500       0.0       0.0         0
38.500   -10.500       0.0       0.0         0
38.500    -9.500     136.3      53.6         9
38.500    -8.500     114.3      40.5         4
38.500    -7.500       0.0       0.0         0
38.500    -6.500       0.0       0.0         0
38.500    -5.500     196.6      17.3         3
38.500    -4.500       0.0       0.0         0
38.500    -3.500       0.0       0.0         0
38.500    -2.500       0.0       0.0         0
39.500   -13.500       0.0       0.0         0
39.500   -12.500       0.0       0.0         0
39.500   -11.500       0.0       0.0         0
39.500   -10.500       0.0       0.0         0
39.500    -9.500      81.2      17.9         9
39.500    -8.500      93.5      30.9        12
39.500    -7.500       0.0       0.0         0
39.500    -6.500       0.0       0.0         0
39.500    -5.500       0.0       0.0         0
39.500    -4.500       0.0       0.0         0
39.500    -3.500       0.0       0.0         0
39.500    -2.500       0.0       0.0         0
40.500   -13.500       0.0       0.0         0
40.500   -12.500       0.0       0.0         0
40.500   -11.500       0.0       0.0         0
40.500   -10.500       0.0       0.0         0
40.500    -9.500       0.0       0.0         0
40.500    -8.500       0.0       0.0         2
40.500    -7.500       0.0       0.0         0
40.500    -6.500       0.0       0.0         0
40.500    -5.500       0.0       0.0         0
40.500    -4.500       0.0       0.0         0
40.500    -3.500       0.0       0.0         0
40.500    -2.500       0.0       0.0         0
41.500   -13.500       0.0       0.0         0
41.500   -12.500       0.0       0.0         0
41.500   -11.500       0.0       0.0         0
41.500   -10.500       0.0       0.0         0
41.500    -9.500       0.0       0.0         0
41.500    -8.500       0.0       0.0         0
41.500    -7.500       0.0       0.0         1
41.500    -6.500       0.0       0.0         0
41.500    -5.500       0.0       0.0         0
41.500    -4.500       0.0       0.0         0
41.500    -3.500       0.0       0.0         0
41.500    -2.500       0.0       0.0         0
42.500   -13.500       0.0       0.0         0
42.500   -12.500       0.0       0.0         0
42.500   -11.500       0.0       0.0         0
42.500   -10.500       0.0       0.0         0
42.500    -9.500       0.0       0.0         0
42.500    -8.500       0.0       0.0         0
42.500    -7.500       0.0       0.0         0
42.500    -6.500       0.0       0.0         0
42.500    -5.500       0.0       0.0         0
42.500    -4.500       0.0       0.0         0
42.500    -3.500       0.0       0.0         0
42.500    -2.500       0.0       0.0         0
43.500   -13.500       0.0       0.0         0
43.500   -12.500       0.0       0.0         0
43.500   -11.500       0.0       0.0         0
43.500   -10.500       0.0       0.0         0
43.500    -9.500       0.0       0.0         0
43.500    -8.500       0.0       0.0         0
43.500    -7.500       0.0       0.0         0
43.500    -6.500       0.0       0.0         0
43.500    -5.500       0.0       0.0         0
43.500    -4.500       0.0       0.0         0
43.500    -3.500       0.0       0.0         0
43.500    -2.500       0.0       0.0         0
freq=   2.00000000
34.500   -13.500       0.0       0.0         0
34.500   -12.500       0.0       0.0         0
34.500   -11.500       0.0       0.0         0
34.500   -10.500       0.0       0.0         0
34.500    -9.500       0.0       0.0         0
34.500    -8.500       0.0       0.0         0
34.500    -7.500       0.0       0.0         0
34.500    -6.500       0.0       0.0         2
34.500    -5.500     129.0      23.5       114
34.500    -4.500       0.0       0.0         0
34.500    -3.500       0.0       0.0         0
34.500    -2.500       0.0       0.0         0
35.500   -13.500       0.0       0.0         0
35.500   -12.500       0.0       0.0         0
35.500   -11.500       0.0       0.0         1
35.500   -10.500     155.4      26.0        23
35.500    -9.500       0.0       0.0         1
35.500    -8.500       0.0       0.0         0
35.500    -7.500       0.0       0.0         0
35.500    -6.500       0.0       0.0         0
35.500    -5.500     155.6      13.4        11
35.500    -4.500       0.0       0.0         0
35.500    -3.500       0.0       0.0         0
35.500    -2.500       0.0       0.0         0
36.500   -13.500       0.0       0.0         0
36.500   -12.500     219.2     106.5         5
36.500   -11.500     141.4      30.3         7
36.500   -10.500       0.0       0.0         0


The output is: Bin midpoint, average Q, standard deviation in average and number of points in bin.

Finally a plot is made with contours of Q, see Figure 27.2.

The map with the contours is produced automatically from the input. The projection is Mercator and the land contour is WORLD.MAP in DAT. Another map file can be used by setting parameter EPIMAP_MAP_FILE in SEISAN.DEF. The commands for running EPIMAP are in output file codaq_area_epimap.inp, so this file can also be modified to change map projection etc (see EPIMAP) and the plot regenerated by giving command

epimap codaq_area_epimap.inp

Next: 27.2 Program CODAQ_POLYGON Up: 27. Calculation of coda Previous: 27.0.4 General recommendations and   Contents   Index
Peter Voss : Mon Nov 19 07:59:27 UTC 2018