Re: [ferret_users] normalization query

["Ansley C. Manke" <ansley.b.manke@xxxxxxxx>]

Hi,

I'm not sure why this is happening.  I am noticing that in the two listings that you show, the headers are different.  It seems that perhaps there are different regions or grids being used as the computations are done.

list ohcc_pps,ohcc_ggs
             LATITUDE: 63S to 63N
             TIME: 15-JUL-2016 00:00 360_DAYS
 Column  1: OHCC_PPS[X=120E:65W] is OHCC_PA2S[L=12]-OHCC_PA2S[L=1]
 Column  2: OHCC_GGS[X=0E:0E(360)] is OHCC_G2S[L=12]-OHCC_G2S[L=1]
           OHCC_PPS  OHCC_GGS
62.5S /   1:  -0.100  -0.087
...

list ohcc_pps/ohcc_ggs

           *** NOTE: Ambiguous coordinates on X axis: OHCC_PPS/OHCC_GGS
             VARIABLE : OHCC_PPS/OHCC_GGS
             SUBSET   : 126 points (LATITUDE)
             LONGITUDE: 120E to 65W
             TIME     : 15-JUL-2016 00:00 360_DAYS
 62.5N / 126:   ....
 61.5N / 125:  1.000
 ...

It might be helpful to specifically give regions in yor definitions that use for the transformations, perhaps something like this, so that the transformations are done over a defined region.

let ohcg_g1s=ohcg1_anm_all[d=1,x=0:360@din,y=63S:63N@iin]/10^20
let ohcg_pa1s=ohcg1_pac[d=3,x=120E:65W@din,y=63S:63N@iin]/10^20

Topics to look at here in the documentation are "Context" and "Transformations", section 3.2.4.

On 12/15/2016 8:13 PM, binny ra wrote:

Hello,

i rectify the error with the help of user guide. i got the required plot but still i am not able to get the normalise plot i.e. quatity1/quantity_global

list ohcc_pps,ohcc_ggs
             LATITUDE: 63S to 63N
             TIME: 15-JUL-2016 00:00 360_DAYS
 Column  1: OHCC_PPS[X=120E:65W] is OHCC_PA2S[L=12]-OHCC_PA2S[L=1]
 Column  2: OHCC_GGS[X=0E:0E(360)] is OHCC_G2S[L=12]-OHCC_G2S[L=1]
           OHCC_PPS  OHCC_GGS
62.5S /   1:  -0.100  -0.087
61.5S /   2:  -0.187  -0.156
60.5S /   3:  -0.249  -0.187
59.5S /   4:  -0.287  -0.174
58.5S /   5:  -0.310  -0.120
57.5S /   6:  -0.330  -0.024
56.5S /   7:  -0.347   0.114
55.5S /   8:  -0.348   0.301
54.5S /   9:  -0.319   0.526
53.5S /  10:  -0.241   0.801
52.5S /  11:  -0.125   1.097
51.5S /  12:   0.009   1.399
50.5S /  13:   0.155   1.703
49.5S /  14:   0.318   2.027
48.5S /  15:   0.494   2.367
47.5S /  16:   0.681   2.722
46.5S /  17:   0.856   3.045
45.5S /  18:   1.015   3.303
44.5S /  19:   1.158   3.513
43.5S /  20:   1.293   3.703
42.5S /  21:   1.433   3.907
41.5S /  22:   1.570   4.128
40.5S /  23:   1.706   4.367
39.5S /  24:   1.838   4.612
38.5S /  25:   1.972   4.852
37.5S /  26:   2.108   5.070
36.5S /  27:   2.250   5.250
35.5S /  28:   2.386   5.374
34.5S /  29:   2.514   5.441
33.5S /  30:   2.613   5.457
32.5S /  31:   2.706   5.446
31.5S /  32:   2.806   5.421
30.5S /  33:   2.908   5.393
29.5S /  34:   2.998   5.364
28.5S /  35:   3.077   5.345
27.5S /  36:   3.150   5.354
26.5S /  37:   3.225   5.405
25.5S /  38:   3.309   5.502
24.5S /  39:   3.408   5.640
23.5S /  40:   3.523   5.806
22.5S /  41:   3.658   5.999
21.5S /  42:   3.809   6.213
20.5S /  43:   3.975   6.441
19.5S /  44:   4.145   6.665
18.5S /  45:   4.314   6.882
17.5S /  46:   4.466   7.077
16.5S /  47:   4.599   7.248
15.5S /  48:   4.693   7.399
14.5S /  49:   4.738   7.512
13.5S /  50:   4.730   7.582
12.5S /  51:   4.673   7.605
11.5S /  52:   4.571   7.597
10.5S /  53:   4.427   7.551
9.5S  /  54:   4.254   7.489
8.5S  /  55:   4.060   7.404
7.5S  /  56:   3.835   7.302
6.5S  /  57:   3.595   7.199
5.5S  /  58:   3.335   7.089
4.5S  /  59:   3.062   6.985
3.5S  /  60:   2.780   6.881
2.5S  /  61:   2.502   6.799
1.5S  /  62:   2.240   6.756
0.5S  /  63:   2.016   6.751
0.5N  /  64:   1.825   6.779
1.5N  /  65:   1.670   6.841
2.5N  /  66:   1.554   6.924
3.5N  /  67:   1.453   6.995
4.5N  /  68:   1.373   7.050
5.5N  /  69:   1.305   7.081
6.5N  /  70:   1.238   7.073
7.5N  /  71:   1.166   7.028
8.5N  /  72:   1.076   6.937
9.5N  /  73:   0.959   6.806
10.5N /  74:   0.828   6.654
11.5N /  75:   0.691   6.490
12.5N /  76:   0.552   6.332
13.5N /  77:   0.434   6.212
14.5N /  78:   0.338   6.132
15.5N /  79:   0.268   6.092
16.5N /  80:   0.228   6.093
17.5N /  81:   0.216   6.084
18.5N /  82:   0.228   6.120
19.5N /  83:   0.255   6.210
20.5N /  84:   0.290   6.348
21.5N /  85:   0.332   6.514
22.5N /  86:   0.388   6.711
23.5N /  87:   0.433   6.902
24.5N /  88:   0.467   7.091
25.5N /  89:   0.491   7.259
26.5N /  90:   0.501   7.412
27.5N /  91:   0.499   7.547
28.5N /  92:   0.495   7.672
29.5N /  93:   0.506   7.799
30.5N /  94:   0.539   7.935
31.5N /  95:   0.614   8.097
32.5N /  96:   0.749   8.303
33.5N /  97:   0.918   8.533
34.5N /  98:   1.129   8.801
35.5N /  99:   1.347   9.076
36.5N / 100:   1.563   9.356
37.5N / 101:   1.732   9.595
38.5N / 102:   1.851   9.775
39.5N / 103:   1.926   9.881
40.5N / 104:   1.985   9.915
41.5N / 105:   2.009   9.861
42.5N / 106:   1.996   9.740
43.5N / 107:   1.967   9.602
44.5N / 108:   1.948   9.459
45.5N / 109:   1.943   9.317
46.5N / 110:   1.949   9.153
47.5N / 111:   1.971   8.971
48.5N / 112:   2.005   8.768
49.5N / 113:   2.050   8.578
50.5N / 114:   2.104   8.413
51.5N / 115:   2.167   8.271
52.5N / 116:   2.237   8.136
53.5N / 117:   2.307   8.001
54.5N / 118:   2.365   7.854
55.5N / 119:   2.410   7.699
56.5N / 120:   2.439   7.537
57.5N / 121:   2.463   7.386
58.5N / 122:   2.480   7.243
59.5N / 123:   2.485   7.106
60.5N / 124:   2.487   6.989
61.5N / 125:   2.488   6.888
62.5N / 126:    ....       6.799

but by use the following commands for this calculation.

cancle data/all

use all_anm.nc
use pac_anm.nc

let ohcg_g1s=ohcg1_anm_all[d=1,x=@din,y=@iin]/10^20
let ohcg_pa1s=ohcg1_pac[d=3,x=@din,y=@iin]/10^20

define axis/edges/t/units=months/t0=15-dec-2004/t=15-jan-2005:15-nov-2016:1/calendar=360_days tmonthly
let ohcc_sog=ohcg_g1s[gt=tmonthly@asn]

define axis/edges/t/units=years/t=15-jan-2005:15-oct-2016:1/calendar=360_days t_yearly
let ohcc_g2s=ohcc_sog[gt=t_yearly@ave]

define axis/edges/t/units=months/t0=15-dec-2004/t=15-jan-2005:15-nov-2016:1/calendar=360_days tmonthly
let ohcc_sop=ohcg_pa1s[gt=tmonthly@asn]

define axis/edges/t/units=years/t=15-jan-2005:15-oct-2016:1/calendar=360_days t_yearly
let ohcc_pa2s=ohcc_sop[gt=t_yearly@ave]

let ohcc_ggs=ohcc_g2s[l=12]-ohcc_g2s[l=1]
let ohcc_pps=ohcc_pa2s[l=12]-ohcc_pa2s[l=1]

list ohcc_pps/ohcc_ggs

           *** NOTE: Ambiguous coordinates on X axis: OHCC_PPS/OHCC_GGS
             VARIABLE : OHCC_PPS/OHCC_GGS
             SUBSET   : 126 points (LATITUDE)
             LONGITUDE: 120E to 65W
             TIME     : 15-JUL-2016 00:00 360_DAYS
 62.5N / 126:   ....
 61.5N / 125:  1.000
 60.5N / 124:  1.000
 59.5N / 123:  1.000
 58.5N / 122:  1.000
 57.5N / 121:  1.000
 56.5N / 120:  1.000
 55.5N / 119:  1.000
 54.5N / 118:  1.000
 53.5N / 117:  1.000
 52.5N / 116:  1.000
 51.5N / 115:  1.000
 50.5N / 114:  1.000
 49.5N / 113:  1.000
 48.5N / 112:  1.000
 47.5N / 111:  1.000
 46.5N / 110:  1.000
 45.5N / 109:  1.000
 44.5N / 108:  1.000
 43.5N / 107:  1.000
 42.5N / 106:  1.000
 41.5N / 105:  1.000
 40.5N / 104:  1.000
 39.5N / 103:  1.000
 38.5N / 102:  1.000
 37.5N / 101:  1.000
 36.5N / 100:  1.000
 35.5N /  99:  1.000
 34.5N /  98:  1.000
 33.5N /  97:  1.000
 32.5N /  96:  1.000
 31.5N /  95:  1.000
 30.5N /  94:  1.000
 29.5N /  93:  1.000
 28.5N /  92:  1.000
 27.5N /  91:  1.000
 26.5N /  90:  1.000
 25.5N /  89:  1.000
 24.5N /  88:  1.000
 23.5N /  87:  1.000
 22.5N /  86:  1.000
 21.5N /  85:  1.000
 20.5N /  84:  1.000
 19.5N /  83:  1.000
 18.5N /  82:  1.000
 17.5N /  81:  1.000
 16.5N /  80:  1.000
 15.5N /  79:  1.000
 14.5N /  78:  1.000
 13.5N /  77:  1.000
 12.5N /  76:  1.000
 11.5N /  75:  1.000
 10.5N /  74:  1.000
 9.5N  /  73:  1.000
 8.5N  /  72:  1.000
 7.5N  /  71:  1.000
 6.5N  /  70:  1.000
 5.5N  /  69:  1.000
 4.5N  /  68:  1.000
 3.5N  /  67:  1.000
 2.5N  /  66:  1.000
 1.5N  /  65:  1.000
 0.5N  /  64:  1.000
 0.5S  /  63:  1.000
 1.5S  /  62:  1.000
 2.5S  /  61:  1.000
 3.5S  /  60:  1.000
 4.5S  /  59:  1.000
 5.5S  /  58:  1.000
 6.5S  /  57:  1.000
 7.5S  /  56:  1.000
 8.5S  /  55:  1.000
 9.5S  /  54:  1.000
 10.5S /  53:  1.000
 11.5S /  52:  1.000
 12.5S /  51:  1.000
 13.5S /  50:  1.000
 14.5S /  49:  1.000
 15.5S /  48:  1.000
 16.5S /  47:  1.000
 17.5S /  46:  1.000
 18.5S /  45:  1.000
 19.5S /  44:  1.000
 20.5S /  43:  1.000
 21.5S /  42:  1.000
 22.5S /  41:  1.000
 23.5S /  40:  1.000
 24.5S /  39:  1.000
 25.5S /  38:  1.000
 26.5S /  37:  1.000
 27.5S /  36:  1.000
 28.5S /  35:  1.000
 29.5S /  34:  1.000
 30.5S /  33:  1.000
 31.5S /  32:  1.000
 32.5S /  31:  1.000
 33.5S /  30:  1.000
 34.5S /  29:  1.000
 35.5S /  28:  1.000
 36.5S /  27:  1.000
 37.5S /  26:  1.000
 38.5S /  25:  1.000
 39.5S /  24:  1.000
 40.5S /  23:  1.000
 41.5S /  22:  1.000
 42.5S /  21:  1.000
 43.5S /  20:  1.000
 44.5S /  19:  1.000
 45.5S /  18:  1.000
 46.5S /  17:  1.000
 47.5S /  16:  1.000
 48.5S /  15:  1.000
 49.5S /  14:  1.000
 50.5S /  13:  1.000
 51.5S /  12:  1.000
 52.5S /  11:  1.000
 53.5S /  10:  1.000
 54.5S /   9:  1.000
 55.5S /   8:  1.000
 56.5S /   7:  1.000
 57.5S /   6:  1.000
 58.5S /   5:  1.000
 59.5S /   4:  1.000
 60.5S /   3:  1.000
 61.5S /   2:  1.000
 62.5S /   1:  1.000

how is this possible ?

i don't understand why all the values becomes 1 at all the latitudes.

i hope i will some help on this issue ?

regards, Binny

On Tue, Dec 6, 2016 at 8:24 AM, Ansley C. Manke <ansley.b.manke@xxxxxxxx> wrote:

Hi,

I don't know what you are intending with the combination of the units of a @DIN definite integral and the @RSUM running sum, but there is a big difference in how those transformations are computed. (See the Information about Transformations: http://ferret.pmel.noaa.gov/Ferret/documentation/users-guide/variables-xpressions/XPRESSIONS#_GeneralInfo). When the grid is in known units on the surface of the earth, the results of the integral are returned in data * square meters.   The running sum is returned as an unweighted sum of the data in each grid cell, so those are just in the units of the heat content variable.  The @DIN, in units*square meter will overwhelm the calculation.

-Ansley

On 12/1/2016 1:15 PM, binny ra wrote:

Dear Ferret Users

I am quite new to ferret and I am performing normalisation of ocean heat content after calculating the running sum and zonal integration.

my script is looking like this

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! anomaly files !!!!!!!!!!!!!!!!!!!!!!!!!!!!

use all_anm.nc      !global (x=0E:0W,y=62.5S:62.5N)
use indi_anm.nc    !indian ocean (20E:120E, 62.5S:30N)

sh da
     currently SET data sets:
    1> ./all_anm.nc
 name     title                                                             I         J         K         L         M         N
  OHCG5_ANM_ALL
          OHCG5-OHCG5_CLI[GT=OHCG5@ASN]    1:360     1:126     ...       1:142     ...       ...
 
    2> ./indi_anm.nc
 name     title                                                            I         J         K         L         M         N
  OHCG5_ANM_IN
          OHCG5-OHCG5_CLI[GT=OHCG5@ASN]    1:100     1:93      ...       1:142     ...       ...

sh gr ohcg5_anm_all[d=1]
    GRID GAN1
 name       axis                       # pts   start                  end                 subset
 LON       LONGITUDE          360mr   0.5E                 0.5W                full
 LAT28_153 LATITUDE           126 r   62.5S                62.5N               full
 normal    Z
 TIME      TIME               142 i   15-JAN-2005 00:00    15-OCT-2016 00:00   full
 normal    E
 normal    F

GRID GFA1
 name       axis                            # pts   start                  end                 subset
 LON21_120 LONGITUDE          100mr   20.5E                119.5E              full
 LAT28_1531_93 LATITUDE        93 r      62.5S                29.5N               full
 normal    Z
 TIME      TIME               142 i   15-JAN-2005 00:00    15-OCT-2016 00:00   full
 normal    E
 normal    F

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! zonal integration and running sum !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

let ohcg_g5s=ohcg5_anm_all[d=1,x=@din,y=@rsum]     ((!! value will come in 10^15 ))
let ohcg_in5s=ohcg5_anm_in[d=2,x=@din,y=@rsum]

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! yearly average !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

define axis/edges/t/units=months/t0=15-dec-2004/t=15-jan-2005:15-nov-2016:1/calendar=360_days tmonthly
let ohcc_gd=ohcg_g5s[gt=tmonthly@asn]

define axis/edges/t/units=years/t=15-jan-2005:15-oct-2016:1/calendar=360_days t_yearly
let ohcc_g5=ohcc_gd[gt=t_yearly@ave]

define axis/edges/t/units=months/t0=15-dec-2004/t=15-jan-2005:15-nov-2016:1/calendar=360_days tmonthly
let ohcc_ind=ohcg_in5s[gt=tmonthly@asn]

define axis/edges/t/units=years/t=15-jan-2005:15-oct-2016:1/calendar=360_days t_yearly
let ohcc_in5=ohcc_ind[gt=t_yearly@ave]

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! difference of two years !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

let ohcc_gg5s=ohcc_g5[l=12]-ohcc_g5[l=1]
let ohcc_ii5s=ohcc_in5[l=12]-ohcc_in5[l=1]

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! normalisation by global value !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

let ohcc_noi=ohcc_ii5s/ohcc_gg5s

list ohcc_noi is showing 1 at every y value

if i try like this way such as
let ohcc_noi=ohcc_ii5s[y=62.5S:30N,x=20E:120E]/ohcc_gg5s[y=62.5S:30N,x=20E:120E]

then also the same thing happens and i got a straight line plot.

this is the list output

list ohcc_noi
29.5N / 93:   ....
 28.5N / 92:   ....
 27.5N / 91:   ....
 26.5N / 90:   ....
 25.5N / 89:   ....
 24.5N / 88:  1.000
 23.5N / 87:  1.000
 22.5N / 86:  1.000
 21.5N / 85:  1.000
 20.5N / 84:  1.000
 19.5N / 83:  1.000
 18.5N / 82:  1.000
 17.5N / 81:  1.000
 16.5N / 80:  1.000
 15.5N / 79:  1.000
 14.5N / 78:  1.000
 13.5N / 77:  1.000
 12.5N / 76:  1.000
 11.5N / 75:  1.000
 10.5N / 74:  1.000
 9.5N  / 73:  1.000
 8.5N  / 72:  1.000
 7.5N  / 71:  1.000
 6.5N  / 70:  1.000
 5.5N  / 69:  1.000
 4.5N  / 68:  1.000
 3.5N  / 67:  1.000
 2.5N  / 66:  1.000
 1.5N  / 65:  1.000
 0.5N  / 64:  1.000
 0.5S  / 63:  1.000
 1.5S  / 62:  1.000
 2.5S  / 61:  1.000
 3.5S  / 60:  1.000
 4.5S  / 59:  1.000
 5.5S  / 58:  1.000
 6.5S  / 57:  1.000
 7.5S  / 56:  1.000
 8.5S  / 55:  1.000
 9.5S  / 54:  1.000
 10.5S / 53:  1.000
 11.5S / 52:  1.000
 12.5S / 51:  1.000
 13.5S / 50:  1.000
 14.5S / 49:  1.000
 15.5S / 48:  1.000
 16.5S / 47:  1.000
 17.5S / 46:  1.000
 18.5S / 45:  1.000
 19.5S / 44:  1.000
 20.5S / 43:  1.000
 21.5S / 42:  1.000
 22.5S / 41:  1.000
 23.5S / 40:  1.000
 24.5S / 39:  1.000
 25.5S / 38:  1.000
 26.5S / 37:  1.000
 27.5S / 36:  1.000
 28.5S / 35:  1.000
 29.5S / 34:  1.000
 30.5S / 33:  1.000
 31.5S / 32:  1.000
 32.5S / 31:  1.000
 33.5S / 30:  1.000
 34.5S / 29:  1.000
 35.5S / 28:  1.000
 36.5S / 27:  1.000
 37.5S / 26:  1.000
 38.5S / 25:  1.000
 39.5S / 24:  1.000
 40.5S / 23:  1.000
 41.5S / 22:  1.000
 42.5S / 21:  1.000
 43.5S / 20:  1.000
 44.5S / 19:  1.000
 45.5S / 18:  1.000
 46.5S / 17:  1.000
 47.5S / 16:  1.000
 48.5S / 15:  1.000
 49.5S / 14:  1.000
 50.5S / 13:  1.000
 51.5S / 12:  1.000
 52.5S / 11:  1.000
 53.5S / 10:  1.000
 54.5S /  9:  1.000
 55.5S /  8:  1.000
 56.5S /  7:  1.000
 57.5S /  6:  1.000
 58.5S /  5:  1.000
 59.5S /  4:  1.000
 60.5S /  3:  1.000
 61.5S /  2:  1.000
 62.5S /  1:  1.000

kindly help me out i tried in every way but not getting any success. i hope ferreters are having any clue to this problem

regards, Binny