[gradsusr] Problem with GrADS in reading ECMWF synoptic monthly means data
Mubashar Dogar
mubashardogar at gmail.com
Sun Sep 18 23:44:39 EDT 2011
Dear Jennifer,
*Here is the output of ncdump -c as requested. I am also giving the output
of wgrib -h for the grib format of the same data at the end:*
ncdump -c ei_mnth_fc_sfc_1.5x1.5_19890101_19891201.nc
netcdf ei_mnth_fc_sfc_1.5x1.5_19890101_19891201 {
dimensions:
longitude = 240 ;
latitude = 121 ;
time = UNLIMITED ; // (96 currently)
variables:
float longitude(longitude) ;
longitude:units = "degrees_east" ;
longitude:long_name = "longitude" ;
float latitude(latitude) ;
latitude:units = "degrees_north" ;
latitude:long_name = "latitude" ;
int time(time) ;
time:units = "hours since 1900-01-01 00:00:0.0" ;
time:long_name = "time" ;
short tp(time, latitude, longitude) ;
tp:scale_factor = 4.25320233951185e-07 ;
tp:add_offset = 0.0139356174654106 ;
tp:_FillValue = -32767s ;
tp:missing_value = -32767s ;
tp:units = "m" ;
tp:long_name = "Total precipitation" ;
// global attributes:
:Conventions = "CF-1.0" ;
:history = "2011-09-18 14:19:37 GMT by mars2netcdf-0.92" ;
data:
longitude = 0, 1.5, 3, 4.5, 6, 7.5, 9, 10.5, 12, 13.5, 15, 16.5, 18, 19.5,
21, 22.5, 24, 25.5, 27, 28.5, 30, 31.5, 33, 34.5, 36, 37.5, 39, 40.5,
42,
43.5, 45, 46.5, 48, 49.5, 51, 52.5, 54, 55.5, 57, 58.5, 60, 61.5, 63,
64.5, 66, 67.5, 69, 70.5, 72, 73.5, 75, 76.5, 78, 79.5, 81, 82.5, 84,
85.5, 87, 88.5, 90, 91.5, 93, 94.5, 96, 97.5, 99, 100.5, 102, 103.5,
105,
106.5, 108, 109.5, 111, 112.5, 114, 115.5, 117, 118.5, 120, 121.5, 123,
124.5, 126, 127.5, 129, 130.5, 132, 133.5, 135, 136.5, 138, 139.5, 141,
142.5, 144, 145.5, 147, 148.5, 150, 151.5, 153, 154.5, 156, 157.5, 159,
160.5, 162, 163.5, 165, 166.5, 168, 169.5, 171, 172.5, 174, 175.5, 177,
178.5, 180, 181.5, 183, 184.5, 186, 187.5, 189, 190.5, 192, 193.5, 195,
196.5, 198, 199.5, 201, 202.5, 204, 205.5, 207, 208.5, 210, 211.5, 213,
214.5, 216, 217.5, 219, 220.5, 222, 223.5, 225, 226.5, 228, 229.5, 231,
232.5, 234, 235.5, 237, 238.5, 240, 241.5, 243, 244.5, 246, 247.5, 249,
250.5, 252, 253.5, 255, 256.5, 258, 259.5, 261, 262.5, 264, 265.5, 267,
268.5, 270, 271.5, 273, 274.5, 276, 277.5, 279, 280.5, 282, 283.5, 285,
286.5, 288, 289.5, 291, 292.5, 294, 295.5, 297, 298.5, 300, 301.5, 303,
304.5, 306, 307.5, 309, 310.5, 312, 313.5, 315, 316.5, 318, 319.5, 321,
322.5, 324, 325.5, 327, 328.5, 330, 331.5, 333, 334.5, 336, 337.5, 339,
340.5, 342, 343.5, 345, 346.5, 348, 349.5, 351, 352.5, 354, 355.5, 357,
358.5 ;
latitude = 90, 88.5, 87, 85.5, 84, 82.5, 81, 79.5, 78, 76.5, 75, 73.5, 72,
70.5, 69, 67.5, 66, 64.5, 63, 61.5, 60, 58.5, 57, 55.5, 54, 52.5, 51,
49.5, 48, 46.5, 45, 43.5, 42, 40.5, 39, 37.5, 36, 34.5, 33, 31.5, 30,
28.5, 27, 25.5, 24, 22.5, 21, 19.5, 18, 16.5, 15, 13.5, 12, 10.5, 9,
7.5,
6, 4.5, 3, 1.5, 0, -1.5, -3, -4.5, -6, -7.5, -9, -10.5, -12, -13.5, -15,
-16.5, -18, -19.5, -21, -22.5, -24, -25.5, -27, -28.5, -30, -31.5, -33,
-34.5, -36, -37.5, -39, -40.5, -42, -43.5, -45, -46.5, -48, -49.5, -51,
-52.5, -54, -55.5, -57, -58.5, -60, -61.5, -63, -64.5, -66, -67.5, -69,
-70.5, -72, -73.5, -75, -76.5, -78, -79.5, -81, -82.5, -84, -85.5, -87,
-88.5, -90 ;
time = 780171, 780174, 780177, 780180, 780183, 780186, 780189, 780192,
780915, 780918, 780921, 780924, 780927, 780930, 780933, 780936, 781587,
781590, 781593, 781596, 781599, 781602, 781605, 781608, 782331, 782334,
782337, 782340, 782343, 782346, 782349, 782352, 783051, 783054, 783057,
783060, 783063, 783066, 783069, 783072, 783795, 783798, 783801, 783804,
783807, 783810, 783813, 783816, 784515, 784518, 784521, 784524, 784527,
784530, 784533, 784536, 785259, 785262, 785265, 785268, 785271, 785274,
785277, 785280, 786003, 786006, 786009, 786012, 786015, 786018, 786021,
786024, 786723, 786726, 786729, 786732, 786735, 786738, 786741, 786744,
787467, 787470, 787473, 787476, 787479, 787482, 787485, 787488, 788187,
788190, 788193, 788196, 788199, 788202, 788205, 788208 ;
}*
Here is the output from wgrib for the same data but downloaded in grib
format:*
wgrib -h ei_mnth_fc_sfc_1.5x1.5_19890101_19891201.grib
1:0:d=89010100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
2:58188:d=89010100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
3:116376:d=89010100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
4:174564:d=89010100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
5:232752:d=89010112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
6:290940:d=89010112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
7:349128:d=89010112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
8:407316:d=89010112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
9:465504:d=89020100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=28
10:523692:d=89020100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=28
11:581880:d=89020100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=28
12:640068:d=89020100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=28
13:698256:d=89020112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=28
14:756444:d=89020112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=28
15:814632:d=89020112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=28
16:872820:d=89020112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=28
17:931008:d=89030100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
18:989196:d=89030100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
19:1047384:d=89030100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
20:1105572:d=89030100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
21:1163760:d=89030112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
22:1221948:d=89030112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
23:1280136:d=89030112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
24:1338324:d=89030112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
25:1396512:d=89040100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=30
26:1454700:d=89040100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=30
27:1512888:d=89040100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=30
28:1571076:d=89040100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=30
29:1629264:d=89040112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=30
30:1687452:d=89040112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=30
31:1745640:d=89040112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=30
32:1803828:d=89040112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=30
33:1862016:d=89050100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
34:1920204:d=89050100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
35:1978392:d=89050100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
36:2036580:d=89050100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
37:2094768:d=89050112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
38:2152956:d=89050112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
39:2211144:d=89050112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
40:2269332:d=89050112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
41:2327520:d=89060100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=30
42:2385708:d=89060100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=30
43:2443896:d=89060100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=30
44:2502084:d=89060100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=30
45:2560272:d=89060112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=30
46:2618460:d=89060112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=30
47:2676648:d=89060112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=30
48:2734836:d=89060112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=30
49:2793024:d=89070100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
50:2851212:d=89070100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
51:2909400:d=89070100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
52:2967588:d=89070100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
53:3025776:d=89070112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
54:3083964:d=89070112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
55:3142152:d=89070112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
56:3200340:d=89070112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
57:3258528:d=89080100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
58:3316716:d=89080100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
59:3374904:d=89080100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
60:3433092:d=89080100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
61:3491280:d=89080112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
62:3549468:d=89080112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
63:3607656:d=89080112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
64:3665844:d=89080112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
65:3724032:d=89090100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=30
66:3782220:d=89090100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=30
67:3840408:d=89090100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=30
68:3898596:d=89090100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=30
69:3956784:d=89090112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=30
70:4014972:d=89090112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=30
71:4073160:d=89090112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=30
72:4131348:d=89090112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=30
73:4189536:d=89100100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
74:4247724:d=89100100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
75:4305912:d=89100100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
76:4364100:d=89100100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
77:4422288:d=89100112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
78:4480476:d=89100112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
79:4538664:d=89100112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
80:4596852:d=89100112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
81:4655040:d=89110100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=30
82:4713228:d=89110100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=30
83:4771416:d=89110100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=30
84:4829604:d=89110100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=30
85:4887792:d=89110112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=30
86:4945980:d=89110112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=30
87:5004168:d=89110112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=30
88:5062356:d=89110112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=30
89:5120544:d=89120100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
90:5178732:d=89120100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
91:5236920:d=89120100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
92:5295108:d=89120100:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
93:5353296:d=89120112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=3:P2=24:TimeU=1:sfc:3hr
fcst:ave at 24hr:mon mean:NAve=31
94:5411484:d=89120112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=6:P2=24:TimeU=1:sfc:6hr
fcst:ave at 24hr:mon mean:NAve=31
95:5469672:d=89120112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=9:P2=24:TimeU=1:sfc:9hr
fcst:ave at 24hr:mon mean:NAve=31
96:5527860:d=89120112:TP:kpds5=228:kpds6=1:kpds7=0:TR=113:P1=12:P2=24:TimeU=1:sfc:12hr
fcst:ave at 24hr:mon mean:NAve=31
> Today's Topics:
>
> 1. Re: Box Plot in GrADS? (Jayakrishnan PR)
> 2. Re: Convert monthly to yearly accumulated rainfall
> (Rafanoharana Serge Claudio)
> 3. Invitation to connect on LinkedIn (Rajeevan K via LinkedIn)
> 4. Re: lats4d and re (Arlindo da Silva)
> 5. Re: Moisture flux convergence/divergence (Arlindo da Silva)
> 6. Problem with GrADS in reading ECMWF synoptic monthly means
> data (Mubashar Dogar)
> 7. Re: Problem with GrADS in reading ECMWF synoptic monthly
> means data (Jennifer Adams)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sat, 17 Sep 2011 10:24:57 +0530
> From: Jayakrishnan PR <prjayakrishnan at gmail.com>
> Subject: Re: [gradsusr] Box Plot in GrADS?
> To: GrADS Users Forum <gradsusr at gradsusr.org>
> Message-ID:
> <CA+P5ZEE1-peEObQ1nMB_c1qFa_PNXNOJZ6mq03Eqi=DiJzbB6A at mail.gmail.com
> >
> Content-Type: text/plain; charset="iso-8859-1"
>
> Dear Matei,
> I am wondering why you are sticking to Grads itself. Grads is
> a software designed to plot griided data and analysis of that data. it is
> not suitable for plotting these kind of graphs. You can choose softwares
> such as NCL or origin for plotting these kind of graphs. No need for
> sticking into Grads.
> >
> >
> >
>
>
> --
> Sincerely
> ***********************************************
> Jayakrishnan.P.R
> CSIR-Senior Research Fellow
> Department of Atmospheric Sciences
> Cochin University of Science and Technology (CUSAT), Cochin-682 016
> Kerala, India.
> Mob: 09895417565
>
> ***********************************************
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>
> ------------------------------
>
> Message: 2
> Date: Sat, 17 Sep 2011 15:11:20 +0700
> From: Rafanoharana Serge Claudio <rafanoharana at gmail.com>
> Subject: Re: [gradsusr] Convert monthly to yearly accumulated rainfall
> To: GrADS Users Forum <gradsusr at gradsusr.org>
> Message-ID:
> <CAPFxStgNLcjM=4girADmnhMXVH+S-bo6=hzzRQxHJrrN6-+CTw at mail.gmail.com
> >
> Content-Type: text/plain; charset="iso-8859-1"
>
> Dear Chris,
>
> I do not know if one can do it directly while having the 50 time steps but
> what I can say is that you can process for every year (then you'll have 50
> outputs), then assign time for every year, then merge using cdo all 50
> years
> into one single file.
>
> Hope this can help,
>
> Serge
>
> On Sat, Sep 17, 2011 at 3:34 AM, Alauda arvensis <a.arvensis at gmail.com
> >wrote:
>
> > Dear GrADS users,
> >
> > My data consists of 50 years of monthly rainfall. I want to convert this
> > data into yearly accumulated rainfall for every year. So I am looking for
> > something like:
> >
> > 'pyearly = sum(pmonthly, t=1, t=12)' ... but I need it for every year, so
> > that in the end I have 50 time steps.
> >
> > Any hints welcome! Thanks!
> >
> > Kind regards,
> > Chris
> >
> > PS: I already tried "mon2yr.gs" from Bin Guan's page, but something does
> > not appear to work.
> >
> > _______________________________________________
> > gradsusr mailing list
> > gradsusr at gradsusr.org
> > http://gradsusr.org/mailman/listinfo/gradsusr
> >
> >
>
>
> --
> Serge
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> ------------------------------
>
> Message: 3
> Date: Sat, 17 Sep 2011 12:23:40 +0000 (UTC)
> From: Rajeevan K via LinkedIn <member at linkedin.com>
> Subject: [gradsusr] Invitation to connect on LinkedIn
> To: Ning Cao <gradsusr at gradsusr.org>
> Message-ID:
> <786703422.8558443.1316262220088.JavaMail.app at ela4-app0131.prod>
> Content-Type: text/plain; charset="utf-8"
>
> LinkedIn
> ------------
>
>
>
>
> Rajeevan K requested to add you as a connection on LinkedIn:
>
> ------------------------------------------
>
> Ning,
>
> I'd like to add you to my professional network on LinkedIn.
>
> - Rajeevan
>
> Accept invitation from Rajeevan K
>
> http://www.linkedin.com/e/ofpc7q-gsokjh2t-51/X_QvJ7UefcfFkLAYwdQqLHU00gfkGZ-5LN/blk/I161349014_13/1BpC5vrmRLoRZcjkkZt5YCpnlOt3RApnhMpmdzgmhxrSNBszYPclYQcj0Vd3cNdz59bT1imBhDqDB3bP8Sd3sRdPoQczgLrCBxbOYWrSlI/EML_comm_afe/?hs=false&tok=3cpy5iTqgDLAU1
>
> View invitation from Rajeevan K
>
> http://www.linkedin.com/e/ofpc7q-gsokjh2t-51/X_QvJ7UefcfFkLAYwdQqLHU00gfkGZ-5LN/blk/I161349014_13/3cNnPgNc3AQcP4SckALqnpPbOYWrSlI/svi/?hs=false&tok=27OH6j0pIDLAU1
>
>
> --
> (c) 2011, LinkedIn Corporation
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> ------------------------------
>
> Message: 4
> Date: Sat, 17 Sep 2011 09:54:51 -0400
> From: Arlindo da Silva <dasilva at alum.mit.edu>
> Subject: Re: [gradsusr] lats4d and re
> To: GrADS Users Forum <gradsusr at gradsusr.org>
> Message-ID:
> <CALz7xZfF+=6FEJbFc_zi1t4WAPHUXwRe0RUYwVPc=qPiVnbuUw at mail.gmail.com
> >
> Content-Type: text/plain; charset="iso-8859-1"
>
> On Fri, Sep 16, 2011 at 5:20 PM, Coly SAR <colysar at gmail.com> wrote:
>
> > I have a 3D nc file with 6 variables and I want to regrid it to 0.5?
> using
> > lats4d.
> > I issued this command below but the file created remains the same as
> infile
> > and no regrid done.
> >
> >
> >
> > >lats4d -i runet.nc -o test_05 -lon -38.5 29 -lat -10.5 25 -func
> re(@,0.5)
> >
> > I am using opengrad v 2.9 and need any suggestion on how to do this
> regrid.
> >
> >
> Type "lats4d -h" and read the section on regridding. Unless you use one of
> the predefined resolutions you will need to create (or point to one)
> dimension environment file (option -de).
>
> Arlindo
>
>
>
> --
> Arlindo da Silva
> dasilva at alum.mit.edu
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> ------------------------------
>
> Message: 5
> Date: Sat, 17 Sep 2011 10:12:57 -0400
> From: Arlindo da Silva <dasilva at alum.mit.edu>
> Subject: Re: [gradsusr] Moisture flux convergence/divergence
> To: GrADS Users Forum <gradsusr at gradsusr.org>
> Message-ID:
> <CALz7xZf5MaHEvP1bX1Z93ysYNg5xVCGOvBdBaM5aHTkEs6+HSw at mail.gmail.com
> >
> Content-Type: text/plain; charset="iso-8859-1"
>
> 2011/9/16 Hyacinth Nnamchi <hyacinth.1 at hotmail.com>
>
> > Jeff,
> >
> > I seems my question wasn't well framed, and so you dealt with the typo. I
> > have attached two Figs showing what the calculations below will give and
> > what exactly I'll like to do.
> >
> >
> >From the attached plot it appears that you want to plot the divergent
> component of the mass flux, as given by the Helmholtz decomposition:
>
> http://en.wikipedia.org/wiki/Helmholtz_decomposition
>
> The first step is to compute the velocity potential
>
> ga-> chi = fish_chi(zon,mer)
>
> (As Roger mentions, make sure to average in the vertical first if this is
> what you want.) Next, the divergent component of the mass flux is related
> to
> the gradient of chi; see this for more information:
>
> Calculating the Divergent
> Wind<
> http://opengrads.org/doc/udxt/fish/fish.html#calculating_the_divergent_wind
> >
>
> Notice that you will need an opengrads build in order to use the fish
> extension; more info here:
>
>
> http://opengrads.org/wiki/index.php?title=Installing_the_OpenGrADS_Bundle
>
> Good luck,
>
> Arlindo
>
>
>
>
>
>
> > Thanks,
> >
> > Hyacinth
> >
> >
> > > Date: Thu, 15 Sep 2011 17:34:50 -0500>
> > From: Jeffrey Duda <jdduda at iastate.edu>>
> > Subject: Re: [gradsusr] Moisture flux convergence/divergence
> > > To: GrADS Users Forum <gradsusr at gradsusr.org>
> > > Message-ID:
> > > <CAP9LQ-VNkxcu-+ey_QkZU7f4MHf+VwJDvav=Dci3ns+x+pjG8Q at mail.gmail.com>
> > > Content-Type: text/plain; charset="iso-8859-1"
> >
> > >
> > > Set the graphics output to vector ('set gxout vector'), then 'd
> zon;mer'
> > > (note the semicolon instead of a comma).
> > >
> > > Jeff Duda
> > >
> > > 2011/9/15 Hyacinth Nnamchi <hyacinth.1 at hotmail.com>
> > >
> > > > Hello,
> > > >
> > > > This is not directly about GrADS but since most of address similar!
> > > > problems, I guess someone on this forum will be able to answer my
> > question.
> > > >
> > > > I understand that to calculate moisture transport, given zonal,
> > meridional
> > > > winds and specific humidity, can simply do:
> > > >
> > > > 'define zon=uwnd.1*shum.3'
> > > > 'define mer=vwnd.2*shum.3'
> > > > 'd zon,mer'
> > > >
> > > > But, I want to plot vectors indicating field of net moisture flux
> (all
> > arrows converging/diverging) instead of just transport.
> > > >
> > > > Thanks for any ideas.
> > > >
> > > > Hyacinth
> > > >
> > > >
> > > > __
> >
> > _______________________________________________
> > gradsusr mailing list
> > gradsusr at gradsusr.org
> > http://gradsusr.org/mailman/listinfo/gradsusr
> >
> >
>
>
> --
> Arlindo da Silva
> dasilva at alum.mit.edu
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> ------------------------------
>
> Message: 6
> Date: Sun, 18 Sep 2011 21:39:04 +0300
> From: Mubashar Dogar <mubashardogar at gmail.com>
> Subject: [gradsusr] Problem with GrADS in reading ECMWF synoptic
> monthly means data
> To: gradsusr at gradsusr.org
> Message-ID:
> <CAHBht237iOnGUtkYuZL6+rXEtm-KSgsti2W1anm6-BY7SkAU2Q at mail.gmail.com
> >
> Content-Type: text/plain; charset="iso-8859-1"
>
> Dear GrADS users,
>
> I am facing a problem with time steps of a netcdf file downloaded for
> synoptic monthly means of ECMWF ERA-INTERIM forecast product for the year
> 1989 (downloaded for surface total precipitation for all time steps
> available from: http://data-portal.ecmwf.int/data/d/interim_mnth/). This
> file is basically synoptic monthly means generated by long term average of
> corresponding 3 hour in all the days of a month, giving 8 time steps in a
> month. So instead of reading 96 values that represents to 12 months (8
> values in each months) GrADS read all these values by considering 8 time
> steps in a day instead in a month. I mean GrADS reads these hours in a
> daily
> format instead of monthly. Does GrADS not deal with synoptic monthly means?
> I have grib file as well for the same data, what should be time increment
> in
> a ctl file to open the same grib file?
>
>
> Mubashar Dogar
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> ------------------------------
>
> Message: 7
> Date: Sun, 18 Sep 2011 15:47:24 -0400
> From: Jennifer Adams <jma at cola.iges.org>
> Subject: Re: [gradsusr] Problem with GrADS in reading ECMWF synoptic
> monthly means data
> To: GrADS Users Forum <gradsusr at gradsusr.org>
> Message-ID: <93628EC9-0E8F-4EE1-9D80-0147B93D7F6A at cola.iges.org>
> Content-Type: text/plain; charset="us-ascii"
>
> Please send the output from ncdump -c on your netcdf file. --Jennifer
>
> On Sep 18, 2011, at 2:39 PM, Mubashar Dogar wrote:
>
> >
> > Dear GrADS users,
> >
> > I am facing a problem with time steps of a netcdf file downloaded
> > for synoptic monthly means of ECMWF ERA-INTERIM forecast product for
> > the year 1989 (downloaded for surface total precipitation for all
> > time steps available from:
> http://data-portal.ecmwf.int/data/d/interim_mnth/)
> > . This file is basically synoptic monthly means generated by long
> > term average of corresponding 3 hour in all the days of a month,
> > giving 8 time steps in a month. So instead of reading 96 values that
> > represents to 12 months (8 values in each months) GrADS read all
> > these values by considering 8 time steps in a day instead in a
> > month. I mean GrADS reads these hours in a daily format instead of
> > monthly. Does GrADS not deal with synoptic monthly means? I have
> > grib file as well for the same data, what should be time increment
> > in a ctl file to open the same grib file?
> >
> >
> > Mubashar Dogar
> >
> >
> > _______________________________________________
> > gradsusr mailing list
> > gradsusr at gradsusr.org
> > http://gradsusr.org/mailman/listinfo/gradsusr
>
> --
> Jennifer M. Adams
> IGES/COLA
> 4041 Powder Mill Road, Suite 302
> Calverton, MD 20705
> jma at cola.iges.org
>
>
>
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>
>
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