I've been trying to run WPS on ERA5 data. I have followed a guide from http://valcap74.blogspot.is/2017/10/how ... a5-on.html on how to use ERA5 data. Everything goes smooth until I try to calculate the ecmwf coefficients. This is the output I'm getting:
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Coefficients for each level: 137
0 0.000000 0.0000000000
1 2.000365 0.0000000000
2 3.102241 0.0000000000
3 4.666084 0.0000000000
4 6.827977 0.0000000000
5 9.746966 0.0000000000
6 13.605424 0.0000000000
7 18.608931 0.0000000000
8 24.985718 0.0000000000
9 32.985710 0.0000000000
10 42.879242 0.0000000000
11 54.955463 0.0000000000
12 69.520576 0.0000000000
13 86.895882 0.0000000000
14 107.415741 0.0000000000
15 131.425507 0.0000000000
16 159.279404 0.0000000000
17 191.338562 0.0000000000
18 227.968948 0.0000000000
19 269.539581 0.0000000000
20 316.420746 0.0000000000
21 368.982361 0.0000000000
22 427.592499 0.0000000000
23 492.616028 0.0000000000
24 564.413452 0.0000000000
25 643.339905 0.0000000000
26 729.744141 0.0000000000
27 823.967834 0.0000000000
28 926.344910 0.0000000000
29 1037.201172 0.0000000000
30 1156.853638 0.0000000000
31 1285.610352 0.0000000000
32 1423.770142 0.0000000000
33 1571.622925 0.0000000000
34 1729.448975 0.0000000000
35 1897.519287 0.0000000000
36 2076.095947 0.0000000000
37 2265.431641 0.0000000000
38 2465.770508 0.0000000000
39 2677.348145 0.0000000000
40 2900.391357 0.0000000000
41 3135.119385 0.0000000000
42 3381.743652 0.0000000000
43 3640.468262 0.0000000000
44 3911.490479 0.0000000000
45 4194.930664 0.0000000000
46 4490.817383 0.0000000000
47 4799.149414 0.0000000000
48 5119.895020 0.0000000000
49 5452.990723 0.0000000000
50 5798.344727 0.0000000000
51 6156.074219 0.0000000000
52 6526.946777 0.0000000000
53 6911.870605 0.0000000000
54 7311.869141 0.0000000000
55 7727.412109 0.0000070000
56 8159.354004 0.0000240000
57 8608.525391 0.0000590000
58 9076.400391 0.0001120000
59 9562.682617 0.0001990000
60 10065.978516 0.0003400000
61 10584.631836 0.0005620000
62 11116.662109 0.0008900000
63 11660.067383 0.0013530001
64 12211.547852 0.0019920000
65 12766.873047 0.0028570001
66 13324.668945 0.0039710002
67 13881.331055 0.0053780000
68 14432.139648 0.0071330001
69 14975.615234 0.0092610000
70 15508.256836 0.0118060000
71 16026.115234 0.0148160001
72 16527.322266 0.0183179993
73 17008.789062 0.0223549996
74 17467.613281 0.0269639995
75 17901.621094 0.0321759991
76 18308.433594 0.0380260013
77 18685.718750 0.0445480011
78 19031.289062 0.0517730005
79 19343.511719 0.0597280003
80 19620.042969 0.0684479997
81 19859.390625 0.0779580027
82 20059.931641 0.0882859975
83 20219.664062 0.0994620025
84 20337.863281 0.1115050018
85 20412.308594 0.1244480014
86 20442.078125 0.1383129954
87 20425.718750 0.1531250030
88 20361.816406 0.1689099967
89 20249.511719 0.1856890023
90 20087.085938 0.2034910023
91 19874.025391 0.2223329991
92 19608.572266 0.2422440052
93 19290.226562 0.2632420063
94 18917.460938 0.2853539884
95 18489.707031 0.3085980117
96 18006.925781 0.3329389989
97 17471.839844 0.3582539856
98 16888.687500 0.3843629956
99 16262.046875 0.4111250043
100 15596.695312 0.4383910000
101 14898.453125 0.4660030007
102 14173.324219 0.4938000143
103 13427.769531 0.5216190219
104 12668.257812 0.5493010283
105 11901.339844 0.5766919851
106 11133.304688 0.6036480069
107 10370.175781 0.6300359964
108 9617.515625 0.6557360291
109 8880.453125 0.6806430221
110 8163.375000 0.7046689987
111 7470.343750 0.7277389765
112 6804.421875 0.7497969866
113 6168.531250 0.7707980275
114 5564.382812 0.7907170057
115 4993.796875 0.8095359802
116 4457.375000 0.8272560239
117 3955.960938 0.8438810110
118 3489.234375 0.8594319820
119 3057.265625 0.8739290237
120 2659.140625 0.8874080181
121 2294.242188 0.8999000192
122 1961.500000 0.9114480019
123 1659.476562 0.9220960140
124 1387.546875 0.9318810105
125 1143.250000 0.9408599734
126 926.507812 0.9490640163
127 734.992188 0.9565500021
128 568.062500 0.9633520246
129 424.414062 0.9695129991
130 302.476562 0.9750779867
131 202.484375 0.9800720215
132 122.101562 0.9845420122
133 62.781250 0.9884999990
134 22.835938 0.9919840097
135 3.757813 0.9950029850
136 0.000000 0.9976300001
137 0.000000 1.0000000000
Reading from FILE at time 2016-03-20_00
Found SOILHGT field in FILE:2016-03-20_00
Found LOGSFP field in FILE:2016-03-20_00
Reading from FILE at time 2016-03-20_01
Found SOILHGT field in FILE:2016-03-20_01
Found LOGSFP field in FILE:2016-03-20_01
calc_ecmwf_p.exe: malloc.c:2868: mremap_chunk: Assertion `((size + offset) & (GLRO (dl_pagesize) - 1)) == 0' failed.
Program received signal SIGABRT: Process abort signal.
Backtrace for this error:
#0 0x7F6900A1FE08
#1 0x7F6900A1EF90
#2 0x7F69003664AF
#3 0x7F6900366428
#4 0x7F6900368029
#5 0x7F69003AE2E7
#6 0x7F69003AE5A2
#7 0x7F69003B576B
#8 0x4051FD in MAIN__ at calc_ecmwf_p.f90:?
Aborted (core dumped)
I've tried running it on multiple datasets, but it always failes at some point giving the same error. I've googled around a bit but havenðt found anyone with the same issue. This error in mremap_chunk seems to be rather common in other programs, but my very little fortran knowledge was not good enough to fin what causes the error. Does anyone have any idea what I am doing wrong, or could this be a bug?
I am using hourly ERA5 data and this is my input.wps:
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&share
wrf_core = 'ARW',
max_dom = 1,
start_date = '2016-03-20_00:00:00',
end_date = '2016-03-20_23:00:00',
interval_seconds = 3600,
io_form_geogrid = 2,
debug_level = 100,
/
&geogrid
parent_id = 1,
parent_grid_ratio = 1,
i_parent_start = 1,
j_parent_start = 1,
e_we = 50,
e_sn = 50,
geog_data_res = '5m',
dx = 9000,
dy = 9000,
map_proj = 'polar',
ref_lat = 64.936,
ref_lon = -18.772,
truelat1 = 64.936,
truelat2 = 90,
stand_lon = -18.772,
geog_data_path = '/geog',
opt_geogrid_tbl_path = '/ERA5/20.mars'
/
&ungrib
out_format = 'WPS',
prefix = 'FILE',
/
&metgrid
fg_name = 'FILE',
io_form_metgrid = 2,
/
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The scripts I use to download the data are the following:
server.retrieve({
# Specify the ERA-Interim data archive. Don't change.
"class": "ea",
"dataset": "era5",
"expver": "1",
"stream": "oper",
# pressure levels (levtype:pl), all available levels (levelist)
"levtype": "sfc",
# forecast (type:fc), from both daily forecast runs (time) with all available forecast steps (step, in hours)
"type": "an",
"time" : "00:00:00/01:00:00/02:00:00/03:00:00/04:00:00/05:00:00/06:00:00/07:00:00/08:00:00/09:00:00/10:00:00/11:00:00/12:00:00/13:00:00/14:00:00/15:00:00/16:00:00/17:00:00/18:00:00/19:00:00/20:00:00/21:00:00/22:00:00/23:00:00" ,
"step": "0",
# all available parameters, for codes see http://apps.ecmwf.int/codes/grib/param-db
#"param": "134.128/139.128/141.128/151.128/165.128/166.128/167.128/168.128/170.128/183.128/235.128/236.128/31.128/33.128/34.128/39.128/40.128/41.128/42.128",
"param": "msl/skt/2t/10u/10v/2d/z/lsm/sst/ci/sd/stl1/stl2/stl3/stl4/swvl1/swvl2/swvl3/swvl4",
# two days worth of data
#"date": "2016-03-14/to/2016-03-15",
"date": "2016-03-20",
# in 0.75 degrees lat/lon
"grid": "0.125/0.125",
# optionally restrict area to Europe (in N/W/S/E).
"area": "75/-35/50/10",
# Optionally get output in NetCDF format. However, this does not work with the above request due to overlapping timestamps.
# "format" : "netcdf",
# set an output file name
"target": "20.3.2016-sfc.grib",
})
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server.retrieve({
# Specify the ERA-Interim data archive. Don't change.
"class": "ea",
"dataset": "era5",
"expver": "1",
"stream": "oper",
# pressure levels (levtype:pl), all available levels (levelist)
"levtype": "ml",
#"levelist": "1/to/137",
"levelist": "1/to/137",
# forecast (type:fc), from both daily forecast runs (time) with all available forecast steps (step, in hours)
"type": "an",
"time" : "00:00:00/01:00:00/02:00:00/03:00:00/04:00:00/05:00:00/06:00:00/07:00:00/08:00:00/09:00:00/10:00:00/11:00:00/12:00:00/13:00:00/14:00:00/15:00:00/16:00:00/17:00:00/18:00:00/19:00:00/20:00:00/21:00:00/22:00:00/23:00:00" ,
"step": "0",
# all available parameters, for codes see http://apps.ecmwf.int/codes/grib/param-db
"param": "129/130/131/132/133/138/152/155/157",
# two days worth of data
"date": "2016-03-20",
# in 0.75 degrees lat/lon
"grid": "0.125/0.125",
# optionally restrict area to Europe (in N/W/S/E).
"area": "75/-35/50/00",
# Optionally get output in NetCDF format. However, this does not work with the above request due to overlapping timestamps.
# "format" : "netcdf",
# set an output file name
"target": "20.3.2016-ml.grib",
