1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
|
#!/usr/bin/env python
import cmor
import numpy
def main():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action=cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id='ukmo',
model_id='HadCM3',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0,
contact='brian clough')
table = 'CMIP5_6hrPlev'
cmor.load_table(table)
axes = [{'table_entry': 'time1',
'units': 'hours since 2000-01-01 00:00:00',
},
{'table_entry': 'plev3',
'units': 'Pa',
'coord_vals': [100000., 92500., 85000., 70000., 60000., 50000., 40000., 30000., 25000., 20000., 15000., 10000., 7000., 5000., 3000., 2000., 1000.]},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
print('doing:', axis)
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, value in (('ta', 'K', 274), ('ua', 'm s-1', 10)):
values = numpy.array([value, ] *
len(axes[1]['coord_vals']), numpy.float32)
varid = cmor.variable(var,
units,
axis_ids,
history='variable history',
missing_value=-99
)
cmor.write(varid, values, time_vals=[0], time_bnds=[[0, 6]])
cmor.close()
if __name__ == '__main__':
main()
|
