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
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
|
import cmor
import numpy
error_flag = cmor.setup(inpath='Test', netcdf_file_action=cmor.CMOR_REPLACE)
error_flag = cmor.dataset_json("Test/CMOR_input_example.json")
# creates 1 degree grid
nlat = 180
nlon = 360
alats = numpy.arange(180) - 89.5
bnds_lat = numpy.arange(181) - 90
alons = numpy.arange(360) + .5
bnds_lon = numpy.arange(361)
cmor.load_table("Tables/CMIP6_Amon.json")
ilat = cmor.axis(
table_entry='latitude',
units='degrees_north',
length=nlat,
coord_vals=alats,
cell_bounds=bnds_lat)
ilon = cmor.axis(
table_entry='longitude',
length=nlon,
units='degrees_east',
coord_vals=alons,
cell_bounds=bnds_lon)
lev = 5
ntimes = 12
plevs = (numpy.arange(lev) + 1) * 1.E4
itim = cmor.axis(
table_entry='time',
units='months since 2030-1-1',
length=ntimes,
interval='1 month')
zlevs = numpy.array((0.1, 0.3, 0.55, 0.7, 0.9))
zlev_bnds = numpy.array((0., .2, .42, .62, .8, 1.))
table_entry = 'hybrid_height'
if table_entry == 'hybrid_height':
ilev = cmor.axis(
table_entry='hybrid_height',
# table_entry='standard_sigma',
# table_entry='standard_hybrid_sigma',
units='m',
length=lev,
coord_vals=zlevs,
cell_bounds=zlev_bnds)
p0 = 0.5e4
## p0 = 1.e5
# a_coeff = (/ 0.1, 0.2, 0.3, 0.2, 0.1 /)
a_coeff = numpy.array((0.2, 0.4, 0.6, 0.8, 0.95))
b_coeff = numpy.array((0.0, 0.1, 0.2, 0.5, 0.8))
# a_coeff_bnds=(/0.,.15, .25, .25, .15, 0./)
a_coeff_bnds = numpy.array((0., .3, .5, .7, .9, 1.))
b_coeff_bnds = numpy.array((0., .05, .15, .35, .65, 1.))
# error_flag = cmor.zfactor(
# zaxis_id=ilev,
# zfactor_name='ptop',
# units='Pa',
# zfactor_values = p0)
error_flag = cmor.zfactor(
zaxis_id=ilev,
zfactor_name='b',
axis_ids=numpy.array((ilev, )),
zfactor_values=b_coeff,
zfactor_bounds=b_coeff_bnds)
# error_flag = cmor.zfactor(
# zaxis_id=ilev,
# zfactor_name='lev',
## axis_ids= numpy.array(( ilev, )),
# units='m',
## zfactor_values = a_coeff,
# zfactor_bounds = a_coeff_bnds )
data2d = numpy.random.random((180, 360)).astype('f') * 8000
zfactor_id = cmor.zfactor(
zaxis_id=ilev,
zfactor_name='orog',
axis_ids=numpy.array((ilon, ilat)),
units='m',
zfactor_values=data2d)
else:
print('yep working case')
ilev = cmor.axis(
table_entry='standard_sigma',
units='1',
length=lev,
coord_vals=zlevs,
cell_bounds=zlev_bnds)
p0 = 0.5E4
a_coeff = numpy.array((0.2, 0.4, 0.6, 0.8, 0.95))
b_coeff = numpy.array((0.0, 0.1, 0.2, 0.5, 0.8))
a_coeff_bnds = numpy.array((0., .3, .5, .7, .9, 1.))
b_coeff_bnds = numpy.array((0., .05, .15, .35, .65, 1.))
error_flag = cmor.zfactor(
zaxis_id=ilev,
zfactor_name='ptop',
units='Pa',
zfactor_values=p0)
error_flag = cmor.zfactor(
zaxis_id=ilev,
zfactor_name='sigma',
axis_ids=numpy.array((ilev, )),
zfactor_values=a_coeff,
zfactor_bounds=a_coeff_bnds)
data2d = numpy.random.random((180, 360)).astype('f') - 97000.
zfactor_id = cmor.zfactor(
zaxis_id=ilev,
zfactor_name='ps',
axis_ids=numpy.array((ilon, ilat, itim)),
units='Pa')
var3d_ids = cmor.variable(
table_entry='cl',
units='%',
axis_ids=numpy.array((ilev, ilon, ilat, itim)),
missing_value=1.0e28,
original_name='cloud')
for it in range(ntimes):
time = numpy.array((it))
bnds_time = numpy.array((it, it + 1))
data3d = numpy.random.random((5, 360, 180)).astype('f') * 40.
error_flag = cmor.write(
var_id=var3d_ids,
data=data3d,
ntimes_passed=1,
time_vals=time,
time_bnds=bnds_time)
error_flag = cmor.close()
|
