Newer
Older
Javier Vegas-Regidor
committed
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
import numpy as np
from box import Box
from diagnostic import Diagnostic
from earthdiagnostics import cdo
from utils import Utils, TempFile
class HeatContentLayer(Diagnostic):
"""
Point-wise Ocean Heat Content in a specified ocean thickness (J/m-2)
:original author: Isabel Andreu Burillo
:contributor: Virginie Guemas <virginie.guemas@bsc.es>
:contributor: Javier Vegas-Regidor<javier.vegas@bsc.es>
:created: June 2012
:last modified: June 2016
"""
def __init__(self, data_manager, startdate, member, chunk, box):
Diagnostic.__init__(self, data_manager)
self.startdate = startdate
self.member = member
self.chunk = chunk
self.box = box
self.required_vars = ['so', 'mlotst']
self.generated_vars = ['scvertsum']
def __str__(self):
return 'Heat content layer Startdate: {0} Member: {1} Chunk: {2}'.format(self.startdate, self.member,
self.chunk)
@classmethod
def generate_jobs(cls, diags, options):
"""
Creates a job for each chunk to compute the diagnostic
:param diags: Diagnostics manager class
:type diags: Diags
:param options: None
:type options: list[str]
:return:
"""
num_options = len(options) - 1
if num_options < 2:
raise Exception('You must specify the minimum and maximum depth to use')
if num_options > 2:
raise Exception('You must specify 2 for the heat content layer diagnostic')
box = Box(True)
box.min_depth = int(options[1])
box.max_depth = int(options[2])
job_list = list()
for startdate, member, chunk in diags.get_chunk_list():
job_list.append(HeatContentLayer(diags.data_manager, startdate, member, chunk, box))
Javier Vegas-Regidor
committed
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
return job_list
def compute(self):
nco = Utils.nco
temp = TempFile.get()
heatc_sl_out = TempFile.get()
heatc_sl_top = TempFile.get()
level_above = TempFile.get()
level_below = TempFile.get()
heatc_sl_bottom = TempFile.get()
heatc_sl_top_invert = TempFile.get()
e3tfile = TempFile.get()
results = TempFile.get()
handler = Utils.openCdf('mesh_zgr.nc')
if 'e3t' in handler.variables:
e3t_name = 'e3t'
elif 'e3t_0' in handler.variables:
e3t_name = 'e3t_0'
else:
raise Exception('e3t variable can not be found')
handler.close()
nco.ncap2(input='mesh_zgr.nc', output=e3tfile, options='-v -O -s "heatc_sl=tmask*{0}"'.format(e3t_name)),
thetao_file = self.data_manager.get_file('ocean', 'thetao', self.startdate, self.member, self.chunk)
nco.ncks(input=thetao_file, output=temp, options='-O -v thetao')
Utils.rename_variable(temp, 'thetao', 'heatc_sl')
cdo.mul(input=' '.join([temp, e3tfile]), output=heatc_sl_out)
# extract the data between the two given depths --> heatc_sl_top.nc
nco.ncks(input=heatc_sl_out, output=heatc_sl_top,
options='-O -d lev,{0}.0,{1}.0'.format(self.box.min_depth, self.box.max_depth))
# now extract a few levels below, to compute the residual ohc
# addition with float returned:
nco.ncks(input=heatc_sl_out, output=heatc_sl_bottom,
options='-O -d lev,{0}.0,{1}.0'.format(self.box.max_depth, self.box.max_depth + 200))
# obtain the weight for the extra level containing the 300 m
# deptht in the gridT files is positive
# weight = (300.0 - depth_top)/(depth_bottom - depth_top)
# and add the thickness down to 300 m in the next layer
nco.ncpdq(options="-a '-lev'", input=heatc_sl_top, output=heatc_sl_top_invert)
nco.ncks(input=heatc_sl_top_invert, output=level_above, options='-O -d lev,0,0,1')
nco.ncks(input=heatc_sl_bottom, output=level_below, options='-O -d lev,0,0,1')
handler = Utils.openCdf(level_above)
lev_above = handler.variables['lev'][:]
handler.close()
handler = Utils.openCdf(level_below)
layerthcknss = handler.variables['lev'][:] - lev_above
heatc_sl_below = handler.variables['heatc_sl'][:]
handler.close()
factor = (self.box.max_depth - lev_above) / layerthcknss
heatc_sl_below = heatc_sl_below * factor
handler = Utils.openCdf(heatc_sl_top)
heatc_sl = handler.variables['heatc_sl'][:]
handler.close()
heatc_sl = np.sum(heatc_sl, 1)
heatc_sl = heatc_sl[:] + heatc_sl_below[:, 0, :]
heatc_sl = heatc_sl[:] * 1020 * 4000
nco.ncks(input=thetao_file, output=results, options='-O -v lon,lat,time')
Utils.rename_variables(results, {'x': 'i', 'y': 'j'}, False, True)
handler_results = Utils.openCdf(results)
handler_results.createVariable('ohc', float, ('time', 'j', 'i'))
handler_results.close()
handler_results = Utils.openCdf(results)
handler_results.variables['ohc'][:] = heatc_sl
handler_results.close()
Utils.setminmax(results, 'ohc')
self.data_manager.send_file(results, 'ocean', 'ohc', self.startdate, self.member, self.chunk, box=self.box)