-
Notifications
You must be signed in to change notification settings - Fork 8
/
alongtrack_sat_vs_nemo.py
executable file
·102 lines (71 loc) · 4.55 KB
/
alongtrack_sat_vs_nemo.py
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
#!/usr/bin/env python3
# -*- Mode: Python; coding: utf-8; indent-tabs-mode: nil; tab-width: 4 -*-
############################################################################
#
# L. Brodeau, 2021
#
############################################################################
import gonzag as gz
from gonzag.config import IsZarr,ldebug, rmissval, l_save_track_on_model_grid
def argument_parsing():
'''
ARGUMENT PARSING / USAGE
'''
import argparse as ap
#
parser = ap.ArgumentParser(description='I interpolate, in space and time, the SSH (or any other 2D field) from a non-regular structured gridded domain of an OGCM onto a satellite track.')
requiredNamed = parser.add_argument_group('required arguments')
requiredNamed.add_argument('-s', '--fsat', required=True, help='satellite alongtrack data NetCDF file to read from')
requiredNamed.add_argument('-n', '--vsat', required=True, default="ssh", help='name of field of interest in satellite file (default="ssh")')
requiredNamed.add_argument('-m', '--fmod', required=True, help='model NetCDF file to read from')
requiredNamed.add_argument('-v', '--vmod', required=True, default="ssh", help='name of field of interest in model file (default="ssh")')
#
parser.add_argument('-l', '--fmsk' , default="0", help='land-sea mask on model grid: "-l <ncfile>" or "-l 0" to use "_FillValue" attribute of field of interest')
parser.add_argument('-k', '--vmsk' , default="tmask", help='name of land-sea mask in <ncfile> if "-l <ncfile>" used')
#
parser.add_argument('-D','--distgrid', dest='distgrid', action='store_true', help='take into acount possible strong local distorsion of the model grid')
parser.set_defaults(distgrid=False)
#
args = parser.parse_args()
print('')
print(' *** Satellite file and variable:\n', ' => ', args.fsat, '"'+args.vsat+'"')
print(' *** Model file and variable:\n', ' => ', args.fmod, '"'+args.vmod,'"\n')
#
flsm = args.fmsk
vlsm = args.vmsk
if flsm == "0": flsm = args.fmod ; vlsm = '_FillValue'
#
return args.fsat, args.vsat, args.fmod, args.vmod, flsm, vlsm, args.distgrid
if __name__ == '__main__':
file_sat, name_ssh_sat, file_mod, name_ssh_mod, file_lsm_mod, name_lsm_mod, l_griddist = argument_parsing()
# Time overlap between model and satellite data ?
(it1,it2), (Nts,Ntm) = gz.GetEpochTimeOverlap( file_sat , file_mod )
print(' *** Time overlap between model and satellite in UNIX epoch time: it1, it2', it1,'--',it2)
print(' => UTC: "'+gz.EpochT2Str(it1)+'" to "'+gz.EpochT2Str(it2)+'"\n')
print('\n\n\n ##### M O D E L 2 D + T D O M A I N a.k.a. S O U R C E #####\n')
clsm = name_lsm_mod
if name_lsm_mod=='_FillValue': clsm = name_lsm_mod+'@'+name_ssh_mod
ModelGrid = gz.ModGrid( file_mod, it1, it2, file_lsm_mod, clsm, distorded_grid=l_griddist )
print('\n\n\n ##### S A T E L L I T E 1 D T R A C K a.k.a. T A R G E T #####\n')
SatelliteTrack = gz.SatTrack( file_sat, it1, it2, Np=Nts, \
domain_bounds=ModelGrid.domain_bounds, l_0_360=ModelGrid.l360 )
# Mapping and interpolation:
RES = gz.Model2SatTrack( ModelGrid, name_ssh_mod, SatelliteTrack, name_ssh_sat )
# Save the result into a NetCDF file:
import numpy as nmp
if not IsZarr:
from gonzag.ncio import SaveTimeSeries, Save2Dfield
else:
from gonzag.zarrio import SaveTimeSeries, Save2Dfield
c1 = 'Model SSH interpolated in space (' ; c2=') and time on satellite track'
vvar = [ 'latitude', 'longitude', name_ssh_mod+'_np' , name_ssh_mod+'_bl' , name_ssh_sat , 'distance' ]
vunits = [ 'deg.N' , 'deg.E' , 'm' , 'm' , 'm' , 'km' ]
vlongN = [ 'Latitude', 'Longitude', c1+'nearest-point'+c2, c1+'bilinear'+c2 , 'Input satellite data', 'Cumulated distance from first point' ]
iw = SaveTimeSeries( RES.time, \
nmp.array( [RES.lat, RES.lon, RES.ssh_mod_np, RES.ssh_mod, RES.ssh_sat, RES.distance] ), \
vvar, 'result.nc', \
time_units='seconds since 1970-01-01 00:00:00', \
vunits=vunits, vlnm=vlongN, missing_val=rmissval )
if l_save_track_on_model_grid:
xmsk = 1 - nmp.ma.getmask(RES.XNPtrack).astype(nmp.int8)
Save2Dfield( 'xnp_msk.nc', RES.XNPtrack, xlon=ModelGrid.lon, xlat=ModelGrid.lat, name='track', mask=xmsk )