1 |
""" |
---|
2 |
Parse data and assert what data creates and updates monthly NetCDF files. |
---|
3 |
|
---|
4 |
Scintec SFAS processed sodar wind profile data. |
---|
5 |
""" |
---|
6 |
|
---|
7 |
import math |
---|
8 |
import numpy as n |
---|
9 |
import pycdf |
---|
10 |
import datetime |
---|
11 |
import procutil |
---|
12 |
from sodar.scintec import maindata |
---|
13 |
|
---|
14 |
nowDt = datetime.datetime.utcnow().replace(microsecond=0) |
---|
15 |
manual = ['z','speed','dir','error'] |
---|
16 |
|
---|
17 |
def parser(platform_info, sensor_info, lines): |
---|
18 |
""" |
---|
19 |
Parse and assign wind profile data from main Sodar file. |
---|
20 |
""" |
---|
21 |
|
---|
22 |
main_data = maindata.MainData(''.join(lines)) |
---|
23 |
|
---|
24 |
num_profiles = len(main_data) |
---|
25 |
min_altitude = sensor_info['min_altitude'] |
---|
26 |
altitude_interval = sensor_info['altitude_interval'] |
---|
27 |
num_altitudes = sensor_info['num_altitudes'] |
---|
28 |
sensor_elevation = sensor_info['sensor_elevation'] |
---|
29 |
|
---|
30 |
altitudes = [(altitude_num * altitude_interval) + min_altitude |
---|
31 |
for altitude_num in range(num_altitudes)] |
---|
32 |
elevations = [altitude + sensor_elevation for altitude in altitudes] |
---|
33 |
|
---|
34 |
data = { |
---|
35 |
'dt' : n.array(n.ones((num_profiles,), dtype=object) * n.nan), |
---|
36 |
'time' : n.array(n.ones((num_profiles,), dtype=long) * n.nan), |
---|
37 |
'z' : n.array(elevations, dtype=float), |
---|
38 |
'u' : n.array(n.ones((num_profiles, |
---|
39 |
num_altitudes), dtype=float) * n.nan), |
---|
40 |
'v' : n.array(n.ones((num_profiles, |
---|
41 |
num_altitudes), dtype=float) * n.nan), |
---|
42 |
} |
---|
43 |
|
---|
44 |
gaps = {} |
---|
45 |
for variable in main_data.variables: |
---|
46 |
symbol = variable['symbol'] |
---|
47 |
gaps[symbol] = variable['gap'] |
---|
48 |
if symbol not in manual: |
---|
49 |
data[symbol.lower()] = n.array(n.ones((num_profiles, |
---|
50 |
num_altitudes), |
---|
51 |
dtype=float) * n.nan) |
---|
52 |
|
---|
53 |
data['error'] = n.array(n.ones((num_profiles, |
---|
54 |
num_altitudes), dtype = int) * n.nan) |
---|
55 |
for (profile_index, profile) in enumerate(main_data): |
---|
56 |
dt = {'month' : profile.stop.month, |
---|
57 |
'day' : profile.stop.day, |
---|
58 |
'year' : profile.stop.year, |
---|
59 |
'hour' : profile.stop.hour, |
---|
60 |
'min' : profile.stop.minute, |
---|
61 |
} |
---|
62 |
dt = '%(month)02d-%(day)02d-%(year)04d %(hour)02d:%(min)02d' % dt |
---|
63 |
dt = procutil.scanf_datetime(dt, fmt='%m-%d-%Y %H:%M') |
---|
64 |
if sensor_info['utc_offset']: |
---|
65 |
dt = dt + datetime.timedelta(hours=sensor_info['utc_offset']) |
---|
66 |
data['dt'][profile_index] = dt |
---|
67 |
|
---|
68 |
data['time'][profile_index] = procutil.dt2es(dt) |
---|
69 |
|
---|
70 |
for (observation_index, observation) in enumerate(profile): |
---|
71 |
radial = observation['speed'] |
---|
72 |
theta = observation['dir'] |
---|
73 |
|
---|
74 |
if radial != gaps['speed'] and theta != gaps['dir']: |
---|
75 |
theta = math.pi * float(theta) / 180.0 |
---|
76 |
radial = float(radial) |
---|
77 |
data['u'][profile_index][observation_index] = \ |
---|
78 |
radial * math.sin(theta) |
---|
79 |
data['v'][profile_index][observation_index] = \ |
---|
80 |
radial * math.cos(theta) |
---|
81 |
|
---|
82 |
for variable in profile.variables: |
---|
83 |
if variable not in manual and \ |
---|
84 |
observation[variable] != gaps[variable]: |
---|
85 |
data[variable.lower()][profile_index][observation_index] = \ |
---|
86 |
float(observation[variable]) |
---|
87 |
|
---|
88 |
data['error'][profile_index][observation_index] = \ |
---|
89 |
int(observation['error']) |
---|
90 |
|
---|
91 |
return data |
---|
92 |
|
---|
93 |
def creator(platform_info, sensor_info, data): |
---|
94 |
|
---|
95 |
|
---|
96 |
title_str = sensor_info['description']+' at '+ platform_info['location'] |
---|
97 |
global_atts = { |
---|
98 |
'title' : title_str, |
---|
99 |
'institution' : 'Unversity of North Carolina at Chapel Hill (UNC-CH)', |
---|
100 |
'institution_url' : 'http://nccoos.unc.edu', |
---|
101 |
'institution_dods_url' : 'http://nccoos.unc.edu', |
---|
102 |
'metadata_url' : 'http://nccoos.unc.edu', |
---|
103 |
'references' : 'http://nccoos.unc.edu', |
---|
104 |
'contact' : 'cbc (cbc@unc.edu)', |
---|
105 |
|
---|
106 |
'source' : 'fixed-profiler (acoustic doppler) observation', |
---|
107 |
'history' : 'raw2proc using ' + sensor_info['process_module'], |
---|
108 |
'comment' : 'File created using pycdf'+pycdf.pycdfVersion()+' and numpy '+pycdf.pycdfArrayPkg(), |
---|
109 |
|
---|
110 |
'Conventions' : 'CF-1.0; SEACOOS-CDL-v2.0', |
---|
111 |
|
---|
112 |
'format_category_code' : 'fixed-profiler', |
---|
113 |
'institution_code' : platform_info['institution'], |
---|
114 |
'platform_code' : platform_info['id'], |
---|
115 |
'package_code' : sensor_info['id'], |
---|
116 |
|
---|
117 |
'project' : 'North Carolina Coastal Ocean Observing System (NCCOOS)', |
---|
118 |
'project_url' : 'http://nccoos.unc.edu', |
---|
119 |
|
---|
120 |
|
---|
121 |
'start_date' : data['dt'][0].strftime("%Y-%m-%d %H:%M:%S"), |
---|
122 |
|
---|
123 |
'end_date' : data['dt'][-1].strftime("%Y-%m-%d %H:%M:%S"), |
---|
124 |
'release_date' : nowDt.strftime("%Y-%m-%d %H:%M:%S"), |
---|
125 |
|
---|
126 |
'creation_date' : nowDt.strftime("%Y-%m-%d %H:%M:%S"), |
---|
127 |
'modification_date' : nowDt.strftime("%Y-%m-%d %H:%M:%S"), |
---|
128 |
'process_level' : 'level1', |
---|
129 |
|
---|
130 |
|
---|
131 |
'_FillValue' : -99999., |
---|
132 |
} |
---|
133 |
|
---|
134 |
var_atts = { |
---|
135 |
|
---|
136 |
'time' : {'short_name': 'time', |
---|
137 |
'long_name': 'Time', |
---|
138 |
'standard_name': 'time', |
---|
139 |
'units': 'seconds since 1970-1-1 00:00:00 -0', |
---|
140 |
'axis': 'T', |
---|
141 |
}, |
---|
142 |
'lat' : {'short_name': 'lat', |
---|
143 |
'long_name': 'Latitude', |
---|
144 |
'standard_name': 'latitude', |
---|
145 |
'reference':'geographic coordinates', |
---|
146 |
'units': 'degrees_north', |
---|
147 |
'valid_range':(-90.,90.), |
---|
148 |
'axis': 'Y', |
---|
149 |
}, |
---|
150 |
'lon' : {'short_name': 'lon', |
---|
151 |
'long_name': 'Longtitude', |
---|
152 |
'standard_name': 'longtitude', |
---|
153 |
'reference':'geographic coordinates', |
---|
154 |
'units': 'degrees_east', |
---|
155 |
'valid_range':(-180.,180.), |
---|
156 |
'axis': 'Y', |
---|
157 |
}, |
---|
158 |
'z' : {'short_name': 'z', |
---|
159 |
'long_name': 'Height', |
---|
160 |
'standard_name': 'height', |
---|
161 |
'reference':'zero at sea-surface', |
---|
162 |
'positive' : 'up', |
---|
163 |
'units': 'm', |
---|
164 |
'axis': 'Z', |
---|
165 |
}, |
---|
166 |
|
---|
167 |
'u': {'short_name' : 'u', |
---|
168 |
'long_name': 'East/West Component of Wind', |
---|
169 |
'standard_name': 'eastward_wind', |
---|
170 |
'units': 'm s-1', |
---|
171 |
}, |
---|
172 |
'v': {'short_name' : 'v', |
---|
173 |
'long_name': 'North/South Component of Wind', |
---|
174 |
'standard_name': 'northward_wind', |
---|
175 |
'units': 'm s-1', |
---|
176 |
}, |
---|
177 |
'w': {'short_name' : 'w', |
---|
178 |
'long_name': 'Vertical Component of Wind', |
---|
179 |
'standard_name': 'upward_wind', |
---|
180 |
'units': 'm s-1', |
---|
181 |
}, |
---|
182 |
'sigw': {'short_name' : 'sigw', |
---|
183 |
'long_name': 'Standard Deviation of Vertical Component', |
---|
184 |
'standard_name': 'sigma_upward_wind', |
---|
185 |
}, |
---|
186 |
'bck' : {'short_name': 'bck', |
---|
187 |
'long_name': 'Backscatter', |
---|
188 |
'standard_name': 'backscatter' |
---|
189 |
}, |
---|
190 |
'error' : {'short_name': 'error', |
---|
191 |
'long_name': 'Error Code', |
---|
192 |
'standard_name': 'error_code' |
---|
193 |
}, |
---|
194 |
} |
---|
195 |
|
---|
196 |
|
---|
197 |
dim_inits = ( |
---|
198 |
('ntime', pycdf.NC.UNLIMITED), |
---|
199 |
('nlat', 1), |
---|
200 |
('nlon', 1), |
---|
201 |
('nz', sensor_info['num_altitudes']) |
---|
202 |
) |
---|
203 |
|
---|
204 |
|
---|
205 |
|
---|
206 |
|
---|
207 |
|
---|
208 |
var_inits = ( |
---|
209 |
|
---|
210 |
('time', pycdf.NC.INT, ('ntime',)), |
---|
211 |
('lat', pycdf.NC.FLOAT, ('nlat',)), |
---|
212 |
('lon', pycdf.NC.FLOAT, ('nlon',)), |
---|
213 |
('z', pycdf.NC.FLOAT, ('nz',)), |
---|
214 |
|
---|
215 |
('u', pycdf.NC.FLOAT, ('ntime', 'nz')), |
---|
216 |
('v', pycdf.NC.FLOAT, ('ntime', 'nz')), |
---|
217 |
('w', pycdf.NC.FLOAT, ('ntime', 'nz')), |
---|
218 |
('sigw', pycdf.NC.FLOAT, ('ntime', 'nz')), |
---|
219 |
('bck', pycdf.NC.FLOAT, ('ntime', 'nz')), |
---|
220 |
('error', pycdf.NC.INT, ('ntime', 'nz')), |
---|
221 |
) |
---|
222 |
|
---|
223 |
|
---|
224 |
i = data['in'] |
---|
225 |
|
---|
226 |
|
---|
227 |
var_data = ( |
---|
228 |
('time', data['time'][i]), |
---|
229 |
('lat', platform_info['lat']), |
---|
230 |
('lon', platform_info['lon']), |
---|
231 |
('z', data['z']), |
---|
232 |
('u', data['u'][i]), |
---|
233 |
('v', data['v'][i]), |
---|
234 |
('w', data['w'][i]), |
---|
235 |
('sigw', data['sigw'][i]), |
---|
236 |
('bck', data['bck'][i]), |
---|
237 |
('error', data['error'][i]), |
---|
238 |
) |
---|
239 |
|
---|
240 |
return (global_atts, var_atts, dim_inits, var_inits, var_data) |
---|
241 |
|
---|
242 |
def updater(platform_info, sensor_info, data): |
---|
243 |
|
---|
244 |
global_atts = { |
---|
245 |
|
---|
246 |
|
---|
247 |
'end_date' : data['dt'][-1].strftime("%Y-%m-%d %H:%M:%S"), |
---|
248 |
'release_date' : nowDt.strftime("%Y-%m-%d %H:%M:%S"), |
---|
249 |
|
---|
250 |
'modification_date' : nowDt.strftime("%Y-%m-%d %H:%M:%S"), |
---|
251 |
} |
---|
252 |
|
---|
253 |
|
---|
254 |
|
---|
255 |
var_atts = {} |
---|
256 |
|
---|
257 |
|
---|
258 |
i = data['in'] |
---|
259 |
|
---|
260 |
|
---|
261 |
var_data = ( |
---|
262 |
('time', data['time'][i]), |
---|
263 |
('u', data['u'][i]), |
---|
264 |
('v', data['v'][i]), |
---|
265 |
('w', data['w'][i]), |
---|
266 |
('sigw', data['sigw'][i]), |
---|
267 |
('bck', data['bck'][i]), |
---|
268 |
('error', data['error'][i]), |
---|
269 |
) |
---|
270 |
|
---|
271 |
return (global_atts, var_atts, var_data) |
---|