def read_AOD1b_geocenter(AOD1B_file, calendar_month):
"""
Reads monthly non-tidal ocean and atmospheric variation geocenter files
Arguments
---------
AOD1B_file: de-aliasing data file
calendar_month: calendar month of data
"""
#-- check that file exists
if not os.access(AOD1B_file, os.F_OK):
raise IOError('AOD1b File {0} not in File System'.format(AOD1B_file))
#-- read AOD1b geocenter skipping over commented header text
with open(AOD1B_file, 'r') as f:
file_contents = [
i for i in f.read().splitlines() if not re.match(r'#', i)
]
#-- extract X,Y,Z from each line in the file
#-- first column: ISO-formatted date and time
#-- second-fourth columns: X, Y and Z geocenter variations
n_lines = len(file_contents)
X = np.zeros((n_lines))
Y = np.zeros((n_lines))
Z = np.zeros((n_lines))
month = np.zeros((n_lines), dtype=np.int)
for i, line in enumerate(file_contents):
line_contents = line.split()
AOD1B_time = time.strptime(line_contents[0], '%Y-%m-%dT%H:%M:%S')
month[i] = AOD1B_time.tm_mon
X[i], Y[i], Z[i] = np.array(line_contents[1:], dtype=np.float)
#-- use only dates within month (should be all)
ii, = np.nonzero(month == calendar_month)
#-- convert mean X,Y,Z into spherical harmonics
return geocenter(X=X[ii].mean(),
Y=Y[ii].mean(),
Z=Z[ii].mean(),
INVERSE=True)
def geocenter_processing_centers(grace_dir, PROC, DREL, START_MON, END_MON,
MISSING):
#-- GRACE months
GAP = [187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197]
months = sorted(set(np.arange(START_MON, END_MON + 1)) - set(MISSING))
#-- labels for each scenario
input_flags = [
'', 'iter', 'SLF_iter', 'SLF_iter_wSLR21', 'SLF_iter_wSLR21_wSLR22'
]
input_labels = ['Static', 'Iterated', 'Iterated SLF']
#-- labels for Release-6
model_str = 'OMCT' if DREL in ('RL04', 'RL05') else 'MPIOM'
#-- degree one coefficient labels
fig_labels = ['C11', 'S11', 'C10']
axes_labels = dict(C10='c)', C11='a)', S11='b)')
ylabels = dict(C10='z', C11='x', S11='y')
#-- plot colors for each dataset
plot_colors = dict(CSR='darkorange',
GFZ='darkorchid',
JPL='mediumseagreen')
plot_colors['GFZwPT'] = 'dodgerblue'
plot_colors['GFZ+CS21'] = 'darkorchid'
plot_colors['GFZ+CS21+CS22'] = 'darkorchid'
#-- 3 row plot (C10, C11 and S11)
ax = {}
fig, (ax[0], ax[1], ax[2]) = plt.subplots(num=1,
ncols=3,
sharey=True,
figsize=(9, 4))
#-- plot geocenter estimates for each processing center
for k, pr in enumerate(PROC):
#-- additionally plot GFZ with SLR replaced pole tide
if pr in ('GFZwPT', 'GFZ+CS21'):
fargs = ('GFZ', DREL, model_str, input_flags[3])
elif (pr == 'GFZ+CS21+CS22'):
fargs = ('GFZ', DREL, model_str, input_flags[4])
else:
fargs = (pr, DREL, model_str, input_flags[2])
#-- read geocenter file for processing center and model
grace_file = '{0}_{1}_{2}_{3}.txt'.format(*fargs)
DEG1 = geocenter().from_UCI(os.path.join(grace_dir, grace_file))
#-- indices for mean months
kk, = np.nonzero((DEG1.month >= START_MON) & (DEG1.month <= 176))
DEG1.mean(apply=True, indices=kk)
#-- setting Load Love Number (kl) to 0.021 to match Swenson et al. (2008)
DEG1.to_cartesian(kl=0.021)
#-- plot each coefficient
for j, key in enumerate(fig_labels):
#-- create a time series with nans for missing months
tdec = np.full_like(months, np.nan, dtype=np.float64)
data = np.full_like(months, np.nan, dtype=np.float64)
val = getattr(DEG1, ylabels[key].upper())
for i, m in enumerate(months):
valid = np.count_nonzero(DEG1.month == m)
if valid:
mm, = np.nonzero(DEG1.month == m)
tdec[i] = DEG1.time[mm]
data[i] = val[mm]
#-- plot all dates
ax[j].plot(tdec, data, color=plot_colors[pr], label=pr)
#-- add axis labels and adjust font sizes for axis ticks
for j, key in enumerate(fig_labels):
#-- vertical line denoting the accelerometer shutoff
acc = convert_calendar_decimal(2016, 9, day=3, hour=12, minute=12)
ax[j].axvline(acc, color='0.5', ls='dashed', lw=0.5, dashes=(8, 4))
#-- vertical lines for end of the GRACE mission and start of GRACE-FO
jj, = np.flatnonzero(DEG1.month == 186)
kk, = np.flatnonzero(DEG1.month == 198)
vs = ax[j].axvspan(DEG1.time[jj],
DEG1.time[kk],
color='0.5',
ls='dashed',
alpha=0.15)
vs._dashes = (4, 2)
#-- axis label
ax[j].set_title(ylabels[key], style='italic', fontsize=14)
ax[j].add_artist(
AnchoredText(axes_labels[key],
pad=0.,
prop=dict(size=16, weight='bold'),
frameon=False,
loc=2))
ax[j].set_xlabel('Time [Yr]', fontsize=14)
#-- set ticks
xmin = 2002 + (START_MON + 1.0) // 12.0
xmax = 2002 + (END_MON + 1.0) / 12.0
major_ticks = np.arange(2005, xmax, 5)
ax[j].xaxis.set_ticks(major_ticks)
minor_ticks = sorted(set(np.arange(xmin, xmax, 1)) - set(major_ticks))
ax[j].xaxis.set_ticks(minor_ticks, minor=True)
ax[j].set_xlim(xmin, xmax)
ax[j].set_ylim(-9.5, 8.5)
#-- axes tick adjustments
ax[j].get_xaxis().set_tick_params(which='both', direction='in')
ax[j].get_yaxis().set_tick_params(which='both', direction='in')
for tick in ax[j].xaxis.get_major_ticks():
tick.label.set_fontsize(14)
for tick in ax[j].yaxis.get_major_ticks():
tick.label.set_fontsize(14)
#-- add legend
lgd = ax[0].legend(loc=3, frameon=False)
lgd.get_frame().set_alpha(1.0)
for line in lgd.get_lines():
line.set_linewidth(6)
for i, text in enumerate(lgd.get_texts()):
text.set_weight('bold')
text.set_color(plot_colors[text.get_text()])
#-- labels and set limits
ax[0].set_ylabel('Geocenter Variation [mm]', fontsize=14)
#-- adjust locations of subplots
fig.subplots_adjust(left=0.06,
right=0.98,
bottom=0.12,
top=0.94,
wspace=0.05)
#-- save figure to file
OUTPUT_FIGURE = 'SV19_{0}_centers.pdf'.format(DREL)
plt.savefig(os.path.join(grace_dir, OUTPUT_FIGURE), format='pdf', dpi=300)
plt.clf()
def read_SLR_geocenter(
geocenter_file,
RADIUS=None,
HEADER=0,
COLUMNS=['time', 'X', 'Y', 'Z', 'X_sigma', 'Y_sigma', 'Z_sigma']):
"""
Reads monthly geocenter files from satellite laser ranging
Arguments
---------
geocenter_file: Satellite Laser Ranging file
Keyword arguments
-----------------
RADIUS: Earth's radius for calculating spherical harmonics from SLR data
HEADER: rows of data to skip when importing data
COLUMNS: column names of ascii file
time: date in decimal-years
X: X-component of geocenter variation
Y: Y-component of geocenter variation
Z: Z-component of geocenter variation
X_sigma: X-component uncertainty
Y_sigma: Y-component uncertainty
Z_sigma: Z-component uncertainty
Returns
-------
C10: cosine d1/o0 spherical harmonic coefficients
C11: cosine d1/o1 spherical harmonic coefficients
S11: sine d1/o1 spherical harmonic coefficients
eC10: cosine d1/o0 spherical harmonic coefficient error
eC11: cosine d1/o1 spherical harmonic coefficient error
eS11: sine d1/o1 spherical harmonic coefficient error
month: GRACE/GRACE-FO month
time: date of each month in year-decimal
"""
#-- check that geocenter file exists
if not os.access(os.path.expanduser(geocenter_file), os.F_OK):
raise IOError('Geocenter file not found in file system')
#-- Input geocenter file and split lines
with open(os.path.expanduser(geocenter_file), 'r') as f:
file_contents = f.read().splitlines()
ndate = len(file_contents) - HEADER
#-- compile regular expression operator to find numerical instances
regex_pattern = r'[-+]?(?:(?:\d*\.\d+)|(?:\d+\.?))(?:[Ee][+-]?\d+)?'
rx = re.compile(regex_pattern, re.VERBOSE)
#-- initializing output data
#-- Degree 1 Stokes Coefficients
C10 = np.zeros((ndate))
C11 = np.zeros((ndate))
S11 = np.zeros((ndate))
#-- Degree 1 Stokes Coefficient Errors
eC10 = np.zeros((ndate))
eC11 = np.zeros((ndate))
eS11 = np.zeros((ndate))
#-- Date information
date = np.zeros((ndate))
JD = np.zeros((ndate))
mon = np.zeros((ndate), dtype=np.int32)
#-- for each date
for t, file_line in enumerate(file_contents[HEADER:]):
#-- find numerical instances in line
#-- replacing fortran double precision exponential
line_contents = rx.findall(file_line.replace('D', 'E'))
#-- extract date
date[t] = np.float(line_contents[COLUMNS.index('time')])
#-- extract geocenter variations
X = np.float(line_contents[COLUMNS.index('X')])
Y = np.float(line_contents[COLUMNS.index('Y')])
Z = np.float(line_contents[COLUMNS.index('Z')])
X_sigma = np.float(line_contents[COLUMNS.index('X_sigma')])
Y_sigma = np.float(line_contents[COLUMNS.index('Y_sigma')])
Z_sigma = np.float(line_contents[COLUMNS.index('Z_sigma')])
#-- converting from geocenter into spherical harmonics
CS1 = geocenter(X=X, Y=Y, Z=Z, RADIUS=RADIUS, INVERSE=True)
dCS1 = geocenter(X=X_sigma,
Y=Y_sigma,
Z=Z_sigma,
RADIUS=RADIUS,
INVERSE=True)
#-- output harmonics
C10[t], C11[t], S11[t] = (CS1['C10'], CS1['C11'], CS1['S11'])
eC10[t], eC11[t], eS11[t] = (dCS1['C10'], dCS1['C11'], dCS1['S11'])
#-- calendar year of date
year = np.floor(date[t])
#-- check if year is a leap year
dpy = 366.0 if ((year % 4) == 0) else 365.0
#-- calculation of day of the year (with decimals for fraction of day)
DofY = dpy * (date[t] % 1)
#-- Calculation of the Julian date from year and DofY
JD[t] = np.float(367.0 * year -
np.floor(7.0 * (year + np.floor(10.0 / 12.0)) / 4.0) -
np.floor(3.0 * (np.floor(
(year - 8.0 / 7.0) / 100.0) + 1.0) / 4.0) +
np.floor(275.0 / 9.0) + DofY + 1721028.5)
#-- convert the julian date into calendar dates (hour, day, month, year)
cal_date = convert_julian(JD[t])
#-- calculate the GRACE/GRACE-FO month (Apr02 == 004)
#-- https://grace.jpl.nasa.gov/data/grace-months/
mon[t] = 12 * (cal_date['year'] - 2002) + cal_date['month']
return {
'C10': C10,
'C11': C11,
'S11': S11,
'eC10': eC10,
'eC11': eC11,
'eS11': eS11,
'month': mon,
'time': date
}
def aod_corrected_SLR_geocenter(geocenter_file,
DREL,
RADIUS=None,
HEADER=0,
COLUMNS=[]):
"""
Reads monthly geocenter files from satellite laser ranging corrected
for non-tidal ocean and atmospheric variation
Arguments
---------
geocenter_file: Satellite Laser Ranging file
DREL: GRACE/GRACE-FO data release
Keyword arguments
-----------------
RADIUS: Earth's radius for calculating spherical harmonics from SLR data
HEADER: rows of data to skip when importing data
COLUMNS: column names of ascii file
time: date in decimal-years
X: X-component of geocenter variation
Y: Y-component of geocenter variation
Z: Z-component of geocenter variation
X_sigma: X-component uncertainty
Y_sigma: Y-component uncertainty
Z_sigma: Z-component uncertainty
Returns
-------
C10: cosine d1/o0 spherical harmonic coefficients
C11: cosine d1/o1 spherical harmonic coefficients
S11: sine d1/o1 spherical harmonic coefficients
eC10: cosine d1/o0 spherical harmonic coefficient error
eC11: cosine d1/o1 spherical harmonic coefficient error
eS11: sine d1/o1 spherical harmonic coefficient error
month: GRACE/GRACE-FO month
time: date of each month in year-decimal
"""
#-- directory setup for AOD1b data starting with input degree 1 file
#-- this will verify that the input paths work
AOD1B_dir = os.path.abspath(
os.path.join(geocenter_file, os.path.pardir, os.path.pardir, 'AOD1B',
DREL, 'geocenter'))
#-- Input geocenter file and split lines
with open(os.path.expanduser(geocenter_file), 'r') as f:
file_contents = f.read().splitlines()
ndate = len(file_contents) - HEADER
#-- compile regular expression operator to find numerical instances
regex_pattern = r'[-+]?(?:(?:\d*\.\d+)|(?:\d+\.?))(?:[Ee][+-]?\d+)?'
rx = re.compile(regex_pattern, re.VERBOSE)
#-- initializing output data
#-- Degree 1 Stokes Coefficients
C10 = np.zeros((ndate))
C11 = np.zeros((ndate))
S11 = np.zeros((ndate))
#-- Degree 1 Stokes Coefficient Errors
eC10 = np.zeros((ndate))
eC11 = np.zeros((ndate))
eS11 = np.zeros((ndate))
#-- Date information
date = np.zeros((ndate))
JD = np.zeros((ndate))
mon = np.zeros((ndate), dtype=np.int32)
#-- for each date
for t, file_line in enumerate(file_contents[HEADER:]):
#-- find numerical instances in line
#-- replacing fortran double precision exponential
line_contents = rx.findall(file_line.replace('D', 'E'))
#-- extract date
date[t] = np.float(line_contents[COLUMNS.index('time')])
#-- extract geocenter variations
X = np.float(line_contents[COLUMNS.index('X')])
Y = np.float(line_contents[COLUMNS.index('Y')])
Z = np.float(line_contents[COLUMNS.index('Z')])
X_sigma = np.float(line_contents[COLUMNS.index('X_sigma')])
Y_sigma = np.float(line_contents[COLUMNS.index('Y_sigma')])
Z_sigma = np.float(line_contents[COLUMNS.index('Z_sigma')])
#-- converting from geocenter into spherical harmonics
CS1 = geocenter(X=X, Y=Y, Z=Z, RADIUS=RADIUS, INVERSE=True)
dCS1 = geocenter(X=X_sigma,
Y=Y_sigma,
Z=Z_sigma,
RADIUS=RADIUS,
INVERSE=True)
#-- calendar year of date
year = np.floor(date[t])
#-- check if year is a leap year
dpy = 366.0 if ((year % 4) == 0) else 365.0
#-- calculation of day of the year (with decimals for fraction of day)
DofY = dpy * (date[t] % 1)
#-- Calculation of the Julian date from year and DofY
JD[t] = np.float(367. * year -
np.floor(7. * (year + np.floor(10. / 12.)) / 4.) -
np.floor(3.0 * (np.floor(
(year - 8.0 / 7.0) / 100.0) + 1.0) / 4.0) +
np.floor(275.0 / 9.0) + DofY + 1721028.5)
#-- convert the julian date into calendar dates (hour, day, month, year)
cal_date = convert_julian(JD[t], ASTYPE=np.int)
#-- full path to AOD geocenter for month (using glo coefficients)
args = (DREL, 'glo', cal_date['year'], cal_date['month'])
AOD1B_file = 'AOD1B_{0}_{1}_{2:4d}_{3:02d}.txt'.format(*args)
Ylms = read_AOD1b_geocenter(os.path.join(AOD1B_dir, AOD1B_file),
cal_date['month'])
#-- remove AOD from output harmonics
C10[t] = CS1['C10'] - Ylms['C10']
C11[t] = CS1['C11'] - Ylms['C11']
S11[t] = CS1['S11'] - Ylms['S11']
eC10[t], eC11[t], eS11[t] = (dCS1['C10'], dCS1['C11'], dCS1['S11'])
#-- calculate the GRACE/GRACE-FO month (Apr02 == 004)
#-- https://grace.jpl.nasa.gov/data/grace-months/
mon[t] = 12 * (cal_date['year'] - 2002) + cal_date['month']
return {
'C10': C10,
'C11': C11,
'S11': S11,
'eC10': eC10,
'eC11': eC11,
'eS11': eS11,
'month': mon,
'time': date
}
def aod1b_geocenter(base_dir, DREL='', DSET='', CLOBBER=False, MODE=0o775):
"""
Creates monthly files of geocenter variations at 6-hour or 3-hour intervals from
GRACE/GRACE-FO level-1b dealiasing data files
Arguments
---------
base_dir: working data directory
Keyword arguments
-----------------
DREL: GRACE/GRACE-FO data release
DSET: GRACE/GRACE-FO dataset
atm: atmospheric loading from ECMWF
ocn: oceanic loading from OMCT/MPIOM
glo: global atmospheric and oceanic loading
oba: ocean bottom pressure from OMCT/MPIOM
CLOBBER: overwrite existing data
MODE: Permission mode of directories and files
"""
#-- compile regular expressions operators for file dates
#-- will extract the year and month from the tar file (.tar.gz)
tx = re.compile(r'AOD1B_(\d+)-(\d+)_\d+\.(tar\.gz|tgz)$', re.VERBOSE)
#-- and the calendar day from the ascii file (.asc or gzipped .asc.gz)
fx = re.compile(r'AOD1B_\d+-\d+-(\d+)_X_\d+.asc(.gz)?$', re.VERBOSE)
#-- compile regular expressions operator for the clm/slm headers
#-- for the specific AOD1b product
hx = re.compile(r'^DATA.*SET.*{0}'.format(DSET), re.VERBOSE)
#-- compile regular expression operator to find numerical instances
#-- will extract the data from the file
regex_pattern = r'[-+]?(?:(?:\d*\.\d+)|(?:\d+\.?))(?:[Ee][+-]?\d+)?'
rx = re.compile(regex_pattern, re.VERBOSE)
#-- output formatting string
fstr = '{0:4d}-{1:02d}-{2:02d}T{3:02d}:00:00 {4:12.8f} {5:12.8f} {6:12.8f}'
#-- set number of hours in a file
#-- set the ocean model for a given release
if DREL in ('RL01', 'RL02', 'RL03', 'RL04', 'RL05'):
#-- for 00, 06, 12 and 18
n_time = 4
ATMOSPHERE = 'ECMWF'
OCEAN_MODEL = 'OMCT'
LMAX = 100
elif DREL in ('RL06', ):
#-- for 00, 03, 06, 09, 12, 15, 18 and 21
n_time = 8
ATMOSPHERE = 'ECMWF'
OCEAN_MODEL = 'MPIOM'
LMAX = 180
else:
raise ValueError('Invalid data release')
#-- Calculating the number of cos and sin harmonics up to LMAX
n_harm = (LMAX**2 + 3 * LMAX) // 2 + 1
#-- AOD1B data products
product = {}
product['atm'] = 'Atmospheric loading from {0}'.format(ATMOSPHERE)
product['ocn'] = 'Oceanic loading from {0}'.format(OCEAN_MODEL)
product['glo'] = 'Global atmospheric and oceanic loading'
product['oba'] = 'Ocean bottom pressure from {0}'.format(OCEAN_MODEL)
#-- AOD1B directory and output geocenter directory
grace_dir = os.path.join(base_dir, 'AOD1B', DREL)
output_dir = os.path.join(grace_dir, 'geocenter')
if not os.access(output_dir, os.F_OK):
os.mkdir(output_dir, MODE)
#-- finding all of the tar files in the AOD1b directory
input_tar_files = [tf for tf in os.listdir(grace_dir) if tx.match(tf)]
#-- for each tar file
for i in sorted(input_tar_files):
#-- extract the year and month from the file
YY, MM, SFX = tx.findall(i).pop()
YY, MM = np.array([YY, MM], dtype=np.int64)
#-- output monthly geocenter file
FILE = 'AOD1B_{0}_{1}_{2:4d}_{3:02d}.txt'.format(DREL, DSET, YY, MM)
#-- if output file exists: check if input tar file is newer
TEST = False
OVERWRITE = ' (clobber)'
#-- check if output file exists
if os.access(os.path.join(output_dir, FILE), os.F_OK):
#-- check last modification time of input and output files
input_mtime = os.stat(os.path.join(grace_dir, i)).st_mtime
output_mtime = os.stat(os.path.join(output_dir, FILE)).st_mtime
#-- if input tar file is newer: overwrite the output file
if (input_mtime > output_mtime):
TEST = True
OVERWRITE = ' (overwrite)'
else:
TEST = True
OVERWRITE = ' (new)'
#-- As there are so many files.. this will only read the new files
#-- or will rewrite if CLOBBER is set (if wanting something changed)
if TEST or CLOBBER:
#-- if verbose: output information about the geocenter file
logging.info('{0}{1}'.format(os.path.join(output_dir, FILE),
OVERWRITE))
#-- open output monthly geocenter file
f = open(os.path.join(output_dir, FILE), 'w')
args = ('Geocenter time series', DREL, DSET)
print('# {0} from {1} AOD1b {2} Product'.format(*args), file=f)
print('# {0}'.format(product[DSET]), file=f)
args = ('ISO-Time', 'X', 'Y', 'Z')
print('# {0:^15} {1:^12} {2:^12} {3:^12}'.format(*args), file=f)
#-- open the AOD1B monthly tar file
tar = tarfile.open(name=os.path.join(grace_dir, i), mode='r:gz')
#-- Iterate over every member within the tar file
for member in tar.getmembers():
#-- get calendar day from file
DD, SFX = fx.findall(member.name).pop()
DD = np.int64(DD)
#-- open data file for day
if (SFX == '.gz'):
fid = gzip.GzipFile(fileobj=tar.extractfile(member))
else:
fid = tar.extractfile(member)
#-- degree 1 spherical harmonics for day and hours
DEG1 = geocenter()
DEG1.C10 = np.zeros((n_time))
DEG1.C11 = np.zeros((n_time))
DEG1.S11 = np.zeros((n_time))
hours = np.zeros((n_time), dtype=np.int64)
#-- create counter for hour in dataset
c = 0
#-- while loop ends when dataset is read
while (c < n_time):
#-- read line
file_contents = fid.readline().decode('ISO-8859-1')
#-- find file header for data product
if bool(hx.search(file_contents)):
#-- extract hour from header and convert to float
HH, = re.findall(r'(\d+):\d+:\d+', file_contents)
hours[c] = np.int64(HH)
#-- read each line of spherical harmonics
for k in range(0, n_harm):
file_contents = fid.readline().decode('ISO-8859-1')
#-- find numerical instances in the data line
line_contents = rx.findall(file_contents)
#-- spherical harmonic degree and order
l1 = np.int64(line_contents[0])
m1 = np.int64(line_contents[1])
if (l1 == 1) and (m1 == 0):
DEG1.C10[c] = np.float64(line_contents[2])
elif (l1 == 1) and (m1 == 1):
DEG1.C11[c] = np.float64(line_contents[2])
DEG1.S11[c] = np.float64(line_contents[3])
#-- add 1 to hour counter
c += 1
#-- close the input file for day
fid.close()
#-- convert from spherical harmonics into geocenter
DEG1.to_cartesian()
#-- write to file for each hour (iterates each 6-hour block)
for h, X, Y, Z in zip(hours, DEG1.X, DEG1.Y, DEG1.Z):
print(fstr.format(YY, MM, DD, h, X, Y, Z), file=f)
#-- close the tar file
tar.close()
#-- close the output file
f.close()
#-- set the permissions mode of the output file
os.chmod(os.path.join(output_dir, FILE), MODE)