def compute_LPET_ICESat2(INPUT_FILE, VERBOSE=False, MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logger = pyTMD.utilities.build_logger('pytmd', level=loglevel)
#-- read data from input file
logger.info('{0} -->'.format(INPUT_FILE))
IS2_atl03_mds, IS2_atl03_attrs, IS2_atl03_beams = read_HDF5_ATL03_main(
INPUT_FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 file name
rx = re.compile(
r'(processed_)?(ATL\d{2})_(\d{4})(\d{2})(\d{2})(\d{2})'
r'(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$')
try:
SUB, PRD, YY, MM, DD, HH, MN, SS, TRK, CYCL, GRAN, RL, VERS, AUX = rx.findall(
INPUT_FILE).pop()
except:
#-- output long-period equilibrium tide HDF5 file (generic)
fileBasename, fileExtension = os.path.splitext(INPUT_FILE)
OUTPUT_FILE = '{0}_{1}{2}'.format(fileBasename, 'LPET', fileExtension)
else:
#-- output long-period equilibrium tide HDF5 file for ASAS/NSIDC granules
args = (PRD, YY, MM, DD, HH, MN, SS, TRK, CYCL, GRAN, RL, VERS, AUX)
file_format = '{0}_LPET_{1}{2}{3}{4}{5}{6}_{7}{8}{9}_{10}_{11}{12}.h5'
OUTPUT_FILE = file_format.format(*args)
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl03_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- copy variables for outputting to HDF5 file
IS2_atl03_tide = {}
IS2_atl03_fill = {}
IS2_atl03_dims = {}
IS2_atl03_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl03_tide['ancillary_data'] = {}
IS2_atl03_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl03_tide['ancillary_data'][key] = IS2_atl03_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl03_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl03_attrs['ancillary_data'][key].items(
):
IS2_atl03_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam within the file
for gtx in sorted(IS2_atl03_beams):
#-- output data dictionaries for beam
IS2_atl03_tide[gtx] = dict(geolocation={}, geophys_corr={})
IS2_atl03_fill[gtx] = dict(geolocation={}, geophys_corr={})
IS2_atl03_dims[gtx] = dict(geolocation={}, geophys_corr={})
IS2_atl03_tide_attrs[gtx] = dict(geolocation={}, geophys_corr={})
#-- read data and attributes for beam
val, attrs = read_HDF5_ATL03_beam(INPUT_FILE, gtx, ATTRIBUTES=True)
#-- number of segments
n_seg = len(val['geolocation']['segment_id'])
#-- extract variables for computing equilibrium tides
segment_id = val['geolocation']['segment_id'].copy()
delta_time = val['geolocation']['delta_time'].copy()
lon = val['geolocation']['reference_photon_lon'].copy()
lat = val['geolocation']['reference_photon_lat'].copy()
#-- invalid value
fv = attrs['geolocation']['sigma_h']['_FillValue']
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + delta_time
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(gps_seconds - leap_seconds,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = pyTMD.utilities.get_data_path(
['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- predict long-period equilibrium tides at latitudes and time
tide_lpe = compute_equilibrium_tide(tide_time + deltat, lat)
#-- group attributes for beam
IS2_atl03_tide_attrs[gtx]['Description'] = attrs['Description']
IS2_atl03_tide_attrs[gtx]['atlas_pce'] = attrs['atlas_pce']
IS2_atl03_tide_attrs[gtx]['atlas_beam_type'] = attrs['atlas_beam_type']
IS2_atl03_tide_attrs[gtx]['groundtrack_id'] = attrs['groundtrack_id']
IS2_atl03_tide_attrs[gtx]['atmosphere_profile'] = attrs[
'atmosphere_profile']
IS2_atl03_tide_attrs[gtx]['atlas_spot_number'] = attrs[
'atlas_spot_number']
IS2_atl03_tide_attrs[gtx]['sc_orientation'] = attrs['sc_orientation']
#-- group attributes for geolocation
IS2_atl03_tide_attrs[gtx]['geolocation']['Description'] = (
"Contains parameters related to "
"geolocation. The rate of all of these parameters is at the rate corresponding to the "
"ICESat-2 Geolocation Along Track Segment interval (nominally 20 m along-track)."
)
IS2_atl03_tide_attrs[gtx]['geolocation']['data_rate'] = (
"Data within this group are "
"stored at the ICESat-2 20m segment rate.")
#-- group attributes for geophys_corr
IS2_atl03_tide_attrs[gtx]['geophys_corr']['Description'] = (
"Contains parameters used to "
"correct photon heights for geophysical effects, such as tides. These parameters are "
"posted at the same interval as the ICESat-2 Geolocation Along-Track Segment interval "
"(nominally 20m along-track).")
IS2_atl03_tide_attrs[gtx]['geophys_corr']['data_rate'] = (
"These parameters are stored at "
"the ICESat-2 Geolocation Along Track Segment rate (nominally every 20 m along-track)."
)
#-- geolocation, time and segment ID
#-- delta time in geolocation group
IS2_atl03_tide[gtx]['geolocation']['delta_time'] = delta_time
IS2_atl03_fill[gtx]['geolocation']['delta_time'] = None
IS2_atl03_dims[gtx]['geolocation']['delta_time'] = None
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'] = {}
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'][
'standard_name'] = "time"
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'][
'calendar'] = "standard"
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time']['description'] = (
"Elapsed seconds "
"from the ATLAS SDP GPS Epoch, corresponding to the transmit time of the reference "
"photon. The ATLAS Standard Data Products (SDP) epoch offset is defined within "
"/ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch "
"(1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset "
"contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds "
"relative to the GPS epoch can be computed.")
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time']['coordinates'] = \
"segment_id reference_photon_lat reference_photon_lon"
#-- delta time in geophys_corr group
IS2_atl03_tide[gtx]['geophys_corr']['delta_time'] = delta_time
IS2_atl03_fill[gtx]['geophys_corr']['delta_time'] = None
IS2_atl03_dims[gtx]['geophys_corr']['delta_time'] = None
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'] = {}
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'][
'standard_name'] = "time"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'][
'calendar'] = "standard"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time']['description'] = (
"Elapsed seconds "
"from the ATLAS SDP GPS Epoch, corresponding to the transmit time of the reference "
"photon. The ATLAS Standard Data Products (SDP) epoch offset is defined within "
"/ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch "
"(1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset "
"contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds "
"relative to the GPS epoch can be computed.")
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time']['coordinates'] = (
"../geolocation/segment_id "
"../geolocation/reference_photon_lat ../geolocation/reference_photon_lon"
)
#-- latitude
IS2_atl03_tide[gtx]['geolocation']['reference_photon_lat'] = lat
IS2_atl03_fill[gtx]['geolocation']['reference_photon_lat'] = None
IS2_atl03_dims[gtx]['geolocation']['reference_photon_lat'] = [
'delta_time'
]
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'] = {}
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'units'] = "degrees_north"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'contentType'] = "physicalMeasurement"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'long_name'] = "Latitude"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'standard_name'] = "latitude"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'description'] = (
"Latitude of each "
"reference photon. Computed from the ECF Cartesian coordinates of the bounce point."
)
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'valid_min'] = -90.0
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'valid_max'] = 90.0
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat']['coordinates'] = \
"segment_id delta_time reference_photon_lon"
#-- longitude
IS2_atl03_tide[gtx]['geolocation']['reference_photon_lon'] = lon
IS2_atl03_fill[gtx]['geolocation']['reference_photon_lon'] = None
IS2_atl03_dims[gtx]['geolocation']['reference_photon_lon'] = [
'delta_time'
]
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'] = {}
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'units'] = "degrees_east"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'contentType'] = "physicalMeasurement"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'long_name'] = "Longitude"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'standard_name'] = "longitude"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'description'] = (
"Longitude of each "
"reference photon. Computed from the ECF Cartesian coordinates of the bounce point."
)
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'valid_min'] = -180.0
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'valid_max'] = 180.0
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon']['coordinates'] = \
"segment_id delta_time reference_photon_lat"
#-- segment ID
IS2_atl03_tide[gtx]['geolocation']['segment_id'] = segment_id
IS2_atl03_fill[gtx]['geolocation']['segment_id'] = None
IS2_atl03_dims[gtx]['geolocation']['segment_id'] = ['delta_time']
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id'] = {}
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id']['units'] = "1"
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id'][
'contentType'] = "referenceInformation"
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id'][
'long_name'] = "Along-track segment ID number"
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id']['description'] = (
"A 7 digit number "
"identifying the along-track geolocation segment number. These are sequential, starting with "
"1 for the first segment after an ascending equatorial crossing node. Equal to the segment_id for "
"the second of the two 20m ATL03 segments included in the 40m ATL03 segment"
)
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id']['coordinates'] = \
"delta_time reference_photon_lat reference_photon_lon"
#-- computed long-period equilibrium tide
IS2_atl03_tide[gtx]['geophys_corr']['tide_equilibrium'] = tide_lpe
IS2_atl03_fill[gtx]['geophys_corr']['tide_equilibrium'] = None
IS2_atl03_dims[gtx]['geophys_corr']['tide_equilibrium'] = [
'delta_time'
]
IS2_atl03_tide_attrs[gtx]['geophys_corr']['tide_equilibrium'] = {}
IS2_atl03_tide_attrs[gtx]['geophys_corr']['tide_equilibrium'][
'units'] = "meters"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['tide_equilibrium'][
'contentType'] = "referenceInformation"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['tide_equilibrium']['long_name'] = \
"Long Period Equilibrium Tide"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['tide_equilibrium'][
'description'] = (
"Long-period "
"equilibrium tidal elevation from the summation of fifteen tidal spectral lines"
)
IS2_atl03_tide_attrs[gtx]['geophys_corr']['tide_equilibrium']['reference'] = \
"https://doi.org/10.1111/j.1365-246X.1973.tb03420.x"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['tide_equilibrium']['coordinates'] = \
("../geolocation/segment_id ../geolocation/delta_time "
"../geolocation/reference_photon_lat ../geolocation/reference_photon_lon")
#-- print file information
logger.info('\t{0}'.format(OUTPUT_FILE))
HDF5_ATL03_tide_write(IS2_atl03_tide,
IS2_atl03_tide_attrs,
CLOBBER=True,
INPUT=os.path.basename(INPUT_FILE),
FILL_VALUE=IS2_atl03_fill,
DIMENSIONS=IS2_atl03_dims,
FILENAME=os.path.join(DIRECTORY, OUTPUT_FILE))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, OUTPUT_FILE), MODE)
def compute_LPET_ICESat2(INPUT_FILE, VERBOSE=False, MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logger = pyTMD.utilities.build_logger('pytmd',level=loglevel)
#-- read data from input file
logger.info('{0} -->'.format(INPUT_FILE))
IS2_atl11_mds,IS2_atl11_attrs,IS2_atl11_pairs = read_HDF5_ATL11(INPUT_FILE,
ATTRIBUTES=True, CROSSOVERS=True)
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 file name
rx = re.compile(r'(processed_)?(ATL\d{2})_(\d{4})(\d{2})_(\d{2})(\d{2})_'
r'(\d{3})_(\d{2})(.*?).h5$')
try:
SUB,PRD,TRK,GRAN,SCYC,ECYC,RL,VERS,AUX = rx.findall(INPUT_FILE).pop()
except:
#-- output long-period equilibrium tide HDF5 file (generic)
fileBasename,fileExtension = os.path.splitext(INPUT_FILE)
OUTPUT_FILE = '{0}_{1}{2}'.format(fileBasename,'LPET',fileExtension)
else:
#-- output long-period equilibrium tide HDF5 file for ASAS/NSIDC granules
args = (PRD,TRK,GRAN,SCYC,ECYC,RL,VERS,AUX)
file_format = '{0}_LPET_{1}{2}_{3}{4}_{5}_{6}{7}.h5'
OUTPUT_FILE = file_format.format(*args)
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl11_mds['ancillary_data']['atlas_sdp_gps_epoch']
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data','merged_deltat.data'])
#-- copy variables for outputting to HDF5 file
IS2_atl11_tide = {}
IS2_atl11_fill = {}
IS2_atl11_dims = {}
IS2_atl11_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl11_tide['ancillary_data'] = {}
IS2_atl11_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl11_tide['ancillary_data'][key] = IS2_atl11_mds['ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl11_tide_attrs['ancillary_data'][key] = {}
for att_name,att_val in IS2_atl11_attrs['ancillary_data'][key].items():
IS2_atl11_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- HDF5 group name for across-track data
XT = 'crossing_track_data'
#-- for each input beam pair within the file
for ptx in sorted(IS2_atl11_pairs):
#-- output data dictionaries for beam
IS2_atl11_tide[ptx] = dict(cycle_stats=collections.OrderedDict(),
crossing_track_data=collections.OrderedDict())
IS2_atl11_fill[ptx] = dict(cycle_stats={},crossing_track_data={})
IS2_atl11_dims[ptx] = dict(cycle_stats={},crossing_track_data={})
IS2_atl11_tide_attrs[ptx] = dict(cycle_stats={},crossing_track_data={})
#-- extract along-track and across-track variables
ref_pt = {}
latitude = {}
longitude = {}
delta_time = {}
#-- along-track (AT) reference point, latitude, longitude and time
ref_pt['AT'] = IS2_atl11_mds[ptx]['ref_pt'].copy()
latitude['AT'] = np.ma.array(IS2_atl11_mds[ptx]['latitude'],
fill_value=IS2_atl11_attrs[ptx]['latitude']['_FillValue'])
longitude['AT'] = np.ma.array(IS2_atl11_mds[ptx]['longitude'],
fill_value=IS2_atl11_attrs[ptx]['longitude']['_FillValue'])
delta_time['AT'] = np.ma.array(IS2_atl11_mds[ptx]['delta_time'],
fill_value=IS2_atl11_attrs[ptx]['delta_time']['_FillValue'])
#-- across-track (XT) reference point, latitude, longitude and time
ref_pt['XT'] = IS2_atl11_mds[ptx][XT]['ref_pt'].copy()
latitude['XT'] = np.ma.array(IS2_atl11_mds[ptx][XT]['latitude'],
fill_value=IS2_atl11_attrs[ptx][XT]['latitude']['_FillValue'])
longitude['XT'] = np.ma.array(IS2_atl11_mds[ptx][XT]['longitude'],
fill_value=IS2_atl11_attrs[ptx][XT]['longitude']['_FillValue'])
delta_time['XT'] = np.ma.array(IS2_atl11_mds[ptx][XT]['delta_time'],
fill_value=IS2_atl11_attrs[ptx][XT]['delta_time']['_FillValue'])
#-- number of average segments and number of included cycles
#-- fill_value for invalid heights and corrections
fv = IS2_atl11_attrs[ptx]['h_corr']['_FillValue']
#-- shape of along-track and across-track data
n_points,n_cycles = delta_time['AT'].shape
n_cross, = delta_time['XT'].shape
#-- allocate for output long-period equilibrium tide variables
tide_lpe = {}
#-- along-track (AT) tides
tide_lpe['AT'] = np.ma.empty((n_points,n_cycles),fill_value=fv)
tide_lpe['AT'].mask = (delta_time['AT'] == delta_time['AT'].fill_value)
#-- across-track (XT) tides
tide_lpe['XT'] = np.ma.empty((n_cross),fill_value=fv)
tide_lpe['XT'].mask = (delta_time['XT'] == delta_time['XT'].fill_value)
#-- calculate tides for along-track and across-track data
for track in ['AT','XT']:
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + delta_time[track]
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(gps_seconds-leap_seconds,
epoch1=(1980,1,6,0,0,0), epoch2=(1992,1,1,0,0,0), scale=1.0/86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = pyTMD.utilities.get_data_path(['data','merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- calculate long-period equilibrium tides for track type
if (track == 'AT'):
#-- calculate LPET for each cycle if along-track
for cycle in range(n_cycles):
#-- find valid time and spatial points for cycle
valid, = np.nonzero(~tide_lpe[track].mask[:,cycle])
#-- predict long-period equilibrium tides at latitudes and time
t = tide_time[valid,cycle] + deltat[valid,cycle]
tide_lpe[track].data[valid,cycle] = compute_equilibrium_tide(t,
latitude[track][valid])
elif (track == 'XT'):
#-- find valid time and spatial points for cycle
valid, = np.nonzero(~tide_lpe[track].mask[:])
#-- predict long-period equilibrium tides at latitudes and time
t = tide_time[valid] + deltat[valid]
tide_lpe[track].data[valid] = compute_equilibrium_tide(t,
latitude[track][valid])
#-- replace masked and nan values with fill value
invalid = np.nonzero(np.isnan(tide_lpe[track].data) | tide_lpe[track].mask)
tide_lpe[track].data[invalid] = tide_lpe[track].fill_value
tide_lpe[track].mask[invalid] = True
#-- group attributes for beam
IS2_atl11_tide_attrs[ptx]['description'] = ('Contains the primary science parameters '
'for this data set')
IS2_atl11_tide_attrs[ptx]['beam_pair'] = IS2_atl11_attrs[ptx]['beam_pair']
IS2_atl11_tide_attrs[ptx]['ReferenceGroundTrack'] = IS2_atl11_attrs[ptx]['ReferenceGroundTrack']
IS2_atl11_tide_attrs[ptx]['first_cycle'] = IS2_atl11_attrs[ptx]['first_cycle']
IS2_atl11_tide_attrs[ptx]['last_cycle'] = IS2_atl11_attrs[ptx]['last_cycle']
IS2_atl11_tide_attrs[ptx]['equatorial_radius'] = IS2_atl11_attrs[ptx]['equatorial_radius']
IS2_atl11_tide_attrs[ptx]['polar_radius'] = IS2_atl11_attrs[ptx]['polar_radius']
#-- geolocation, time and reference point
#-- reference point
IS2_atl11_tide[ptx]['ref_pt'] = ref_pt['AT'].copy()
IS2_atl11_fill[ptx]['ref_pt'] = None
IS2_atl11_dims[ptx]['ref_pt'] = None
IS2_atl11_tide_attrs[ptx]['ref_pt'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx]['ref_pt']['units'] = "1"
IS2_atl11_tide_attrs[ptx]['ref_pt']['contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx]['ref_pt']['long_name'] = "Reference point number"
IS2_atl11_tide_attrs[ptx]['ref_pt']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['ref_pt']['description'] = ("The reference point is the "
"7 digit segment_id number corresponding to the center of the ATL06 data used "
"for each ATL11 point. These are sequential, starting with 1 for the first "
"segment after an ascending equatorial crossing node.")
IS2_atl11_tide_attrs[ptx]['ref_pt']['coordinates'] = \
"delta_time latitude longitude"
#-- cycle_number
IS2_atl11_tide[ptx]['cycle_number'] = IS2_atl11_mds[ptx]['cycle_number'].copy()
IS2_atl11_fill[ptx]['cycle_number'] = None
IS2_atl11_dims[ptx]['cycle_number'] = None
IS2_atl11_tide_attrs[ptx]['cycle_number'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx]['cycle_number']['units'] = "1"
IS2_atl11_tide_attrs[ptx]['cycle_number']['long_name'] = "Orbital cycle number"
IS2_atl11_tide_attrs[ptx]['cycle_number']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['cycle_number']['description'] = ("Number of 91-day periods "
"that have elapsed since ICESat-2 entered the science orbit. Each of the 1,387 "
"reference ground track (RGTs) is targeted in the polar regions once "
"every 91 days.")
#-- delta time
IS2_atl11_tide[ptx]['delta_time'] = delta_time['AT'].copy()
IS2_atl11_fill[ptx]['delta_time'] = delta_time['AT'].fill_value
IS2_atl11_dims[ptx]['delta_time'] = ['ref_pt','cycle_number']
IS2_atl11_tide_attrs[ptx]['delta_time'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx]['delta_time']['units'] = "seconds since 2018-01-01"
IS2_atl11_tide_attrs[ptx]['delta_time']['long_name'] = "Elapsed GPS seconds"
IS2_atl11_tide_attrs[ptx]['delta_time']['standard_name'] = "time"
IS2_atl11_tide_attrs[ptx]['delta_time']['calendar'] = "standard"
IS2_atl11_tide_attrs[ptx]['delta_time']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['delta_time']['description'] = ("Number of GPS "
"seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset "
"is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds "
"between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By "
"adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the "
"time in gps_seconds relative to the GPS epoch can be computed.")
IS2_atl11_tide_attrs[ptx]['delta_time']['coordinates'] = \
"ref_pt cycle_number latitude longitude"
#-- latitude
IS2_atl11_tide[ptx]['latitude'] = latitude['AT'].copy()
IS2_atl11_fill[ptx]['latitude'] = latitude['AT'].fill_value
IS2_atl11_dims[ptx]['latitude'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx]['latitude'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx]['latitude']['units'] = "degrees_north"
IS2_atl11_tide_attrs[ptx]['latitude']['contentType'] = "physicalMeasurement"
IS2_atl11_tide_attrs[ptx]['latitude']['long_name'] = "Latitude"
IS2_atl11_tide_attrs[ptx]['latitude']['standard_name'] = "latitude"
IS2_atl11_tide_attrs[ptx]['latitude']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['latitude']['description'] = ("Center latitude of "
"selected segments")
IS2_atl11_tide_attrs[ptx]['latitude']['valid_min'] = -90.0
IS2_atl11_tide_attrs[ptx]['latitude']['valid_max'] = 90.0
IS2_atl11_tide_attrs[ptx]['latitude']['coordinates'] = \
"ref_pt delta_time longitude"
#-- longitude
IS2_atl11_tide[ptx]['longitude'] = longitude['AT'].copy()
IS2_atl11_fill[ptx]['longitude'] = longitude['AT'].fill_value
IS2_atl11_dims[ptx]['longitude'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx]['longitude'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx]['longitude']['units'] = "degrees_east"
IS2_atl11_tide_attrs[ptx]['longitude']['contentType'] = "physicalMeasurement"
IS2_atl11_tide_attrs[ptx]['longitude']['long_name'] = "Longitude"
IS2_atl11_tide_attrs[ptx]['longitude']['standard_name'] = "longitude"
IS2_atl11_tide_attrs[ptx]['longitude']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['longitude']['description'] = ("Center longitude of "
"selected segments")
IS2_atl11_tide_attrs[ptx]['longitude']['valid_min'] = -180.0
IS2_atl11_tide_attrs[ptx]['longitude']['valid_max'] = 180.0
IS2_atl11_tide_attrs[ptx]['longitude']['coordinates'] = \
"ref_pt delta_time latitude"
#-- cycle statistics variables
IS2_atl11_tide_attrs[ptx]['cycle_stats']['Description'] = ("The cycle_stats subgroup "
"contains summary information about segments for each reference point, including "
"the uncorrected mean heights for reference surfaces, blowing snow and cloud "
"indicators, and geolocation and height misfit statistics.")
IS2_atl11_tide_attrs[ptx]['cycle_stats']['data_rate'] = ("Data within this group "
"are stored at the average segment rate.")
#-- computed long-period equilibrium tide
IS2_atl11_tide[ptx]['cycle_stats']['tide_equilibrium'] = tide_lpe['AT'].copy()
IS2_atl11_fill[ptx]['cycle_stats']['tide_equilibrium'] = tide_lpe['AT'].fill_value
IS2_atl11_dims[ptx]['cycle_stats']['tide_equilibrium'] = ['ref_pt','cycle_number']
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['units'] = "meters"
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['long_name'] = \
"Long Period Equilibrium Tide"
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['description'] = ("Long-period "
"equilibrium tidal elevation from the summation of fifteen tidal spectral lines")
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['reference'] = \
"https://doi.org/10.1111/j.1365-246X.1973.tb03420.x"
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['coordinates'] = \
"../ref_pt ../cycle_number ../delta_time ../latitude ../longitude"
#-- crossing track variables
IS2_atl11_tide_attrs[ptx][XT]['Description'] = ("The crossing_track_data "
"subgroup contains elevation data at crossover locations. These are "
"locations where two ICESat-2 pair tracks cross, so data are available "
"from both the datum track, for which the granule was generated, and "
"from the crossing track.")
IS2_atl11_tide_attrs[ptx][XT]['data_rate'] = ("Data within this group are "
"stored at the average segment rate.")
#-- reference point
IS2_atl11_tide[ptx][XT]['ref_pt'] = ref_pt['XT'].copy()
IS2_atl11_fill[ptx][XT]['ref_pt'] = None
IS2_atl11_dims[ptx][XT]['ref_pt'] = None
IS2_atl11_tide_attrs[ptx][XT]['ref_pt'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx][XT]['ref_pt']['units'] = "1"
IS2_atl11_tide_attrs[ptx][XT]['ref_pt']['contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx][XT]['ref_pt']['long_name'] = ("fit center reference point number, "
"segment_id")
IS2_atl11_tide_attrs[ptx][XT]['ref_pt']['source'] = "derived, ATL11 algorithm"
IS2_atl11_tide_attrs[ptx][XT]['ref_pt']['description'] = ("The reference-point number of the "
"fit center for the datum track. The reference point is the 7 digit segment_id number "
"corresponding to the center of the ATL06 data used for each ATL11 point. These are "
"sequential, starting with 1 for the first segment after an ascending equatorial "
"crossing node.")
IS2_atl11_tide_attrs[ptx][XT]['ref_pt']['coordinates'] = \
"delta_time latitude longitude"
#-- reference ground track of the crossing track
IS2_atl11_tide[ptx][XT]['rgt'] = IS2_atl11_mds[ptx][XT]['rgt'].copy()
IS2_atl11_fill[ptx][XT]['rgt'] = IS2_atl11_attrs[ptx][XT]['rgt']['_FillValue']
IS2_atl11_dims[ptx][XT]['rgt'] = None
IS2_atl11_tide_attrs[ptx][XT]['rgt'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx][XT]['rgt']['units'] = "1"
IS2_atl11_tide_attrs[ptx][XT]['rgt']['contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx][XT]['rgt']['long_name'] = "crossover reference ground track"
IS2_atl11_tide_attrs[ptx][XT]['rgt']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx][XT]['rgt']['description'] = "The RGT number for the crossing data."
IS2_atl11_tide_attrs[ptx][XT]['rgt']['coordinates'] = \
"ref_pt delta_time latitude longitude"
#-- cycle_number of the crossing track
IS2_atl11_tide[ptx][XT]['cycle_number'] = IS2_atl11_mds[ptx][XT]['cycle_number'].copy()
IS2_atl11_fill[ptx][XT]['cycle_number'] = IS2_atl11_attrs[ptx][XT]['cycle_number']['_FillValue']
IS2_atl11_dims[ptx][XT]['cycle_number'] = None
IS2_atl11_tide_attrs[ptx][XT]['cycle_number'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx][XT]['cycle_number']['units'] = "1"
IS2_atl11_tide_attrs[ptx][XT]['cycle_number']['long_name'] = "crossover cycle number"
IS2_atl11_tide_attrs[ptx][XT]['cycle_number']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx][XT]['cycle_number']['description'] = ("Cycle number for the "
"crossing data. Number of 91-day periods that have elapsed since ICESat-2 entered "
"the science orbit. Each of the 1,387 reference ground track (RGTs) is targeted "
"in the polar regions once every 91 days.")
#-- delta time of the crossing track
IS2_atl11_tide[ptx][XT]['delta_time'] = delta_time['XT'].copy()
IS2_atl11_fill[ptx][XT]['delta_time'] = delta_time['XT'].fill_value
IS2_atl11_dims[ptx][XT]['delta_time'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx][XT]['delta_time'] = {}
IS2_atl11_tide_attrs[ptx][XT]['delta_time']['units'] = "seconds since 2018-01-01"
IS2_atl11_tide_attrs[ptx][XT]['delta_time']['long_name'] = "Elapsed GPS seconds"
IS2_atl11_tide_attrs[ptx][XT]['delta_time']['standard_name'] = "time"
IS2_atl11_tide_attrs[ptx][XT]['delta_time']['calendar'] = "standard"
IS2_atl11_tide_attrs[ptx][XT]['delta_time']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx][XT]['delta_time']['description'] = ("Number of GPS "
"seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset "
"is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds "
"between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By "
"adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the "
"time in gps_seconds relative to the GPS epoch can be computed.")
IS2_atl11_tide_attrs[ptx]['delta_time']['coordinates'] = \
"ref_pt latitude longitude"
#-- latitude of the crossover measurement
IS2_atl11_tide[ptx][XT]['latitude'] = latitude['XT'].copy()
IS2_atl11_fill[ptx][XT]['latitude'] = latitude['XT'].fill_value
IS2_atl11_dims[ptx][XT]['latitude'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx][XT]['latitude'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx][XT]['latitude']['units'] = "degrees_north"
IS2_atl11_tide_attrs[ptx][XT]['latitude']['contentType'] = "physicalMeasurement"
IS2_atl11_tide_attrs[ptx][XT]['latitude']['long_name'] = "crossover latitude"
IS2_atl11_tide_attrs[ptx][XT]['latitude']['standard_name'] = "latitude"
IS2_atl11_tide_attrs[ptx][XT]['latitude']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx][XT]['latitude']['description'] = ("Center latitude of "
"selected segments")
IS2_atl11_tide_attrs[ptx][XT]['latitude']['valid_min'] = -90.0
IS2_atl11_tide_attrs[ptx][XT]['latitude']['valid_max'] = 90.0
IS2_atl11_tide_attrs[ptx][XT]['latitude']['coordinates'] = \
"ref_pt delta_time longitude"
#-- longitude of the crossover measurement
IS2_atl11_tide[ptx][XT]['longitude'] = longitude['XT'].copy()
IS2_atl11_fill[ptx][XT]['longitude'] = longitude['XT'].fill_value
IS2_atl11_dims[ptx][XT]['longitude'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx][XT]['longitude'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx][XT]['longitude']['units'] = "degrees_east"
IS2_atl11_tide_attrs[ptx][XT]['longitude']['contentType'] = "physicalMeasurement"
IS2_atl11_tide_attrs[ptx][XT]['longitude']['long_name'] = "crossover longitude"
IS2_atl11_tide_attrs[ptx][XT]['longitude']['standard_name'] = "longitude"
IS2_atl11_tide_attrs[ptx][XT]['longitude']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx][XT]['longitude']['description'] = ("Center longitude of "
"selected segments")
IS2_atl11_tide_attrs[ptx][XT]['longitude']['valid_min'] = -180.0
IS2_atl11_tide_attrs[ptx][XT]['longitude']['valid_max'] = 180.0
IS2_atl11_tide_attrs[ptx][XT]['longitude']['coordinates'] = \
"ref_pt delta_time latitude"
#-- computed long-period equilibrium tide for the crossover measurement
IS2_atl11_tide[ptx][XT]['tide_equilibrium'] = tide_lpe['XT'].copy()
IS2_atl11_fill[ptx][XT]['tide_equilibrium'] = tide_lpe['XT'].fill_value
IS2_atl11_dims[ptx][XT]['tide_equilibrium'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx][XT]['tide_equilibrium'] = collections.OrderedDict()
IS2_atl11_tide_attrs[ptx][XT]['tide_equilibrium']['units'] = "meters"
IS2_atl11_tide_attrs[ptx][XT]['tide_equilibrium']['contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx][XT]['tide_equilibrium']['long_name'] = \
"Long Period Equilibrium Tide"
IS2_atl11_tide_attrs[ptx][XT]['tide_equilibrium']['description'] = ("Long-period "
"equilibrium tidal elevation from the summation of fifteen tidal spectral lines")
IS2_atl11_tide_attrs[ptx][XT]['tide_equilibrium']['reference'] = \
"https://doi.org/10.1111/j.1365-246X.1973.tb03420.x"
IS2_atl11_tide_attrs[ptx][XT]['tide_equilibrium']['coordinates'] = \
"ref_pt delta_time latitude longitude"
#-- print file information
logger.info('\t{0}'.format(OUTPUT_FILE))
HDF5_ATL11_tide_write(IS2_atl11_tide, IS2_atl11_tide_attrs,
CLOBBER=True, INPUT=os.path.basename(INPUT_FILE),
FILL_VALUE=IS2_atl11_fill, DIMENSIONS=IS2_atl11_dims,
FILENAME=os.path.join(DIRECTORY,OUTPUT_FILE))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY,OUTPUT_FILE), MODE)
def compute_tide_corrections(x,
y,
delta_time,
DIRECTORY=None,
MODEL=None,
ATLAS_FORMAT='netcdf',
GZIP=False,
DEFINITION_FILE=None,
EPSG=3031,
EPOCH=(2000, 1, 1, 0, 0, 0),
TYPE='drift',
TIME='UTC',
METHOD='spline',
EXTRAPOLATE=False,
CUTOFF=10.0,
FILL_VALUE=np.nan):
"""
Compute tides at points and times using tidal harmonics
Parameters
----------
x: float
x-coordinates in projection EPSG
y: float
y-coordinates in projection EPSG
delta_time: float
seconds since EPOCH or datetime array
DIRECTORY: str or NoneType, default None
working data directory for tide models
MODEL: str or NoneType, default None
Tide model to use in correction
ATLAS_FORMAT: str, default 'netcdf'
ATLAS tide model format (OTIS, netcdf)
ATLAS tide model format
- ``'OTIS'``
- ``'netcdf'``
GZIP: bool, default False
Tide model files are gzip compressed
DEFINITION_FILE: str or NoneType, default None
Tide model definition file for use
EPSG: int, default: 3031 (Polar Stereographic South, WGS84)
Input coordinate system
EPOCH: tuple, default (2000,1,1,0,0,0)
Time period for calculating delta times
TYPE: str or NoneType, default 'drift'
Input data type
- ``None``: determined from input variable dimensions
- ``'drift'``: drift buoys or satellite/airborne altimetry
- ``'grid'``: spatial grids or images
- ``'time series'``: time series at a single point
TIME: str, default 'UTC'
Time type if need to compute leap seconds to convert to UTC
- ``'GPS'``: leap seconds needed
- ``'LORAN'``: leap seconds needed (LORAN = GPS + 9 seconds)
- ``'TAI'``: leap seconds needed (TAI = GPS + 19 seconds)
- ``'UTC'``: no leap seconds needed
- ``'datetime'``: numpy datatime array in UTC
METHOD: str
Interpolation method
- ```bilinear```: quick bilinear interpolation
- ```spline```: scipy bivariate spline interpolation
- ```linear```, ```nearest```: scipy regular grid interpolations
EXTRAPOLATE: bool, default False
Extrapolate with nearest-neighbors
CUTOFF: float, default 10.0
Extrapolation cutoff in kilometers
Set to np.inf to extrapolate for all points
FILL_VALUE: float, default np.nan
Output invalid value
Returns
-------
tide: float
tidal elevation at coordinates and time in meters
"""
#-- check that tide directory is accessible
try:
os.access(DIRECTORY, os.F_OK)
except:
raise FileNotFoundError("Invalid tide directory")
#-- get parameters for tide model
if DEFINITION_FILE is not None:
model = pyTMD.model(DIRECTORY).from_file(DEFINITION_FILE)
else:
model = pyTMD.model(DIRECTORY, format=ATLAS_FORMAT,
compressed=GZIP).elevation(MODEL)
#-- determine input data type based on variable dimensions
if not TYPE:
TYPE = pyTMD.spatial.data_type(x, y, delta_time)
#-- reform coordinate dimensions for input grids
#-- or verify coordinate dimension shapes
if (TYPE.lower() == 'grid') and (np.size(x) != np.size(y)):
x, y = np.meshgrid(np.copy(x), np.copy(y))
elif (TYPE.lower() == 'grid'):
x = np.atleast_2d(x)
y = np.atleast_2d(y)
elif TYPE.lower() in ('time series', 'drift'):
x = np.atleast_1d(x)
y = np.atleast_1d(y)
#-- converting x,y from EPSG to latitude/longitude
try:
#-- EPSG projection code string or int
crs1 = pyproj.CRS.from_string("epsg:{0:d}".format(int(EPSG)))
except (ValueError, pyproj.exceptions.CRSError):
#-- Projection SRS string
crs1 = pyproj.CRS.from_string(EPSG)
crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(4326))
transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True)
lon, lat = transformer.transform(x.flatten(), y.flatten())
#-- assert delta time is an array
delta_time = np.atleast_1d(delta_time)
#-- calculate leap seconds if specified
if (TIME.upper() == 'GPS'):
GPS_Epoch_Time = pyTMD.time.convert_delta_time(0,
epoch1=EPOCH,
epoch2=(1980, 1, 6, 0,
0, 0),
scale=1.0)
GPS_Time = pyTMD.time.convert_delta_time(delta_time,
epoch1=EPOCH,
epoch2=(1980, 1, 6, 0, 0, 0),
scale=1.0)
#-- calculate difference in leap seconds from start of epoch
leap_seconds = pyTMD.time.count_leap_seconds(GPS_Time) - \
pyTMD.time.count_leap_seconds(np.atleast_1d(GPS_Epoch_Time))
elif (TIME.upper() == 'LORAN'):
#-- LORAN time is ahead of GPS time by 9 seconds
GPS_Epoch_Time = pyTMD.time.convert_delta_time(-9.0,
epoch1=EPOCH,
epoch2=(1980, 1, 6, 0,
0, 0),
scale=1.0)
GPS_Time = pyTMD.time.convert_delta_time(delta_time - 9.0,
epoch1=EPOCH,
epoch2=(1980, 1, 6, 0, 0, 0),
scale=1.0)
#-- calculate difference in leap seconds from start of epoch
leap_seconds = pyTMD.time.count_leap_seconds(GPS_Time) - \
pyTMD.time.count_leap_seconds(np.atleast_1d(GPS_Epoch_Time))
elif (TIME.upper() == 'TAI'):
#-- TAI time is ahead of GPS time by 19 seconds
GPS_Epoch_Time = pyTMD.time.convert_delta_time(-19.0,
epoch1=EPOCH,
epoch2=(1980, 1, 6, 0,
0, 0),
scale=1.0)
GPS_Time = pyTMD.time.convert_delta_time(delta_time - 19.0,
epoch1=EPOCH,
epoch2=(1980, 1, 6, 0, 0, 0),
scale=1.0)
#-- calculate difference in leap seconds from start of epoch
leap_seconds = pyTMD.time.count_leap_seconds(GPS_Time) - \
pyTMD.time.count_leap_seconds(np.atleast_1d(GPS_Epoch_Time))
else:
leap_seconds = 0.0
#-- convert delta times or datetimes objects
if (TIME.lower() == 'datetime'):
#-- convert delta time array from datetime object
#-- to days relative to 1992-01-01T00:00:00
t = pyTMD.time.convert_datetime(delta_time,
epoch=(1992, 1, 1, 0, 0, 0)) / 86400.0
else:
#-- convert time to days relative to Jan 1, 1992 (48622mjd)
t = pyTMD.time.convert_delta_time(delta_time - leap_seconds,
epoch1=EPOCH,
epoch2=(1992, 1, 1, 0, 0, 0),
scale=(1.0 / 86400.0))
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data', 'merged_deltat.data'])
#-- read tidal constants and interpolate to grid points
if model.format in ('OTIS', 'ATLAS'):
amp, ph, D, c = extract_tidal_constants(lon,
lat,
model.grid_file,
model.model_file,
model.projection,
TYPE=model.type,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
GRID=model.format)
deltat = np.zeros_like(t)
elif (model.format == 'netcdf'):
amp, ph, D, c = extract_netcdf_constants(lon,
lat,
model.grid_file,
model.model_file,
TYPE=model.type,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=model.scale,
GZIP=model.compressed)
deltat = np.zeros_like(t)
elif (model.format == 'GOT'):
amp, ph, c = extract_GOT_constants(lon,
lat,
model.model_file,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=model.scale,
GZIP=model.compressed)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, t)
elif (model.format == 'FES'):
amp, ph = extract_FES_constants(lon,
lat,
model.model_file,
TYPE=model.type,
VERSION=model.version,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=model.scale,
GZIP=model.compressed)
#-- available model constituents
c = model.constituents
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, t)
#-- calculate complex phase in radians for Euler's
cph = -1j * ph * np.pi / 180.0
#-- calculate constituent oscillation
hc = amp * np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
if (TYPE.lower() == 'grid'):
ny, nx = np.shape(x)
nt = len(t)
tide = np.ma.zeros((ny, nx, nt), fill_value=FILL_VALUE)
tide.mask = np.zeros((ny, nx, nt), dtype=bool)
for i in range(nt):
TIDE = predict_tide(t[i],
hc,
c,
DELTAT=deltat[i],
CORRECTIONS=model.format)
MINOR = infer_minor_corrections(t[i],
hc,
c,
DELTAT=deltat[i],
CORRECTIONS=model.format)
#-- add major and minor components and reform grid
tide[:, :, i] = np.reshape((TIDE + MINOR), (ny, nx))
tide.mask[:, :, i] = np.reshape((TIDE.mask | MINOR.mask), (ny, nx))
elif (TYPE.lower() == 'drift'):
npts = len(t)
tide = np.ma.zeros((npts), fill_value=FILL_VALUE)
tide.mask = np.any(hc.mask, axis=1)
tide.data[:] = predict_tide_drift(t,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model.format)
minor = infer_minor_corrections(t,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model.format)
tide.data[:] += minor.data[:]
elif (TYPE.lower() == 'time series'):
npts = len(t)
tide = np.ma.zeros((npts), fill_value=FILL_VALUE)
tide.mask = np.any(hc.mask, axis=1)
tide.data[:] = predict_tidal_ts(t,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model.format)
minor = infer_minor_corrections(t,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model.format)
tide.data[:] += minor.data[:]
#-- replace invalid values with fill value
tide.data[tide.mask] = tide.fill_value
#-- return the tide correction
return tide
def compute_LPET_ICESat2(INPUT_FILE, VERBOSE=False, MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logger = pyTMD.utilities.build_logger('pytmd', level=loglevel)
#-- read data from input file
logger.info('{0} -->'.format(INPUT_FILE))
IS2_atl10_mds, IS2_atl10_attrs, IS2_atl10_beams = read_HDF5_ATL10(
INPUT_FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 sea ice file name
rx = re.compile(
r'(processed_)?(ATL\d{2})-(\d{2})_(\d{4})(\d{2})(\d{2})'
r'(\d{2})(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$'
)
try:
SUB, PRD, HEM, YY, MM, DD, HH, MN, SS, TRK, CYCL, SN, RL, VERS, AUX = rx.findall(
INPUT_FILE).pop()
except:
#-- output long-period equilibrium tide HDF5 file (generic)
fileBasename, fileExtension = os.path.splitext(INPUT_FILE)
OUTPUT_FILE = '{0}_{1}{2}'.format(fileBasename, 'LPET', fileExtension)
else:
#-- output long-period equilibrium tide HDF5 file for ASAS/NSIDC granules
args = (PRD, HEM, YY, MM, DD, HH, MN, SS, TRK, CYCL, SN, RL, VERS, AUX)
file_format = '{0}-{1}_LPET_{2}{3}{4}{5}{6}{7}_{8}{9}{10}_{11}_{12}{13}.h5'
OUTPUT_FILE = file_format.format(*args)
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl10_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- copy variables for outputting to HDF5 file
IS2_atl10_tide = {}
IS2_atl10_fill = {}
IS2_atl10_dims = {}
IS2_atl10_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl10_tide['ancillary_data'] = {}
IS2_atl10_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl10_tide['ancillary_data'][key] = IS2_atl10_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl10_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl10_attrs['ancillary_data'][key].items(
):
IS2_atl10_tide_attrs['ancillary_data'][key][att_name] = att_val
for gtx in sorted(IS2_atl10_beams):
#-- output data dictionaries for beam
IS2_atl10_tide[gtx] = dict(freeboard_beam_segment={}, leads={})
IS2_atl10_fill[gtx] = dict(freeboard_beam_segment={}, leads={})
IS2_atl10_dims[gtx] = dict(freeboard_beam_segment={}, leads={})
IS2_atl10_tide_attrs[gtx] = dict(freeboard_beam_segment={}, leads={})
#-- group attributes for beam
IS2_atl10_tide_attrs[gtx]['Description'] = IS2_atl10_attrs[gtx][
'Description']
IS2_atl10_tide_attrs[gtx]['atlas_pce'] = IS2_atl10_attrs[gtx][
'atlas_pce']
IS2_atl10_tide_attrs[gtx]['atlas_beam_type'] = IS2_atl10_attrs[gtx][
'atlas_beam_type']
IS2_atl10_tide_attrs[gtx]['groundtrack_id'] = IS2_atl10_attrs[gtx][
'groundtrack_id']
IS2_atl10_tide_attrs[gtx]['atmosphere_profile'] = IS2_atl10_attrs[gtx][
'atmosphere_profile']
IS2_atl10_tide_attrs[gtx]['atlas_spot_number'] = IS2_atl10_attrs[gtx][
'atlas_spot_number']
IS2_atl10_tide_attrs[gtx]['sc_orientation'] = IS2_atl10_attrs[gtx][
'sc_orientation']
#-- group attributes for freeboard_beam_segment
IS2_atl10_tide_attrs[gtx]['freeboard_beam_segment']['Description'] = (
"Contains freeboard "
"estimate and associated height segment parameters for only the sea ice segments by beam."
)
IS2_atl10_tide_attrs[gtx]['freeboard_beam_segment']['data_rate'] = (
"Data within this "
"group are stored at the freeboard swath segment rate.")
#-- group attributes for leads
IS2_atl10_tide_attrs[gtx]['leads']['Description'] = (
"Contains parameters relating "
"to the freeboard values.")
IS2_atl10_tide_attrs[gtx]['leads']['data_rate'] = (
"Data within this "
"group are stored at the lead index rate.")
#-- for each ATL10 group
for group in ['freeboard_beam_segment', 'leads']:
#-- number of segments
val = IS2_atl10_mds[gtx][group]
n_seg = len(val['delta_time'])
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + val['delta_time']
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(
gps_seconds - leap_seconds,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = pyTMD.utilities.get_data_path(
['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- predict long-period equilibrium tides at latitudes and time
tide_lpe = compute_equilibrium_tide(tide_time + deltat,
val['latitude'])
#-- delta time
IS2_atl10_tide[gtx][group]['delta_time'] = val['delta_time'].copy()
IS2_atl10_fill[gtx][group]['delta_time'] = None
IS2_atl10_dims[gtx][group]['delta_time'] = None
IS2_atl10_tide_attrs[gtx][group]['delta_time'] = {}
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'standard_name'] = "time"
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'source'] = "telemetry"
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'calendar'] = "standard"
IS2_atl10_tide_attrs[gtx][group]['delta_time']['description'] = (
"Number of "
"GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch "
"offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS "
"seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP "
"epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time "
"parameters, the time in gps_seconds relative to the GPS epoch can be computed."
)
IS2_atl10_tide_attrs[gtx][group]['delta_time']['coordinates'] = \
"latitude longitude"
#-- latitude
IS2_atl10_tide[gtx][group]['latitude'] = val['latitude'].copy()
IS2_atl10_fill[gtx][group]['latitude'] = None
IS2_atl10_dims[gtx][group]['latitude'] = ['delta_time']
IS2_atl10_tide_attrs[gtx][group]['latitude'] = {}
IS2_atl10_tide_attrs[gtx][group]['latitude'][
'units'] = "degrees_north"
IS2_atl10_tide_attrs[gtx][group]['latitude'][
'contentType'] = "physicalMeasurement"
IS2_atl10_tide_attrs[gtx][group]['latitude'][
'long_name'] = "Latitude"
IS2_atl10_tide_attrs[gtx][group]['latitude'][
'standard_name'] = "latitude"
IS2_atl10_tide_attrs[gtx][group]['latitude']['description'] = (
"Latitude of "
"segment center")
IS2_atl10_tide_attrs[gtx][group]['latitude']['valid_min'] = -90.0
IS2_atl10_tide_attrs[gtx][group]['latitude']['valid_max'] = 90.0
IS2_atl10_tide_attrs[gtx][group]['latitude']['coordinates'] = \
"delta_time longitude"
#-- longitude
IS2_atl10_tide[gtx][group]['longitude'] = val['longitude'].copy()
IS2_atl10_fill[gtx][group]['longitude'] = None
IS2_atl10_dims[gtx][group]['longitude'] = ['delta_time']
IS2_atl10_tide_attrs[gtx][group]['longitude'] = {}
IS2_atl10_tide_attrs[gtx][group]['longitude'][
'units'] = "degrees_east"
IS2_atl10_tide_attrs[gtx][group]['longitude'][
'contentType'] = "physicalMeasurement"
IS2_atl10_tide_attrs[gtx][group]['longitude'][
'long_name'] = "Longitude"
IS2_atl10_tide_attrs[gtx][group]['longitude'][
'standard_name'] = "longitude"
IS2_atl10_tide_attrs[gtx][group]['longitude']['description'] = (
"Longitude of "
"segment center")
IS2_atl10_tide_attrs[gtx][group]['longitude']['valid_min'] = -180.0
IS2_atl10_tide_attrs[gtx][group]['longitude']['valid_max'] = 180.0
IS2_atl10_tide_attrs[gtx][group]['longitude']['coordinates'] = \
"delta_time latitude"
#-- geophysical variables
IS2_atl10_tide[gtx][group]['geophysical'] = {}
IS2_atl10_fill[gtx][group]['geophysical'] = {}
IS2_atl10_dims[gtx][group]['geophysical'] = {}
IS2_atl10_tide_attrs[gtx][group]['geophysical'] = {}
IS2_atl10_tide_attrs[gtx][group]['geophysical']['Description'] = (
"Contains geophysical "
"parameters and corrections used to correct photon heights for geophysical "
"effects, such as tides.")
IS2_atl10_tide_attrs[gtx][group]['geophysical']['data_rate'] = (
"Data within this group "
"are stored at the variable segment rate.")
#-- computed long-period equilibrium tide
IS2_atl10_tide[gtx][group]['geophysical'][
'height_segment_lpe'] = tide_lpe
IS2_atl10_fill[gtx][group]['geophysical'][
'height_segment_lpe'] = None
IS2_atl10_dims[gtx][group]['geophysical']['height_segment_lpe'] = [
'delta_time'
]
IS2_atl10_tide_attrs[gtx][group]['geophysical'][
'height_segment_lpe'] = {}
IS2_atl10_tide_attrs[gtx][group]['geophysical'][
'height_segment_lpe']['units'] = "meters"
IS2_atl10_tide_attrs[gtx][group]['geophysical']['height_segment_lpe']['contentType'] = \
"referenceInformation"
IS2_atl10_tide_attrs[gtx][group]['geophysical']['height_segment_lpe']['long_name'] = \
"Long Period Equilibrium Tide"
IS2_atl10_tide_attrs[gtx][group]['geophysical'][
'height_segment_lpe']['description'] = (
"Long-period "
"equilibrium tidal elevation from the summation of fifteen tidal spectral lines"
)
IS2_atl10_tide_attrs[gtx][group]['geophysical']['height_segment_lpe']['reference'] = \
"https://doi.org/10.1111/j.1365-246X.1973.tb03420.x"
IS2_atl10_tide_attrs[gtx][group]['geophysical']['height_segment_lpe']['coordinates'] = \
"../delta_time ../latitude ../longitude"
#-- print file information
logger.info('\t{0}'.format(OUTPUT_FILE))
HDF5_ATL10_tide_write(IS2_atl10_tide,
IS2_atl10_tide_attrs,
CLOBBER=True,
INPUT=os.path.basename(INPUT_FILE),
FILL_VALUE=IS2_atl10_fill,
DIMENSIONS=IS2_atl10_dims,
FILENAME=os.path.join(DIRECTORY, OUTPUT_FILE))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, OUTPUT_FILE), MODE)
def compute_LPET_elevations(input_file, output_file,
FORMAT='csv', VARIABLES=['time','lat','lon','data'], HEADER=0, TYPE='drift',
TIME_UNITS='days since 1858-11-17T00:00:00', TIME=None, PROJECTION='4326',
VERBOSE=False, MODE=0o775):
#-- output netCDF4 and HDF5 file attributes
#-- will be added to YAML header in csv files
attrib = {}
#-- latitude
attrib['lat'] = {}
attrib['lat']['long_name'] = 'Latitude'
attrib['lat']['units'] = 'Degrees_North'
#-- longitude
attrib['lon'] = {}
attrib['lon']['long_name'] = 'Longitude'
attrib['lon']['units'] = 'Degrees_East'
#-- long-period equilibrium tides
attrib['tide_lpe'] = {}
attrib['tide_lpe']['long_name'] = 'Equilibrium_Tide'
attrib['tide_lpe']['description'] = ('Long-period_equilibrium_tidal_'
'elevation_from_the_summation_of_fifteen_tidal_spectral_lines')
attrib['tide_lpe']['reference'] = ('https://doi.org/10.1111/'
'j.1365-246X.1973.tb03420.x')
attrib['tide_lpe']['units'] = 'meters'
#-- time
attrib['time'] = {}
attrib['time']['long_name'] = 'Time'
attrib['time']['units'] = 'days since 1992-01-01T00:00:00'
attrib['time']['calendar'] = 'standard'
#-- read input file to extract time, spatial coordinates and data
if (FORMAT == 'csv'):
dinput = pyTMD.spatial.from_ascii(input_file, columns=VARIABLES,
header=HEADER, verbose=VERBOSE)
elif (FORMAT == 'netCDF4'):
dinput = pyTMD.spatial.from_netCDF4(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3],
verbose=VERBOSE)
elif (FORMAT == 'HDF5'):
dinput = pyTMD.spatial.from_HDF5(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3],
verbose=VERBOSE)
elif (FORMAT == 'geotiff'):
dinput = pyTMD.spatial.from_geotiff(input_file, verbose=VERBOSE)
#-- copy global geotiff attributes for projection and grid parameters
for att_name in ['projection','wkt','spacing','extent']:
attrib[att_name] = dinput['attributes'][att_name]
#-- update time variable if entered as argument
if TIME is not None:
dinput['time'] = np.copy(TIME)
#-- converting x,y from projection to latitude/longitude
#-- could try to extract projection attributes from netCDF4 and HDF5 files
try:
crs1 = pyproj.CRS.from_string("epsg:{0:d}".format(int(PROJECTION)))
except (ValueError,pyproj.exceptions.CRSError):
crs1 = pyproj.CRS.from_string(PROJECTION)
crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(4326))
transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True)
if (TYPE == 'grid'):
ny,nx = (len(dinput['y']),len(dinput['x']))
gridx,gridy = np.meshgrid(dinput['x'],dinput['y'])
lon,lat = transformer.transform(gridx.flatten(),gridy.flatten())
elif (TYPE == 'drift'):
lon,lat = transformer.transform(dinput['x'].flatten(),
dinput['y'].flatten())
#-- extract time units from netCDF4 and HDF5 attributes or from TIME_UNITS
try:
time_string = dinput['attributes']['time']['units']
except (TypeError, KeyError):
epoch1,to_secs = pyTMD.time.parse_date_string(TIME_UNITS)
else:
epoch1,to_secs = pyTMD.time.parse_date_string(time_string)
#-- convert time from units to days since 1992-01-01T00:00:00
tide_time = pyTMD.time.convert_delta_time(to_secs*dinput['time'].flatten(),
epoch1=epoch1, epoch2=(1992,1,1,0,0,0), scale=1.0/86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data','merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- number of time points
nt = len(tide_time)
#-- predict long-period equilibrium tides at time
if (TYPE == 'grid'):
tide_lpe = np.zeros((ny,nx,nt))
for i in range(nt):
lpet = compute_equilibrium_tide(tide_time[i] + deltat[i], lat)
tide_lpe[:,:,i] = np.reshape(lpet,(ny,nx))
elif (TYPE == 'drift'):
tide_lpe = compute_equilibrium_tide(tide_time + deltat, lat)
#-- output to file
output = dict(time=tide_time,lon=lon,lat=lat,tide_lpe=tide_lpe)
if (FORMAT == 'csv'):
pyTMD.spatial.to_ascii(output, attrib, output_file, delimiter=',',
columns=['time','lat','lon','tide_lpe'], verbose=VERBOSE)
elif (FORMAT == 'netCDF4'):
pyTMD.spatial.to_netCDF4(output, attrib, output_file, verbose=VERBOSE)
elif (FORMAT == 'HDF5'):
pyTMD.spatial.to_HDF5(output, attrib, output_file, verbose=VERBOSE)
elif (FORMAT == 'geotiff'):
pyTMD.spatial.to_geotiff(output, attrib, output_file, verbose=VERBOSE,
varname='tide_lpe')
#-- change the permissions level to MODE
os.chmod(output_file, MODE)
def compute_tidal_currents(tide_dir, input_file, output_file,
TIDE_MODEL=None, FORMAT='csv', VARIABLES=['time','lat','lon','data'],
HEADER=0, TYPE='drift', TIME_UNITS='days since 1858-11-17T00:00:00',
TIME=None, PROJECTION='4326', METHOD='spline', EXTRAPOLATE=False,
VERBOSE=False, MODE=0o775):
#-- select between tide models
if (TIDE_MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir,'cats0201_tmd','grid_CATS')
model_file = os.path.join(tide_dir,'cats0201_tmd','UV0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
model_format = 'OTIS'
EPSG = '4326'
TYPES = ['u','v']
elif (TIDE_MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir,'CATS2008','grid_CATS2008')
model_file = os.path.join(tide_dir,'CATS2008','uv.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPES = ['u','v']
elif (TIDE_MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas')
grid_file = 'grid_tpxo9_atlas.nc.gz'
model_files = {}
model_files['u'] = ['u_q1_tpxo9_atlas_30.nc.gz','u_o1_tpxo9_atlas_30.nc.gz',
'u_p1_tpxo9_atlas_30.nc.gz','u_k1_tpxo9_atlas_30.nc.gz',
'u_n2_tpxo9_atlas_30.nc.gz','u_m2_tpxo9_atlas_30.nc.gz',
'u_s2_tpxo9_atlas_30.nc.gz','u_k2_tpxo9_atlas_30.nc.gz',
'u_m4_tpxo9_atlas_30.nc.gz','u_ms4_tpxo9_atlas_30.nc.gz',
'u_mn4_tpxo9_atlas_30.nc.gz','u_2n2_tpxo9_atlas_30.nc.gz']
model_files['v'] = ['v_q1_tpxo9_atlas_30.nc.gz','v_o1_tpxo9_atlas_30.nc.gz',
'v_p1_tpxo9_atlas_30.nc.gz','v_k1_tpxo9_atlas_30.nc.gz',
'v_n2_tpxo9_atlas_30.nc.gz','v_m2_tpxo9_atlas_30.nc.gz',
'v_s2_tpxo9_atlas_30.nc.gz','v_k2_tpxo9_atlas_30.nc.gz',
'v_m4_tpxo9_atlas_30.nc.gz','v_ms4_tpxo9_atlas_30.nc.gz',
'v_mn4_tpxo9_atlas_30.nc.gz','v_2n2_tpxo9_atlas_30.nc.gz']
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
model_format = 'netcdf'
TYPES = ['u','v']
model_scale = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v2'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v2')
grid_file = 'grid_tpxo9_atlas_30_v2.nc.gz'
model_files = {}
model_files['u'] = ['u_q1_tpxo9_atlas_30_v2.nc.gz','u_o1_tpxo9_atlas_30_v2.nc.gz',
'u_p1_tpxo9_atlas_30_v2.nc.gz','u_k1_tpxo9_atlas_30_v2.nc.gz',
'u_n2_tpxo9_atlas_30_v2.nc.gz','u_m2_tpxo9_atlas_30_v2.nc.gz',
'u_s2_tpxo9_atlas_30_v2.nc.gz','u_k2_tpxo9_atlas_30_v2.nc.gz',
'u_m4_tpxo9_atlas_30_v2.nc.gz','u_ms4_tpxo9_atlas_30_v2.nc.gz',
'u_mn4_tpxo9_atlas_30_v2.nc.gz','u_2n2_tpxo9_atlas_30_v2.nc.gz']
model_files['v'] = ['v_q1_tpxo9_atlas_30_v2.nc.gz','v_o1_tpxo9_atlas_30_v2.nc.gz',
'v_p1_tpxo9_atlas_30_v2.nc.gz','v_k1_tpxo9_atlas_30_v2.nc.gz',
'v_n2_tpxo9_atlas_30_v2.nc.gz','v_m2_tpxo9_atlas_30_v2.nc.gz',
'v_s2_tpxo9_atlas_30_v2.nc.gz','v_k2_tpxo9_atlas_30_v2.nc.gz',
'v_m4_tpxo9_atlas_30_v2.nc.gz','v_ms4_tpxo9_atlas_30_v2.nc.gz',
'v_mn4_tpxo9_atlas_30_v2.nc.gz','v_2n2_tpxo9_atlas_30_v2.nc.gz']
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
model_format = 'netcdf'
TYPES = ['u','v']
model_scale = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir,'TPXO9.1','DATA','grid_tpxo9')
model_file = os.path.join(tide_dir,'TPXO9.1','DATA','u_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
model_format = 'OTIS'
EPSG = '4326'
TYPES = ['u','v']
elif (TIDE_MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir,'tpxo8_atlas','grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir,'tpxo8_atlas','uv.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
model_format = 'ATLAS'
EPSG = '4326'
TYPES = ['u','v']
elif (TIDE_MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir,'TPXO7.2_tmd','grid_tpxo7.2')
model_file = os.path.join(tide_dir,'TPXO7.2_tmd','u_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
model_format = 'OTIS'
EPSG = '4326'
TYPES = ['u','v']
elif (TIDE_MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir,'aodtm5_tmd','grid_Arc5km')
model_file = os.path.join(tide_dir,'aodtm5_tmd','UV0_Arc5km')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPES = ['u','v']
elif (TIDE_MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir,'aotim5_tmd','grid_Arc5km')
model_file = os.path.join(tide_dir,'aotim5_tmd','UV_Arc5km')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPES = ['u','v']
elif (TIDE_MODEL == 'AOTIM-5-2018'):
grid_file = os.path.join(tide_dir,'Arc5km2018','grid_Arc5km2018')
model_file = os.path.join(tide_dir,'Arc5km2018','UV_Arc5km2018')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPES = ['u','v']
elif (TIDE_MODEL == 'FES2014'):
model_directory = {}
model_directory['u'] = os.path.join(tide_dir,'fes2014','eastward_velocity')
model_directory['v'] = os.path.join(tide_dir,'fes2014','northward_velocity')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',
'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',
'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
model_format = 'FES'
TYPES = ['u','v']
model_scale = 1.0
#-- invalid value
fill_value = -9999.0
#-- output netCDF4 and HDF5 file attributes
#-- will be added to YAML header in csv files
attrib = {}
#-- latitude
attrib['lat'] = {}
attrib['lat']['long_name'] = 'Latitude'
attrib['lat']['units'] = 'Degrees_North'
#-- longitude
attrib['lon'] = {}
attrib['lon']['long_name'] = 'Longitude'
attrib['lon']['units'] = 'Degrees_East'
#-- zonal tidal currents
attrib['u'] = {}
attrib['u']['description'] = ('depth_averaged_tidal_zonal_current_'
'from_harmonic_constants')
attrib['u']['model'] = TIDE_MODEL
attrib['u']['units'] = 'cm/s'
attrib['u']['long_name'] = 'zonal_tidal_current'
attrib['u']['_FillValue'] = fill_value
#-- meridional tidal currents
attrib['v'] = {}
attrib['v']['description'] = ('depth_averaged_tidal_meridional_current_'
'from_harmonic_constants')
attrib['v']['model'] = TIDE_MODEL
attrib['v']['units'] = 'cm/s'
attrib['v']['long_name'] = 'meridional_tidal_current'
attrib['v']['_FillValue'] = fill_value
#-- time
attrib['time'] = {}
attrib['time']['long_name'] = 'Time'
attrib['time']['units'] = 'days since 1992-01-01T00:00:00'
attrib['time']['calendar'] = 'standard'
#-- read input file to extract time, spatial coordinates and data
if (FORMAT == 'csv'):
dinput = pyTMD.spatial.from_ascii(input_file, columns=VARIABLES,
header=HEADER, verbose=VERBOSE)
elif (FORMAT == 'netCDF4'):
dinput = pyTMD.spatial.from_netCDF4(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3],
verbose=VERBOSE)
elif (FORMAT == 'HDF5'):
dinput = pyTMD.spatial.from_HDF5(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3],
verbose=VERBOSE)
elif (FORMAT == 'geotiff'):
dinput = pyTMD.spatial.from_geotiff(input_file, verbose=VERBOSE)
#-- copy global geotiff attributes for projection and grid parameters
for att_name in ['projection','wkt','spacing','extent']:
attrib[att_name] = dinput['attributes'][att_name]
#-- update time variable if entered as argument
if TIME is not None:
dinput['time'] = np.copy(TIME)
#-- converting x,y from projection to latitude/longitude
#-- could try to extract projection attributes from netCDF4 and HDF5 files
try:
crs1 = pyproj.CRS.from_string("epsg:{0:d}".format(int(PROJECTION)))
except (ValueError,pyproj.exceptions.CRSError):
crs1 = pyproj.CRS.from_string(PROJECTION)
crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(4326))
transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True)
if (TYPE == 'grid'):
ny,nx = (len(dinput['y']),len(dinput['x']))
gridx,gridy = np.meshgrid(dinput['x'],dinput['y'])
lon,lat = transformer.transform(gridx,gridy)
elif (TYPE == 'drift'):
lon,lat = transformer.transform(dinput['x'],dinput['y'])
#-- extract time units from netCDF4 and HDF5 attributes or from TIME_UNITS
try:
time_string = dinput['attributes']['time']['units']
except (TypeError, KeyError):
epoch1,to_secs = pyTMD.time.parse_date_string(TIME_UNITS)
else:
epoch1,to_secs = pyTMD.time.parse_date_string(time_string)
#-- convert time from units to days since 1992-01-01T00:00:00
tide_time = pyTMD.time.convert_delta_time(to_secs*dinput['time'].flatten(),
epoch1=epoch1, epoch2=(1992,1,1,0,0,0), scale=1.0/86400.0)
#-- number of time points
nt = len(tide_time)
#-- python dictionary with output data
output = {'time':tide_time,'lon':lon,'lat':lat}
#-- iterate over u and v currents
for t in TYPES:
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS','ATLAS'):
amp,ph,D,c = extract_tidal_constants(lon.flatten(), lat.flatten(),
grid_file, model_file, EPSG, TYPE=t, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, GRID=model_format)
deltat = np.zeros((nt))
elif (model_format == 'netcdf'):
amp,ph,D,c = extract_netcdf_constants(lon.flatten(), lat.flatten(),
model_directory, grid_file, model_files[t], TYPE=t,
METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE, SCALE=model_scale,
GZIP=GZIP)
deltat = np.zeros((nt))
elif (model_format == 'FES'):
amp,ph = extract_FES_constants(lon.flatten(), lat.flatten(),
model_directory[t], model_files, TYPE=t, VERSION=TIDE_MODEL,
METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE, SCALE=model_scale)
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data','merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j*ph*np.pi/180.0
#-- calculate constituent oscillation
hc = amp*np.exp(cph)
#-- predict tidal currents at time and infer minor corrections
if (TYPE == 'grid'):
output[t] = np.ma.zeros((ny,nx,nt),fill_value=fill_value)
output[t].mask = np.zeros((ny,nx,nt),dtype=np.bool)
for i in range(nt):
TIDE = predict_tide(tide_time[i], hc, c,
DELTAT=deltat[i], CORRECTIONS=model_format)
MINOR = infer_minor_corrections(tide_time[i], hc, c,
DELTAT=deltat[i], CORRECTIONS=model_format)
#-- add major and minor components and reform grid
output[t][:,:,i] = np.reshape((TIDE+MINOR), (ny,nx))
output[t].mask[:,:,i] = np.reshape((TIDE.mask | MINOR.mask),
(ny,nx))
elif (TYPE == 'drift'):
output[t] = np.ma.zeros((nt), fill_value=fill_value)
output[t].mask = np.any(hc.mask,axis=1)
output[t].data[:] = predict_tide_drift(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
minor = infer_minor_corrections(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
output[t].data[:] += minor.data[:]
#-- replace invalid values with fill value
output[t].data[output[t].mask] = output[t].fill_value
#-- output to file
if (FORMAT == 'csv'):
pyTMD.spatial.to_ascii(output, attrib, output_file, delimiter=',',
columns=['time','lat','lon','u','v'], verbose=VERBOSE)
elif (FORMAT == 'netCDF4'):
pyTMD.spatial.to_netCDF4(output, attrib, output_file, verbose=VERBOSE)
elif (FORMAT == 'HDF5'):
pyTMD.spatial.to_HDF5(output, attrib, output_file, verbose=VERBOSE)
elif (FORMAT == 'geotiff'):
#-- merge current variables into a single variable
output['data'] = np.concatenate((output['u'],output['v']),axis=-1)
attrib['data'] = {'_FillValue':fill_value}
pyTMD.spatial.to_geotiff(output, attrib, output_file, verbose=VERBOSE,
varname='data')
#-- change the permissions level to MODE
os.chmod(output_file, MODE)
def compute_tides_ICESat2(tide_dir,
INPUT_FILE,
TIDE_MODEL=None,
ATLAS_FORMAT=None,
GZIP=True,
DEFINITION_FILE=None,
METHOD='spline',
EXTRAPOLATE=False,
CUTOFF=None,
VERBOSE=False,
MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logger = pyTMD.utilities.build_logger('pytmd', level=loglevel)
#-- get parameters for tide model
if DEFINITION_FILE is not None:
model = pyTMD.model(tide_dir).from_file(DEFINITION_FILE)
else:
model = pyTMD.model(tide_dir, format=ATLAS_FORMAT,
compressed=GZIP).elevation(TIDE_MODEL)
#-- read data from input file
logger.info('{0} -->'.format(INPUT_FILE))
IS2_atl03_mds, IS2_atl03_attrs, IS2_atl03_beams = read_HDF5_ATL03_main(
INPUT_FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 file name
rx = re.compile(
r'(processed_)?(ATL\d{2})_(\d{4})(\d{2})(\d{2})(\d{2})'
r'(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$')
try:
SUB, PRD, YY, MM, DD, HH, MN, SS, TRK, CYCL, GRAN, RL, VERS, AUX = rx.findall(
INPUT_FILE).pop()
except:
#-- output tide HDF5 file (generic)
fileBasename, fileExtension = os.path.splitext(INPUT_FILE)
args = (fileBasename, model.name, fileExtension)
OUTPUT_FILE = '{0}_{1}_TIDES{2}'.format(*args)
else:
#-- output tide HDF5 file for ASAS/NSIDC granules
args = (PRD, model.name, YY, MM, DD, HH, MN, SS, TRK, CYCL, GRAN, RL,
VERS, AUX)
file_format = '{0}_{1}_TIDES_{2}{3}{4}{5}{6}{7}_{8}{9}{10}_{11}_{12}{13}.h5'
OUTPUT_FILE = file_format.format(*args)
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl03_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data', 'merged_deltat.data'])
#-- copy variables for outputting to HDF5 file
IS2_atl03_tide = {}
IS2_atl03_fill = {}
IS2_atl03_dims = {}
IS2_atl03_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl03_tide['ancillary_data'] = {}
IS2_atl03_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl03_tide['ancillary_data'][key] = IS2_atl03_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl03_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl03_attrs['ancillary_data'][key].items(
):
IS2_atl03_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam within the file
for gtx in sorted(IS2_atl03_beams):
#-- output data dictionaries for beam
IS2_atl03_tide[gtx] = dict(geolocation={}, geophys_corr={})
IS2_atl03_fill[gtx] = dict(geolocation={}, geophys_corr={})
IS2_atl03_dims[gtx] = dict(geolocation={}, geophys_corr={})
IS2_atl03_tide_attrs[gtx] = dict(geolocation={}, geophys_corr={})
#-- read data and attributes for beam
val, attrs = read_HDF5_ATL03_beam(INPUT_FILE, gtx, ATTRIBUTES=True)
#-- number of segments
n_seg = len(val['geolocation']['segment_id'])
#-- extract variables for computing tides
segment_id = val['geolocation']['segment_id'].copy()
delta_time = val['geolocation']['delta_time'].copy()
lon = val['geolocation']['reference_photon_lon'].copy()
lat = val['geolocation']['reference_photon_lat'].copy()
#-- invalid value
fv = attrs['geolocation']['sigma_h']['_FillValue']
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + delta_time
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(gps_seconds - leap_seconds,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- read tidal constants and interpolate to grid points
if model.format in ('OTIS', 'ATLAS'):
amp, ph, D, c = extract_tidal_constants(lon,
lat,
model.grid_file,
model.model_file,
model.projection,
TYPE=model.type,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
GRID=model.format)
deltat = np.zeros_like(tide_time)
elif (model.format == 'netcdf'):
amp, ph, D, c = extract_netcdf_constants(lon,
lat,
model.grid_file,
model.model_file,
TYPE=model.type,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=model.scale,
GZIP=model.compressed)
deltat = np.zeros_like(tide_time)
elif (model.format == 'GOT'):
amp, ph, c = extract_GOT_constants(lon,
lat,
model.model_file,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=model.scale,
GZIP=model.compressed)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
elif (model.format == 'FES'):
amp, ph = extract_FES_constants(lon,
lat,
model.model_file,
TYPE=model.type,
VERSION=model.version,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=model.scale,
GZIP=model.compressed)
#-- available model constituents
c = model.constituents
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j * ph * np.pi / 180.0
#-- calculate constituent oscillation
hc = amp * np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
tide = np.ma.empty((n_seg), fill_value=fv)
tide.mask = np.any(hc.mask, axis=1)
tide.data[:] = predict_tide_drift(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model.format)
minor = infer_minor_corrections(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model.format)
tide.data[:] += minor.data[:]
#-- replace masked and nan values with fill value
invalid, = np.nonzero(np.isnan(tide.data) | tide.mask)
tide.data[invalid] = tide.fill_value
tide.mask[invalid] = True
#-- group attributes for beam
IS2_atl03_tide_attrs[gtx]['Description'] = attrs['Description']
IS2_atl03_tide_attrs[gtx]['atlas_pce'] = attrs['atlas_pce']
IS2_atl03_tide_attrs[gtx]['atlas_beam_type'] = attrs['atlas_beam_type']
IS2_atl03_tide_attrs[gtx]['groundtrack_id'] = attrs['groundtrack_id']
IS2_atl03_tide_attrs[gtx]['atmosphere_profile'] = attrs[
'atmosphere_profile']
IS2_atl03_tide_attrs[gtx]['atlas_spot_number'] = attrs[
'atlas_spot_number']
IS2_atl03_tide_attrs[gtx]['sc_orientation'] = attrs['sc_orientation']
#-- group attributes for geolocation
IS2_atl03_tide_attrs[gtx]['geolocation']['Description'] = (
"Contains parameters related to "
"geolocation. The rate of all of these parameters is at the rate corresponding to the "
"ICESat-2 Geolocation Along Track Segment interval (nominally 20 m along-track)."
)
IS2_atl03_tide_attrs[gtx]['geolocation']['data_rate'] = (
"Data within this group are "
"stored at the ICESat-2 20m segment rate.")
#-- group attributes for geophys_corr
IS2_atl03_tide_attrs[gtx]['geophys_corr']['Description'] = (
"Contains parameters used to "
"correct photon heights for geophysical effects, such as tides. These parameters are "
"posted at the same interval as the ICESat-2 Geolocation Along-Track Segment interval "
"(nominally 20m along-track).")
IS2_atl03_tide_attrs[gtx]['geophys_corr']['data_rate'] = (
"These parameters are stored at "
"the ICESat-2 Geolocation Along Track Segment rate (nominally every 20 m along-track)."
)
#-- geolocation, time and segment ID
#-- delta time in geolocation group
IS2_atl03_tide[gtx]['geolocation']['delta_time'] = delta_time
IS2_atl03_fill[gtx]['geolocation']['delta_time'] = None
IS2_atl03_dims[gtx]['geolocation']['delta_time'] = None
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'] = {}
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'][
'standard_name'] = "time"
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time'][
'calendar'] = "standard"
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time']['description'] = (
"Elapsed seconds "
"from the ATLAS SDP GPS Epoch, corresponding to the transmit time of the reference "
"photon. The ATLAS Standard Data Products (SDP) epoch offset is defined within "
"/ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch "
"(1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset "
"contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds "
"relative to the GPS epoch can be computed.")
IS2_atl03_tide_attrs[gtx]['geolocation']['delta_time']['coordinates'] = \
"segment_id reference_photon_lat reference_photon_lon"
#-- delta time in geophys_corr group
IS2_atl03_tide[gtx]['geophys_corr']['delta_time'] = delta_time
IS2_atl03_fill[gtx]['geophys_corr']['delta_time'] = None
IS2_atl03_dims[gtx]['geophys_corr']['delta_time'] = None
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'] = {}
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'][
'standard_name'] = "time"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time'][
'calendar'] = "standard"
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time']['description'] = (
"Elapsed seconds "
"from the ATLAS SDP GPS Epoch, corresponding to the transmit time of the reference "
"photon. The ATLAS Standard Data Products (SDP) epoch offset is defined within "
"/ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds between the GPS epoch "
"(1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By adding the offset "
"contained within atlas_sdp_gps_epoch to delta time parameters, the time in gps_seconds "
"relative to the GPS epoch can be computed.")
IS2_atl03_tide_attrs[gtx]['geophys_corr']['delta_time']['coordinates'] = (
"../geolocation/segment_id "
"../geolocation/reference_photon_lat ../geolocation/reference_photon_lon"
)
#-- latitude
IS2_atl03_tide[gtx]['geolocation']['reference_photon_lat'] = lat
IS2_atl03_fill[gtx]['geolocation']['reference_photon_lat'] = None
IS2_atl03_dims[gtx]['geolocation']['reference_photon_lat'] = [
'delta_time'
]
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'] = {}
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'units'] = "degrees_north"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'contentType'] = "physicalMeasurement"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'long_name'] = "Latitude"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'standard_name'] = "latitude"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'description'] = (
"Latitude of each "
"reference photon. Computed from the ECF Cartesian coordinates of the bounce point."
)
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'valid_min'] = -90.0
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat'][
'valid_max'] = 90.0
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lat']['coordinates'] = \
"segment_id delta_time reference_photon_lon"
#-- longitude
IS2_atl03_tide[gtx]['geolocation']['reference_photon_lon'] = lon
IS2_atl03_fill[gtx]['geolocation']['reference_photon_lon'] = None
IS2_atl03_dims[gtx]['geolocation']['reference_photon_lon'] = [
'delta_time'
]
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'] = {}
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'units'] = "degrees_east"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'contentType'] = "physicalMeasurement"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'long_name'] = "Longitude"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'standard_name'] = "longitude"
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'description'] = (
"Longitude of each "
"reference photon. Computed from the ECF Cartesian coordinates of the bounce point."
)
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'valid_min'] = -180.0
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon'][
'valid_max'] = 180.0
IS2_atl03_tide_attrs[gtx]['geolocation']['reference_photon_lon']['coordinates'] = \
"segment_id delta_time reference_photon_lat"
#-- segment ID
IS2_atl03_tide[gtx]['geolocation']['segment_id'] = segment_id
IS2_atl03_fill[gtx]['geolocation']['segment_id'] = None
IS2_atl03_dims[gtx]['geolocation']['segment_id'] = ['delta_time']
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id'] = {}
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id']['units'] = "1"
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id'][
'contentType'] = "referenceInformation"
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id'][
'long_name'] = "Along-track segment ID number"
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id']['description'] = (
"A 7 digit number "
"identifying the along-track geolocation segment number. These are sequential, starting with "
"1 for the first segment after an ascending equatorial crossing node. Equal to the segment_id for "
"the second of the two 20m ATL03 segments included in the 40m ATL03 segment"
)
IS2_atl03_tide_attrs[gtx]['geolocation']['segment_id']['coordinates'] = \
"delta_time reference_photon_lat reference_photon_lon"
#-- computed tide
IS2_atl03_tide[gtx]['geophys_corr'][model.atl03] = tide
IS2_atl03_fill[gtx]['geophys_corr'][model.atl03] = tide.fill_value
IS2_atl03_dims[gtx]['geophys_corr'][model.atl03] = ['delta_time']
IS2_atl03_tide_attrs[gtx]['geophys_corr'][model.atl03] = {}
IS2_atl03_tide_attrs[gtx]['geophys_corr'][
model.atl03]['units'] = "meters"
IS2_atl03_tide_attrs[gtx]['geophys_corr'][
model.atl03]['contentType'] = "referenceInformation"
IS2_atl03_tide_attrs[gtx]['geophys_corr'][
model.atl03]['long_name'] = model.long_name
IS2_atl03_tide_attrs[gtx]['geophys_corr'][
model.atl03]['description'] = model.description
IS2_atl03_tide_attrs[gtx]['geophys_corr'][
model.atl03]['source'] = model.name
IS2_atl03_tide_attrs[gtx]['geophys_corr'][
model.atl03]['reference'] = model.reference
IS2_atl03_tide_attrs[gtx]['geophys_corr'][model.atl03]['coordinates'] = \
("../geolocation/segment_id ../geolocation/delta_time "
"../geolocation/reference_photon_lat ../geolocation/reference_photon_lon")
#-- print file information
logger.info('\t{0}'.format(OUTPUT_FILE))
HDF5_ATL03_tide_write(IS2_atl03_tide,
IS2_atl03_tide_attrs,
CLOBBER=True,
INPUT=os.path.basename(INPUT_FILE),
FILL_VALUE=IS2_atl03_fill,
DIMENSIONS=IS2_atl03_dims,
FILENAME=os.path.join(DIRECTORY, OUTPUT_FILE))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, OUTPUT_FILE), MODE)
def compute_tides_icebridge_data(tide_dir, arg, TIDE_MODEL,
METHOD='spline', EXTRAPOLATE=False, VERBOSE=False, MODE=0o775):
#-- extract file name and subsetter indices lists
match_object = re.match(r'(.*?)(\[(.*?)\])?$',arg)
input_file = os.path.expanduser(match_object.group(1))
#-- subset input file to indices
if match_object.group(2):
#-- decompress ranges and add to list
input_subsetter = []
for i in re.findall(r'((\d+)-(\d+)|(\d+))',match_object.group(3)):
input_subsetter.append(int(i[3])) if i[3] else \
input_subsetter.extend(range(int(i[1]),int(i[2])+1))
else:
input_subsetter = None
#-- output directory for input_file
DIRECTORY = os.path.dirname(input_file)
#-- calculate if input files are from ATM or LVIS (+GH)
regex = {}
regex['ATM'] = r'(BLATM2|ILATM2)_(\d+)_(\d+)_smooth_nadir(.*?)(csv|seg|pt)$'
regex['ATM1b'] = r'(BLATM1b|ILATM1b)_(\d+)_(\d+)(.*?).(qi|TXT|h5)$'
regex['LVIS'] = r'(BLVIS2|BVLIS2|ILVIS2)_(.*?)(\d+)_(\d+)_(R\d+)_(\d+).H5$'
regex['LVGH'] = r'(ILVGH2)_(.*?)(\d+)_(\d+)_(R\d+)_(\d+).H5$'
for key,val in regex.items():
if re.match(val, os.path.basename(input_file)):
OIB = key
#-- select between tide models
if (TIDE_MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir,'cats0201_tmd','grid_CATS')
model_file = os.path.join(tide_dir,'cats0201_tmd','h0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir,'CATS2008','grid_CATS2008')
model_file = os.path.join(tide_dir,'CATS2008','hf.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008_load'):
grid_file = os.path.join(tide_dir,'CATS2008a_SPOTL_Load','grid_CATS2008a_opt')
model_file = os.path.join(tide_dir,'CATS2008a_SPOTL_Load','h_CATS2008a_SPOTL_load')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30.nc.gz','h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz','h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz','h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz','h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz','h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz','h_2n2_tpxo9_atlas_30.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v2'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v2')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v2.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30_v2.nc.gz','h_o1_tpxo9_atlas_30_v2.nc.gz',
'h_p1_tpxo9_atlas_30_v2.nc.gz','h_k1_tpxo9_atlas_30_v2.nc.gz',
'h_n2_tpxo9_atlas_30_v2.nc.gz','h_m2_tpxo9_atlas_30_v2.nc.gz',
'h_s2_tpxo9_atlas_30_v2.nc.gz','h_k2_tpxo9_atlas_30_v2.nc.gz',
'h_m4_tpxo9_atlas_30_v2.nc.gz','h_ms4_tpxo9_atlas_30_v2.nc.gz',
'h_mn4_tpxo9_atlas_30_v2.nc.gz','h_2n2_tpxo9_atlas_30_v2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v3'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v3')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v3.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30_v3.nc.gz','h_o1_tpxo9_atlas_30_v3.nc.gz',
'h_p1_tpxo9_atlas_30_v3.nc.gz','h_k1_tpxo9_atlas_30_v3.nc.gz',
'h_n2_tpxo9_atlas_30_v3.nc.gz','h_m2_tpxo9_atlas_30_v3.nc.gz',
'h_s2_tpxo9_atlas_30_v3.nc.gz','h_k2_tpxo9_atlas_30_v3.nc.gz',
'h_m4_tpxo9_atlas_30_v3.nc.gz','h_ms4_tpxo9_atlas_30_v3.nc.gz',
'h_mn4_tpxo9_atlas_30_v3.nc.gz','h_2n2_tpxo9_atlas_30_v3.nc.gz',
'h_mf_tpxo9_atlas_30_v3.nc.gz','h_mm_tpxo9_atlas_30_v3.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
output_variable = 'tide_ocean'
variable_long_name = "Ocean Tide"
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v4'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v4')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v4')
model_files = ['h_q1_tpxo9_atlas_30_v4','h_o1_tpxo9_atlas_30_v4',
'h_p1_tpxo9_atlas_30_v4','h_k1_tpxo9_atlas_30_v4',
'h_n2_tpxo9_atlas_30_v4','h_m2_tpxo9_atlas_30_v4',
'h_s2_tpxo9_atlas_30_v4','h_k2_tpxo9_atlas_30_v4',
'h_m4_tpxo9_atlas_30_v4','h_ms4_tpxo9_atlas_30_v4',
'h_mn4_tpxo9_atlas_30_v4','h_2n2_tpxo9_atlas_30_v4',
'h_mf_tpxo9_atlas_30_v4','h_mm_tpxo9_atlas_30_v4']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir,'TPXO9.1','DATA','grid_tpxo9')
model_file = os.path.join(tide_dir,'TPXO9.1','DATA','h_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir,'tpxo8_atlas','grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir,'tpxo8_atlas','hf.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'ATLAS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir,'TPXO7.2_tmd','grid_tpxo7.2')
model_file = os.path.join(tide_dir,'TPXO7.2_tmd','h_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(tide_dir,'TPXO7.2_load','grid_tpxo6.2')
model_file = os.path.join(tide_dir,'TPXO7.2_load','h_tpxo7.2_load')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir,'aodtm5_tmd','grid_Arc5km')
model_file = os.path.join(tide_dir,'aodtm5_tmd','h0_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir,'aotim5_tmd','grid_Arc5km')
model_file = os.path.join(tide_dir,'aotim5_tmd','h_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5-2018'):
grid_file = os.path.join(tide_dir,'Arc5km2018','grid_Arc5km2018')
model_file = os.path.join(tide_dir,'Arc5km2018','h_Arc5km2018')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'GOT4.7'):
model_directory = os.path.join(tide_dir,'GOT4.7','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.7_load'):
model_directory = os.path.join(tide_dir,'GOT4.7','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.8'):
model_directory = os.path.join(tide_dir,'got4.8','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.8_load'):
model_directory = os.path.join(tide_dir,'got4.8','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.10'):
model_directory = os.path.join(tide_dir,'GOT4.10c','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.10_load'):
model_directory = os.path.join(tide_dir,'GOT4.10c','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'FES2014'):
model_directory = os.path.join(tide_dir,'fes2014','ocean_tide')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',
'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',
'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'FES2014_load'):
model_directory = os.path.join(tide_dir,'fes2014','load_tide')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',
'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',
'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0/100.0
GZIP = True
#-- HDF5 file attributes
attrib = {}
#-- latitude
attrib['lat'] = {}
attrib['lat']['long_name'] = 'Latitude_of_measurement'
attrib['lat']['description'] = ('Corresponding_to_the_measurement_'
'position_at_the_acquisition_time')
attrib['lat']['units'] = 'Degrees_North'
#-- longitude
attrib['lon'] = {}
attrib['lon']['long_name'] = 'Longitude_of_measurement'
attrib['lon']['description'] = ('Corresponding_to_the_measurement_'
'position_at_the_acquisition_time')
attrib['lon']['units'] = 'Degrees_East'
#-- tides
attrib[output_variable] = {}
attrib[output_variable]['description'] = ('Tidal_elevation_from_harmonic_'
'constants_at_the_measurement_position_at_the_acquisition_time')
attrib[output_variable]['reference'] = reference
attrib[output_variable]['model'] = TIDE_MODEL
attrib[output_variable]['units'] = 'meters'
attrib[output_variable]['long_name'] = variable_long_name
#-- time
attrib['time'] = {}
attrib['time']['long_name'] = 'Time'
attrib['time']['description'] = ('Time_corresponding_to_the_measurement_'
'position')
attrib['time']['units'] = 'Days since 1992-01-01T00:00:00'
attrib['time']['calendar'] = 'standard'
#-- extract information from first input file
#-- acquisition year, month and day
#-- number of points
#-- instrument (PRE-OIB ATM or LVIS, OIB ATM or LVIS)
if OIB in ('ATM','ATM1b'):
M1,YYMMDD1,HHMMSS1,AX1,SF1 = re.findall(regex[OIB], input_file).pop()
#-- early date strings omitted century and millenia (e.g. 93 for 1993)
if (len(YYMMDD1) == 6):
ypre,MM1,DD1 = YYMMDD1[:2],YYMMDD1[2:4],YYMMDD1[4:]
if (np.float64(ypre) >= 90):
YY1 = '{0:4.0f}'.format(np.float64(ypre) + 1900.0)
else:
YY1 = '{0:4.0f}'.format(np.float64(ypre) + 2000.0)
elif (len(YYMMDD1) == 8):
YY1,MM1,DD1 = YYMMDD1[:4],YYMMDD1[4:6],YYMMDD1[6:]
elif OIB in ('LVIS','LVGH'):
M1,RG1,YY1,MMDD1,RLD1,SS1 = re.findall(regex[OIB], input_file).pop()
MM1,DD1 = MMDD1[:2],MMDD1[2:]
#-- read data from input_file
print('{0} -->'.format(input_file)) if VERBOSE else None
if (OIB == 'ATM'):
#-- load IceBridge ATM data from input_file
dinput,file_lines,HEM = read_ATM_icessn_file(input_file,input_subsetter)
elif (OIB == 'ATM1b'):
#-- load IceBridge Level-1b ATM data from input_file
dinput,file_lines,HEM = read_ATM_qfit_file(input_file,input_subsetter)
elif OIB in ('LVIS','LVGH'):
#-- load IceBridge LVIS data from input_file
dinput,file_lines,HEM = read_LVIS_HDF5_file(input_file,input_subsetter)
#-- convert time from J2000 to days relative to Jan 1, 1992 (48622mjd)
#-- J2000: seconds since 2000-01-01 12:00:00 UTC
t = pyTMD.time.convert_delta_time(dinput['time'],
epoch1=(2000,1,1,12,0,0), epoch2=(1992,1,1,0,0,0),
scale=1.0/86400.0)
#-- delta time (TT - UT1) file
delta_file = get_data_path(['data','merged_deltat.data'])
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS','ATLAS'):
amp,ph,D,c = extract_tidal_constants(dinput['lon'], dinput['lat'],
grid_file, model_file, EPSG, TYPE=TYPE, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, GRID=model_format)
deltat = np.zeros_like(t)
elif model_format in ('netcdf'):
amp,ph,D,c = extract_netcdf_constants(dinput['lon'], dinput['lat'],
grid_file, model_file, TYPE=TYPE, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, SCALE=SCALE, GZIP=GZIP)
deltat = np.zeros_like(t)
elif (model_format == 'GOT'):
amp,ph,c = extract_GOT_constants(dinput['lon'], dinput['lat'],
model_file, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
SCALE=SCALE, GZIP=GZIP)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, t)
elif (model_format == 'FES'):
amp,ph = extract_FES_constants(dinput['lon'], dinput['lat'],
model_file, TYPE=TYPE, VERSION=TIDE_MODEL, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, SCALE=SCALE, GZIP=GZIP)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, t)
#-- calculate complex phase in radians for Euler's
cph = -1j*ph*np.pi/180.0
#-- calculate constituent oscillation
hc = amp*np.exp(cph)
#-- output tidal HDF5 file
#-- form: rg_NASA_model_TIDES_WGS84_fl1yyyymmddjjjjj.H5
#-- where rg is the hemisphere flag (GR or AN) for the region
#-- model is the tidal TIDE_MODEL flag (e.g. CATS0201)
#-- fl1 and fl2 are the data flags (ATM, LVIS, GLAS)
#-- yymmddjjjjj is the year, month, day and second of the input file
#-- output region flags: GR for Greenland and AN for Antarctica
hem_flag = {'N':'GR','S':'AN'}
#-- use starting second to distinguish between files for the day
JJ1 = np.min(dinput['time']) % 86400
#-- output file format
args = (hem_flag[HEM],TIDE_MODEL,OIB,YY1,MM1,DD1,JJ1)
FILENAME = '{0}_NASA_{1}_TIDES_WGS84_{2}{3}{4}{5}{6:05.0f}.H5'.format(*args)
#-- print file information
print('\t{0}'.format(FILENAME)) if VERBOSE else None
#-- open output HDF5 file
fid = h5py.File(os.path.join(DIRECTORY,FILENAME), 'w')
#-- predict tidal elevations at time and infer minor corrections
fill_value = -9999.0
tide = np.ma.empty((file_lines),fill_value=fill_value)
tide.mask = np.any(hc.mask,axis=1)
tide.data[:] = predict_tide_drift(t, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
minor = infer_minor_corrections(t, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
tide.data[:] += minor.data[:]
#-- replace invalid values with fill value
tide.data[tide.mask] = tide.fill_value
#-- add latitude and longitude to output file
for key in ['lat','lon']:
#-- Defining the HDF5 dataset variables for lat/lon
h5 = fid.create_dataset(key, (file_lines,), data=dinput[key][:],
dtype=dinput[key].dtype, compression='gzip')
#-- add HDF5 variable attributes
for att_name,att_val in attrib[key].items():
h5.attrs[att_name] = att_val
#-- attach dimensions
h5.dims[0].label = 'RECORD_SIZE'
#-- output tides to HDF5 dataset
h5 = fid.create_dataset(output_variable, (file_lines,), data=tide,
dtype=tide.dtype, fillvalue=fill_value, compression='gzip')
#-- add HDF5 variable attributes
tide_count = np.count_nonzero(tide != fill_value)
h5.attrs['tide_count'] = tide_count
h5.attrs['_FillValue'] = fill_value
for att_name,att_val in attrib[output_variable].items():
h5.attrs[att_name] = att_val
#-- attach dimensions
h5.dims[0].label = 'RECORD_SIZE'
#-- output days to HDF5 dataset
h5 = fid.create_dataset('time', (file_lines,), data=t,
dtype=t.dtype, compression='gzip')
#-- add HDF5 variable attributes
for att_name,att_val in attrib['time'].items():
h5.attrs[att_name] = att_val
#-- attach dimensions
h5.dims[0].label = 'RECORD_SIZE'
#-- HDF5 file attributes
fid.attrs['featureType'] = 'trajectory'
fid.attrs['title'] = 'Tidal_correction_for_elevation_measurements'
fid.attrs['summary'] = ('Tidal_correction_computed_at_elevation_'
'measurements_using_a_tidal_model_driver.')
fid.attrs['project'] = 'NASA_Operation_IceBridge'
fid.attrs['processing_level'] = '4'
fid.attrs['date_created'] = time.strftime('%Y-%m-%d',time.localtime())
#-- add attributes for input file
fid.attrs['elevation_file'] = os.path.basename(input_file)
fid.attrs['tide_model'] = TIDE_MODEL
#-- add geospatial and temporal attributes
fid.attrs['geospatial_lat_min'] = dinput['lat'].min()
fid.attrs['geospatial_lat_max'] = dinput['lat'].max()
fid.attrs['geospatial_lon_min'] = dinput['lon'].min()
fid.attrs['geospatial_lon_max'] = dinput['lon'].max()
fid.attrs['geospatial_lat_units'] = "degrees_north"
fid.attrs['geospatial_lon_units'] = "degrees_east"
fid.attrs['geospatial_ellipsoid'] = "WGS84"
fid.attrs['time_type'] = 'UTC'
#-- convert start/end time from days since 1992-01-01 into Julian days
time_range = np.array([np.min(t),np.max(t)])
time_julian = 2400000.5 + pyTMD.time.convert_delta_time(time_range,
epoch1=(1992,1,1,0,0,0), epoch2=(1858,11,17,0,0,0), scale=1.0)
#-- convert to calendar date
cal = pyTMD.time.convert_julian(time_julian,ASTYPE=int)
#-- add attributes with measurement date start, end and duration
args = (cal['hour'][0],cal['minute'][0],cal['second'][0])
fid.attrs['RangeBeginningTime'] = '{0:02d}:{1:02d}:{2:02d}'.format(*args)
args = (cal['hour'][-1],cal['minute'][-1],cal['second'][-1])
fid.attrs['RangeEndingTime'] = '{0:02d}:{1:02d}:{2:02d}'.format(*args)
args = (cal['year'][0],cal['month'][0],cal['day'][0])
fid.attrs['RangeBeginningDate'] = '{0:4d}-{1:02d}-{2:02d}'.format(*args)
args = (cal['year'][-1],cal['month'][-1],cal['day'][-1])
fid.attrs['RangeEndingDate'] = '{0:4d}-{1:02d}-{2:02d}'.format(*args)
duration = np.round(time_julian[-1]*86400.0 - time_julian[0]*86400.0)
fid.attrs['DurationTimeSeconds'] = '{0:0.0f}'.format(duration)
#-- close the output HDF5 dataset
fid.close()
#-- change the permissions level to MODE
os.chmod(os.path.join(DIRECTORY,FILENAME), MODE)
def compute_LPET_ICESat(INPUT_FILE, VERBOSE=False, MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logger = pyTMD.utilities.build_logger('pytmd', level=loglevel)
#-- get directory from INPUT_FILE
logger.info('{0} -->'.format(INPUT_FILE))
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- compile regular expression operator for extracting information from file
rx = re.compile((r'GLAH(\d{2})_(\d{3})_(\d{1})(\d{1})(\d{2})_(\d{3})_'
r'(\d{4})_(\d{1})_(\d{2})_(\d{4})\.H5'), re.VERBOSE)
#-- extract parameters from ICESat/GLAS HDF5 file name
#-- PRD: Product number (01, 05, 06, 12, 13, 14, or 15)
#-- RL: Release number for process that created the product = 634
#-- RGTP: Repeat ground-track phase (1=8-day, 2=91-day, 3=transfer orbit)
#-- ORB: Reference orbit number (starts at 1 and increments each time a
#-- new reference orbit ground track file is obtained.)
#-- INST: Instance number (increments every time the satellite enters a
#-- different reference orbit)
#-- CYCL: Cycle of reference orbit for this phase
#-- TRK: Track within reference orbit
#-- SEG: Segment of orbit
#-- GRAN: Granule version number
#-- TYPE: File type
try:
PRD, RL, RGTP, ORB, INST, CYCL, TRK, SEG, GRAN, TYPE = rx.findall(
INPUT_FILE).pop()
except:
#-- output long-period equilibrium tide HDF5 file (generic)
fileBasename, fileExtension = os.path.splitext(INPUT_FILE)
OUTPUT_FILE = '{0}_{1}{2}'.format(fileBasename, 'LPET', fileExtension)
else:
#-- output long-period equilibrium tide HDF5 file for NSIDC granules
args = (PRD, RL, RGTP, ORB, INST, CYCL, TRK, SEG, GRAN, TYPE)
file_format = 'GLAH{0}_{1}_LPET_{2}{3}{4}_{5}_{6}_{7}_{8}_{9}.h5'
OUTPUT_FILE = file_format.format(*args)
#-- read GLAH12 HDF5 file
fileID = h5py.File(INPUT_FILE, 'r')
n_40HZ, = fileID['Data_40HZ']['Time']['i_rec_ndx'].shape
#-- get variables and attributes
rec_ndx_40HZ = fileID['Data_40HZ']['Time']['i_rec_ndx'][:].copy()
#-- seconds since 2000-01-01 12:00:00 UTC (J2000)
DS_UTCTime_40HZ = fileID['Data_40HZ']['DS_UTCTime_40'][:].copy()
#-- Latitude (degrees North)
lat_TPX = fileID['Data_40HZ']['Geolocation']['d_lat'][:].copy()
#-- Longitude (degrees East)
lon_40HZ = fileID['Data_40HZ']['Geolocation']['d_lon'][:].copy()
#-- Elevation (height above TOPEX/Poseidon ellipsoid in meters)
elev_TPX = fileID['Data_40HZ']['Elevation_Surfaces']['d_elev'][:].copy()
fv = fileID['Data_40HZ']['Elevation_Surfaces']['d_elev'].attrs[
'_FillValue']
#-- semimajor axis (a) and flattening (f) for TP and WGS84 ellipsoids
atop, ftop = (6378136.3, 1.0 / 298.257)
awgs, fwgs = (6378137.0, 1.0 / 298.257223563)
#-- convert from Topex/Poseidon to WGS84 Ellipsoids
lat_40HZ, elev_40HZ = pyTMD.spatial.convert_ellipsoid(lat_TPX,
elev_TPX,
atop,
ftop,
awgs,
fwgs,
eps=1e-12,
itmax=10)
#-- convert time from J2000 to days relative to Jan 1, 1992 (48622mjd)
#-- J2000: seconds since 2000-01-01 12:00:00 UTC
tide_time = pyTMD.time.convert_delta_time(DS_UTCTime_40HZ,
epoch1=(2000, 1, 1, 12, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = pyTMD.utilities.get_data_path(['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- predict long-period equilibrium tides at latitudes and time
tide_lpe = compute_equilibrium_tide(tide_time + deltat, lat_40HZ)
#-- copy variables for outputting to HDF5 file
IS_gla12_tide = dict(Data_40HZ={})
IS_gla12_fill = dict(Data_40HZ={})
IS_gla12_tide_attrs = dict(Data_40HZ={})
#-- copy global file attributes
global_attribute_list = [
'featureType', 'title', 'comment', 'summary', 'license', 'references',
'AccessConstraints', 'CitationforExternalPublication',
'contributor_role', 'contributor_name', 'creator_name',
'creator_email', 'publisher_name', 'publisher_email', 'publisher_url',
'platform', 'instrument', 'processing_level', 'date_created',
'spatial_coverage_type', 'history', 'keywords', 'keywords_vocabulary',
'naming_authority', 'project', 'time_type', 'date_type',
'time_coverage_start', 'time_coverage_end', 'time_coverage_duration',
'source', 'HDFVersion', 'identifier_product_type',
'identifier_product_format_version', 'Conventions', 'institution',
'ReprocessingPlanned', 'ReprocessingActual', 'LocalGranuleID',
'ProductionDateTime', 'LocalVersionID', 'PGEVersion', 'OrbitNumber',
'StartOrbitNumber', 'StopOrbitNumber', 'EquatorCrossingLongitude',
'EquatorCrossingTime', 'EquatorCrossingDate', 'ShortName', 'VersionID',
'InputPointer', 'RangeBeginningTime', 'RangeEndingTime',
'RangeBeginningDate', 'RangeEndingDate', 'PercentGroundHit',
'OrbitQuality', 'Cycle', 'Track', 'Instrument_State', 'Timing_Bias',
'ReferenceOrbit', 'SP_ICE_PATH_NO', 'SP_ICE_GLAS_StartBlock',
'SP_ICE_GLAS_EndBlock', 'Instance', 'Range_Bias',
'Instrument_State_Date', 'Instrument_State_Time', 'Range_Bias_Date',
'Range_Bias_Time', 'Timing_Bias_Date', 'Timing_Bias_Time',
'identifier_product_doi', 'identifier_file_uuid',
'identifier_product_doi_authority'
]
for att in global_attribute_list:
IS_gla12_tide_attrs[att] = fileID.attrs[att]
#-- copy ICESat campaign name from ancillary data
IS_gla12_tide_attrs['Campaign'] = fileID['ANCILLARY_DATA'].attrs[
'Campaign']
#-- add attributes for input GLA12 file
IS_gla12_tide_attrs['input_files'] = os.path.basename(INPUT_FILE)
#-- update geospatial ranges for ellipsoid
IS_gla12_tide_attrs['geospatial_lat_min'] = np.min(lat_40HZ)
IS_gla12_tide_attrs['geospatial_lat_max'] = np.max(lat_40HZ)
IS_gla12_tide_attrs['geospatial_lon_min'] = np.min(lon_40HZ)
IS_gla12_tide_attrs['geospatial_lon_max'] = np.max(lon_40HZ)
IS_gla12_tide_attrs['geospatial_lat_units'] = "degrees_north"
IS_gla12_tide_attrs['geospatial_lon_units'] = "degrees_east"
IS_gla12_tide_attrs['geospatial_ellipsoid'] = "WGS84"
#-- copy 40Hz group attributes
for att_name, att_val in fileID['Data_40HZ'].attrs.items():
IS_gla12_tide_attrs['Data_40HZ'][att_name] = att_val
#-- copy attributes for time, geolocation and geophysical groups
for var in ['Time', 'Geolocation', 'Geophysical']:
IS_gla12_tide['Data_40HZ'][var] = {}
IS_gla12_fill['Data_40HZ'][var] = {}
IS_gla12_tide_attrs['Data_40HZ'][var] = {}
for att_name, att_val in fileID['Data_40HZ'][var].attrs.items():
IS_gla12_tide_attrs['Data_40HZ'][var][att_name] = att_val
#-- J2000 time
IS_gla12_tide['Data_40HZ']['DS_UTCTime_40'] = DS_UTCTime_40HZ
IS_gla12_fill['Data_40HZ']['DS_UTCTime_40'] = None
IS_gla12_tide_attrs['Data_40HZ']['DS_UTCTime_40'] = {}
for att_name, att_val in fileID['Data_40HZ']['DS_UTCTime_40'].attrs.items(
):
if att_name not in ('DIMENSION_LIST', 'CLASS', 'NAME'):
IS_gla12_tide_attrs['Data_40HZ']['DS_UTCTime_40'][
att_name] = att_val
#-- record
IS_gla12_tide['Data_40HZ']['Time']['i_rec_ndx'] = rec_ndx_40HZ
IS_gla12_fill['Data_40HZ']['Time']['i_rec_ndx'] = None
IS_gla12_tide_attrs['Data_40HZ']['Time']['i_rec_ndx'] = {}
for att_name, att_val in fileID['Data_40HZ']['Time'][
'i_rec_ndx'].attrs.items():
if att_name not in ('DIMENSION_LIST', 'CLASS', 'NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Time']['i_rec_ndx'][
att_name] = att_val
#-- latitude
IS_gla12_tide['Data_40HZ']['Geolocation']['d_lat'] = lat_40HZ
IS_gla12_fill['Data_40HZ']['Geolocation']['d_lat'] = None
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lat'] = {}
for att_name, att_val in fileID['Data_40HZ']['Geolocation'][
'd_lat'].attrs.items():
if att_name not in ('DIMENSION_LIST', 'CLASS', 'NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lat'][
att_name] = att_val
#-- longitude
IS_gla12_tide['Data_40HZ']['Geolocation']['d_lon'] = lon_40HZ
IS_gla12_fill['Data_40HZ']['Geolocation']['d_lon'] = None
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lon'] = {}
for att_name, att_val in fileID['Data_40HZ']['Geolocation'][
'd_lon'].attrs.items():
if att_name not in ('DIMENSION_LIST', 'CLASS', 'NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lon'][
att_name] = att_val
#-- geophysical variables
#-- computed long-period equilibrium tide
IS_gla12_tide['Data_40HZ']['Geophysical']['d_eqElv'] = tide_lpe
IS_gla12_fill['Data_40HZ']['Geophysical']['d_eqElv'] = None
IS_gla12_tide_attrs['Data_40HZ']['Geophysical']['d_eqElv'] = {}
IS_gla12_tide_attrs['Data_40HZ']['Geophysical']['d_eqElv'][
'units'] = "meters"
IS_gla12_tide_attrs['Data_40HZ']['Geophysical']['d_eqElv']['long_name'] = \
"Long Period Equilibrium Tide"
IS_gla12_tide_attrs['Data_40HZ']['Geophysical']['d_eqElv']['description'] = (
"Long-period "
"equilibrium tidal elevation from the summation of fifteen tidal spectral lines"
)
IS_gla12_tide_attrs['Data_40HZ']['Geophysical']['d_eqElv']['reference'] = \
"https://doi.org/10.1111/j.1365-246X.1973.tb03420.x"
IS_gla12_tide_attrs['Data_40HZ']['Geophysical']['d_eqElv']['coordinates'] = \
"../DS_UTCTime_40"
#-- close the input HDF5 file
fileID.close()
#-- print file information
logger.info('\t{0}'.format(OUTPUT_FILE))
HDF5_GLA12_tide_write(IS_gla12_tide,
IS_gla12_tide_attrs,
FILENAME=os.path.join(DIRECTORY, OUTPUT_FILE),
FILL_VALUE=IS_gla12_fill,
CLOBBER=True)
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, OUTPUT_FILE), MODE)
def compute_tidal_elevations(tide_dir,
input_file,
output_file,
TIDE_MODEL='',
MODE=0775):
#-- read input *.csv file to extract MJD, latitude, longitude and elevation
dtype = dict(names=('MJD', 'lat', 'lon', 'h'),
formats=('f8', 'f8', 'f8', 'f8'))
dinput = np.loadtxt(input_file, delimiter=',', dtype=dtype)
#-- select between tide models
if (TIDE_MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir, 'cats0201_tmd', 'grid_CATS')
model_file = os.path.join(tide_dir, 'cats0201_tmd', 'h0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir, 'CATS2008', 'grid_CATS2008a_opt')
model_file = os.path.join(tide_dir, 'CATS2008', 'hf.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
model_format = 'OTIS'
EPSG = 'CATS2008'
type = 'z'
elif (TIDE_MODEL == 'CATS2008_load'):
grid_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'grid_CATS2008a_opt')
model_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'h_CATS2008a_SPOTL_load')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
model_format = 'OTIS'
EPSG = 'CATS2008'
type = 'z'
elif (MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas')
grid_file = 'grid_tpxo9_atlas.nc.gz'
model_files = [
'h_q1_tpxo9_atlas_30.nc.gz', 'h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz', 'h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz', 'h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz', 'h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz', 'h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz', 'h_2n2_tpxo9_atlas_30.nc.gz'
]
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
model_format = 'netcdf'
type = 'z'
SCALE = 1.0 / 1000.0
elif (MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'grid_tpxo9')
model_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'h_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir, 'tpxo8_atlas',
'grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir, 'tpxo8_atlas',
'hf.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
model_format = 'ATLAS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'grid_tpxo7.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'h_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_load', 'grid_tpxo6.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_load', 'h_tpxo7.2_load')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir, 'aodtm5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aodtm5_tmd', 'h0_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
model_format = 'OTIS'
EPSG = '3996'
type = 'z'
elif (TIDE_MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir, 'aotim5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aotim5_tmd', 'h_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
model_format = 'OTIS'
EPSG = '3996'
type = 'z'
elif (TIDE_MODEL == 'GOT4.7'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.7_load'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'GOT4.8'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.8_load'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'GOT4.10'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.10_load'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 1000.0
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS', 'ATLAS'):
amp, ph, D, c = extract_tidal_constants(dinput['lon'],
dinput['lat'],
grid_file,
model_file,
EPSG,
type,
METHOD='spline')
deltat = np.zeros_like(dinput['MJD'])
elif (model_format == 'netcdf'):
amp, ph, D, c = extract_netcdf_constants(dinput['lon'],
dinput['lat'],
model_directory,
grid_file,
model_files,
type,
METHOD='spline',
SCALE=SCALE)
deltat = np.zeros_like(dinput['MJD'])
elif (model_format == 'GOT'):
amp, ph = extract_GOT_constants(dinput['lon'],
dinput['lat'],
model_directory,
model_files,
METHOD='spline',
SCALE=SCALE)
delta_file = os.path.join(tide_dir, 'deltat.data')
deltat = calc_delta_time(delta_file, dinput['MJD'])
#-- convert phase to radians
cph = -1j * ph * np.pi / 180.0
hc = amp * np.exp(cph)
#-- convert time from MJD to days relative to Jan 1, 1992 (48622 MJD)
#-- predict tidal elevations at time 1 and infer minor corrections
tide = predict_tide_drift(dinput['MJD'] - 48622.0,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model_format)
tide += infer_minor_corrections(dinput['MJD'] - 48622.0,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model_format)
#-- replace invalid values with fill value
fill_value = -9999.0
tide.data[tide.mask] = fill_value
#-- output to file
with open(output_file, 'w') as f:
for d, lt, ln, td in zip(dinput['MJD'], dinput['lat'], dinput['lon'],
tide):
f.write('{0:0.6f},{1:0.2f},{2:0.2f},{3:0.2f}\n'.format(
d, lt, ln, td))
#-- change the permissions level to MODE
os.chmod(output_file, MODE)
def compute_LPET_icebridge_data(arg, VERBOSE=False, MODE=0o775):
#-- extract file name and subsetter indices lists
match_object = re.match(r'(.*?)(\[(.*?)\])?$', arg)
input_file = os.path.expanduser(match_object.group(1))
#-- subset input file to indices
if match_object.group(2):
#-- decompress ranges and add to list
input_subsetter = []
for i in re.findall(r'((\d+)-(\d+)|(\d+))', match_object.group(3)):
input_subsetter.append(int(i[3])) if i[3] else \
input_subsetter.extend(range(int(i[1]),int(i[2])+1))
else:
input_subsetter = None
#-- output directory for input_file
DIRECTORY = os.path.dirname(input_file)
#-- calculate if input files are from ATM or LVIS (+GH)
regex = {}
regex[
'ATM'] = r'(BLATM2|ILATM2)_(\d+)_(\d+)_smooth_nadir(.*?)(csv|seg|pt)$'
regex['ATM1b'] = r'(BLATM1b|ILATM1b)_(\d+)_(\d+)(.*?).(qi|TXT|h5)$'
regex['LVIS'] = r'(BLVIS2|BVLIS2|ILVIS2)_(.*?)(\d+)_(\d+)_(R\d+)_(\d+).H5$'
regex['LVGH'] = r'(ILVGH2)_(.*?)(\d+)_(\d+)_(R\d+)_(\d+).H5$'
for key, val in regex.items():
if re.match(val, os.path.basename(input_file)):
OIB = key
#-- HDF5 file attributes
attrib = dict(lon={}, lat={}, tide_lpe={}, day={})
#-- latitude
attrib['lat']['long_name'] = 'Latitude_of_measurement'
attrib['lat']['description'] = ('Corresponding_to_the_measurement_'
'position_at_the_acquisition_time')
attrib['lat']['units'] = 'Degrees_North'
#-- longitude
attrib['lon']['long_name'] = 'Longitude_of_measurement'
attrib['lon']['description'] = ('Corresponding_to_the_measurement_'
'position_at_the_acquisition_time')
attrib['lon']['units'] = 'Degrees_East'
#-- long-period equilibrium tides
attrib['tide_lpe']['long_name'] = 'Equilibrium_Tide'
attrib['tide_lpe']['description'] = (
'Long-period_equilibrium_tidal_elevation_'
'from_the_summation_of_fifteen_tidal_spectral_lines_at_the_measurement_'
'position_at_the_acquisition_time')
attrib['tide_lpe']['reference'] = ('https://doi.org/10.1111/'
'j.1365-246X.1973.tb03420.x')
attrib['tide_lpe']['units'] = 'meters'
#-- time
attrib['time'] = {}
attrib['time']['long_name'] = 'Time'
attrib['time']['units'] = 'days since 1992-01-01T00:00:00'
attrib['time']['calendar'] = 'standard'
#-- extract information from first input file
#-- acquisition year, month and day
#-- number of points
#-- instrument (PRE-OIB ATM or LVIS, OIB ATM or LVIS)
if OIB in ('ATM', 'ATM1b'):
M1, YYMMDD1, HHMMSS1, AX1, SF1 = re.findall(regex[OIB],
input_file).pop()
#-- early date strings omitted century and millenia (e.g. 93 for 1993)
if (len(YYMMDD1) == 6):
ypre, MM1, DD1 = YYMMDD1[:2], YYMMDD1[2:4], YYMMDD1[4:]
if (np.float(ypre) >= 90):
YY1 = '{0:4.0f}'.format(np.float(ypre) + 1900.0)
else:
YY1 = '{0:4.0f}'.format(np.float(ypre) + 2000.0)
elif (len(YYMMDD1) == 8):
YY1, MM1, DD1 = YYMMDD1[:4], YYMMDD1[4:6], YYMMDD1[6:]
elif OIB in ('LVIS', 'LVGH'):
M1, RG1, YY1, MMDD1, RLD1, SS1 = re.findall(regex[OIB],
input_file).pop()
MM1, DD1 = MMDD1[:2], MMDD1[2:]
#-- read data from input_file
print('{0} -->'.format(input_file)) if VERBOSE else None
if (OIB == 'ATM'):
#-- load IceBridge ATM data from input_file
dinput, file_lines, HEM = read_ATM_icessn_file(input_file,
input_subsetter)
elif (OIB == 'ATM1b'):
#-- load IceBridge Level-1b ATM data from input_file
dinput, file_lines, HEM = read_ATM_qfit_file(input_file,
input_subsetter)
elif OIB in ('LVIS', 'LVGH'):
#-- load IceBridge LVIS data from input_file
dinput, file_lines, HEM = read_LVIS_HDF5_file(input_file,
input_subsetter)
#-- convert time from J2000 to days relative to Jan 1, 1992 (48622mjd)
#-- J2000: seconds since 2000-01-01 12:00:00 UTC
tide_time = pyTMD.time.convert_delta_time(dinput['time'],
epoch1=(2000, 1, 1, 12, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- output tidal HDF5 file
#-- form: rg_NASA_model_EQUILIBRIUM_TIDES_WGS84_fl1yyyymmddjjjjj.H5
#-- where rg is the hemisphere flag (GR or AN) for the region
#-- fl1 and fl2 are the data flags (ATM, LVIS, GLAS)
#-- yymmddjjjjj is the year, month, day and second of the input file
#-- output region flags: GR for Greenland and AN for Antarctica
hem_flag = {'N': 'GR', 'S': 'AN'}
#-- use starting second to distinguish between files for the day
JJ1 = np.min(dinput['time']) % 86400
#-- output file format
file_format = '{0}_NASA_EQUILIBRIUM_TIDES_WGS84_{1}{2}{3}{4}{5:05.0f}.H5'
FILENAME = file_format.format(hem_flag[HEM], OIB, YY1, MM1, DD1, JJ1)
#-- print file information
print('\t{0}'.format(FILENAME)) if VERBOSE else None
#-- open output HDF5 file
fid = h5py.File(os.path.join(DIRECTORY, FILENAME), 'w')
#-- predict long-period equilibrium tides at time
tide_lpe = compute_equilibrium_tide(tide_time + deltat, dinput['lat'])
#-- add latitude and longitude to output file
for key in ['lat', 'lon']:
#-- Defining the HDF5 dataset variables for lat/lon
h5 = fid.create_dataset(key, (file_lines, ),
data=dinput[key][:],
dtype=dinput[key].dtype,
compression='gzip')
#-- add HDF5 variable attributes
for att_name, att_val in attrib[key].items():
h5.attrs[att_name] = att_val
#-- attach dimensions
h5.dims[0].label = 'RECORD_SIZE'
#-- output tides to HDF5 dataset
h5 = fid.create_dataset('tide_lpe', (file_lines, ),
data=tide_lpe,
dtype=tide_lpe.dtype,
compression='gzip')
#-- add HDF5 variable attributes
for att_name, att_val in attrib['tide_lpe'].items():
h5.attrs[att_name] = att_val
#-- attach dimensions
h5.dims[0].label = 'RECORD_SIZE'
#-- output days to HDF5 dataset
h5 = fid.create_dataset('time', (file_lines, ),
data=tide_time,
dtype=tide_time.dtype,
compression='gzip')
#-- add HDF5 variable attributes
for att_name, att_val in attrib['time'].items():
h5.attrs[att_name] = att_val
#-- attach dimensions
h5.dims[0].label = 'RECORD_SIZE'
#-- HDF5 file attributes
fid.attrs['featureType'] = 'trajectory'
fid.attrs['title'] = ('Long-Period_Equilibrium_tidal_correction_for_'
'elevation_measurements')
fid.attrs['summary'] = ('Tidal_correction_computed_at_elevation_'
'measurements_using_fifteen_spectral_lines.')
fid.attrs['project'] = 'NASA_Operation_IceBridge'
fid.attrs['processing_level'] = '4'
fid.attrs['date_created'] = time.strftime('%Y-%m-%d', time.localtime())
#-- add attributes for input files
fid.attrs['elevation_file'] = os.path.basename(input_file)
#-- add geospatial and temporal attributes
fid.attrs['geospatial_lat_min'] = dinput['lat'].min()
fid.attrs['geospatial_lat_max'] = dinput['lat'].max()
fid.attrs['geospatial_lon_min'] = dinput['lon'].min()
fid.attrs['geospatial_lon_max'] = dinput['lon'].max()
fid.attrs['geospatial_lat_units'] = "degrees_north"
fid.attrs['geospatial_lon_units'] = "degrees_east"
fid.attrs['geospatial_ellipsoid'] = "WGS84"
fid.attrs['time_type'] = 'UTC'
#-- convert start/end time from days since 1992-01-01 into Julian days
time_range = np.array([np.min(tide_time), np.max(tide_time)])
time_julian = 2400000.5 + pyTMD.time.convert_delta_time(
time_range,
epoch1=(1992, 1, 1, 0, 0, 0),
epoch2=(1858, 11, 17, 0, 0, 0),
scale=1.0)
#-- convert to calendar date
cal = pyTMD.time.convert_julian(time_julian, ASTYPE=np.int)
#-- add attributes with measurement date start, end and duration
args = (cal['hour'][0], cal['minute'][0], cal['second'][0])
fid.attrs['RangeBeginningTime'] = '{0:02d}:{1:02d}:{2:02d}'.format(*args)
args = (cal['hour'][-1], cal['minute'][-1], cal['second'][-1])
fid.attrs['RangeEndingTime'] = '{0:02d}:{1:02d}:{2:02d}'.format(*args)
args = (cal['year'][0], cal['month'][0], cal['day'][0])
fid.attrs['RangeBeginningDate'] = '{0:4d}-{1:02d}-{2:02d}'.format(*args)
args = (cal['year'][-1], cal['month'][-1], cal['day'][-1])
fid.attrs['RangeEndingDate'] = '{0:4d}-{1:02d}-{2:02d}'.format(*args)
duration = np.round(time_julian[-1] * 86400.0 - time_julian[0] * 86400.0)
fid.attrs['DurationTimeSeconds'] = '{0:0.0f}'.format(duration)
#-- close the output HDF5 dataset
fid.close()
#-- change the permissions level to MODE
os.chmod(os.path.join(DIRECTORY, FILENAME), MODE)
def compute_tides_icebridge_data(tide_dir, arg, TIDE_MODEL,
ATLAS_FORMAT=None, GZIP=True, DEFINITION_FILE=None, METHOD='spline',
EXTRAPOLATE=False, CUTOFF=None, VERBOSE=False, MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logger = pyTMD.utilities.build_logger('pytmd',level=loglevel)
#-- get parameters for tide model
if DEFINITION_FILE is not None:
model = pyTMD.model(tide_dir).from_file(DEFINITION_FILE)
else:
model = pyTMD.model(tide_dir, format=ATLAS_FORMAT,
compressed=GZIP).elevation(TIDE_MODEL)
#-- extract file name and subsetter indices lists
match_object = re.match(r'(.*?)(\[(.*?)\])?$',arg)
input_file = os.path.expanduser(match_object.group(1))
#-- subset input file to indices
if match_object.group(2):
#-- decompress ranges and add to list
input_subsetter = []
for i in re.findall(r'((\d+)-(\d+)|(\d+))',match_object.group(3)):
input_subsetter.append(int(i[3])) if i[3] else \
input_subsetter.extend(range(int(i[1]),int(i[2])+1))
else:
input_subsetter = None
#-- output directory for input_file
DIRECTORY = os.path.dirname(input_file)
#-- calculate if input files are from ATM or LVIS (+GH)
regex = {}
regex['ATM'] = r'(BLATM2|ILATM2)_(\d+)_(\d+)_smooth_nadir(.*?)(csv|seg|pt)$'
regex['ATM1b'] = r'(BLATM1b|ILATM1b)_(\d+)_(\d+)(.*?).(qi|TXT|h5)$'
regex['LVIS'] = r'(BLVIS2|BVLIS2|ILVIS2)_(.*?)(\d+)_(\d+)_(R\d+)_(\d+).H5$'
regex['LVGH'] = r'(ILVGH2)_(.*?)(\d+)_(\d+)_(R\d+)_(\d+).H5$'
for key,val in regex.items():
if re.match(val, os.path.basename(input_file)):
OIB = key
#-- HDF5 file attributes
attrib = collections.OrderedDict()
#-- time
attrib['time'] = {}
attrib['time']['long_name'] = 'Time'
attrib['time']['description'] = ('Time_corresponding_to_the_measurement_'
'position')
attrib['time']['units'] = 'Days since 1992-01-01T00:00:00'
attrib['time']['standard_name'] = 'time'
attrib['time']['calendar'] = 'standard'
#-- latitude
attrib['lat'] = {}
attrib['lat']['long_name'] = 'Latitude_of_measurement'
attrib['lat']['description'] = ('Corresponding_to_the_measurement_'
'position_at_the_acquisition_time')
attrib['lat']['units'] = 'Degrees_North'
#-- longitude
attrib['lon'] = {}
attrib['lon']['long_name'] = 'Longitude_of_measurement'
attrib['lon']['description'] = ('Corresponding_to_the_measurement_'
'position_at_the_acquisition_time')
attrib['lon']['units'] = 'Degrees_East'
#-- tides
attrib[model.variable] = {}
attrib[model.variable]['description'] = model.description
attrib[model.variable]['reference'] = model.reference
attrib[model.variable]['model'] = model.name
attrib[model.variable]['units'] = 'meters'
attrib[model.variable]['long_name'] = model.long_name
#-- extract information from first input file
#-- acquisition year, month and day
#-- number of points
#-- instrument (PRE-OIB ATM or LVIS, OIB ATM or LVIS)
if OIB in ('ATM','ATM1b'):
M1,YYMMDD1,HHMMSS1,AX1,SF1 = re.findall(regex[OIB], input_file).pop()
#-- early date strings omitted century and millenia (e.g. 93 for 1993)
if (len(YYMMDD1) == 6):
ypre,MM1,DD1 = YYMMDD1[:2],YYMMDD1[2:4],YYMMDD1[4:]
if (np.float64(ypre) >= 90):
YY1 = '{0:4.0f}'.format(np.float64(ypre) + 1900.0)
else:
YY1 = '{0:4.0f}'.format(np.float64(ypre) + 2000.0)
elif (len(YYMMDD1) == 8):
YY1,MM1,DD1 = YYMMDD1[:4],YYMMDD1[4:6],YYMMDD1[6:]
elif OIB in ('LVIS','LVGH'):
M1,RG1,YY1,MMDD1,RLD1,SS1 = re.findall(regex[OIB], input_file).pop()
MM1,DD1 = MMDD1[:2],MMDD1[2:]
#-- read data from input_file
logger.info('{0} -->'.format(input_file))
if (OIB == 'ATM'):
#-- load IceBridge ATM data from input_file
dinput,file_lines,HEM = read_ATM_icessn_file(input_file,input_subsetter)
elif (OIB == 'ATM1b'):
#-- load IceBridge Level-1b ATM data from input_file
dinput,file_lines,HEM = read_ATM_qfit_file(input_file,input_subsetter)
elif OIB in ('LVIS','LVGH'):
#-- load IceBridge LVIS data from input_file
dinput,file_lines,HEM = read_LVIS_HDF5_file(input_file,input_subsetter)
#-- convert time from J2000 to days relative to Jan 1, 1992 (48622mjd)
#-- J2000: seconds since 2000-01-01 12:00:00 UTC
t = pyTMD.time.convert_delta_time(dinput['time'],
epoch1=(2000,1,1,12,0,0), epoch2=(1992,1,1,0,0,0),
scale=1.0/86400.0)
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data','merged_deltat.data'])
#-- read tidal constants and interpolate to grid points
if model.format in ('OTIS','ATLAS'):
amp,ph,D,c = extract_tidal_constants(dinput['lon'], dinput['lat'],
model.grid_file, model.model_file, model.projection,
TYPE=model.type, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF, GRID=model.format)
deltat = np.zeros_like(t)
elif model.format in ('netcdf'):
amp,ph,D,c = extract_netcdf_constants(dinput['lon'], dinput['lat'],
model.grid_file, model.model_file, TYPE=model.type, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, CUTOFF=CUTOFF, SCALE=model.scale,
GZIP=model.compressed)
deltat = np.zeros_like(t)
elif (model.format == 'GOT'):
amp,ph,c = extract_GOT_constants(dinput['lon'], dinput['lat'],
model.model_file, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF, SCALE=model.scale, GZIP=model.compressed)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, t)
elif (model.format == 'FES'):
amp,ph = extract_FES_constants(dinput['lon'], dinput['lat'],
model.model_file, TYPE=model.type, VERSION=model.version,
METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE, CUTOFF=CUTOFF,
SCALE=model.scale, GZIP=model.compressed)
#-- available model constituents
c = model.constituents
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, t)
#-- calculate complex phase in radians for Euler's
cph = -1j*ph*np.pi/180.0
#-- calculate constituent oscillation
hc = amp*np.exp(cph)
#-- output tidal HDF5 file
#-- form: rg_NASA_model_TIDES_WGS84_fl1yyyymmddjjjjj.H5
#-- where rg is the hemisphere flag (GR or AN) for the region
#-- model is the tidal model name flag (e.g. CATS0201)
#-- fl1 and fl2 are the data flags (ATM, LVIS, GLAS)
#-- yymmddjjjjj is the year, month, day and second of the input file
#-- output region flags: GR for Greenland and AN for Antarctica
hem_flag = {'N':'GR','S':'AN'}
#-- use starting second to distinguish between files for the day
JJ1 = np.min(dinput['time']) % 86400
#-- output file format
args = (hem_flag[HEM],model.name,OIB,YY1,MM1,DD1,JJ1)
FILENAME = '{0}_NASA_{1}_TIDES_WGS84_{2}{3}{4}{5}{6:05.0f}.H5'.format(*args)
#-- print file information
logger.info('\t{0}'.format(FILENAME))
#-- open output HDF5 file
fid = h5py.File(os.path.join(DIRECTORY,FILENAME), 'w')
#-- predict tidal elevations at time and infer minor corrections
fill_value = -9999.0
tide = np.ma.empty((file_lines),fill_value=fill_value)
tide.mask = np.any(hc.mask,axis=1)
tide.data[:] = predict_tide_drift(t, hc, c,
DELTAT=deltat, CORRECTIONS=model.format)
minor = infer_minor_corrections(t, hc, c,
DELTAT=deltat, CORRECTIONS=model.format)
tide.data[:] += minor.data[:]
#-- replace invalid values with fill value
tide.data[tide.mask] = tide.fill_value
#-- copy tide to output variable
dinput[model.variable] = tide.copy()
#-- output dictionary with HDF5 variables
h5 = {}
#-- add variables to output file
for key,attributes in attrib.items():
#-- Defining the HDF5 dataset variables for lat/lon
h5[key] = fid.create_dataset(key, (file_lines,),
data=dinput[key][:], dtype=dinput[key].dtype,
compression='gzip')
#-- add HDF5 variable attributes
for att_name,att_val in attributes.items():
h5[key].attrs[att_name] = att_val
#-- attach dimensions
if key not in ('time',):
for i,dim in enumerate(['time']):
h5[key].dims[i].label = 'RECORD_SIZE'
h5[key].dims[i].attach_scale(h5[dim])
#-- HDF5 file attributes
fid.attrs['featureType'] = 'trajectory'
fid.attrs['title'] = 'Tidal_correction_for_elevation_measurements'
fid.attrs['summary'] = ('Tidal_correction_computed_at_elevation_'
'measurements_using_a_tidal_model_driver.')
fid.attrs['project'] = 'NASA_Operation_IceBridge'
fid.attrs['processing_level'] = '4'
fid.attrs['date_created'] = time.strftime('%Y-%m-%d',time.localtime())
#-- add attributes for input file
fid.attrs['elevation_file'] = os.path.basename(input_file)
fid.attrs['tide_model'] = model.name
#-- add geospatial and temporal attributes
fid.attrs['geospatial_lat_min'] = dinput['lat'].min()
fid.attrs['geospatial_lat_max'] = dinput['lat'].max()
fid.attrs['geospatial_lon_min'] = dinput['lon'].min()
fid.attrs['geospatial_lon_max'] = dinput['lon'].max()
fid.attrs['geospatial_lat_units'] = "degrees_north"
fid.attrs['geospatial_lon_units'] = "degrees_east"
fid.attrs['geospatial_ellipsoid'] = "WGS84"
fid.attrs['time_type'] = 'UTC'
#-- convert start/end time from days since 1992-01-01 into Julian days
time_range = np.array([np.min(t),np.max(t)])
time_julian = 2400000.5 + pyTMD.time.convert_delta_time(time_range,
epoch1=(1992,1,1,0,0,0), epoch2=(1858,11,17,0,0,0), scale=1.0)
#-- convert to calendar date
cal = pyTMD.time.convert_julian(time_julian,ASTYPE=int)
#-- add attributes with measurement date start, end and duration
args = (cal['hour'][0],cal['minute'][0],cal['second'][0])
fid.attrs['RangeBeginningTime'] = '{0:02d}:{1:02d}:{2:02d}'.format(*args)
args = (cal['hour'][-1],cal['minute'][-1],cal['second'][-1])
fid.attrs['RangeEndingTime'] = '{0:02d}:{1:02d}:{2:02d}'.format(*args)
args = (cal['year'][0],cal['month'][0],cal['day'][0])
fid.attrs['RangeBeginningDate'] = '{0:4d}-{1:02d}-{2:02d}'.format(*args)
args = (cal['year'][-1],cal['month'][-1],cal['day'][-1])
fid.attrs['RangeEndingDate'] = '{0:4d}-{1:02d}-{2:02d}'.format(*args)
duration = np.round(time_julian[-1]*86400.0 - time_julian[0]*86400.0)
fid.attrs['DurationTimeSeconds'] = '{0:0.0f}'.format(duration)
#-- close the output HDF5 dataset
fid.close()
#-- change the permissions level to MODE
os.chmod(os.path.join(DIRECTORY,FILENAME), MODE)
def compute_LPET_elevations(input_file, output_file,
FORMAT='csv', VARIABLES=['time','lat','lon','data'],
TIME_UNITS='days since 1858-11-17T00:00:00', PROJECTION='4326',
VERBOSE=False, MODE=0o775):
#-- output netCDF4 and HDF5 file attributes
#-- will be added to YAML header in csv files
attrib = {}
#-- latitude
attrib['lat'] = {}
attrib['lat']['long_name'] = 'Latitude'
attrib['lat']['units'] = 'Degrees_North'
#-- longitude
attrib['lon'] = {}
attrib['lon']['long_name'] = 'Longitude'
attrib['lon']['units'] = 'Degrees_East'
#-- long-period equilibrium tides
attrib['tide_lpe'] = {}
attrib['tide_lpe']['long_name'] = 'Equilibrium_Tide'
attrib['tide_lpe']['description'] = ('Long-period_equilibrium_tidal_'
'elevation_from_the_summation_of_fifteen_tidal_spectral_lines')
attrib['tide_lpe']['reference'] = ('https://doi.org/10.1111/'
'j.1365-246X.1973.tb03420.x')
attrib['tide_lpe']['units'] = 'meters'
#-- time
attrib['time'] = {}
attrib['time']['long_name'] = 'Time'
attrib['time']['units'] = 'days since 1992-01-01T00:00:00'
attrib['time']['calendar'] = 'standard'
#-- read input file to extract time, spatial coordinates and data
if (FORMAT == 'csv'):
dinput = pyTMD.spatial.from_ascii(input_file, columns=VARIABLES,
header=0, verbose=VERBOSE)
elif (FORMAT == 'netCDF4'):
dinput = pyTMD.spatial.from_netCDF4(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3],
verbose=VERBOSE)
elif (FORMAT == 'HDF5'):
dinput = pyTMD.spatial.from_HDF5(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3],
verbose=VERBOSE)
#-- converting x,y from projection to latitude/longitude
#-- could try to extract projection attributes from netCDF4 and HDF5 files
try:
crs1 = pyproj.CRS.from_string("epsg:{0:d}".format(int(PROJECTION)))
except (ValueError,pyproj.exceptions.CRSError):
crs1 = pyproj.CRS.from_string(PROJECTION)
crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(4326))
transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True)
lon,lat = transformer.transform(dinput['x'].flatten(),dinput['y'].flatten())
#-- extract time units from netCDF4 and HDF5 attributes or from TIME_UNITS
try:
time_string = dinput['attributes']['time']['units']
except (TypeError, KeyError):
epoch1,to_secs = pyTMD.time.parse_date_string(TIME_UNITS)
else:
epoch1,to_secs = pyTMD.time.parse_date_string(time_string)
#-- convert time from units to days since 1992-01-01T00:00:00
tide_time = pyTMD.time.convert_delta_time(to_secs*dinput['time'].flatten(),
epoch1=epoch1, epoch2=(1992,1,1,0,0,0), scale=1.0/86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data','merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- predict long-period equilibrium tides at time
tide_lpe = compute_equilibrium_tide(tide_time + deltat, lat)
#-- output to file
output = dict(time=tide_time,lon=lon,lat=lat,tide_lpe=tide_lpe)
if (FORMAT == 'csv'):
pyTMD.spatial.to_ascii(output, attrib, output_file, delimiter=',',
columns=['time','lat','lon','tide_lpe'], verbose=VERBOSE)
elif (FORMAT == 'netCDF4'):
pyTMD.spatial.to_netCDF4(output, attrib, output_file, verbose=VERBOSE)
elif (FORMAT == 'HDF5'):
pyTMD.spatial.to_HDF5(output, attrib, output_file, verbose=VERBOSE)
#-- change the permissions level to MODE
os.chmod(output_file, MODE)
def compute_tides_ICESat(tide_dir, INPUT_FILE, TIDE_MODEL=None,
ATLAS_FORMAT=None, GZIP=True, DEFINITION_FILE=None, METHOD='spline',
EXTRAPOLATE=False, CUTOFF=None, VERBOSE=False, MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logger = pyTMD.utilities.build_logger('pytmd',level=loglevel)
#-- get parameters for tide model
if DEFINITION_FILE is not None:
model = pyTMD.model(tide_dir).from_file(DEFINITION_FILE)
else:
model = pyTMD.model(tide_dir, format=ATLAS_FORMAT,
compressed=GZIP).elevation(TIDE_MODEL)
#-- get directory from INPUT_FILE
logger.info('{0} -->'.format(INPUT_FILE))
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- compile regular expression operator for extracting information from file
rx = re.compile((r'GLAH(\d{2})_(\d{3})_(\d{1})(\d{1})(\d{2})_(\d{3})_'
r'(\d{4})_(\d{1})_(\d{2})_(\d{4})\.H5'), re.VERBOSE)
#-- extract parameters from ICESat/GLAS HDF5 file name
#-- PRD: Product number (01, 05, 06, 12, 13, 14, or 15)
#-- RL: Release number for process that created the product = 634
#-- RGTP: Repeat ground-track phase (1=8-day, 2=91-day, 3=transfer orbit)
#-- ORB: Reference orbit number (starts at 1 and increments each time a
#-- new reference orbit ground track file is obtained.)
#-- INST: Instance number (increments every time the satellite enters a
#-- different reference orbit)
#-- CYCL: Cycle of reference orbit for this phase
#-- TRK: Track within reference orbit
#-- SEG: Segment of orbit
#-- GRAN: Granule version number
#-- TYPE: File type
try:
PRD,RL,RGTP,ORB,INST,CYCL,TRK,SEG,GRAN,TYPE = rx.findall(INPUT_FILE).pop()
except:
#-- output tide HDF5 file (generic)
fileBasename,fileExtension = os.path.splitext(INPUT_FILE)
args = (fileBasename,model.name,fileExtension)
OUTPUT_FILE = '{0}_{1}_TIDES{2}'.format(*args)
else:
#-- output tide HDF5 file for NSIDC granules
args = (PRD,RL,model.name,RGTP,ORB,INST,CYCL,TRK,SEG,GRAN,TYPE)
file_format = 'GLAH{0}_{1}_{2}_TIDES_{3}{4}{5}_{6}_{7}_{8}_{9}_{10}.h5'
OUTPUT_FILE = file_format.format(*args)
#-- read GLAH12 HDF5 file
fileID = h5py.File(INPUT_FILE,'r')
n_40HZ, = fileID['Data_40HZ']['Time']['i_rec_ndx'].shape
#-- get variables and attributes
rec_ndx_40HZ = fileID['Data_40HZ']['Time']['i_rec_ndx'][:].copy()
#-- seconds since 2000-01-01 12:00:00 UTC (J2000)
DS_UTCTime_40HZ = fileID['Data_40HZ']['DS_UTCTime_40'][:].copy()
#-- Latitude (degrees North)
lat_TPX = fileID['Data_40HZ']['Geolocation']['d_lat'][:].copy()
#-- Longitude (degrees East)
lon_40HZ = fileID['Data_40HZ']['Geolocation']['d_lon'][:].copy()
#-- Elevation (height above TOPEX/Poseidon ellipsoid in meters)
elev_TPX = fileID['Data_40HZ']['Elevation_Surfaces']['d_elev'][:].copy()
fv = fileID['Data_40HZ']['Elevation_Surfaces']['d_elev'].attrs['_FillValue']
#-- semimajor axis (a) and flattening (f) for TP and WGS84 ellipsoids
atop,ftop = (6378136.3,1.0/298.257)
awgs,fwgs = (6378137.0,1.0/298.257223563)
#-- convert from Topex/Poseidon to WGS84 Ellipsoids
lat_40HZ,elev_40HZ = pyTMD.spatial.convert_ellipsoid(lat_TPX, elev_TPX,
atop, ftop, awgs, fwgs, eps=1e-12, itmax=10)
#-- convert time from J2000 to days relative to Jan 1, 1992 (48622mjd)
#-- J2000: seconds since 2000-01-01 12:00:00 UTC
tide_time = pyTMD.time.convert_delta_time(DS_UTCTime_40HZ,
epoch1=(2000,1,1,12,0,0), epoch2=(1992,1,1,0,0,0), scale=1.0/86400.0)
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data','merged_deltat.data'])
#-- read tidal constants and interpolate to grid points
if model.format in ('OTIS','ATLAS'):
amp,ph,D,c = extract_tidal_constants(lon_40HZ, lat_40HZ,
model.grid_file, model.model_file, model.projection, TYPE=TYPE,
METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF, GRID=model.format)
deltat = np.zeros_like(tide_time)
elif (model.format == 'netcdf'):
amp,ph,D,c = extract_netcdf_constants(lon_40HZ, lat_40HZ,
model.grid_file, model.model_file, TYPE=TYPE, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, CUTOFF=CUTOFF, SCALE=model.scale,
GZIP=model.compressed)
deltat = np.zeros_like(tide_time)
elif (model.format == 'GOT'):
amp,ph,c = extract_GOT_constants(lon_40HZ, lat_40HZ,
model.model_file, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF, SCALE=model.scale, GZIP=model.compressed)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
elif (model.format == 'FES'):
amp,ph = extract_FES_constants(lon_40HZ, lat_40HZ,
model.model_file, TYPE=TYPE, VERSION=model.version,
METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE, CUTOFF=CUTOFF,
SCALE=model.scale, GZIP=model.compressed)
#-- available model constituents
c = model.constituents
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j*ph*np.pi/180.0
#-- calculate constituent oscillation
hc = amp*np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
tide = np.ma.empty((n_40HZ),fill_value=fv)
tide.mask = np.any(hc.mask,axis=1)
tide.data[:] = predict_tide_drift(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model.format)
minor = infer_minor_corrections(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model.format)
tide.data[:] += minor.data[:]
#-- replace masked and nan values with fill value
invalid, = np.nonzero(np.isnan(tide.data) | tide.mask)
tide.data[invalid] = tide.fill_value
tide.mask[invalid] = True
#-- copy variables for outputting to HDF5 file
IS_gla12_tide = dict(Data_40HZ={})
IS_gla12_fill = dict(Data_40HZ={})
IS_gla12_tide_attrs = dict(Data_40HZ={})
#-- copy global file attributes of interest
global_attribute_list = ['featureType','title','comment','summary','license',
'references','AccessConstraints','CitationforExternalPublication',
'contributor_role','contributor_name','creator_name','creator_email',
'publisher_name','publisher_email','publisher_url','platform','instrument',
'processing_level','date_created','spatial_coverage_type','history',
'keywords','keywords_vocabulary','naming_authority','project','time_type',
'date_type','time_coverage_start','time_coverage_end',
'time_coverage_duration','source','HDFVersion','identifier_product_type',
'identifier_product_format_version','Conventions','institution',
'ReprocessingPlanned','ReprocessingActual','LocalGranuleID',
'ProductionDateTime','LocalVersionID','PGEVersion','OrbitNumber',
'StartOrbitNumber','StopOrbitNumber','EquatorCrossingLongitude',
'EquatorCrossingTime','EquatorCrossingDate','ShortName','VersionID',
'InputPointer','RangeBeginningTime','RangeEndingTime','RangeBeginningDate',
'RangeEndingDate','PercentGroundHit','OrbitQuality','Cycle','Track',
'Instrument_State','Timing_Bias','ReferenceOrbit','SP_ICE_PATH_NO',
'SP_ICE_GLAS_StartBlock','SP_ICE_GLAS_EndBlock','Instance','Range_Bias',
'Instrument_State_Date','Instrument_State_Time','Range_Bias_Date',
'Range_Bias_Time','Timing_Bias_Date','Timing_Bias_Time',
'identifier_product_doi','identifier_file_uuid',
'identifier_product_doi_authority']
for att in global_attribute_list:
IS_gla12_tide_attrs[att] = fileID.attrs[att]
#-- copy ICESat campaign name from ancillary data
IS_gla12_tide_attrs['Campaign'] = fileID['ANCILLARY_DATA'].attrs['Campaign']
#-- add attributes for input GLA12 file
IS_gla12_tide_attrs['input_files'] = os.path.basename(INPUT_FILE)
#-- update geospatial ranges for ellipsoid
IS_gla12_tide_attrs['geospatial_lat_min'] = np.min(lat_40HZ)
IS_gla12_tide_attrs['geospatial_lat_max'] = np.max(lat_40HZ)
IS_gla12_tide_attrs['geospatial_lon_min'] = np.min(lon_40HZ)
IS_gla12_tide_attrs['geospatial_lon_max'] = np.max(lon_40HZ)
IS_gla12_tide_attrs['geospatial_lat_units'] = "degrees_north"
IS_gla12_tide_attrs['geospatial_lon_units'] = "degrees_east"
IS_gla12_tide_attrs['geospatial_ellipsoid'] = "WGS84"
#-- copy 40Hz group attributes
for att_name,att_val in fileID['Data_40HZ'].attrs.items():
IS_gla12_tide_attrs['Data_40HZ'][att_name] = att_val
#-- copy attributes for time, geolocation and geophysical groups
for var in ['Time','Geolocation','Geophysical']:
IS_gla12_tide['Data_40HZ'][var] = {}
IS_gla12_fill['Data_40HZ'][var] = {}
IS_gla12_tide_attrs['Data_40HZ'][var] = {}
for att_name,att_val in fileID['Data_40HZ'][var].attrs.items():
IS_gla12_tide_attrs['Data_40HZ'][var][att_name] = att_val
#-- J2000 time
IS_gla12_tide['Data_40HZ']['DS_UTCTime_40'] = DS_UTCTime_40HZ
IS_gla12_fill['Data_40HZ']['DS_UTCTime_40'] = None
IS_gla12_tide_attrs['Data_40HZ']['DS_UTCTime_40'] = {}
for att_name,att_val in fileID['Data_40HZ']['DS_UTCTime_40'].attrs.items():
if att_name not in ('DIMENSION_LIST','CLASS','NAME'):
IS_gla12_tide_attrs['Data_40HZ']['DS_UTCTime_40'][att_name] = att_val
#-- record
IS_gla12_tide['Data_40HZ']['Time']['i_rec_ndx'] = rec_ndx_40HZ
IS_gla12_fill['Data_40HZ']['Time']['i_rec_ndx'] = None
IS_gla12_tide_attrs['Data_40HZ']['Time']['i_rec_ndx'] = {}
IS_gla12_tide_attrs['Data_40HZ']['Time']['i_rec_ndx']['coordinates'] = \
"../DS_UTCTime_40"
for att_name,att_val in fileID['Data_40HZ']['Time']['i_rec_ndx'].attrs.items():
if att_name not in ('DIMENSION_LIST','CLASS','NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Time']['i_rec_ndx'][att_name] = att_val
#-- latitude
IS_gla12_tide['Data_40HZ']['Geolocation']['d_lat'] = lat_40HZ
IS_gla12_fill['Data_40HZ']['Geolocation']['d_lat'] = None
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lat'] = {}
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lat']['coordinates'] = \
"../DS_UTCTime_40"
for att_name,att_val in fileID['Data_40HZ']['Geolocation']['d_lat'].attrs.items():
if att_name not in ('DIMENSION_LIST','CLASS','NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lat'][att_name] = att_val
#-- longitude
IS_gla12_tide['Data_40HZ']['Geolocation']['d_lon'] = lon_40HZ
IS_gla12_fill['Data_40HZ']['Geolocation']['d_lon'] = None
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lon'] = {}
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lon']['coordinates'] = \
"../DS_UTCTime_40"
for att_name,att_val in fileID['Data_40HZ']['Geolocation']['d_lon'].attrs.items():
if att_name not in ('DIMENSION_LIST','CLASS','NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lon'][att_name] = att_val
#-- geophysical variables
#-- computed tide
IS_gla12_tide['Data_40HZ']['Geophysical'][model.gla12] = tide
IS_gla12_fill['Data_40HZ']['Geophysical'][model.gla12] = tide.fill_value
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][model.gla12] = {}
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][model.gla12]['units'] = "meters"
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][model.gla12]['long_name'] = model.long_name
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][model.gla12]['description'] = model.description
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][model.gla12]['source'] = model.name
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][model.gla12]['reference'] = model.reference
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][model.gla12]['coordinates'] = \
"../DS_UTCTime_40"
#-- close the input HDF5 file
fileID.close()
#-- print file information
logger.info('\t{0}'.format(OUTPUT_FILE))
HDF5_GLA12_tide_write(IS_gla12_tide, IS_gla12_tide_attrs,
FILENAME=os.path.join(DIRECTORY,OUTPUT_FILE),
FILL_VALUE=IS_gla12_fill, CLOBBER=True)
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY,OUTPUT_FILE), MODE)
def compute_tides_ICESat2(tide_dir,
FILE,
TIDE_MODEL=None,
METHOD='spline',
EXTRAPOLATE=False,
VERBOSE=False,
MODE=0o775):
#-- select between tide models
if (TIDE_MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir, 'cats0201_tmd', 'grid_CATS')
model_file = os.path.join(tide_dir, 'cats0201_tmd', 'h0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir, 'CATS2008', 'grid_CATS2008')
model_file = os.path.join(tide_dir, 'CATS2008', 'hf.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008_load'):
grid_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'grid_CATS2008a_opt')
model_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'h_CATS2008a_SPOTL_load')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas')
grid_file = 'grid_tpxo9_atlas.nc.gz'
model_files = [
'h_q1_tpxo9_atlas_30.nc.gz', 'h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz', 'h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz', 'h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz', 'h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz', 'h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz', 'h_2n2_tpxo9_atlas_30.nc.gz'
]
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'TPXO9-atlas-v2'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas_v2')
grid_file = 'grid_tpxo9_atlas_30_v2.nc.gz'
model_files = [
'h_q1_tpxo9_atlas_30_v2.nc.gz', 'h_o1_tpxo9_atlas_30_v2.nc.gz',
'h_p1_tpxo9_atlas_30_v2.nc.gz', 'h_k1_tpxo9_atlas_30_v2.nc.gz',
'h_n2_tpxo9_atlas_30_v2.nc.gz', 'h_m2_tpxo9_atlas_30_v2.nc.gz',
'h_s2_tpxo9_atlas_30_v2.nc.gz', 'h_k2_tpxo9_atlas_30_v2.nc.gz',
'h_m4_tpxo9_atlas_30_v2.nc.gz', 'h_ms4_tpxo9_atlas_30_v2.nc.gz',
'h_mn4_tpxo9_atlas_30_v2.nc.gz', 'h_2n2_tpxo9_atlas_30_v2.nc.gz'
]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'TPXO9-atlas-v3'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas_v3')
grid_file = 'grid_tpxo9_atlas_30_v3.nc.gz'
model_files = [
'h_q1_tpxo9_atlas_30_v3.nc.gz', 'h_o1_tpxo9_atlas_30_v3.nc.gz',
'h_p1_tpxo9_atlas_30_v3.nc.gz', 'h_k1_tpxo9_atlas_30_v3.nc.gz',
'h_n2_tpxo9_atlas_30_v3.nc.gz', 'h_m2_tpxo9_atlas_30_v3.nc.gz',
'h_s2_tpxo9_atlas_30_v3.nc.gz', 'h_k2_tpxo9_atlas_30_v3.nc.gz',
'h_m4_tpxo9_atlas_30_v3.nc.gz', 'h_ms4_tpxo9_atlas_30_v3.nc.gz',
'h_mn4_tpxo9_atlas_30_v3.nc.gz', 'h_2n2_tpxo9_atlas_30_v3.nc.gz',
'h_mf_tpxo9_atlas_30_v3.nc.gz', 'h_mm_tpxo9_atlas_30_v3.nc.gz'
]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'grid_tpxo9')
model_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'h_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir, 'tpxo8_atlas',
'grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir, 'tpxo8_atlas',
'hf.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'ATLAS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'grid_tpxo7.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'h_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_load', 'grid_tpxo6.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_load', 'h_tpxo7.2_load')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir, 'aodtm5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aodtm5_tmd', 'h0_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir, 'aotim5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aotim5_tmd', 'h_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5-2018'):
grid_file = os.path.join(tide_dir, 'Arc5km2018', 'grid_Arc5km2018')
model_file = os.path.join(tide_dir, 'Arc5km2018', 'h_Arc5km2018')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'GOT4.7'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.7_load'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'GOT4.8'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.8_load'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'GOT4.10'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.10_load'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'FES2014'):
model_directory = os.path.join(tide_dir, 'fes2014', 'ocean_tide')
model_files = [
'2n2.nc.gz', 'eps2.nc.gz', 'j1.nc.gz', 'k1.nc.gz', 'k2.nc.gz',
'l2.nc.gz', 'la2.nc.gz', 'm2.nc.gz', 'm3.nc.gz', 'm4.nc.gz',
'm6.nc.gz', 'm8.nc.gz', 'mf.nc.gz', 'mks2.nc.gz', 'mm.nc.gz',
'mn4.nc.gz', 'ms4.nc.gz', 'msf.nc.gz', 'msqm.nc.gz', 'mtm.nc.gz',
'mu2.nc.gz', 'n2.nc.gz', 'n4.nc.gz', 'nu2.nc.gz', 'o1.nc.gz',
'p1.nc.gz', 'q1.nc.gz', 'r2.nc.gz', 's1.nc.gz', 's2.nc.gz',
's4.nc.gz', 'sa.nc.gz', 'ssa.nc.gz', 't2.nc.gz'
]
c = [
'2n2', 'eps2', 'j1', 'k1', 'k2', 'l2', 'lambda2', 'm2', 'm3', 'm4',
'm6', 'm8', 'mf', 'mks2', 'mm', 'mn4', 'ms4', 'msf', 'msqm', 'mtm',
'mu2', 'n2', 'n4', 'nu2', 'o1', 'p1', 'q1', 'r2', 's1', 's2', 's4',
'sa', 'ssa', 't2'
]
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'FES2014_load'):
model_directory = os.path.join(tide_dir, 'fes2014', 'load_tide')
model_files = [
'2n2.nc.gz', 'eps2.nc.gz', 'j1.nc.gz', 'k1.nc.gz', 'k2.nc.gz',
'l2.nc.gz', 'la2.nc.gz', 'm2.nc.gz', 'm3.nc.gz', 'm4.nc.gz',
'm6.nc.gz', 'm8.nc.gz', 'mf.nc.gz', 'mks2.nc.gz', 'mm.nc.gz',
'mn4.nc.gz', 'ms4.nc.gz', 'msf.nc.gz', 'msqm.nc.gz', 'mtm.nc.gz',
'mu2.nc.gz', 'n2.nc.gz', 'n4.nc.gz', 'nu2.nc.gz', 'o1.nc.gz',
'p1.nc.gz', 'q1.nc.gz', 'r2.nc.gz', 's1.nc.gz', 's2.nc.gz',
's4.nc.gz', 'sa.nc.gz', 'ssa.nc.gz', 't2.nc.gz'
]
c = [
'2n2', 'eps2', 'j1', 'k1', 'k2', 'l2', 'lambda2', 'm2', 'm3', 'm4',
'm6', 'm8', 'mf', 'mks2', 'mm', 'mn4', 'ms4', 'msf', 'msqm', 'mtm',
'mu2', 'n2', 'n4', 'nu2', 'o1', 'p1', 'q1', 'r2', 's1', 's2', 's4',
'sa', 'ssa', 't2'
]
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0 / 100.0
#-- read data from FILE
print('{0} -->'.format(os.path.basename(FILE))) if VERBOSE else None
IS2_atl11_mds, IS2_atl11_attrs, IS2_atl11_pairs = read_HDF5_ATL11(
FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 file name
rx = re.compile(r'(processed_)?(ATL\d{2})_(\d{4})(\d{2})_(\d{2})(\d{2})_'
r'(\d{3})_(\d{2})(.*?).h5$')
SUB, PRD, TRK, GRAN, SCYC, ECYC, RL, VERS, AUX = rx.findall(FILE).pop()
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl11_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- copy variables for outputting to HDF5 file
IS2_atl11_tide = {}
IS2_atl11_fill = {}
IS2_atl11_dims = {}
IS2_atl11_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl11_tide['ancillary_data'] = {}
IS2_atl11_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl11_tide['ancillary_data'][key] = IS2_atl11_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl11_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl11_attrs['ancillary_data'][key].items(
):
IS2_atl11_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam pair within the file
for ptx in sorted(IS2_atl11_pairs):
#-- output data dictionaries for beam
IS2_atl11_tide[ptx] = dict(cycle_stats={})
IS2_atl11_fill[ptx] = dict(cycle_stats={})
IS2_atl11_dims[ptx] = dict(cycle_stats={})
IS2_atl11_tide_attrs[ptx] = dict(cycle_stats={})
#-- number of average segments and number of included cycles
invalid_time = IS2_atl11_attrs[ptx]['delta_time']['_FillValue']
n_points, n_cycles = IS2_atl11_mds[ptx]['delta_time'].shape
#-- find valid average segments for beam pair
fv = IS2_atl11_attrs[ptx]['h_corr']['_FillValue']
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + IS2_atl11_mds[ptx]['delta_time']
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(gps_seconds - leap_seconds,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS', 'ATLAS'):
amp, ph, D, c = extract_tidal_constants(
IS2_atl11_mds[ptx]['longitude'],
IS2_atl11_mds[ptx]['latitude'],
grid_file,
model_file,
EPSG,
TYPE=TYPE,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
GRID=model_format)
deltat = np.zeros_like(tide_time)
elif (model_format == 'netcdf'):
amp, ph, D, c = extract_netcdf_constants(
IS2_atl11_mds[ptx]['longitude'],
IS2_atl11_mds[ptx]['latitude'],
model_directory,
grid_file,
model_files,
TYPE=TYPE,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
SCALE=SCALE)
deltat = np.zeros_like(tide_time)
elif (model_format == 'GOT'):
amp, ph = extract_GOT_constants(IS2_atl11_mds[ptx]['longitude'],
IS2_atl11_mds[ptx]['latitude'],
model_directory,
model_files,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
SCALE=SCALE)
#-- interpolate delta times from calendar dates to tide time
delta_file = pyTMD.utilities.get_data_path(
['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
elif (model_format == 'FES'):
amp, ph = extract_FES_constants(IS2_atl11_mds[ptx]['longitude'],
IS2_atl11_mds[ptx]['latitude'],
model_directory,
model_files,
TYPE=TYPE,
VERSION=TIDE_MODEL,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
SCALE=SCALE)
#-- interpolate delta times from calendar dates to tide time
delta_file = pyTMD.utilities.get_data_path(
['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j * ph * np.pi / 180.0
#-- calculate constituent oscillation
hc = amp * np.exp(cph)
#-- allocate for each cycle
tide = np.ma.empty((n_points, n_cycles), fill_value=fv)
tide.mask = (IS2_atl11_mds[ptx]['delta_time'] == invalid_time)
for cycle in range(n_cycles):
#-- find valid time and spatial points for cycle
tide.mask[:, cycle] |= np.any(hc.mask, axis=1)
valid, = np.nonzero(~tide.mask[:, cycle])
#-- predict tidal elevations and infer minor corrections
tide.data[valid,
cycle] = predict_tide_drift(tide_time[valid, cycle],
hc[valid, :],
c,
DELTAT=deltat[valid, cycle],
CORRECTIONS=model_format)
minor = infer_minor_corrections(tide_time[valid, cycle],
hc[valid, :],
c,
DELTAT=deltat[valid, cycle],
CORRECTIONS=model_format)
tide.data[valid, cycle] += minor.data[:]
#-- replace masked and nan values with fill value
invalid = np.nonzero(np.isnan(tide.data) | tide.mask)
tide.data[invalid] = tide.fill_value
tide.mask[invalid] = True
#-- group attributes for beam
IS2_atl11_tide_attrs[ptx]['description'] = (
'Contains the primary science parameters for this '
'data set')
IS2_atl11_tide_attrs[ptx]['beam_pair'] = IS2_atl11_attrs[ptx][
'beam_pair']
IS2_atl11_tide_attrs[ptx]['ReferenceGroundTrack'] = IS2_atl11_attrs[
ptx]['ReferenceGroundTrack']
IS2_atl11_tide_attrs[ptx]['first_cycle'] = IS2_atl11_attrs[ptx][
'first_cycle']
IS2_atl11_tide_attrs[ptx]['last_cycle'] = IS2_atl11_attrs[ptx][
'last_cycle']
IS2_atl11_tide_attrs[ptx]['equatorial_radius'] = IS2_atl11_attrs[ptx][
'equatorial_radius']
IS2_atl11_tide_attrs[ptx]['polar_radius'] = IS2_atl11_attrs[ptx][
'polar_radius']
#-- geolocation, time and reference point
#-- cycle_number
IS2_atl11_tide[ptx]['cycle_number'] = IS2_atl11_mds[ptx][
'cycle_number'].copy()
IS2_atl11_fill[ptx]['cycle_number'] = None
IS2_atl11_dims[ptx]['cycle_number'] = None
IS2_atl11_tide_attrs[ptx]['cycle_number'] = {}
IS2_atl11_tide_attrs[ptx]['cycle_number']['units'] = "1"
IS2_atl11_tide_attrs[ptx]['cycle_number'][
'long_name'] = "Orbital cycle number"
IS2_atl11_tide_attrs[ptx]['cycle_number']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['cycle_number']['description'] = (
"Number of 91-day periods "
"that have elapsed since ICESat-2 entered the science orbit. Each of the 1,387 "
"reference ground track (RGTs) is targeted in the polar regions once "
"every 91 days.")
#-- delta time
IS2_atl11_tide[ptx]['delta_time'] = IS2_atl11_mds[ptx][
'delta_time'].copy()
IS2_atl11_fill[ptx]['delta_time'] = IS2_atl11_attrs[ptx]['delta_time'][
'_FillValue']
IS2_atl11_dims[ptx]['delta_time'] = ['ref_pt', 'cycle_number']
IS2_atl11_tide_attrs[ptx]['delta_time'] = {}
IS2_atl11_tide_attrs[ptx]['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl11_tide_attrs[ptx]['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl11_tide_attrs[ptx]['delta_time']['standard_name'] = "time"
IS2_atl11_tide_attrs[ptx]['delta_time']['calendar'] = "standard"
IS2_atl11_tide_attrs[ptx]['delta_time']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['delta_time']['description'] = (
"Number of GPS "
"seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset "
"is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds "
"between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By "
"adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the "
"time in gps_seconds relative to the GPS epoch can be computed.")
IS2_atl11_tide_attrs[ptx]['delta_time']['coordinates'] = \
"ref_pt cycle_number latitude longitude"
#-- latitude
IS2_atl11_tide[ptx]['latitude'] = IS2_atl11_mds[ptx]['latitude'].copy()
IS2_atl11_fill[ptx]['latitude'] = IS2_atl11_attrs[ptx]['latitude'][
'_FillValue']
IS2_atl11_dims[ptx]['latitude'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx]['latitude'] = {}
IS2_atl11_tide_attrs[ptx]['latitude']['units'] = "degrees_north"
IS2_atl11_tide_attrs[ptx]['latitude'][
'contentType'] = "physicalMeasurement"
IS2_atl11_tide_attrs[ptx]['latitude']['long_name'] = "Latitude"
IS2_atl11_tide_attrs[ptx]['latitude']['standard_name'] = "latitude"
IS2_atl11_tide_attrs[ptx]['latitude']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['latitude']['description'] = (
"Center latitude of "
"selected segments")
IS2_atl11_tide_attrs[ptx]['latitude']['valid_min'] = -90.0
IS2_atl11_tide_attrs[ptx]['latitude']['valid_max'] = 90.0
IS2_atl11_tide_attrs[ptx]['latitude']['coordinates'] = \
"ref_pt delta_time longitude"
#-- longitude
IS2_atl11_tide[ptx]['longitude'] = IS2_atl11_mds[ptx][
'longitude'].copy()
IS2_atl11_fill[ptx]['longitude'] = IS2_atl11_attrs[ptx]['longitude'][
'_FillValue']
IS2_atl11_dims[ptx]['longitude'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx]['longitude'] = {}
IS2_atl11_tide_attrs[ptx]['longitude']['units'] = "degrees_east"
IS2_atl11_tide_attrs[ptx]['longitude'][
'contentType'] = "physicalMeasurement"
IS2_atl11_tide_attrs[ptx]['longitude']['long_name'] = "Longitude"
IS2_atl11_tide_attrs[ptx]['longitude']['standard_name'] = "longitude"
IS2_atl11_tide_attrs[ptx]['longitude']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['longitude']['description'] = (
"Center longitude of "
"selected segments")
IS2_atl11_tide_attrs[ptx]['longitude']['valid_min'] = -180.0
IS2_atl11_tide_attrs[ptx]['longitude']['valid_max'] = 180.0
IS2_atl11_tide_attrs[ptx]['longitude']['coordinates'] = \
"ref_pt delta_time latitude"
#-- reference point
IS2_atl11_tide[ptx]['ref_pt'] = IS2_atl11_mds[ptx]['ref_pt'].copy()
IS2_atl11_fill[ptx]['ref_pt'] = None
IS2_atl11_dims[ptx]['ref_pt'] = None
IS2_atl11_tide_attrs[ptx]['ref_pt'] = {}
IS2_atl11_tide_attrs[ptx]['ref_pt']['units'] = "1"
IS2_atl11_tide_attrs[ptx]['ref_pt'][
'contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx]['ref_pt'][
'long_name'] = "Reference point number"
IS2_atl11_tide_attrs[ptx]['ref_pt']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['ref_pt']['description'] = (
"The reference point is the 7 digit segment_id "
"number corresponding to the center of the ATL06 data used for each ATL11 point. These are "
"sequential, starting with 1 for the first segment after an ascending equatorial crossing node."
)
IS2_atl11_tide_attrs[ptx]['ref_pt']['coordinates'] = \
"delta_time latitude longitude"
#-- cycle statistics variables
IS2_atl11_tide_attrs[ptx]['cycle_stats']['Description'] = (
"The cycle_stats subgroup "
"contains summary information about segments for each reference point, including "
"the uncorrected mean heights for reference surfaces, blowing snow and cloud "
"indicators, and geolocation and height misfit statistics.")
IS2_atl11_tide_attrs[ptx]['cycle_stats']['data_rate'] = (
"Data within this group "
"are stored at the average segment rate.")
#-- computed tide
IS2_atl11_tide[ptx]['cycle_stats'][variable] = tide
IS2_atl11_fill[ptx]['cycle_stats'][variable] = tide.fill_value
IS2_atl11_dims[ptx]['cycle_stats'][variable] = [
'ref_pt', 'cycle_number'
]
IS2_atl11_tide_attrs[ptx]['cycle_stats'][variable] = {}
IS2_atl11_tide_attrs[ptx]['cycle_stats'][variable]['units'] = "meters"
IS2_atl11_tide_attrs[ptx]['cycle_stats'][variable][
'contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx]['cycle_stats'][variable][
'long_name'] = long_name
IS2_atl11_tide_attrs[ptx]['cycle_stats'][variable][
'description'] = description
IS2_atl11_tide_attrs[ptx]['cycle_stats'][variable][
'source'] = TIDE_MODEL
IS2_atl11_tide_attrs[ptx]['cycle_stats'][variable][
'reference'] = reference
IS2_atl11_tide_attrs[ptx]['cycle_stats'][variable]['coordinates'] = \
"../ref_pt ../cycle_number ../delta_time ../latitude ../longitude"
#-- output tidal HDF5 file
args = (PRD, TIDE_MODEL, TRK, GRAN, SCYC, ECYC, RL, VERS, AUX)
file_format = '{0}_{1}_TIDES_{2}{3}_{4}{5}_{6}_{7}{8}.h5'
#-- print file information
print('\t{0}'.format(file_format.format(*args))) if VERBOSE else None
HDF5_ATL11_tide_write(IS2_atl11_tide,
IS2_atl11_tide_attrs,
CLOBBER=True,
INPUT=os.path.basename(FILE),
FILL_VALUE=IS2_atl11_fill,
DIMENSIONS=IS2_atl11_dims,
FILENAME=os.path.join(DIRECTORY,
file_format.format(*args)))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, file_format.format(*args)), MODE)
def compute_LPET_ICESat2(FILE, VERBOSE=False, MODE=0o775):
#-- read data from FILE
print('{0} -->'.format(os.path.basename(FILE))) if VERBOSE else None
IS2_atl07_mds, IS2_atl07_attrs, IS2_atl07_beams = read_HDF5_ATL07(
FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 sea ice file name
rx = re.compile(
r'(processed_)?(ATL\d{2})-(\d{2})_(\d{4})(\d{2})(\d{2})'
r'(\d{2})(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$'
)
SUB, PRD, HEM, YY, MM, DD, HH, MN, SS, TRK, CYCL, SN, RL, VERS, AUX = rx.findall(
FILE).pop()
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl07_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- copy variables for outputting to HDF5 file
IS2_atl07_tide = {}
IS2_atl07_fill = {}
IS2_atl07_dims = {}
IS2_atl07_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl07_tide['ancillary_data'] = {}
IS2_atl07_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl07_tide['ancillary_data'][key] = IS2_atl07_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl07_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl07_attrs['ancillary_data'][key].items(
):
IS2_atl07_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam within the file
for gtx in sorted(IS2_atl07_beams):
#-- output data dictionaries for beam
IS2_atl07_tide[gtx] = dict(sea_ice_segments={})
IS2_atl07_fill[gtx] = dict(sea_ice_segments={})
IS2_atl07_dims[gtx] = dict(sea_ice_segments={})
IS2_atl07_tide_attrs[gtx] = dict(sea_ice_segments={})
#-- number of segments
val = IS2_atl07_mds[gtx]['sea_ice_segments']
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + val['delta_time']
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(gps_seconds - leap_seconds,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- predict long-period equilibrium tides at latitudes and time
tide_lpe = compute_equilibrium_tide(tide_time + deltat,
val['latitude'])
#-- group attributes for beam
IS2_atl07_tide_attrs[gtx]['Description'] = IS2_atl07_attrs[gtx][
'Description']
IS2_atl07_tide_attrs[gtx]['atlas_pce'] = IS2_atl07_attrs[gtx][
'atlas_pce']
IS2_atl07_tide_attrs[gtx]['atlas_beam_type'] = IS2_atl07_attrs[gtx][
'atlas_beam_type']
IS2_atl07_tide_attrs[gtx]['groundtrack_id'] = IS2_atl07_attrs[gtx][
'groundtrack_id']
IS2_atl07_tide_attrs[gtx]['atmosphere_profile'] = IS2_atl07_attrs[gtx][
'atmosphere_profile']
IS2_atl07_tide_attrs[gtx]['atlas_spot_number'] = IS2_atl07_attrs[gtx][
'atlas_spot_number']
IS2_atl07_tide_attrs[gtx]['sc_orientation'] = IS2_atl07_attrs[gtx][
'sc_orientation']
#-- group attributes for sea_ice_segments
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['Description'] = (
"Top group for sea "
"ice segments as computed by the ATBD algorithm.")
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['data_rate'] = (
"Data within this "
"group are stored at the variable segment rate.")
#-- geolocation, time and segment ID
#-- delta time
IS2_atl07_tide[gtx]['sea_ice_segments']['delta_time'] = val[
'delta_time'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['delta_time'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['delta_time'] = None
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time'][
'standard_name'] = "time"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time'][
'source'] = "telemetry"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time'][
'calendar'] = "standard"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['description'] = (
"Number of "
"GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch "
"offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS "
"seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP "
"epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time "
"parameters, the time in gps_seconds relative to the GPS epoch can be computed."
)
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['coordinates'] = \
"height_segment_id latitude longitude"
#-- latitude
IS2_atl07_tide[gtx]['sea_ice_segments']['latitude'] = val[
'latitude'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['latitude'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['latitude'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'][
'units'] = "degrees_north"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'][
'contentType'] = "physicalMeasurement"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'][
'long_name'] = "Latitude"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'][
'standard_name'] = "latitude"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'][
'description'] = ("Latitude of "
"segment center")
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'][
'valid_min'] = -90.0
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'][
'valid_max'] = 90.0
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['coordinates'] = \
"height_segment_id delta_time longitude"
#-- longitude
IS2_atl07_tide[gtx]['sea_ice_segments']['longitude'] = val[
'longitude'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['longitude'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['longitude'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'][
'units'] = "degrees_east"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'][
'contentType'] = "physicalMeasurement"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'][
'long_name'] = "Longitude"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'][
'standard_name'] = "longitude"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'][
'description'] = ("Longitude of "
"segment center")
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'][
'valid_min'] = -180.0
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'][
'valid_max'] = 180.0
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['coordinates'] = \
"height_segment_id delta_time latitude"
#-- segment ID
IS2_atl07_tide[gtx]['sea_ice_segments']['height_segment_id'] = val[
'height_segment_id']
IS2_atl07_fill[gtx]['sea_ice_segments']['height_segment_id'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['height_segment_id'] = [
'delta_time'
]
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id'][
'units'] = "1"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id'][
'contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id']['long_name'] = \
"Identifier of each height segment"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id']['description'] = \
"Identifier of each height segment"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id']['coordinates'] = \
"delta_time latitude longitude"
#-- geolocation segment beginning
IS2_atl07_tide[gtx]['sea_ice_segments']['geoseg_beg'] = val[
'geoseg_beg'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['geoseg_beg'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['geoseg_beg'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg'][
'units'] = "1"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg'][
'contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg'][
'long_name'] = "Beginning GEOSEG"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg']['description'] = \
"Geolocation segment (geoseg) ID associated with the first photon used in this sea ice segment"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg']['coordinates'] = \
"height_segment_id delta_time latitude longitude"
#-- geolocation segment ending
IS2_atl07_tide[gtx]['sea_ice_segments']['geoseg_end'] = val[
'geoseg_end'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['geoseg_end'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['geoseg_end'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end'][
'units'] = "1"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end'][
'contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end'][
'long_name'] = "Ending GEOSEG"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end']['description'] = \
"Geolocation segment (geoseg) ID associated with the last photon used in this sea ice segment"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end']['coordinates'] = \
"height_segment_id delta_time latitude longitude"
#-- along track distance
IS2_atl07_tide[gtx]['sea_ice_segments']['seg_dist_x'] = val[
'seg_dist_x'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['seg_dist_x'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['seg_dist_x'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x'][
'units'] = "meters"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x'][
'contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x'][
'long_name'] = "Along track distance"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x']['description'] = \
"Along-track distance from the equator crossing to the segment center."
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x']['coordinates'] = \
"height_segment_id delta_time latitude longitude"
#-- geophysical variables
IS2_atl07_tide[gtx]['sea_ice_segments']['geophysical'] = {}
IS2_atl07_fill[gtx]['sea_ice_segments']['geophysical'] = {}
IS2_atl07_dims[gtx]['sea_ice_segments']['geophysical'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][
'Description'] = (
"Contains geophysical "
"parameters and corrections used to correct photon heights for geophysical effects, such as tides."
)
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][
'data_rate'] = ("Data within this group "
"are stored at the sea_ice_height segment rate.")
#-- computed long-period equilibrium tide
IS2_atl07_tide[gtx]['sea_ice_segments']['geophysical'][
'height_segment_lpe'] = tide_lpe
IS2_atl07_fill[gtx]['sea_ice_segments']['geophysical'][
'height_segment_lpe'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['geophysical'][
'height_segment_lpe'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][
'height_segment_lpe'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][
'height_segment_lpe']['units'] = "meters"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][
'height_segment_lpe']['contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical']['height_segment_lpe']['long_name'] = \
"Long Period Equilibrium Tide"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][
'height_segment_lpe']['description'] = (
"Long-period "
"equilibrium tidal elevation from the summation of fifteen tidal spectral lines"
)
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical']['height_segment_lpe']['reference'] = \
"https://doi.org/10.1111/j.1365-246X.1973.tb03420.x"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical']['height_segment_lpe']['coordinates'] = \
"../height_segment_id ../delta_time ../latitude ../longitude"
#-- output equilibrium tide HDF5 file
args = (PRD, HEM, YY, MM, DD, HH, MN, SS, TRK, CYCL, SN, RL, VERS, AUX)
ff = '{0}-{1}_LPET_{2}{3}{4}{5}{6}{7}_{8}{9}{10}_{11}_{12}{13}.h5'
#-- print file information
print('\t{0}'.format(ff.format(*args))) if VERBOSE else None
HDF5_ATL07_tide_write(IS2_atl07_tide,
IS2_atl07_tide_attrs,
CLOBBER=True,
INPUT=os.path.basename(FILE),
FILL_VALUE=IS2_atl07_fill,
DIMENSIONS=IS2_atl07_dims,
FILENAME=os.path.join(DIRECTORY, ff.format(*args)))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, ff.format(*args)), MODE)
def compute_LPET_ICESat2(INPUT_FILE, VERBOSE=False, MODE=0o775):
#-- read data from input file
print('{0} -->'.format(os.path.basename(INPUT_FILE))) if VERBOSE else None
IS2_atl06_mds, IS2_atl06_attrs, IS2_atl06_beams = read_HDF5_ATL06(
INPUT_FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 file name
rx = re.compile(
r'(processed_)?(ATL\d{2})_(\d{4})(\d{2})(\d{2})(\d{2})'
r'(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$')
try:
SUB, PRD, YY, MM, DD, HH, MN, SS, TRK, CYCL, GRAN, RL, VERS, AUX = rx.findall(
INPUT_FILE).pop()
except:
#-- output long-period equilibrium tide HDF5 file (generic)
fileBasename, fileExtension = os.path.splitext(INPUT_FILE)
OUTPUT_FILE = '{0}_{1}{2}'.format(fileBasename, 'LPET', fileExtension)
else:
#-- output long-period equilibrium tide HDF5 file for ASAS/NSIDC granules
args = (PRD, YY, MM, DD, HH, MN, SS, TRK, CYCL, GRAN, RL, VERS, AUX)
file_format = '{0}_LPET_{1}{2}{3}{4}{5}{6}_{7}{8}{9}_{10}_{11}{12}.h5'
OUTPUT_FILE = file_format.format(*args)
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl06_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- copy variables for outputting to HDF5 file
IS2_atl06_tide = {}
IS2_atl06_fill = {}
IS2_atl06_dims = {}
IS2_atl06_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl06_tide['ancillary_data'] = {}
IS2_atl06_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl06_tide['ancillary_data'][key] = IS2_atl06_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl06_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl06_attrs['ancillary_data'][key].items(
):
IS2_atl06_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam within the file
for gtx in sorted(IS2_atl06_beams):
#-- output data dictionaries for beam
IS2_atl06_tide[gtx] = dict(land_ice_segments={})
IS2_atl06_fill[gtx] = dict(land_ice_segments={})
IS2_atl06_dims[gtx] = dict(land_ice_segments={})
IS2_atl06_tide_attrs[gtx] = dict(land_ice_segments={})
#-- number of segments
val = IS2_atl06_mds[gtx]['land_ice_segments']
n_seg = len(val['segment_id'])
#-- find valid segments for beam
fv = IS2_atl06_attrs[gtx]['land_ice_segments']['h_li']['_FillValue']
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + val['delta_time']
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(gps_seconds - leap_seconds,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- predict long-period equilibrium tides at latitudes and time
tide_lpe = np.ma.zeros((n_seg), fill_value=fv)
tide_lpe.data[:] = compute_equilibrium_tide(tide_time + deltat,
val['latitude'])
tide_lpe.mask = (val['latitude'] == fv) | (val['delta_time'] == fv)
#-- group attributes for beam
IS2_atl06_tide_attrs[gtx]['Description'] = IS2_atl06_attrs[gtx][
'Description']
IS2_atl06_tide_attrs[gtx]['atlas_pce'] = IS2_atl06_attrs[gtx][
'atlas_pce']
IS2_atl06_tide_attrs[gtx]['atlas_beam_type'] = IS2_atl06_attrs[gtx][
'atlas_beam_type']
IS2_atl06_tide_attrs[gtx]['groundtrack_id'] = IS2_atl06_attrs[gtx][
'groundtrack_id']
IS2_atl06_tide_attrs[gtx]['atmosphere_profile'] = IS2_atl06_attrs[gtx][
'atmosphere_profile']
IS2_atl06_tide_attrs[gtx]['atlas_spot_number'] = IS2_atl06_attrs[gtx][
'atlas_spot_number']
IS2_atl06_tide_attrs[gtx]['sc_orientation'] = IS2_atl06_attrs[gtx][
'sc_orientation']
#-- group attributes for land_ice_segments
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['Description'] = (
"The land_ice_segments group "
"contains the primary set of derived products. This includes geolocation, height, and "
"standard error and quality measures for each segment. This group is sparse, meaning "
"that parameters are provided only for pairs of segments for which at least one beam "
"has a valid surface-height measurement.")
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['data_rate'] = (
"Data within this group are "
"sparse. Data values are provided only for those ICESat-2 20m segments where at "
"least one beam has a valid land ice height measurement.")
#-- geolocation, time and segment ID
#-- delta time
delta_time = np.ma.array(val['delta_time'],
fill_value=fv,
mask=(val['delta_time'] == fv))
IS2_atl06_tide[gtx]['land_ice_segments']['delta_time'] = delta_time
IS2_atl06_fill[gtx]['land_ice_segments'][
'delta_time'] = delta_time.fill_value
IS2_atl06_dims[gtx]['land_ice_segments']['delta_time'] = None
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'standard_name'] = "time"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'calendar'] = "standard"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'description'] = (
"Number of GPS "
"seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset "
"is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds "
"between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By "
"adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the "
"time in gps_seconds relative to the GPS epoch can be computed."
)
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time']['coordinates'] = \
"segment_id latitude longitude"
#-- latitude
latitude = np.ma.array(val['latitude'],
fill_value=fv,
mask=(val['latitude'] == fv))
IS2_atl06_tide[gtx]['land_ice_segments']['latitude'] = latitude
IS2_atl06_fill[gtx]['land_ice_segments'][
'latitude'] = latitude.fill_value
IS2_atl06_dims[gtx]['land_ice_segments']['latitude'] = ['delta_time']
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'units'] = "degrees_north"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'contentType'] = "physicalMeasurement"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'long_name'] = "Latitude"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'standard_name'] = "latitude"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'description'] = ("Latitude of "
"segment center")
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'valid_min'] = -90.0
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'valid_max'] = 90.0
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude']['coordinates'] = \
"segment_id delta_time longitude"
#-- longitude
longitude = np.ma.array(val['longitude'],
fill_value=fv,
mask=(val['longitude'] == fv))
IS2_atl06_tide[gtx]['land_ice_segments']['longitude'] = longitude
IS2_atl06_fill[gtx]['land_ice_segments'][
'longitude'] = longitude.fill_value
IS2_atl06_dims[gtx]['land_ice_segments']['longitude'] = ['delta_time']
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'units'] = "degrees_east"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'contentType'] = "physicalMeasurement"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'long_name'] = "Longitude"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'standard_name'] = "longitude"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'description'] = ("Longitude of "
"segment center")
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'valid_min'] = -180.0
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'valid_max'] = 180.0
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude']['coordinates'] = \
"segment_id delta_time latitude"
#-- segment ID
IS2_atl06_tide[gtx]['land_ice_segments']['segment_id'] = val[
'segment_id']
IS2_atl06_fill[gtx]['land_ice_segments']['segment_id'] = None
IS2_atl06_dims[gtx]['land_ice_segments']['segment_id'] = ['delta_time']
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'][
'units'] = "1"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'][
'contentType'] = "referenceInformation"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'][
'long_name'] = "Along-track segment ID number"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'][
'description'] = (
"A 7 digit number "
"identifying the along-track geolocation segment number. These are sequential, starting with "
"1 for the first segment after an ascending equatorial crossing node. Equal to the segment_id for "
"the second of the two 20m ATL03 segments included in the 40m ATL06 segment"
)
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id']['coordinates'] = \
"delta_time latitude longitude"
#-- geophysical variables
IS2_atl06_tide[gtx]['land_ice_segments']['geophysical'] = {}
IS2_atl06_fill[gtx]['land_ice_segments']['geophysical'] = {}
IS2_atl06_dims[gtx]['land_ice_segments']['geophysical'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
'Description'] = (
"The geophysical group "
"contains parameters used to correct segment heights for geophysical effects, parameters "
"related to solar background and parameters indicative of the presence or absence of clouds."
)
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
'data_rate'] = (
"Data within this group "
"are stored at the land_ice_segments segment rate.")
#-- computed long-period equilibrium tide
IS2_atl06_tide[gtx]['land_ice_segments']['geophysical'][
'tide_equilibrium'] = tide_lpe
IS2_atl06_fill[gtx]['land_ice_segments']['geophysical'][
'tide_equilibrium'] = tide_lpe.fill_value
IS2_atl06_dims[gtx]['land_ice_segments']['geophysical'][
'tide_equilibrium'] = ['delta_time']
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
'tide_equilibrium'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
'tide_equilibrium']['units'] = "meters"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
'tide_equilibrium']['contentType'] = "referenceInformation"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical']['tide_equilibrium']['long_name'] = \
"Long Period Equilibrium Tide"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
'tide_equilibrium']['description'] = (
"Long-period "
"equilibrium tidal elevation from the summation of fifteen tidal spectral lines"
)
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical']['tide_equilibrium']['reference'] = \
"https://doi.org/10.1111/j.1365-246X.1973.tb03420.x"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical']['tide_equilibrium']['coordinates'] = \
"../segment_id ../delta_time ../latitude ../longitude"
#-- print file information
print('\t{0}'.format(OUTPUT_FILE)) if VERBOSE else None
HDF5_ATL06_tide_write(IS2_atl06_tide,
IS2_atl06_tide_attrs,
CLOBBER=True,
INPUT=os.path.basename(INPUT_FILE),
FILL_VALUE=IS2_atl06_fill,
DIMENSIONS=IS2_atl06_dims,
FILENAME=os.path.join(DIRECTORY, OUTPUT_FILE))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, OUTPUT_FILE), MODE)
def compute_tidal_elevations(tide_dir, input_file, output_file,
TIDE_MODEL=None, ATLAS_FORMAT='netcdf', GZIP=True,
DEFINITION_FILE=None, FORMAT='csv', VARIABLES=[], HEADER=0,
TYPE='drift', TIME_UNITS='days since 1858-11-17T00:00:00',
TIME_STANDARD='UTC', TIME=None, PROJECTION='4326', METHOD='spline',
EXTRAPOLATE=False, CUTOFF=None, VERBOSE=False, MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logging.basicConfig(level=loglevel)
#-- get parameters for tide model
if DEFINITION_FILE is not None:
model = pyTMD.model(tide_dir).from_file(DEFINITION_FILE)
else:
model = pyTMD.model(tide_dir, format=ATLAS_FORMAT,
compressed=GZIP).elevation(TIDE_MODEL)
output_variable = model.variable
#-- invalid value
fill_value = -9999.0
#-- output netCDF4 and HDF5 file attributes
#-- will be added to YAML header in csv files
attrib = {}
#-- latitude
attrib['lat'] = {}
attrib['lat']['long_name'] = 'Latitude'
attrib['lat']['units'] = 'Degrees_North'
#-- longitude
attrib['lon'] = {}
attrib['lon']['long_name'] = 'Longitude'
attrib['lon']['units'] = 'Degrees_East'
#-- tides
attrib[output_variable] = {}
attrib[output_variable]['description'] = model.description
attrib[output_variable]['reference'] = model.reference
attrib[output_variable]['model'] = model.name
attrib[output_variable]['units'] = 'meters'
attrib[output_variable]['long_name'] = model.long_name
attrib[output_variable]['_FillValue'] = fill_value
#-- time
attrib['time'] = {}
attrib['time']['long_name'] = 'Time'
attrib['time']['units'] = 'days since 1992-01-01T00:00:00'
attrib['time']['calendar'] = 'standard'
#-- read input file to extract time, spatial coordinates and data
if (FORMAT == 'csv'):
dinput = pyTMD.spatial.from_ascii(input_file, columns=VARIABLES,
header=HEADER)
elif (FORMAT == 'netCDF4'):
dinput = pyTMD.spatial.from_netCDF4(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3])
elif (FORMAT == 'HDF5'):
dinput = pyTMD.spatial.from_HDF5(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3])
elif (FORMAT == 'geotiff'):
dinput = pyTMD.spatial.from_geotiff(input_file)
#-- copy global geotiff attributes for projection and grid parameters
for att_name in ['projection','wkt','spacing','extent']:
attrib[att_name] = dinput['attributes'][att_name]
#-- update time variable if entered as argument
if TIME is not None:
dinput['time'] = np.copy(TIME)
#-- converting x,y from projection to latitude/longitude
crs1 = get_projection(dinput['attributes'], PROJECTION)
crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(4326))
transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True)
if (TYPE == 'grid'):
ny,nx = (len(dinput['y']),len(dinput['x']))
gridx,gridy = np.meshgrid(dinput['x'],dinput['y'])
lon,lat = transformer.transform(gridx,gridy)
elif (TYPE == 'drift'):
lon,lat = transformer.transform(dinput['x'],dinput['y'])
#-- extract time units from netCDF4 and HDF5 attributes or from TIME_UNITS
try:
time_string = dinput['attributes']['time']['units']
epoch1,to_secs = pyTMD.time.parse_date_string(time_string)
except (TypeError, KeyError, ValueError):
epoch1,to_secs = pyTMD.time.parse_date_string(TIME_UNITS)
#-- convert time to seconds
delta_time = to_secs*dinput['time'].flatten()
#-- calculate leap seconds if specified
if (TIME_STANDARD.upper() == 'GPS'):
GPS_Epoch_Time = pyTMD.time.convert_delta_time(0, epoch1=epoch1,
epoch2=(1980,1,6,0,0,0), scale=1.0)
GPS_Time = pyTMD.time.convert_delta_time(delta_time, epoch1=epoch1,
epoch2=(1980,1,6,0,0,0), scale=1.0)
#-- calculate difference in leap seconds from start of epoch
leap_seconds = pyTMD.time.count_leap_seconds(GPS_Time) - \
pyTMD.time.count_leap_seconds(np.atleast_1d(GPS_Epoch_Time))
elif (TIME_STANDARD.upper() == 'LORAN'):
#-- LORAN time is ahead of GPS time by 9 seconds
GPS_Epoch_Time = pyTMD.time.convert_delta_time(-9.0, epoch1=epoch1,
epoch2=(1980,1,6,0,0,0), scale=1.0)
GPS_Time = pyTMD.time.convert_delta_time(delta_time-9.0, epoch1=epoch1,
epoch2=(1980,1,6,0,0,0), scale=1.0)
#-- calculate difference in leap seconds from start of epoch
leap_seconds = pyTMD.time.count_leap_seconds(GPS_Time) - \
pyTMD.time.count_leap_seconds(np.atleast_1d(GPS_Epoch_Time))
elif (TIME_STANDARD.upper() == 'TAI'):
#-- TAI time is ahead of GPS time by 19 seconds
GPS_Epoch_Time = pyTMD.time.convert_delta_time(-19.0, epoch1=epoch1,
epoch2=(1980,1,6,0,0,0), scale=1.0)
GPS_Time = pyTMD.time.convert_delta_time(delta_time-19.0, epoch1=epoch1,
epoch2=(1980,1,6,0,0,0), scale=1.0)
#-- calculate difference in leap seconds from start of epoch
leap_seconds = pyTMD.time.count_leap_seconds(GPS_Time) - \
pyTMD.time.count_leap_seconds(np.atleast_1d(GPS_Epoch_Time))
else:
leap_seconds = 0.0
#-- convert time from units to days since 1992-01-01T00:00:00
tide_time = pyTMD.time.convert_delta_time(delta_time-leap_seconds,
epoch1=epoch1, epoch2=(1992,1,1,0,0,0), scale=1.0/86400.0)
#-- number of time points
nt = len(tide_time)
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data','merged_deltat.data'])
#-- read tidal constants and interpolate to grid points
if model.format in ('OTIS','ATLAS'):
amp,ph,D,c = extract_tidal_constants(lon.flatten(), lat.flatten(),
model.grid_file, model.model_file, model.projection,
TYPE=model.type, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF, GRID=model.format)
deltat = np.zeros((nt))
elif (model.format == 'netcdf'):
amp,ph,D,c = extract_netcdf_constants(lon.flatten(), lat.flatten(),
model.grid_file, model.model_file, TYPE=model.type,
METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE, CUTOFF=CUTOFF,
SCALE=model.scale, GZIP=model.compressed)
deltat = np.zeros((nt))
elif (model.format == 'GOT'):
amp,ph,c = extract_GOT_constants(lon.flatten(), lat.flatten(),
model.model_file, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF, SCALE=model.scale, GZIP=model.compressed)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file,tide_time)
elif (model.format == 'FES'):
amp,ph = extract_FES_constants(lon.flatten(), lat.flatten(),
model.model_file, TYPE=model.type, VERSION=model.version,
METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE, CUTOFF=CUTOFF,
SCALE=model.scale, GZIP=model.compressed)
#-- available model constituents
c = model.constituents
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file,tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j*ph*np.pi/180.0
#-- calculate constituent oscillation
hc = amp*np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
if (TYPE == 'grid'):
tide = np.ma.zeros((ny,nx,nt),fill_value=fill_value)
tide.mask = np.zeros((ny,nx,nt),dtype=bool)
for i in range(nt):
TIDE = predict_tide(tide_time[i], hc, c,
DELTAT=deltat[i], CORRECTIONS=model.format)
MINOR = infer_minor_corrections(tide_time[i], hc, c,
DELTAT=deltat[i], CORRECTIONS=model.format)
#-- add major and minor components and reform grid
tide[:,:,i] = np.reshape((TIDE+MINOR), (ny,nx))
tide.mask[:,:,i] = np.reshape((TIDE.mask | MINOR.mask), (ny,nx))
elif (TYPE == 'drift'):
tide = np.ma.zeros((nt), fill_value=fill_value)
tide.mask = np.any(hc.mask,axis=1)
tide.data[:] = predict_tide_drift(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model.format)
minor = infer_minor_corrections(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model.format)
tide.data[:] += minor.data[:]
#-- replace invalid values with fill value
tide.data[tide.mask] = tide.fill_value
#-- output to file
output = {'time':tide_time,'lon':lon,'lat':lat,output_variable:tide}
if (FORMAT == 'csv'):
pyTMD.spatial.to_ascii(output, attrib, output_file, delimiter=',',
columns=['time','lat','lon',output_variable])
elif (FORMAT == 'netCDF4'):
pyTMD.spatial.to_netCDF4(output, attrib, output_file)
elif (FORMAT == 'HDF5'):
pyTMD.spatial.to_HDF5(output, attrib, output_file)
elif (FORMAT == 'geotiff'):
pyTMD.spatial.to_geotiff(output, attrib, output_file,
varname=output_variable)
#-- change the permissions level to MODE
os.chmod(output_file, MODE)
def compute_LPET_ICESat2(FILE, VERBOSE=False, MODE=0o775):
#-- read data from FILE
print('{0} -->'.format(os.path.basename(FILE))) if VERBOSE else None
IS2_atl11_mds, IS2_atl11_attrs, IS2_atl11_pairs = read_HDF5_ATL11(
FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 file name
rx = re.compile(r'(processed_)?(ATL\d{2})_(\d{4})(\d{2})_(\d{2})(\d{2})_'
r'(\d{3})_(\d{2})(.*?).h5$')
SUB, PRD, TRK, GRAN, SCYC, ECYC, RL, VERS, AUX = rx.findall(FILE).pop()
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl11_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- copy variables for outputting to HDF5 file
IS2_atl11_tide = {}
IS2_atl11_fill = {}
IS2_atl11_dims = {}
IS2_atl11_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl11_tide['ancillary_data'] = {}
IS2_atl11_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl11_tide['ancillary_data'][key] = IS2_atl11_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl11_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl11_attrs['ancillary_data'][key].items(
):
IS2_atl11_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam pair within the file
for ptx in sorted(IS2_atl11_pairs):
#-- output data dictionaries for beam
IS2_atl11_tide[ptx] = dict(cycle_stats={})
IS2_atl11_fill[ptx] = dict(cycle_stats={})
IS2_atl11_dims[ptx] = dict(cycle_stats={})
IS2_atl11_tide_attrs[ptx] = dict(cycle_stats={})
#-- number of average segments and number of included cycles
invalid_time = IS2_atl11_attrs[ptx]['delta_time']['_FillValue']
n_points, n_cycles = IS2_atl11_mds[ptx]['delta_time'].shape
#-- latitudinal values
lat = IS2_atl11_mds[ptx]['latitude'].copy()
#-- find valid average segments for beam pair
fv = IS2_atl11_attrs[ptx]['h_corr']['_FillValue']
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + IS2_atl11_mds[ptx]['delta_time']
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(gps_seconds - leap_seconds,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data', 'merged_deltat.data'])
deltat = calc_delta_time(delta_file, tide_time)
#-- allocate for each cycle
tide_lpe = np.ma.empty((n_points, n_cycles), fill_value=fv)
tide_lpe.mask = (IS2_atl11_mds[ptx]['delta_time'] == invalid_time)
for cycle in range(n_cycles):
#-- find valid time and spatial points for cycle
valid, = np.nonzero(~tide_lpe.mask[:, cycle])
#-- predict long-period equilibrium tides at latitudes and time
t = tide_time[valid, cycle] + deltat[valid, cycle]
tide_lpe.data[valid,
cycle] = compute_equilibrium_tide(t, lat[valid])
#-- replace masked and nan values with fill value
invalid = np.nonzero(np.isnan(tide_lpe.data) | tide_lpe.mask)
tide_lpe.data[invalid] = tide_lpe.fill_value
tide_lpe.mask[invalid] = True
#-- group attributes for beam
IS2_atl11_tide_attrs[ptx]['description'] = (
'Contains the primary science parameters for this '
'data set')
IS2_atl11_tide_attrs[ptx]['beam_pair'] = IS2_atl11_attrs[ptx][
'beam_pair']
IS2_atl11_tide_attrs[ptx]['ReferenceGroundTrack'] = IS2_atl11_attrs[
ptx]['ReferenceGroundTrack']
IS2_atl11_tide_attrs[ptx]['first_cycle'] = IS2_atl11_attrs[ptx][
'first_cycle']
IS2_atl11_tide_attrs[ptx]['last_cycle'] = IS2_atl11_attrs[ptx][
'last_cycle']
IS2_atl11_tide_attrs[ptx]['equatorial_radius'] = IS2_atl11_attrs[ptx][
'equatorial_radius']
IS2_atl11_tide_attrs[ptx]['polar_radius'] = IS2_atl11_attrs[ptx][
'polar_radius']
#-- geolocation, time and reference point
#-- cycle_number
IS2_atl11_tide[ptx]['cycle_number'] = IS2_atl11_mds[ptx][
'cycle_number'].copy()
IS2_atl11_fill[ptx]['cycle_number'] = None
IS2_atl11_dims[ptx]['cycle_number'] = None
IS2_atl11_tide_attrs[ptx]['cycle_number'] = {}
IS2_atl11_tide_attrs[ptx]['cycle_number']['units'] = "1"
IS2_atl11_tide_attrs[ptx]['cycle_number'][
'long_name'] = "Orbital cycle number"
IS2_atl11_tide_attrs[ptx]['cycle_number']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['cycle_number']['description'] = (
"Number of 91-day periods "
"that have elapsed since ICESat-2 entered the science orbit. Each of the 1,387 "
"reference ground track (RGTs) is targeted in the polar regions once "
"every 91 days.")
#-- delta time
IS2_atl11_tide[ptx]['delta_time'] = IS2_atl11_mds[ptx][
'delta_time'].copy()
IS2_atl11_fill[ptx]['delta_time'] = IS2_atl11_attrs[ptx]['delta_time'][
'_FillValue']
IS2_atl11_dims[ptx]['delta_time'] = ['ref_pt', 'cycle_number']
IS2_atl11_tide_attrs[ptx]['delta_time'] = {}
IS2_atl11_tide_attrs[ptx]['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl11_tide_attrs[ptx]['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl11_tide_attrs[ptx]['delta_time']['standard_name'] = "time"
IS2_atl11_tide_attrs[ptx]['delta_time']['calendar'] = "standard"
IS2_atl11_tide_attrs[ptx]['delta_time']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['delta_time']['description'] = (
"Number of GPS "
"seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset "
"is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds "
"between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By "
"adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the "
"time in gps_seconds relative to the GPS epoch can be computed.")
IS2_atl11_tide_attrs[ptx]['delta_time']['coordinates'] = \
"ref_pt cycle_number latitude longitude"
#-- latitude
IS2_atl11_tide[ptx]['latitude'] = IS2_atl11_mds[ptx]['latitude'].copy()
IS2_atl11_fill[ptx]['latitude'] = IS2_atl11_attrs[ptx]['latitude'][
'_FillValue']
IS2_atl11_dims[ptx]['latitude'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx]['latitude'] = {}
IS2_atl11_tide_attrs[ptx]['latitude']['units'] = "degrees_north"
IS2_atl11_tide_attrs[ptx]['latitude'][
'contentType'] = "physicalMeasurement"
IS2_atl11_tide_attrs[ptx]['latitude']['long_name'] = "Latitude"
IS2_atl11_tide_attrs[ptx]['latitude']['standard_name'] = "latitude"
IS2_atl11_tide_attrs[ptx]['latitude']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['latitude']['description'] = (
"Center latitude of "
"selected segments")
IS2_atl11_tide_attrs[ptx]['latitude']['valid_min'] = -90.0
IS2_atl11_tide_attrs[ptx]['latitude']['valid_max'] = 90.0
IS2_atl11_tide_attrs[ptx]['latitude']['coordinates'] = \
"ref_pt delta_time longitude"
#-- longitude
IS2_atl11_tide[ptx]['longitude'] = IS2_atl11_mds[ptx][
'longitude'].copy()
IS2_atl11_fill[ptx]['longitude'] = IS2_atl11_attrs[ptx]['longitude'][
'_FillValue']
IS2_atl11_dims[ptx]['longitude'] = ['ref_pt']
IS2_atl11_tide_attrs[ptx]['longitude'] = {}
IS2_atl11_tide_attrs[ptx]['longitude']['units'] = "degrees_east"
IS2_atl11_tide_attrs[ptx]['longitude'][
'contentType'] = "physicalMeasurement"
IS2_atl11_tide_attrs[ptx]['longitude']['long_name'] = "Longitude"
IS2_atl11_tide_attrs[ptx]['longitude']['standard_name'] = "longitude"
IS2_atl11_tide_attrs[ptx]['longitude']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['longitude']['description'] = (
"Center longitude of "
"selected segments")
IS2_atl11_tide_attrs[ptx]['longitude']['valid_min'] = -180.0
IS2_atl11_tide_attrs[ptx]['longitude']['valid_max'] = 180.0
IS2_atl11_tide_attrs[ptx]['longitude']['coordinates'] = \
"ref_pt delta_time latitude"
#-- reference point
IS2_atl11_tide[ptx]['ref_pt'] = IS2_atl11_mds[ptx]['ref_pt'].copy()
IS2_atl11_fill[ptx]['ref_pt'] = None
IS2_atl11_dims[ptx]['ref_pt'] = None
IS2_atl11_tide_attrs[ptx]['ref_pt'] = {}
IS2_atl11_tide_attrs[ptx]['ref_pt']['units'] = "1"
IS2_atl11_tide_attrs[ptx]['ref_pt'][
'contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx]['ref_pt'][
'long_name'] = "Reference point number"
IS2_atl11_tide_attrs[ptx]['ref_pt']['source'] = "ATL06"
IS2_atl11_tide_attrs[ptx]['ref_pt']['description'] = (
"The reference point is the 7 digit segment_id "
"number corresponding to the center of the ATL06 data used for each ATL11 point. These are "
"sequential, starting with 1 for the first segment after an ascending equatorial crossing node."
)
IS2_atl11_tide_attrs[ptx]['ref_pt']['coordinates'] = \
"delta_time latitude longitude"
#-- cycle statistics variables
IS2_atl11_tide_attrs[ptx]['cycle_stats']['Description'] = (
"The cycle_stats subgroup "
"contains summary information about segments for each reference point, including "
"the uncorrected mean heights for reference surfaces, blowing snow and cloud "
"indicators, and geolocation and height misfit statistics.")
IS2_atl11_tide_attrs[ptx]['cycle_stats']['data_rate'] = (
"Data within this group "
"are stored at the average segment rate.")
#-- computed long-period equilibrium tide
IS2_atl11_tide[ptx]['cycle_stats']['tide_equilibrium'] = tide_lpe
IS2_atl11_fill[ptx]['cycle_stats'][
'tide_equilibrium'] = tide_lpe.fill_value
IS2_atl11_dims[ptx]['cycle_stats']['tide_equilibrium'] = [
'ref_pt', 'cycle_number'
]
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium'] = {}
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium'][
'units'] = "meters"
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium'][
'contentType'] = "referenceInformation"
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['long_name'] = \
"Long Period Equilibrium Tide"
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium'][
'description'] = (
"Long-period "
"equilibrium tidal elevation from the summation of fifteen tidal spectral lines"
)
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['reference'] = \
"https://doi.org/10.1111/j.1365-246X.1973.tb03420.x"
IS2_atl11_tide_attrs[ptx]['cycle_stats']['tide_equilibrium']['coordinates'] = \
"../ref_pt ../cycle_number ../delta_time ../latitude ../longitude"
#-- output tidal HDF5 file
args = (PRD, TRK, GRAN, SCYC, ECYC, RL, VERS, AUX)
file_format = '{0}_LPET_{1}{2}_{3}{4}_{5}_{6}{7}.h5'
#-- print file information
print('\t{0}'.format(file_format.format(*args))) if VERBOSE else None
HDF5_ATL11_tide_write(IS2_atl11_tide,
IS2_atl11_tide_attrs,
CLOBBER=True,
INPUT=os.path.basename(FILE),
FILL_VALUE=IS2_atl11_fill,
DIMENSIONS=IS2_atl11_dims,
FILENAME=os.path.join(DIRECTORY,
file_format.format(*args)))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, file_format.format(*args)), MODE)
def compute_tide_corrections(x, y, delta_time, DIRECTORY=None, MODEL=None,
EPSG=3031, EPOCH=(2000,1,1,0,0,0), TYPE='drift', TIME='UTC',
METHOD='spline', EXTRAPOLATE=False, FILL_VALUE=np.nan):
"""
Compute tides at points and times using tidal harmonics
Arguments
---------
x: x-coordinates in projection EPSG
y: y-coordinates in projection EPSG
delta_time: seconds since EPOCH
Keyword arguments
-----------------
DIRECTORY: working data directory for tide models
MODEL: Tide model to use in correction
EPOCH: time period for calculating delta times
default: J2000 (seconds since 2000-01-01T00:00:00)
TYPE: input data type
drift: drift buoys or satellite/airborne altimetry (time per data point)
grid: spatial grids or images (single time per image)
TIME: time type if need to compute leap seconds to convert to UTC
GPS: leap seconds needed
TAI: leap seconds needed (TAI = GPS + 19 seconds)
UTC: no leap seconds needed
EPSG: input coordinate system
default: 3031 Polar Stereographic South, WGS84
METHOD: interpolation method
bilinear: quick bilinear interpolation
spline: scipy bivariate spline interpolation
linear, nearest: scipy regular grid interpolations
FILL_VALUE: output invalid value (default NaN)
Returns
-------
tide: tidal elevation at coordinates and time in meters
"""
#-- select between tide models
if (MODEL == 'CATS0201'):
grid_file = os.path.join(DIRECTORY,'cats0201_tmd','grid_CATS')
model_file = os.path.join(DIRECTORY,'cats0201_tmd','h0_CATS02_01')
model_format = 'OTIS'
model_EPSG = '4326'
model_type = 'z'
elif (MODEL == 'CATS2008'):
grid_file = os.path.join(DIRECTORY,'CATS2008','grid_CATS2008')
model_file = os.path.join(DIRECTORY,'CATS2008','hf.CATS2008.out')
model_format = 'OTIS'
model_EPSG = 'CATS2008'
model_type = 'z'
elif (MODEL == 'CATS2008_load'):
grid_file = os.path.join(DIRECTORY,'CATS2008a_SPOTL_Load','grid_CATS2008a_opt')
model_file = os.path.join(DIRECTORY,'CATS2008a_SPOTL_Load','h_CATS2008a_SPOTL_load')
model_format = 'OTIS'
model_EPSG = 'CATS2008'
model_type = 'z'
elif (MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(DIRECTORY,'TPXO9_atlas')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30.nc.gz','h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz','h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz','h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz','h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz','h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz','h_2n2_tpxo9_atlas_30.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'netcdf'
model_type = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (MODEL == 'TPXO9-atlas-v2'):
model_directory = os.path.join(DIRECTORY,'TPXO9_atlas_v2')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v2.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30_v2.nc.gz','h_o1_tpxo9_atlas_30_v2.nc.gz',
'h_p1_tpxo9_atlas_30_v2.nc.gz','h_k1_tpxo9_atlas_30_v2.nc.gz',
'h_n2_tpxo9_atlas_30_v2.nc.gz','h_m2_tpxo9_atlas_30_v2.nc.gz',
'h_s2_tpxo9_atlas_30_v2.nc.gz','h_k2_tpxo9_atlas_30_v2.nc.gz',
'h_m4_tpxo9_atlas_30_v2.nc.gz','h_ms4_tpxo9_atlas_30_v2.nc.gz',
'h_mn4_tpxo9_atlas_30_v2.nc.gz','h_2n2_tpxo9_atlas_30_v2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'netcdf'
model_type = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (MODEL == 'TPXO9-atlas-v3'):
model_directory = os.path.join(DIRECTORY,'TPXO9_atlas_v3')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v3.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30_v3.nc.gz','h_o1_tpxo9_atlas_30_v3.nc.gz',
'h_p1_tpxo9_atlas_30_v3.nc.gz','h_k1_tpxo9_atlas_30_v3.nc.gz',
'h_n2_tpxo9_atlas_30_v3.nc.gz','h_m2_tpxo9_atlas_30_v3.nc.gz',
'h_s2_tpxo9_atlas_30_v3.nc.gz','h_k2_tpxo9_atlas_30_v3.nc.gz',
'h_m4_tpxo9_atlas_30_v3.nc.gz','h_ms4_tpxo9_atlas_30_v3.nc.gz',
'h_mn4_tpxo9_atlas_30_v3.nc.gz','h_2n2_tpxo9_atlas_30_v3.nc.gz',
'h_mf_tpxo9_atlas_30_v3.nc.gz','h_mm_tpxo9_atlas_30_v3.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'netcdf'
model_type = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (MODEL == 'TPXO9-atlas-v4'):
model_directory = os.path.join(DIRECTORY,'TPXO9_atlas_v4')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v4')
model_files = ['h_q1_tpxo9_atlas_30_v4','h_o1_tpxo9_atlas_30_v4',
'h_p1_tpxo9_atlas_30_v4','h_k1_tpxo9_atlas_30_v4',
'h_n2_tpxo9_atlas_30_v4','h_m2_tpxo9_atlas_30_v4',
'h_s2_tpxo9_atlas_30_v4','h_k2_tpxo9_atlas_30_v4',
'h_m4_tpxo9_atlas_30_v4','h_ms4_tpxo9_atlas_30_v4',
'h_mn4_tpxo9_atlas_30_v4','h_2n2_tpxo9_atlas_30_v4',
'h_mf_tpxo9_atlas_30_v4','h_mm_tpxo9_atlas_30_v4']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'OTIS'
model_EPSG = '4326'
model_type = 'z'
elif (MODEL == 'TPXO9.1'):
grid_file = os.path.join(DIRECTORY,'TPXO9.1','DATA','grid_tpxo9')
model_file = os.path.join(DIRECTORY,'TPXO9.1','DATA','h_tpxo9.v1')
model_format = 'OTIS'
model_EPSG = '4326'
model_type = 'z'
elif (MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(DIRECTORY,'tpxo8_atlas','grid_tpxo8atlas_30_v1')
model_file = os.path.join(DIRECTORY,'tpxo8_atlas','hf.tpxo8_atlas_30_v1')
model_format = 'ATLAS'
model_EPSG = '4326'
model_type = 'z'
elif (MODEL == 'TPXO7.2'):
grid_file = os.path.join(DIRECTORY,'TPXO7.2_tmd','grid_tpxo7.2')
model_file = os.path.join(DIRECTORY,'TPXO7.2_tmd','h_tpxo7.2')
model_format = 'OTIS'
model_EPSG = '4326'
model_type = 'z'
elif (MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(DIRECTORY,'TPXO7.2_load','grid_tpxo6.2')
model_file = os.path.join(DIRECTORY,'TPXO7.2_load','h_tpxo7.2_load')
model_format = 'OTIS'
model_EPSG = '4326'
model_type = 'z'
elif (MODEL == 'AODTM-5'):
grid_file = os.path.join(DIRECTORY,'aodtm5_tmd','grid_Arc5km')
model_file = os.path.join(DIRECTORY,'aodtm5_tmd','h0_Arc5km.oce')
model_format = 'OTIS'
model_EPSG = 'PSNorth'
model_type = 'z'
elif (MODEL == 'AOTIM-5'):
grid_file = os.path.join(DIRECTORY,'aotim5_tmd','grid_Arc5km')
model_file = os.path.join(DIRECTORY,'aotim5_tmd','h_Arc5km.oce')
model_format = 'OTIS'
model_EPSG = 'PSNorth'
model_type = 'z'
elif (MODEL == 'AOTIM-5-2018'):
grid_file = os.path.join(DIRECTORY,'Arc5km2018','grid_Arc5km2018')
model_file = os.path.join(DIRECTORY,'Arc5km2018','h_Arc5km2018')
model_format = 'OTIS'
model_EPSG = 'PSNorth'
model_type = 'z'
elif (MODEL == 'GOT4.7'):
model_directory = os.path.join(DIRECTORY,'GOT4.7','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (MODEL == 'GOT4.7_load'):
model_directory = os.path.join(DIRECTORY,'GOT4.7','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (MODEL == 'GOT4.8'):
model_directory = os.path.join(DIRECTORY,'got4.8','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (MODEL == 'GOT4.8_load'):
model_directory = os.path.join(DIRECTORY,'got4.8','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (MODEL == 'GOT4.10'):
model_directory = os.path.join(DIRECTORY,'GOT4.10c','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (MODEL == 'GOT4.10_load'):
model_directory = os.path.join(DIRECTORY,'GOT4.10c','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (MODEL == 'FES2014'):
model_directory = os.path.join(DIRECTORY,'fes2014','ocean_tide')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6','m8',
'mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2','n4',
'nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0/100.0
GZIP = True
elif (MODEL == 'FES2014_load'):
model_directory = os.path.join(DIRECTORY,'fes2014','load_tide')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',
'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',
'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
model_format = 'FES'
model_type = 'z'
SCALE = 1.0/100.0
GZIP = True
else:
raise Exception("Unlisted tide model")
#-- converting x,y from EPSG to latitude/longitude
crs1 = pyproj.CRS.from_string("epsg:{0:d}".format(EPSG))
crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(4326))
transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True)
lon,lat = transformer.transform(x.flatten(), y.flatten())
#-- assert delta time is an array
delta_time = np.atleast_1d(delta_time)
#-- calculate leap seconds if specified
if (TIME.upper() == 'GPS'):
GPS_Epoch_Time = pyTMD.time.convert_delta_time(0, epoch1=EPOCH,
epoch2=(1980,1,6,0,0,0), scale=1.0)
GPS_Time = pyTMD.time.convert_delta_time(delta_time, epoch1=EPOCH,
epoch2=(1980,1,6,0,0,0), scale=1.0)
#-- calculate difference in leap seconds from start of epoch
leap_seconds = pyTMD.time.count_leap_seconds(GPS_Time) - \
pyTMD.time.count_leap_seconds(np.atleast_1d(GPS_Epoch_Time))
elif (TIME.upper() == 'TAI'):
#-- TAI time is ahead of GPS time by 19 seconds
GPS_Epoch_Time = pyTMD.time.convert_delta_time(-19.0, epoch1=EPOCH,
epoch2=(1980,1,6,0,0,0), scale=1.0)
GPS_Time = pyTMD.time.convert_delta_time(delta_time-19.0, epoch1=EPOCH,
epoch2=(1980,1,6,0,0,0), scale=1.0)
#-- calculate difference in leap seconds from start of epoch
leap_seconds = pyTMD.time.count_leap_seconds(GPS_Time) - \
pyTMD.time.count_leap_seconds(np.atleast_1d(GPS_Epoch_Time))
else:
leap_seconds = 0.0
#-- convert time to days relative to Jan 1, 1992 (48622mjd)
t = pyTMD.time.convert_delta_time(delta_time - leap_seconds, epoch1=EPOCH,
epoch2=(1992,1,1,0,0,0), scale=(1.0/86400.0))
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data','merged_deltat.data'])
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS','ATLAS'):
amp,ph,D,c = extract_tidal_constants(lon, lat, grid_file, model_file,
model_EPSG, TYPE=model_type, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
GRID=model_format)
deltat = np.zeros_like(t)
elif (model_format == 'netcdf'):
amp,ph,D,c = extract_netcdf_constants(lon, lat, grid_file, model_file,
TYPE=model_type, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
SCALE=SCALE, GZIP=GZIP)
deltat = np.zeros_like(t)
elif (model_format == 'GOT'):
amp,ph,c = extract_GOT_constants(lon, lat, model_file, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, SCALE=SCALE, GZIP=GZIP)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, t)
elif (model_format == 'FES'):
amp,ph = extract_FES_constants(lon, lat, model_file, TYPE=model_type,
VERSION=MODEL, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE,
SCALE=SCALE, GZIP=GZIP)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, t)
#-- calculate complex phase in radians for Euler's
cph = -1j*ph*np.pi/180.0
#-- calculate constituent oscillation
hc = amp*np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
if (TYPE.lower() == 'grid'):
ny,nx = np.shape(x); nt = len(t)
tide = np.ma.zeros((ny,nx,nt),fill_value=FILL_VALUE)
tide.mask = np.zeros((ny,nx,nt),dtype=bool)
for i in range(nt):
TIDE = predict_tide(t[i], hc, c,
DELTAT=deltat[i], CORRECTIONS=model_format)
MINOR = infer_minor_corrections(t[i], hc, c,
DELTAT=deltat[i], CORRECTIONS=model_format)
#-- add major and minor components and reform grid
tide[:,:,i] = np.reshape((TIDE+MINOR), (ny,nx))
tide.mask[:,:,i] = np.reshape((TIDE.mask | MINOR.mask), (ny,nx))
else:
npts = len(t)
tide = np.ma.zeros((npts), fill_value=FILL_VALUE)
tide.mask = np.any(hc.mask,axis=1)
tide.data[:] = predict_tide_drift(t, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
minor = infer_minor_corrections(t, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
tide.data[:] += minor.data[:]
#-- replace invalid values with fill value
tide.data[tide.mask] = tide.fill_value
#-- return the tide correction
return tide
def compute_tides_ICESat2(tide_dir, FILE, MODEL, VERBOSE=False, MODE=0o775):
#-- select between tide models
if (MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir, 'cats0201_tmd', 'grid_CATS')
model_file = os.path.join(tide_dir, 'cats0201_tmd', 'h0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir, 'CATS2008', 'grid_CATS2008a_opt')
model_file = os.path.join(tide_dir, 'CATS2008', 'hf.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'CATS2008'
type = 'z'
elif (MODEL == 'CATS2008_load'):
grid_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'grid_CATS2008a_opt')
model_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'h_CATS2008a_SPOTL_load')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'OTIS'
EPSG = 'CATS2008'
type = 'z'
elif (MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas')
grid_file = 'grid_tpxo9_atlas.nc.gz'
model_files = [
'h_q1_tpxo9_atlas_30.nc.gz', 'h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz', 'h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz', 'h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz', 'h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz', 'h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz', 'h_2n2_tpxo9_atlas_30.nc.gz'
]
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
type = 'z'
SCALE = 1.0 / 1000.0
elif (MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'grid_tpxo9')
model_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'h_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir, 'tpxo8_atlas',
'grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir, 'tpxo8_atlas',
'hf.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'ATLAS'
EPSG = '4326'
type = 'z'
elif (MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'grid_tpxo7.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'h_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_load', 'grid_tpxo6.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_load', 'h_tpxo7.2_load')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir, 'aodtm5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aodtm5_tmd', 'h0_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '3996'
type = 'z'
elif (MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir, 'aotim5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aotim5_tmd', 'h_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '3996'
type = 'z'
elif (MODEL == 'GOT4.7'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (MODEL == 'GOT4.7_load'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (MODEL == 'GOT4.8'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (MODEL == 'GOT4.8_load'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (MODEL == 'GOT4.10'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (MODEL == 'GOT4.10_load'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'tide_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
#-- read data from FILE
print('{0} -->'.format(os.path.basename(FILE))) if VERBOSE else None
IS2_atl06_mds, IS2_atl06_attrs, IS2_atl06_beams = read_HDF5_ATL06(
FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 file name
rx = re.compile(
'(processed_)?(ATL\d{2})_(\d{4})(\d{2})(\d{2})(\d{2})'
'(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$')
SUB, PRD, YY, MM, DD, HH, MN, SS, TRK, CYCL, GRAN, RL, VERS, AUX = rx.findall(
FILE).pop()
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl06_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- copy variables for outputting to HDF5 file
IS2_atl06_tide = {}
IS2_atl06_fill = {}
IS2_atl06_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl06_tide['ancillary_data'] = {}
IS2_atl06_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl06_tide['ancillary_data'][key] = IS2_atl06_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl06_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl06_attrs['ancillary_data'][key].items(
):
IS2_atl06_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam within the file
for gtx in sorted(IS2_atl06_beams):
#-- output data dictionaries for beam
IS2_atl06_tide[gtx] = dict(land_ice_segments={})
IS2_atl06_fill[gtx] = dict(land_ice_segments={})
IS2_atl06_tide_attrs[gtx] = dict(land_ice_segments={})
#-- number of segments
val = IS2_atl06_mds[gtx]['land_ice_segments']
n_seg = len(val['segment_id'])
#-- find valid segments for beam
fv = IS2_atl06_attrs[gtx]['land_ice_segments']['h_li']['_FillValue']
h_li = np.ma.array(val['h_li'],
fill_value=fv,
mask=(val['h_li'] == fv))
ii, = np.nonzero(~h_li.mask)
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + val['delta_time'][ii]
tide_time = (gps_seconds -
count_leap_seconds(gps_seconds)) / 86400.0 - 4378.0
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS', 'ATLAS'):
amp, ph, D, c = extract_tidal_constants(val['longitude'][ii],
val['latitude'][ii],
grid_file,
model_file,
EPSG,
type,
METHOD='spline',
GRID=model_format)
deltat = np.zeros_like(tide_time)
elif (model_format == 'netcdf'):
amp, ph, D, c = extract_netcdf_constants(val['longitude'][ii],
val['latitude'][ii],
model_directory,
grid_file,
model_files,
type,
METHOD='spline',
SCALE=SCALE)
deltat = np.zeros_like(tide_time)
elif (model_format == 'GOT'):
amp, ph = extract_GOT_constants(val['longitude'][ii],
val['latitude'][ii],
model_directory,
model_files,
METHOD='spline',
SCALE=SCALE)
#-- convert time to Modified Julian Days for calculating deltat
delta_file = os.path.join(tide_dir, 'deltat.data')
deltat = calc_delta_time(delta_file, tide_time + 48622.0)
cph = -1j * ph * np.pi / 180.0
hc = amp * np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
tide = np.ma.empty((n_seg), fill_value=fv)
tide.mask = np.copy(h_li.mask)
tide.data[ii] = predict_tide_drift(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model_format)
tide.data[ii] += infer_minor_corrections(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model_format)
#-- replace masked and nan values with fill value
invalid, = np.nonzero(np.isnan(tide.data) | tide.mask)
tide.data[invalid] = tide.fill_value
tide.mask[invalid] = True
#-- group attributes for beam
IS2_atl06_tide_attrs[gtx]['Description'] = IS2_atl06_attrs[gtx][
'Description']
IS2_atl06_tide_attrs[gtx]['atlas_pce'] = IS2_atl06_attrs[gtx][
'atlas_pce']
IS2_atl06_tide_attrs[gtx]['atlas_beam_type'] = IS2_atl06_attrs[gtx][
'atlas_beam_type']
IS2_atl06_tide_attrs[gtx]['groundtrack_id'] = IS2_atl06_attrs[gtx][
'groundtrack_id']
IS2_atl06_tide_attrs[gtx]['atmosphere_profile'] = IS2_atl06_attrs[gtx][
'atmosphere_profile']
IS2_atl06_tide_attrs[gtx]['atlas_spot_number'] = IS2_atl06_attrs[gtx][
'atlas_spot_number']
IS2_atl06_tide_attrs[gtx]['sc_orientation'] = IS2_atl06_attrs[gtx][
'sc_orientation']
#-- group attributes for land_ice_segments
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['Description'] = (
"The land_ice_segments group "
"contains the primary set of derived products. This includes geolocation, height, and "
"standard error and quality measures for each segment. This group is sparse, meaning "
"that parameters are provided only for pairs of segments for which at least one beam "
"has a valid surface-height measurement.")
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['data_rate'] = (
"Data within this group are "
"sparse. Data values are provided only for those ICESat-2 20m segments where at "
"least one beam has a valid land ice height measurement.")
#-- geolocation, time and segment ID
#-- delta time
delta_time = np.ma.array(val['delta_time'],
fill_value=fv,
mask=(val['delta_time'] == fv))
IS2_atl06_tide[gtx]['land_ice_segments']['delta_time'] = delta_time
IS2_atl06_fill[gtx]['land_ice_segments'][
'delta_time'] = delta_time.fill_value
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'standard_name'] = "time"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'calendar'] = "standard"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time'][
'description'] = (
"Number of GPS "
"seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch offset "
"is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS seconds "
"between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP epoch. By "
"adding the offset contained within atlas_sdp_gps_epoch to delta time parameters, the "
"time in gps_seconds relative to the GPS epoch can be computed."
)
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['delta_time']['coordinates'] = \
"segment_id latitude longitude"
#-- latitude
latitude = np.ma.array(val['latitude'],
fill_value=fv,
mask=(val['latitude'] == fv))
IS2_atl06_tide[gtx]['land_ice_segments']['latitude'] = latitude
IS2_atl06_fill[gtx]['land_ice_segments'][
'latitude'] = latitude.fill_value
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'units'] = "degrees_north"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'contentType'] = "physicalMeasurement"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'long_name'] = "Latitude"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'standard_name'] = "latitude"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'description'] = ("Latitude of "
"segment center")
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'valid_min'] = -90.0
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude'][
'valid_max'] = 90.0
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['latitude']['coordinates'] = \
"segment_id delta_time longitude"
#-- longitude
longitude = np.ma.array(val['longitude'],
fill_value=fv,
mask=(val['longitude'] == fv))
IS2_atl06_tide[gtx]['land_ice_segments']['longitude'] = longitude
IS2_atl06_fill[gtx]['land_ice_segments'][
'longitude'] = longitude.fill_value
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'units'] = "degrees_east"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'contentType'] = "physicalMeasurement"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'long_name'] = "Longitude"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'standard_name'] = "longitude"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'description'] = ("Longitude of "
"segment center")
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'valid_min'] = -180.0
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude'][
'valid_max'] = 180.0
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['longitude']['coordinates'] = \
"segment_id delta_time latitude"
#-- segment ID
IS2_atl06_tide[gtx]['land_ice_segments']['segment_id'] = val[
'segment_id']
IS2_atl06_fill[gtx]['land_ice_segments']['segment_id'] = None
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'][
'units'] = "1"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'][
'contentType'] = "referenceInformation"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'][
'long_name'] = "Along-track segment ID number"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id'][
'description'] = (
"A 7 digit number "
"identifying the along-track geolocation segment number. These are sequential, starting with "
"1 for the first segment after an ascending equatorial crossing node. Equal to the segment_id for "
"the second of the two 20m ATL03 segments included in the 40m ATL06 segment"
)
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['segment_id']['coordinates'] = \
"delta_time latitude longitude"
#-- geophysical variables
IS2_atl06_tide[gtx]['land_ice_segments']['geophysical'] = {}
IS2_atl06_fill[gtx]['land_ice_segments']['geophysical'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
'Description'] = (
"The geophysical group "
"contains parameters used to correct segment heights for geophysical effects, parameters "
"related to solar background and parameters indicative of the presence or absence of clouds."
)
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
'data_rate'] = (
"Data within this group "
"are stored at the land_ice_segments segment rate.")
#-- computed tide
IS2_atl06_tide[gtx]['land_ice_segments']['geophysical'][
variable] = tide
IS2_atl06_fill[gtx]['land_ice_segments']['geophysical'][
variable] = tide.fill_value
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
variable] = {}
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
variable]['units'] = "meters"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
variable]['contentType'] = "referenceInformation"
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
variable]['long_name'] = long_name
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
variable]['description'] = description
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
variable]['source'] = MODEL
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][
variable]['reference'] = reference
IS2_atl06_tide_attrs[gtx]['land_ice_segments']['geophysical'][variable]['coordinates'] = \
"../segment_id ../delta_time ../latitude ../longitude"
#-- output tidal HDF5 file
args = (PRD, MODEL, YY, MM, DD, HH, MN, SS, TRK, CYCL, GRAN, RL, VERS, AUX)
file_format = '{0}_{1}_TIDES_{2}{3}{4}{5}{6}{7}_{8}{9}{10}_{11}_{12}{13}.h5'
#-- print file information
print('\t{0}'.format(file_format.format(*args))) if VERBOSE else None
HDF5_ATL06_tide_write(IS2_atl06_tide,
IS2_atl06_tide_attrs,
CLOBBER='Y',
INPUT=os.path.basename(FILE),
FILL_VALUE=IS2_atl06_fill,
FILENAME=os.path.join(DIRECTORY,
file_format.format(*args)))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, file_format.format(*args)), MODE)
def compute_tidal_elevations(tide_dir, input_file, output_file,
TIDE_MODEL=None, FORMAT='csv', VARIABLES=['time','lat','lon','data'],
TIME_UNITS='days since 1858-11-17T00:00:00', PROJECTION='4326',
METHOD='spline', VERBOSE=False, MODE=0o775):
#-- select between tide models
if (TIDE_MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir,'cats0201_tmd','grid_CATS')
model_file = os.path.join(tide_dir,'cats0201_tmd','h0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir,'CATS2008','grid_CATS2008')
model_file = os.path.join(tide_dir,'CATS2008','hf.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008_load'):
grid_file = os.path.join(tide_dir,'CATS2008a_SPOTL_Load','grid_CATS2008a_opt')
model_file = os.path.join(tide_dir,'CATS2008a_SPOTL_Load','h_CATS2008a_SPOTL_load')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas')
grid_file = 'grid_tpxo9_atlas.nc.gz'
model_files = ['h_q1_tpxo9_atlas_30.nc.gz','h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz','h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz','h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz','h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz','h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz','h_2n2_tpxo9_atlas_30.nc.gz']
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
elif (TIDE_MODEL == 'TPXO9-atlas-v2'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v2')
grid_file = 'grid_tpxo9_atlas_30_v2.nc.gz'
model_files = ['h_q1_tpxo9_atlas_30_v2.nc.gz','h_o1_tpxo9_atlas_30_v2.nc.gz',
'h_p1_tpxo9_atlas_30_v2.nc.gz','h_k1_tpxo9_atlas_30_v2.nc.gz',
'h_n2_tpxo9_atlas_30_v2.nc.gz','h_m2_tpxo9_atlas_30_v2.nc.gz',
'h_s2_tpxo9_atlas_30_v2.nc.gz','h_k2_tpxo9_atlas_30_v2.nc.gz',
'h_m4_tpxo9_atlas_30_v2.nc.gz','h_ms4_tpxo9_atlas_30_v2.nc.gz',
'h_mn4_tpxo9_atlas_30_v2.nc.gz','h_2n2_tpxo9_atlas_30_v2.nc.gz']
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
elif (TIDE_MODEL == 'TPXO9-atlas-v3'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v3')
grid_file = 'grid_tpxo9_atlas_30_v3.nc.gz'
model_files = ['h_q1_tpxo9_atlas_30_v3.nc.gz','h_o1_tpxo9_atlas_30_v3.nc.gz',
'h_p1_tpxo9_atlas_30_v3.nc.gz','h_k1_tpxo9_atlas_30_v3.nc.gz',
'h_n2_tpxo9_atlas_30_v3.nc.gz','h_m2_tpxo9_atlas_30_v3.nc.gz',
'h_s2_tpxo9_atlas_30_v3.nc.gz','h_k2_tpxo9_atlas_30_v3.nc.gz',
'h_m4_tpxo9_atlas_30_v3.nc.gz','h_ms4_tpxo9_atlas_30_v3.nc.gz',
'h_mn4_tpxo9_atlas_30_v3.nc.gz','h_2n2_tpxo9_atlas_30_v3.nc.gz',
'h_mf_tpxo9_atlas_30_v3.nc.gz','h_mm_tpxo9_atlas_30_v3.nc.gz']
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'tide_ocean'
long_name = "Ocean_Tide"
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
elif (TIDE_MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir,'TPXO9.1','DATA','grid_tpxo9')
model_file = os.path.join(tide_dir,'TPXO9.1','DATA','h_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir,'tpxo8_atlas','grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir,'tpxo8_atlas','hf.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'ATLAS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir,'TPXO7.2_tmd','grid_tpxo7.2')
model_file = os.path.join(tide_dir,'TPXO7.2_tmd','h_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(tide_dir,'TPXO7.2_load','grid_tpxo6.2')
model_file = os.path.join(tide_dir,'TPXO7.2_load','h_tpxo7.2_load')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir,'aodtm5_tmd','grid_Arc5km')
model_file = os.path.join(tide_dir,'aodtm5_tmd','h0_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir,'aotim5_tmd','grid_Arc5km')
model_file = os.path.join(tide_dir,'aotim5_tmd','h_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5-2018'):
grid_file = os.path.join(tide_dir,'Arc5km2018','grid_Arc5km2018')
model_file = os.path.join(tide_dir,'Arc5km2018','h_Arc5km2018')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'GOT4.7'):
model_directory = os.path.join(tide_dir,'GOT4.7','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'GOT'
SCALE = 1.0/100.0
elif (TIDE_MODEL == 'GOT4.7_load'):
model_directory = os.path.join(tide_dir,'GOT4.7','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'GOT'
SCALE = 1.0/1000.0
elif (TIDE_MODEL == 'GOT4.8'):
model_directory = os.path.join(tide_dir,'got4.8','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'GOT'
SCALE = 1.0/100.0
elif (TIDE_MODEL == 'GOT4.8_load'):
model_directory = os.path.join(tide_dir,'got4.8','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'GOT'
SCALE = 1.0/1000.0
elif (TIDE_MODEL == 'GOT4.10'):
model_directory = os.path.join(tide_dir,'GOT4.10c','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'GOT'
SCALE = 1.0/100.0
elif (TIDE_MODEL == 'GOT4.10_load'):
model_directory = os.path.join(tide_dir,'GOT4.10c','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'GOT'
SCALE = 1.0/1000.0
elif (TIDE_MODEL == 'FES2014'):
model_directory = os.path.join(tide_dir,'fes2014','ocean_tide')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',
'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',
'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
reference = ('https://www.aviso.altimetry.fr/data/products/'
'auxiliary-products/global-tide-fes.html')
output_variable = 'tide_ocean'
variable_long_name = 'Ocean_Tide'
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0/100.0
elif (TIDE_MODEL == 'FES2014_load'):
model_directory = os.path.join(tide_dir,'fes2014','load_tide')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',
'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',
'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
reference = ('https://www.aviso.altimetry.fr/data/products/'
'auxiliary-products/global-tide-fes.html')
output_variable = 'tide_load'
variable_long_name = 'Load_Tide'
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0/100.0
#-- invalid value
fill_value = -9999.0
#-- output netCDF4 and HDF5 file attributes
#-- will be added to YAML header in csv files
attrib = {}
#-- latitude
attrib['lat'] = {}
attrib['lat']['long_name'] = 'Latitude'
attrib['lat']['units'] = 'Degrees_North'
#-- longitude
attrib['lon'] = {}
attrib['lon']['long_name'] = 'Longitude'
attrib['lon']['units'] = 'Degrees_East'
#-- tides
attrib[output_variable] = {}
attrib[output_variable]['description'] = ('tidal_elevation_from_harmonic_'
'constants')
attrib[output_variable]['model'] = TIDE_MODEL
attrib[output_variable]['units'] = 'meters'
attrib[output_variable]['long_name'] = variable_long_name
attrib[output_variable]['_FillValue'] = fill_value
#-- time
attrib['time'] = {}
attrib['time']['long_name'] = 'Time'
attrib['time']['units'] = 'days since 1992-01-01T00:00:00'
attrib['time']['calendar'] = 'standard'
#-- read input file to extract time, spatial coordinates and data
if (FORMAT == 'csv'):
dinput = pyTMD.spatial.from_ascii(input_file, columns=VARIABLES,
header=0, verbose=VERBOSE)
elif (FORMAT == 'netCDF4'):
dinput = pyTMD.spatial.from_netCDF4(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3],
verbose=VERBOSE)
elif (FORMAT == 'HDF5'):
dinput = pyTMD.spatial.from_HDF5(input_file, timename=VARIABLES[0],
xname=VARIABLES[2], yname=VARIABLES[1], varname=VARIABLES[3],
verbose=VERBOSE)
#-- converting x,y from projection to latitude/longitude
#-- could try to extract projection attributes from netCDF4 and HDF5 files
try:
crs1 = pyproj.CRS.from_string("epsg:{0:d}".format(int(PROJECTION)))
except (ValueError,pyproj.exceptions.CRSError):
crs1 = pyproj.CRS.from_string(PROJECTION)
crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(4326))
transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True)
lon,lat = transformer.transform(dinput['x'].flatten(),dinput['y'].flatten())
#-- extract time units from netCDF4 and HDF5 attributes or from TIME_UNITS
try:
time_string = dinput['attributes']['time']['units']
except (TypeError, KeyError):
epoch1,to_secs = pyTMD.time.parse_date_string(TIME_UNITS)
else:
epoch1,to_secs = pyTMD.time.parse_date_string(time_string)
#-- convert time from units to days since 1992-01-01T00:00:00
tide_time = pyTMD.time.convert_delta_time(to_secs*dinput['time'].flatten(),
epoch1=epoch1, epoch2=(1992,1,1,0,0,0), scale=1.0/86400.0)
n_time = len(tide_time)
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS','ATLAS'):
amp,ph,D,c = extract_tidal_constants(lon, lat, grid_file, model_file,
EPSG, TYPE=TYPE, METHOD=METHOD)
deltat = np.zeros((n_time))
elif (model_format == 'netcdf'):
amp,ph,D,c = extract_netcdf_constants(lon, lat, model_directory,
grid_file, model_files, TYPE=TYPE, METHOD=METHOD, SCALE=SCALE)
deltat = np.zeros((n_time))
elif (model_format == 'GOT'):
amp,ph = extract_GOT_constants(lon, lat, model_directory, model_files,
METHOD=METHOD, SCALE=SCALE)
#-- convert times from modified julian days to days since 1992-01-01
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data','merged_deltat.data'])
deltat = calc_delta_time(delta_file,tide_time)
elif (model_format == 'FES'):
amp,ph = extract_FES_constants(lon, lat, model_directory, model_files,
TYPE=TYPE, VERSION=TIDE_MODEL, METHOD=METHOD, SCALE=SCALE)
#-- convert times from modified julian days to days since 1992-01-01
#-- interpolate delta times from calendar dates to tide time
delta_file = get_data_path(['data','merged_deltat.data'])
deltat = calc_delta_time(delta_file,tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j*ph*np.pi/180.0
#-- calculate constituent oscillation
hc = amp*np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
tide = np.ma.zeros((n_time), fill_value=fill_value)
tide.mask = np.any(hc.mask,axis=1)
tide.data[:] = predict_tide_drift(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
minor = infer_minor_corrections(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
tide.data[:] += minor.data[:]
#-- replace invalid values with fill value
tide.data[tide.mask] = tide.fill_value
#-- output to file
output = {'time':tide_time,'lon':lon,'lat':lat,output_variable:tide}
if (FORMAT == 'csv'):
pyTMD.spatial.to_ascii(output, attrib, output_file, delimiter=',',
columns=['time','lat','lon',output_variable], verbose=VERBOSE)
elif (FORMAT == 'netCDF4'):
pyTMD.spatial.to_netCDF4(output, attrib, output_file, verbose=VERBOSE)
elif (FORMAT == 'HDF5'):
pyTMD.spatial.to_HDF5(output, attrib, output_file, verbose=VERBOSE)
#-- change the permissions level to MODE
os.chmod(output_file, MODE)
def compute_tides_ICESat2(tide_dir,
INPUT_FILE,
TIDE_MODEL=None,
ATLAS_FORMAT=None,
GZIP=True,
DEFINITION_FILE=None,
METHOD='spline',
EXTRAPOLATE=False,
CUTOFF=None,
VERBOSE=False,
MODE=0o775):
#-- create logger for verbosity level
loglevel = logging.INFO if VERBOSE else logging.CRITICAL
logger = pyTMD.utilities.build_logger('pytmd', level=loglevel)
#-- get parameters for tide model
if DEFINITION_FILE is not None:
model = pyTMD.model(tide_dir).from_file(DEFINITION_FILE)
else:
model = pyTMD.model(tide_dir, format=ATLAS_FORMAT,
compressed=GZIP).elevation(TIDE_MODEL)
#-- read data from input file
logger.info('{0} -->'.format(INPUT_FILE))
IS2_atl10_mds, IS2_atl10_attrs, IS2_atl10_beams = read_HDF5_ATL10(
INPUT_FILE, ATTRIBUTES=True)
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 sea ice file name
rx = re.compile(
r'(processed_)?(ATL\d{2})-(\d{2})_(\d{4})(\d{2})(\d{2})'
r'(\d{2})(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$'
)
try:
SUB, PRD, HEM, YY, MM, DD, HH, MN, SS, TRK, CYCL, SN, RL, VERS, AUX = rx.findall(
INPUT_FILE).pop()
except:
#-- output tide HDF5 file (generic)
fileBasename, fileExtension = os.path.splitext(INPUT_FILE)
args = (fileBasename, model.name, fileExtension)
OUTPUT_FILE = '{0}_{1}_TIDES{2}'.format(*args)
else:
#-- output tide HDF5 file for ASAS/NSIDC granules
args = (PRD, HEM, model.name, YY, MM, DD, HH, MN, SS, TRK, CYCL, SN,
RL, VERS, AUX)
ff = '{0}-{1}_{2}_TIDES_{3}{4}{5}{6}{7}{8}_{9}{10}{11}_{12}_{13}{14}.h5'
OUTPUT_FILE = ff.format(*args)
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl10_mds['ancillary_data'][
'atlas_sdp_gps_epoch']
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data', 'merged_deltat.data'])
#-- copy variables for outputting to HDF5 file
IS2_atl10_tide = {}
IS2_atl10_fill = {}
IS2_atl10_dims = {}
IS2_atl10_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl10_tide['ancillary_data'] = {}
IS2_atl10_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl10_tide['ancillary_data'][key] = IS2_atl10_mds[
'ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl10_tide_attrs['ancillary_data'][key] = {}
for att_name, att_val in IS2_atl10_attrs['ancillary_data'][key].items(
):
IS2_atl10_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam within the file
for gtx in sorted(IS2_atl10_beams):
#-- output data dictionaries for beam
IS2_atl10_tide[gtx] = dict(freeboard_beam_segment={}, leads={})
IS2_atl10_fill[gtx] = dict(freeboard_beam_segment={}, leads={})
IS2_atl10_dims[gtx] = dict(freeboard_beam_segment={}, leads={})
IS2_atl10_tide_attrs[gtx] = dict(freeboard_beam_segment={}, leads={})
#-- group attributes for beam
IS2_atl10_tide_attrs[gtx]['Description'] = IS2_atl10_attrs[gtx][
'Description']
IS2_atl10_tide_attrs[gtx]['atlas_pce'] = IS2_atl10_attrs[gtx][
'atlas_pce']
IS2_atl10_tide_attrs[gtx]['atlas_beam_type'] = IS2_atl10_attrs[gtx][
'atlas_beam_type']
IS2_atl10_tide_attrs[gtx]['groundtrack_id'] = IS2_atl10_attrs[gtx][
'groundtrack_id']
IS2_atl10_tide_attrs[gtx]['atmosphere_profile'] = IS2_atl10_attrs[gtx][
'atmosphere_profile']
IS2_atl10_tide_attrs[gtx]['atlas_spot_number'] = IS2_atl10_attrs[gtx][
'atlas_spot_number']
IS2_atl10_tide_attrs[gtx]['sc_orientation'] = IS2_atl10_attrs[gtx][
'sc_orientation']
#-- group attributes for freeboard_beam_segment
IS2_atl10_tide_attrs[gtx]['freeboard_beam_segment']['Description'] = (
"Contains freeboard "
"estimate and associated height segment parameters for only the sea ice segments by beam."
)
IS2_atl10_tide_attrs[gtx]['freeboard_beam_segment']['data_rate'] = (
"Data within this "
"group are stored at the freeboard swath segment rate.")
#-- group attributes for leads
IS2_atl10_tide_attrs[gtx]['leads']['Description'] = (
"Contains parameters relating "
"to the freeboard values.")
IS2_atl10_tide_attrs[gtx]['leads']['data_rate'] = (
"Data within this "
"group are stored at the lead index rate.")
#-- for each ATL10 group
for group in ['freeboard_beam_segment', 'leads']:
#-- number of segments
val = IS2_atl10_mds[gtx][group]
n_seg = len(val['delta_time'])
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + val['delta_time']
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(
gps_seconds - leap_seconds,
epoch1=(1980, 1, 6, 0, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- read tidal constants and interpolate to grid points
if model.format in ('OTIS', 'ATLAS'):
amp, ph, D, c = extract_tidal_constants(
val['longitude'],
val['latitude'],
model.grid_file,
model.model_file,
model.projection,
TYPE=model.type,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
GRID=model.format)
deltat = np.zeros_like(tide_time)
elif (model.format == 'netcdf'):
amp, ph, D, c = extract_netcdf_constants(
val['longitude'],
val['latitude'],
model.grid_file,
model.model_file,
TYPE=model.type,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
SCALE=model.scale,
CUTOFF=CUTOFF,
GZIP=model.compressed)
deltat = np.zeros_like(tide_time)
elif (model.format == 'GOT'):
amp, ph, c = extract_GOT_constants(val['longitude'],
val['latitude'],
model.model_file,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=model.scale,
GZIP=model.compressed)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
elif (model.format == 'FES'):
amp, ph = extract_FES_constants(val['longitude'],
val['latitude'],
model.model_file,
TYPE=model.type,
VERSION=model.version,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=model.scale,
GZIP=model.compressed)
#-- available model constituents
c = model.constituents
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j * ph * np.pi / 180.0
#-- calculate constituent oscillation
hc = amp * np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
tide = np.ma.empty((n_seg))
tide.mask = np.any(hc.mask, axis=1)
tide.data[:] = predict_tide_drift(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model.format)
minor = infer_minor_corrections(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model.format)
tide.data[:] += minor.data[:]
#-- replace masked and nan values with fill value
invalid, = np.nonzero(np.isnan(tide.data) | tide.mask)
tide.data[invalid] = tide.fill_value
tide.mask[invalid] = True
#-- geolocation, time and segment ID
#-- delta time
IS2_atl10_tide[gtx][group]['delta_time'] = val['delta_time'].copy()
IS2_atl10_fill[gtx][group]['delta_time'] = None
IS2_atl10_dims[gtx][group]['delta_time'] = None
IS2_atl10_tide_attrs[gtx][group]['delta_time'] = {}
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'units'] = "seconds since 2018-01-01"
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'long_name'] = "Elapsed GPS seconds"
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'standard_name'] = "time"
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'source'] = "telemetry"
IS2_atl10_tide_attrs[gtx][group]['delta_time'][
'calendar'] = "standard"
IS2_atl10_tide_attrs[gtx][group]['delta_time']['description'] = (
"Number of "
"GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch "
"offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS "
"seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP "
"epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time "
"parameters, the time in gps_seconds relative to the GPS epoch can be computed."
)
IS2_atl10_tide_attrs[gtx][group]['delta_time']['coordinates'] = \
"latitude longitude"
#-- latitude
IS2_atl10_tide[gtx][group]['latitude'] = val['latitude'].copy()
IS2_atl10_fill[gtx][group]['latitude'] = None
IS2_atl10_dims[gtx][group]['latitude'] = ['delta_time']
IS2_atl10_tide_attrs[gtx][group]['latitude'] = {}
IS2_atl10_tide_attrs[gtx][group]['latitude'][
'units'] = "degrees_north"
IS2_atl10_tide_attrs[gtx][group]['latitude'][
'contentType'] = "physicalMeasurement"
IS2_atl10_tide_attrs[gtx][group]['latitude'][
'long_name'] = "Latitude"
IS2_atl10_tide_attrs[gtx][group]['latitude'][
'standard_name'] = "latitude"
IS2_atl10_tide_attrs[gtx][group]['latitude']['description'] = (
"Latitude of "
"segment center")
IS2_atl10_tide_attrs[gtx][group]['latitude']['valid_min'] = -90.0
IS2_atl10_tide_attrs[gtx][group]['latitude']['valid_max'] = 90.0
IS2_atl10_tide_attrs[gtx][group]['latitude']['coordinates'] = \
"delta_time longitude"
#-- longitude
IS2_atl10_tide[gtx][group]['longitude'] = val['longitude'].copy()
IS2_atl10_fill[gtx][group]['longitude'] = None
IS2_atl10_dims[gtx][group]['longitude'] = ['delta_time']
IS2_atl10_tide_attrs[gtx][group]['longitude'] = {}
IS2_atl10_tide_attrs[gtx][group]['longitude'][
'units'] = "degrees_east"
IS2_atl10_tide_attrs[gtx][group]['longitude'][
'contentType'] = "physicalMeasurement"
IS2_atl10_tide_attrs[gtx][group]['longitude'][
'long_name'] = "Longitude"
IS2_atl10_tide_attrs[gtx][group]['longitude'][
'standard_name'] = "longitude"
IS2_atl10_tide_attrs[gtx][group]['longitude']['description'] = (
"Longitude of "
"segment center")
IS2_atl10_tide_attrs[gtx][group]['longitude']['valid_min'] = -180.0
IS2_atl10_tide_attrs[gtx][group]['longitude']['valid_max'] = 180.0
IS2_atl10_tide_attrs[gtx][group]['longitude']['coordinates'] = \
"delta_time latitude"
#-- geophysical variables
IS2_atl10_tide[gtx][group]['geophysical'] = {}
IS2_atl10_fill[gtx][group]['geophysical'] = {}
IS2_atl10_dims[gtx][group]['geophysical'] = {}
IS2_atl10_tide_attrs[gtx][group]['geophysical'] = {}
IS2_atl10_tide_attrs[gtx][group]['geophysical']['Description'] = (
"Contains geophysical "
"parameters and corrections used to correct photon heights for geophysical effects, "
"such as tides.")
IS2_atl10_tide_attrs[gtx][group]['geophysical']['data_rate'] = (
"Data within this group "
"are stored at the variable segment rate.")
#-- computed tide
IS2_atl10_tide[gtx][group]['geophysical'][
model.atl10] = tide.copy()
IS2_atl10_fill[gtx][group]['geophysical'][
model.atl10] = tide.fill_value
IS2_atl10_dims[gtx][group]['geophysical'][model.atl10] = [
'delta_time'
]
IS2_atl10_tide_attrs[gtx][group]['geophysical'][model.atl10] = {}
IS2_atl10_tide_attrs[gtx][group]['geophysical'][
model.atl10]['units'] = "meters"
IS2_atl10_tide_attrs[gtx][group]['geophysical'][model.atl10]['contentType'] = \
"referenceInformation"
IS2_atl10_tide_attrs[gtx][group]['geophysical'][
model.atl10]['long_name'] = model.long_name
IS2_atl10_tide_attrs[gtx][group]['geophysical'][
model.atl10]['description'] = model.description
IS2_atl10_tide_attrs[gtx][group]['geophysical'][
model.atl10]['source'] = model.name
IS2_atl10_tide_attrs[gtx][group]['geophysical'][
model.atl10]['reference'] = model.reference
IS2_atl10_tide_attrs[gtx][group]['geophysical'][model.atl10]['coordinates'] = \
"../delta_time ../latitude ../longitude"
#-- print file information
logger.info('\t{0}'.format(OUTPUT_FILE))
HDF5_ATL10_tide_write(IS2_atl10_tide,
IS2_atl10_tide_attrs,
CLOBBER=True,
INPUT=os.path.basename(INPUT_FILE),
FILL_VALUE=IS2_atl10_fill,
DIMENSIONS=IS2_atl10_dims,
FILENAME=os.path.join(DIRECTORY, OUTPUT_FILE))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, OUTPUT_FILE), MODE)
def compute_tides_ICESat2(tide_dir, FILE, TIDE_MODEL=None, METHOD='spline',
EXTRAPOLATE=False, VERBOSE=False, MODE=0o775):
#-- select between tide models
if (TIDE_MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir,'cats0201_tmd','grid_CATS')
model_file = os.path.join(tide_dir,'cats0201_tmd','h0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir,'CATS2008','grid_CATS2008')
model_file = os.path.join(tide_dir,'CATS2008','hf.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008_load'):
grid_file = os.path.join(tide_dir,'CATS2008a_SPOTL_Load','grid_CATS2008a_opt')
model_file = os.path.join(tide_dir,'CATS2008a_SPOTL_Load','h_CATS2008a_SPOTL_load')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
variable = 'height_segment_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30.nc.gz','h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz','h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz','h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz','h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz','h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz','h_2n2_tpxo9_atlas_30.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v2'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v2')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v2.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30_v2.nc.gz','h_o1_tpxo9_atlas_30_v2.nc.gz',
'h_p1_tpxo9_atlas_30_v2.nc.gz','h_k1_tpxo9_atlas_30_v2.nc.gz',
'h_n2_tpxo9_atlas_30_v2.nc.gz','h_m2_tpxo9_atlas_30_v2.nc.gz',
'h_s2_tpxo9_atlas_30_v2.nc.gz','h_k2_tpxo9_atlas_30_v2.nc.gz',
'h_m4_tpxo9_atlas_30_v2.nc.gz','h_ms4_tpxo9_atlas_30_v2.nc.gz',
'h_mn4_tpxo9_atlas_30_v2.nc.gz','h_2n2_tpxo9_atlas_30_v2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v3'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v3')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v3.nc.gz')
model_files = ['h_q1_tpxo9_atlas_30_v3.nc.gz','h_o1_tpxo9_atlas_30_v3.nc.gz',
'h_p1_tpxo9_atlas_30_v3.nc.gz','h_k1_tpxo9_atlas_30_v3.nc.gz',
'h_n2_tpxo9_atlas_30_v3.nc.gz','h_m2_tpxo9_atlas_30_v3.nc.gz',
'h_s2_tpxo9_atlas_30_v3.nc.gz','h_k2_tpxo9_atlas_30_v3.nc.gz',
'h_m4_tpxo9_atlas_30_v3.nc.gz','h_ms4_tpxo9_atlas_30_v3.nc.gz',
'h_mn4_tpxo9_atlas_30_v3.nc.gz','h_2n2_tpxo9_atlas_30_v3.nc.gz',
'h_mf_tpxo9_atlas_30_v3.nc.gz','h_mm_tpxo9_atlas_30_v3.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v4'):
model_directory = os.path.join(tide_dir,'TPXO9_atlas_v4')
grid_file = os.path.join(model_directory,'grid_tpxo9_atlas_30_v4')
model_files = ['h_q1_tpxo9_atlas_30_v4','h_o1_tpxo9_atlas_30_v4',
'h_p1_tpxo9_atlas_30_v4','h_k1_tpxo9_atlas_30_v4',
'h_n2_tpxo9_atlas_30_v4','h_m2_tpxo9_atlas_30_v4',
'h_s2_tpxo9_atlas_30_v4','h_k2_tpxo9_atlas_30_v4',
'h_m4_tpxo9_atlas_30_v4','h_ms4_tpxo9_atlas_30_v4',
'h_mn4_tpxo9_atlas_30_v4','h_2n2_tpxo9_atlas_30_v4',
'h_mf_tpxo9_atlas_30_v4','h_mm_tpxo9_atlas_30_v4']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir,'TPXO9.1','DATA','grid_tpxo9')
model_file = os.path.join(tide_dir,'TPXO9.1','DATA','h_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir,'tpxo8_atlas','grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir,'tpxo8_atlas','hf.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'ATLAS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir,'TPXO7.2_tmd','grid_tpxo7.2')
model_file = os.path.join(tide_dir,'TPXO7.2_tmd','h_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(tide_dir,'TPXO7.2_load','grid_tpxo6.2')
model_file = os.path.join(tide_dir,'TPXO7.2_load','h_tpxo7.2_load')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'height_segment_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir,'aodtm5_tmd','grid_Arc5km')
model_file = os.path.join(tide_dir,'aodtm5_tmd','h0_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir,'aotim5_tmd','grid_Arc5km')
model_file = os.path.join(tide_dir,'aotim5_tmd','h_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5-2018'):
grid_file = os.path.join(tide_dir,'Arc5km2018','grid_Arc5km2018')
model_file = os.path.join(tide_dir,'Arc5km2018','h_Arc5km2018')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
variable = 'tide_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'GOT4.7'):
model_directory = os.path.join(tide_dir,'GOT4.7','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.7_load'):
model_directory = os.path.join(tide_dir,'GOT4.7','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'height_segment_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.8'):
model_directory = os.path.join(tide_dir,'got4.8','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.8_load'):
model_directory = os.path.join(tide_dir,'got4.8','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'height_segment_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.10'):
model_directory = os.path.join(tide_dir,'GOT4.10c','grids_oceantide')
model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',
'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.10_load'):
model_directory = os.path.join(tide_dir,'GOT4.10c','grids_loadtide')
model_files = ['q1load.d.gz','o1load.d.gz','p1load.d.gz','k1load.d.gz',
'n2load.d.gz','m2load.d.gz','s2load.d.gz','k2load.d.gz',
's1load.d.gz','m4load.d.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'height_segment_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0/1000.0
GZIP = True
elif (TIDE_MODEL == 'FES2014'):
model_directory = os.path.join(tide_dir,'fes2014','ocean_tide')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',
'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',
'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
variable = 'height_segment_ocean'
long_name = "Ocean Tide"
description = ("Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0/100.0
GZIP = True
elif (TIDE_MODEL == 'FES2014_load'):
model_directory = os.path.join(tide_dir,'fes2014','load_tide')
model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',
'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',
'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',
'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',
'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',
'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',
'ssa.nc.gz','t2.nc.gz']
model_file = [os.path.join(model_directory,m) for m in model_files]
c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',
'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',
'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
variable = 'height_segment_load'
long_name = "Load Tide"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0/100.0
GZIP = True
#-- read data from FILE
print('{0} -->'.format(os.path.basename(FILE))) if VERBOSE else None
IS2_atl07_mds,IS2_atl07_attrs,IS2_atl07_beams = read_HDF5_ATL07(FILE,
ATTRIBUTES=True)
DIRECTORY = os.path.dirname(FILE)
#-- extract parameters from ICESat-2 ATLAS HDF5 sea ice file name
rx = re.compile(r'(processed_)?(ATL\d{2})-(\d{2})_(\d{4})(\d{2})(\d{2})'
r'(\d{2})(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$')
SUB,PRD,HEM,YY,MM,DD,HH,MN,SS,TRK,CYCL,SN,RL,VERS,AUX=rx.findall(FILE).pop()
#-- number of GPS seconds between the GPS epoch
#-- and ATLAS Standard Data Product (SDP) epoch
atlas_sdp_gps_epoch = IS2_atl07_mds['ancillary_data']['atlas_sdp_gps_epoch']
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data','merged_deltat.data'])
#-- copy variables for outputting to HDF5 file
IS2_atl07_tide = {}
IS2_atl07_fill = {}
IS2_atl07_dims = {}
IS2_atl07_tide_attrs = {}
#-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC)
#-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC)
#-- Add this value to delta time parameters to compute full gps_seconds
IS2_atl07_tide['ancillary_data'] = {}
IS2_atl07_tide_attrs['ancillary_data'] = {}
for key in ['atlas_sdp_gps_epoch']:
#-- get each HDF5 variable
IS2_atl07_tide['ancillary_data'][key] = IS2_atl07_mds['ancillary_data'][key]
#-- Getting attributes of group and included variables
IS2_atl07_tide_attrs['ancillary_data'][key] = {}
for att_name,att_val in IS2_atl07_attrs['ancillary_data'][key].items():
IS2_atl07_tide_attrs['ancillary_data'][key][att_name] = att_val
#-- for each input beam within the file
for gtx in sorted(IS2_atl07_beams):
#-- output data dictionaries for beam
IS2_atl07_tide[gtx] = dict(sea_ice_segments={})
IS2_atl07_fill[gtx] = dict(sea_ice_segments={})
IS2_atl07_dims[gtx] = dict(sea_ice_segments={})
IS2_atl07_tide_attrs[gtx] = dict(sea_ice_segments={})
#-- number of segments
val = IS2_atl07_mds[gtx]['sea_ice_segments']
n_seg = len(val['height_segment_id'])
#-- convert time from ATLAS SDP to days relative to Jan 1, 1992
gps_seconds = atlas_sdp_gps_epoch + val['delta_time']
leap_seconds = pyTMD.time.count_leap_seconds(gps_seconds)
tide_time = pyTMD.time.convert_delta_time(gps_seconds-leap_seconds,
epoch1=(1980,1,6,0,0,0), epoch2=(1992,1,1,0,0,0), scale=1.0/86400.0)
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS','ATLAS'):
amp,ph,D,c = extract_tidal_constants(val['longitude'],
val['latitude'], grid_file, model_file, EPSG, TYPE=TYPE,
METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE, GRID=model_format)
deltat = np.zeros_like(tide_time)
elif (model_format == 'netcdf'):
amp,ph,D,c = extract_netcdf_constants(val['longitude'],
val['latitude'], grid_file, model_file, TYPE=TYPE, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, SCALE=SCALE, GZIP=GZIP)
deltat = np.zeros_like(tide_time)
elif (model_format == 'GOT'):
amp,ph,c = extract_GOT_constants(val['longitude'], val['latitude'],
model_file, METHOD=METHOD, EXTRAPOLATE=EXTRAPOLATE, SCALE=SCALE,
GZIP=GZIP)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
elif (model_format == 'FES'):
amp,ph = extract_FES_constants(val['longitude'], val['latitude'],
model_file, TYPE=TYPE, VERSION=TIDE_MODEL, METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE, SCALE=SCALE, GZIP=GZIP)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j*ph*np.pi/180.0
#-- calculate constituent oscillation
hc = amp*np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
tide = np.ma.empty((n_seg))
tide.mask = np.any(hc.mask,axis=1)
tide.data[:] = predict_tide_drift(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
minor = infer_minor_corrections(tide_time, hc, c,
DELTAT=deltat, CORRECTIONS=model_format)
tide.data[:] += minor.data[:]
#-- replace masked and nan values with fill value
invalid, = np.nonzero(np.isnan(tide.data) | tide.mask)
tide.data[invalid] = tide.fill_value
tide.mask[invalid] = True
#-- group attributes for beam
IS2_atl07_tide_attrs[gtx]['Description'] = IS2_atl07_attrs[gtx]['Description']
IS2_atl07_tide_attrs[gtx]['atlas_pce'] = IS2_atl07_attrs[gtx]['atlas_pce']
IS2_atl07_tide_attrs[gtx]['atlas_beam_type'] = IS2_atl07_attrs[gtx]['atlas_beam_type']
IS2_atl07_tide_attrs[gtx]['groundtrack_id'] = IS2_atl07_attrs[gtx]['groundtrack_id']
IS2_atl07_tide_attrs[gtx]['atmosphere_profile'] = IS2_atl07_attrs[gtx]['atmosphere_profile']
IS2_atl07_tide_attrs[gtx]['atlas_spot_number'] = IS2_atl07_attrs[gtx]['atlas_spot_number']
IS2_atl07_tide_attrs[gtx]['sc_orientation'] = IS2_atl07_attrs[gtx]['sc_orientation']
#-- group attributes for sea_ice_segments
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['Description'] = ("Top group for sea "
"ice segments as computed by the ATBD algorithm.")
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['data_rate'] = ("Data within this "
"group are stored at the variable segment rate.")
#-- geolocation, time and segment ID
#-- delta time
IS2_atl07_tide[gtx]['sea_ice_segments']['delta_time'] = val['delta_time'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['delta_time'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['delta_time'] = None
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['units'] = "seconds since 2018-01-01"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['long_name'] = "Elapsed GPS seconds"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['standard_name'] = "time"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['source'] = "telemetry"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['calendar'] = "standard"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['description'] = ("Number of "
"GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch "
"offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS "
"seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP "
"epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time "
"parameters, the time in gps_seconds relative to the GPS epoch can be computed.")
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['delta_time']['coordinates'] = \
"height_segment_id latitude longitude"
#-- latitude
IS2_atl07_tide[gtx]['sea_ice_segments']['latitude'] = val['latitude'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['latitude'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['latitude'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['units'] = "degrees_north"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['contentType'] = "physicalMeasurement"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['long_name'] = "Latitude"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['standard_name'] = "latitude"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['description'] = ("Latitude of "
"segment center")
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['valid_min'] = -90.0
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['valid_max'] = 90.0
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['latitude']['coordinates'] = \
"height_segment_id delta_time longitude"
#-- longitude
IS2_atl07_tide[gtx]['sea_ice_segments']['longitude'] = val['longitude'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['longitude'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['longitude'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['units'] = "degrees_east"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['contentType'] = "physicalMeasurement"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['long_name'] = "Longitude"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['standard_name'] = "longitude"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['description'] = ("Longitude of "
"segment center")
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['valid_min'] = -180.0
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['valid_max'] = 180.0
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['longitude']['coordinates'] = \
"height_segment_id delta_time latitude"
#-- segment ID
IS2_atl07_tide[gtx]['sea_ice_segments']['height_segment_id'] = val['height_segment_id']
IS2_atl07_fill[gtx]['sea_ice_segments']['height_segment_id'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['height_segment_id'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id']['units'] = "1"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id']['contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id']['long_name'] = \
"Identifier of each height segment"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id']['description'] = \
"Identifier of each height segment"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['height_segment_id']['coordinates'] = \
"delta_time latitude longitude"
#-- geolocation segment beginning
IS2_atl07_tide[gtx]['sea_ice_segments']['geoseg_beg'] = val['geoseg_beg'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['geoseg_beg'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['geoseg_beg'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg']['units'] = "1"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg']['contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg']['long_name'] = "Beginning GEOSEG"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg']['description'] = \
"Geolocation segment (geoseg) ID associated with the first photon used in this sea ice segment"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_beg']['coordinates'] = \
"height_segment_id delta_time latitude longitude"
#-- geolocation segment ending
IS2_atl07_tide[gtx]['sea_ice_segments']['geoseg_end'] = val['geoseg_end'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['geoseg_end'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['geoseg_end'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end']['units'] = "1"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end']['contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end']['long_name'] = "Ending GEOSEG"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end']['description'] = \
"Geolocation segment (geoseg) ID associated with the last photon used in this sea ice segment"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geoseg_end']['coordinates'] = \
"height_segment_id delta_time latitude longitude"
#-- along track distance
IS2_atl07_tide[gtx]['sea_ice_segments']['seg_dist_x'] = val['seg_dist_x'].copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['seg_dist_x'] = None
IS2_atl07_dims[gtx]['sea_ice_segments']['seg_dist_x'] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x']['units'] = "meters"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x']['contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x']['long_name'] = "Along track distance"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x']['description'] = \
"Along-track distance from the equator crossing to the segment center."
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['seg_dist_x']['coordinates'] = \
"height_segment_id delta_time latitude longitude"
#-- geophysical variables
IS2_atl07_tide[gtx]['sea_ice_segments']['geophysical'] = {}
IS2_atl07_fill[gtx]['sea_ice_segments']['geophysical'] = {}
IS2_atl07_dims[gtx]['sea_ice_segments']['geophysical'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical']['Description'] = ("Contains geophysical "
"parameters and corrections used to correct photon heights for geophysical effects, such as tides.")
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical']['data_rate'] = ("Data within this group "
"are stored at the sea_ice_height segment rate.")
#-- computed tide
IS2_atl07_tide[gtx]['sea_ice_segments']['geophysical'][variable] = tide.copy()
IS2_atl07_fill[gtx]['sea_ice_segments']['geophysical'][variable] = tide.fill_value
IS2_atl07_dims[gtx]['sea_ice_segments']['geophysical'][variable] = ['delta_time']
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][variable] = {}
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][variable]['units'] = "meters"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][variable]['contentType'] = "referenceInformation"
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][variable]['long_name'] = long_name
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][variable]['description'] = description
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][variable]['source'] = TIDE_MODEL
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][variable]['reference'] = reference
IS2_atl07_tide_attrs[gtx]['sea_ice_segments']['geophysical'][variable]['coordinates'] = \
"../height_segment_id ../delta_time ../latitude ../longitude"
#-- output tidal HDF5 file
args = (PRD,HEM,TIDE_MODEL,YY,MM,DD,HH,MN,SS,TRK,CYCL,SN,RL,VERS,AUX)
ff = '{0}-{1}_{2}_TIDES_{3}{4}{5}{6}{7}{8}_{9}{10}{11}_{12}_{13}{14}.h5'
#-- print file information
print('\t{0}'.format(ff.format(*args))) if VERBOSE else None
HDF5_ATL07_tide_write(IS2_atl07_tide, IS2_atl07_tide_attrs,
CLOBBER=True, INPUT=os.path.basename(FILE),
FILL_VALUE=IS2_atl07_fill, DIMENSIONS=IS2_atl07_dims,
FILENAME=os.path.join(DIRECTORY,ff.format(*args)))
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY,ff.format(*args)), MODE)
def compute_tides_ICESat(tide_dir,
INPUT_FILE,
TIDE_MODEL=None,
METHOD='spline',
EXTRAPOLATE=False,
CUTOFF=None,
VERBOSE=False,
MODE=0o775):
#-- select between tide models
if (TIDE_MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir, 'cats0201_tmd', 'grid_CATS')
model_file = os.path.join(tide_dir, 'cats0201_tmd', 'h0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir, 'CATS2008', 'grid_CATS2008')
model_file = os.path.join(tide_dir, 'CATS2008', 'hf.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'CATS2008_load'):
grid_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'grid_CATS2008a_opt')
model_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'h_CATS2008a_SPOTL_load')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
variable = 'd_ldElv'
long_name = "Load Tide Elevation"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'OTIS'
EPSG = 'CATS2008'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas')
grid_file = os.path.join(model_directory, 'grid_tpxo9_atlas.nc.gz')
model_files = [
'h_q1_tpxo9_atlas_30.nc.gz', 'h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz', 'h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz', 'h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz', 'h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz', 'h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz', 'h_2n2_tpxo9_atlas_30.nc.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0 / 1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v2'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas_v2')
grid_file = os.path.join(model_directory,
'grid_tpxo9_atlas_30_v2.nc.gz')
model_files = [
'h_q1_tpxo9_atlas_30_v2.nc.gz', 'h_o1_tpxo9_atlas_30_v2.nc.gz',
'h_p1_tpxo9_atlas_30_v2.nc.gz', 'h_k1_tpxo9_atlas_30_v2.nc.gz',
'h_n2_tpxo9_atlas_30_v2.nc.gz', 'h_m2_tpxo9_atlas_30_v2.nc.gz',
'h_s2_tpxo9_atlas_30_v2.nc.gz', 'h_k2_tpxo9_atlas_30_v2.nc.gz',
'h_m4_tpxo9_atlas_30_v2.nc.gz', 'h_ms4_tpxo9_atlas_30_v2.nc.gz',
'h_mn4_tpxo9_atlas_30_v2.nc.gz', 'h_2n2_tpxo9_atlas_30_v2.nc.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0 / 1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v3'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas_v3')
grid_file = os.path.join(model_directory,
'grid_tpxo9_atlas_30_v3.nc.gz')
model_files = [
'h_q1_tpxo9_atlas_30_v3.nc.gz', 'h_o1_tpxo9_atlas_30_v3.nc.gz',
'h_p1_tpxo9_atlas_30_v3.nc.gz', 'h_k1_tpxo9_atlas_30_v3.nc.gz',
'h_n2_tpxo9_atlas_30_v3.nc.gz', 'h_m2_tpxo9_atlas_30_v3.nc.gz',
'h_s2_tpxo9_atlas_30_v3.nc.gz', 'h_k2_tpxo9_atlas_30_v3.nc.gz',
'h_m4_tpxo9_atlas_30_v3.nc.gz', 'h_ms4_tpxo9_atlas_30_v3.nc.gz',
'h_mn4_tpxo9_atlas_30_v3.nc.gz', 'h_2n2_tpxo9_atlas_30_v3.nc.gz',
'h_mf_tpxo9_atlas_30_v3.nc.gz', 'h_mm_tpxo9_atlas_30_v3.nc.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'netcdf'
TYPE = 'z'
SCALE = 1.0 / 1000.0
GZIP = True
elif (TIDE_MODEL == 'TPXO9-atlas-v4'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas_v4')
grid_file = os.path.join(model_directory, 'grid_tpxo9_atlas_30_v4')
model_files = [
'h_q1_tpxo9_atlas_30_v4', 'h_o1_tpxo9_atlas_30_v4',
'h_p1_tpxo9_atlas_30_v4', 'h_k1_tpxo9_atlas_30_v4',
'h_n2_tpxo9_atlas_30_v4', 'h_m2_tpxo9_atlas_30_v4',
'h_s2_tpxo9_atlas_30_v4', 'h_k2_tpxo9_atlas_30_v4',
'h_m4_tpxo9_atlas_30_v4', 'h_ms4_tpxo9_atlas_30_v4',
'h_mn4_tpxo9_atlas_30_v4', 'h_2n2_tpxo9_atlas_30_v4',
'h_mf_tpxo9_atlas_30_v4', 'h_mm_tpxo9_atlas_30_v4'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
reference = 'https://www.tpxo.net/global/tpxo9-atlas'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'grid_tpxo9')
model_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'h_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir, 'tpxo8_atlas',
'grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir, 'tpxo8_atlas',
'hf.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'ATLAS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'grid_tpxo7.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'h_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_load', 'grid_tpxo6.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_load', 'h_tpxo7.2_load')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
variable = 'd_ldElv'
long_name = "Load Tide Elevation"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'OTIS'
EPSG = '4326'
TYPE = 'z'
elif (TIDE_MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir, 'aodtm5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aodtm5_tmd', 'h0_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir, 'aotim5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aotim5_tmd', 'h_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'AOTIM-5-2018'):
grid_file = os.path.join(tide_dir, 'Arc5km2018', 'grid_Arc5km2018')
model_file = os.path.join(tide_dir, 'Arc5km2018', 'h_Arc5km2018')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = 'PSNorth'
TYPE = 'z'
elif (TIDE_MODEL == 'Gr1km-v2'):
grid_file = os.path.join(tide_dir, 'greenlandTMD_v2',
'grid_Greenland8.v2')
model_file = os.path.join(tide_dir, 'greenlandTMD_v2',
'h_Greenland8.v2')
reference = 'https://doi.org/10.1002/2016RG000546'
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'OTIS'
EPSG = '3413'
TYPE = 'z'
elif (TIDE_MODEL == 'GOT4.7'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.7_load'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'd_ldElv'
long_name = "Load Tide Elevation"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.8'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.8_load'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'd_ldElv'
long_name = "Load Tide Elevation"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.10'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'GOT'
SCALE = 1.0 / 100.0
GZIP = True
elif (TIDE_MODEL == 'GOT4.10_load'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
variable = 'd_ldElv'
long_name = "Load Tide Elevation"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'GOT'
SCALE = 1.0 / 1000.0
GZIP = True
elif (TIDE_MODEL == 'FES2014'):
model_directory = os.path.join(tide_dir, 'fes2014', 'ocean_tide')
model_files = [
'2n2.nc.gz', 'eps2.nc.gz', 'j1.nc.gz', 'k1.nc.gz', 'k2.nc.gz',
'l2.nc.gz', 'la2.nc.gz', 'm2.nc.gz', 'm3.nc.gz', 'm4.nc.gz',
'm6.nc.gz', 'm8.nc.gz', 'mf.nc.gz', 'mks2.nc.gz', 'mm.nc.gz',
'mn4.nc.gz', 'ms4.nc.gz', 'msf.nc.gz', 'msqm.nc.gz', 'mtm.nc.gz',
'mu2.nc.gz', 'n2.nc.gz', 'n4.nc.gz', 'nu2.nc.gz', 'o1.nc.gz',
'p1.nc.gz', 'q1.nc.gz', 'r2.nc.gz', 's1.nc.gz', 's2.nc.gz',
's4.nc.gz', 'sa.nc.gz', 'ssa.nc.gz', 't2.nc.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
c = [
'2n2', 'eps2', 'j1', 'k1', 'k2', 'l2', 'lambda2', 'm2', 'm3', 'm4',
'm6', 'm8', 'mf', 'mks2', 'mm', 'mn4', 'ms4', 'msf', 'msqm', 'mtm',
'mu2', 'n2', 'n4', 'nu2', 'o1', 'p1', 'q1', 'r2', 's1', 's2', 's4',
'sa', 'ssa', 't2'
]
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
variable = 'd_ocElv'
long_name = "Ocean Tide Elevation"
description = (
"Ocean Tides including diurnal and semi-diurnal "
"(harmonic analysis), and longer period tides (dynamic and "
"self-consistent equilibrium).")
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0 / 100.0
GZIP = True
elif (TIDE_MODEL == 'FES2014_load'):
model_directory = os.path.join(tide_dir, 'fes2014', 'load_tide')
model_files = [
'2n2.nc.gz', 'eps2.nc.gz', 'j1.nc.gz', 'k1.nc.gz', 'k2.nc.gz',
'l2.nc.gz', 'la2.nc.gz', 'm2.nc.gz', 'm3.nc.gz', 'm4.nc.gz',
'm6.nc.gz', 'm8.nc.gz', 'mf.nc.gz', 'mks2.nc.gz', 'mm.nc.gz',
'mn4.nc.gz', 'ms4.nc.gz', 'msf.nc.gz', 'msqm.nc.gz', 'mtm.nc.gz',
'mu2.nc.gz', 'n2.nc.gz', 'n4.nc.gz', 'nu2.nc.gz', 'o1.nc.gz',
'p1.nc.gz', 'q1.nc.gz', 'r2.nc.gz', 's1.nc.gz', 's2.nc.gz',
's4.nc.gz', 'sa.nc.gz', 'ssa.nc.gz', 't2.nc.gz'
]
model_file = [os.path.join(model_directory, m) for m in model_files]
c = [
'2n2', 'eps2', 'j1', 'k1', 'k2', 'l2', 'lambda2', 'm2', 'm3', 'm4',
'm6', 'm8', 'mf', 'mks2', 'mm', 'mn4', 'ms4', 'msf', 'msqm', 'mtm',
'mu2', 'n2', 'n4', 'nu2', 'o1', 'p1', 'q1', 'r2', 's1', 's2', 's4',
'sa', 'ssa', 't2'
]
reference = ('https://www.aviso.altimetry.fr/en/data/products'
'auxiliary-products/global-tide-fes.html')
variable = 'd_ldElv'
long_name = "Load Tide Elevation"
description = "Local displacement due to Ocean Loading (-6 to 0 cm)"
model_format = 'FES'
TYPE = 'z'
SCALE = 1.0 / 100.0
GZIP = True
#-- get directory from INPUT_FILE
print('{0} -->'.format(os.path.basename(INPUT_FILE))) if VERBOSE else None
DIRECTORY = os.path.dirname(INPUT_FILE)
#-- compile regular expression operator for extracting information from file
rx = re.compile((r'GLAH(\d{2})_(\d{3})_(\d{1})(\d{1})(\d{2})_(\d{3})_'
r'(\d{4})_(\d{1})_(\d{2})_(\d{4})\.H5'), re.VERBOSE)
#-- extract parameters from ICESat/GLAS HDF5 file name
#-- PRD: Product number (01, 05, 06, 12, 13, 14, or 15)
#-- RL: Release number for process that created the product = 634
#-- RGTP: Repeat ground-track phase (1=8-day, 2=91-day, 3=transfer orbit)
#-- ORB: Reference orbit number (starts at 1 and increments each time a
#-- new reference orbit ground track file is obtained.)
#-- INST: Instance number (increments every time the satellite enters a
#-- different reference orbit)
#-- CYCL: Cycle of reference orbit for this phase
#-- TRK: Track within reference orbit
#-- SEG: Segment of orbit
#-- GRAN: Granule version number
#-- TYPE: File type
try:
PRD, RL, RGTP, ORB, INST, CYCL, TRK, SEG, GRAN, TYPE = rx.findall(
INPUT_FILE).pop()
except:
#-- output tide HDF5 file (generic)
fileBasename, fileExtension = os.path.splitext(INPUT_FILE)
args = (fileBasename, TIDE_MODEL, fileExtension)
OUTPUT_FILE = '{0}_{1}_TIDES{2}'.format(*args)
else:
#-- output tide HDF5 file for NSIDC granules
args = (PRD, RL, TIDE_MODEL, RGTP, ORB, INST, CYCL, TRK, SEG, GRAN,
TYPE)
file_format = 'GLAH{0}_{1}_{2}_TIDES_{3}{4}{5}_{6}_{7}_{8}_{9}_{10}.h5'
OUTPUT_FILE = file_format.format(*args)
#-- read GLAH12 HDF5 file
fileID = h5py.File(INPUT_FILE, 'r')
n_40HZ, = fileID['Data_40HZ']['Time']['i_rec_ndx'].shape
#-- get variables and attributes
rec_ndx_40HZ = fileID['Data_40HZ']['Time']['i_rec_ndx'][:].copy()
#-- seconds since 2000-01-01 12:00:00 UTC (J2000)
DS_UTCTime_40HZ = fileID['Data_40HZ']['DS_UTCTime_40'][:].copy()
#-- Latitude (degrees North)
lat_TPX = fileID['Data_40HZ']['Geolocation']['d_lat'][:].copy()
#-- Longitude (degrees East)
lon_40HZ = fileID['Data_40HZ']['Geolocation']['d_lon'][:].copy()
#-- Elevation (height above TOPEX/Poseidon ellipsoid in meters)
elev_TPX = fileID['Data_40HZ']['Elevation_Surfaces']['d_elev'][:].copy()
fv = fileID['Data_40HZ']['Elevation_Surfaces']['d_elev'].attrs[
'_FillValue']
#-- semimajor axis (a) and flattening (f) for TP and WGS84 ellipsoids
atop, ftop = (6378136.3, 1.0 / 298.257)
awgs, fwgs = (6378137.0, 1.0 / 298.257223563)
#-- convert from Topex/Poseidon to WGS84 Ellipsoids
lat_40HZ, elev_40HZ = pyTMD.spatial.convert_ellipsoid(lat_TPX,
elev_TPX,
atop,
ftop,
awgs,
fwgs,
eps=1e-12,
itmax=10)
#-- convert time from J2000 to days relative to Jan 1, 1992 (48622mjd)
#-- J2000: seconds since 2000-01-01 12:00:00 UTC
tide_time = pyTMD.time.convert_delta_time(DS_UTCTime_40HZ,
epoch1=(2000, 1, 1, 12, 0, 0),
epoch2=(1992, 1, 1, 0, 0, 0),
scale=1.0 / 86400.0)
#-- delta time (TT - UT1) file
delta_file = pyTMD.utilities.get_data_path(['data', 'merged_deltat.data'])
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS', 'ATLAS'):
amp, ph, D, c = extract_tidal_constants(lon_40HZ,
lat_40HZ,
grid_file,
model_file,
EPSG,
TYPE=TYPE,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
GRID=model_format)
deltat = np.zeros_like(tide_time)
elif (model_format == 'netcdf'):
amp, ph, D, c = extract_netcdf_constants(lon_40HZ,
lat_40HZ,
grid_file,
model_file,
TYPE=TYPE,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=SCALE,
GZIP=GZIP)
deltat = np.zeros_like(tide_time)
elif (model_format == 'GOT'):
amp, ph, c = extract_GOT_constants(lon_40HZ,
lat_40HZ,
model_file,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=SCALE,
GZIP=GZIP)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
elif (model_format == 'FES'):
amp, ph = extract_FES_constants(lon_40HZ,
lat_40HZ,
model_file,
TYPE=TYPE,
VERSION=TIDE_MODEL,
METHOD=METHOD,
EXTRAPOLATE=EXTRAPOLATE,
CUTOFF=CUTOFF,
SCALE=SCALE,
GZIP=GZIP)
#-- interpolate delta times from calendar dates to tide time
deltat = calc_delta_time(delta_file, tide_time)
#-- calculate complex phase in radians for Euler's
cph = -1j * ph * np.pi / 180.0
#-- calculate constituent oscillation
hc = amp * np.exp(cph)
#-- predict tidal elevations at time and infer minor corrections
tide = np.ma.empty((n_40HZ), fill_value=fv)
tide.mask = np.any(hc.mask, axis=1)
tide.data[:] = predict_tide_drift(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model_format)
minor = infer_minor_corrections(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model_format)
tide.data[:] += minor.data[:]
#-- replace masked and nan values with fill value
invalid, = np.nonzero(np.isnan(tide.data) | tide.mask)
tide.data[invalid] = tide.fill_value
tide.mask[invalid] = True
#-- copy variables for outputting to HDF5 file
IS_gla12_tide = dict(Data_40HZ={})
IS_gla12_fill = dict(Data_40HZ={})
IS_gla12_tide_attrs = dict(Data_40HZ={})
#-- copy global file attributes
global_attribute_list = [
'featureType', 'title', 'comment', 'summary', 'license', 'references',
'AccessConstraints', 'CitationforExternalPublication',
'contributor_role', 'contributor_name', 'creator_name',
'creator_email', 'publisher_name', 'publisher_email', 'publisher_url',
'platform', 'instrument', 'processing_level', 'date_created',
'spatial_coverage_type', 'history', 'keywords', 'keywords_vocabulary',
'naming_authority', 'project', 'time_type', 'date_type',
'time_coverage_start', 'time_coverage_end', 'time_coverage_duration',
'source', 'HDFVersion', 'identifier_product_type',
'identifier_product_format_version', 'Conventions', 'institution',
'ReprocessingPlanned', 'ReprocessingActual', 'LocalGranuleID',
'ProductionDateTime', 'LocalVersionID', 'PGEVersion', 'OrbitNumber',
'StartOrbitNumber', 'StopOrbitNumber', 'EquatorCrossingLongitude',
'EquatorCrossingTime', 'EquatorCrossingDate', 'ShortName', 'VersionID',
'InputPointer', 'RangeBeginningTime', 'RangeEndingTime',
'RangeBeginningDate', 'RangeEndingDate', 'PercentGroundHit',
'OrbitQuality', 'Cycle', 'Track', 'Instrument_State', 'Timing_Bias',
'ReferenceOrbit', 'SP_ICE_PATH_NO', 'SP_ICE_GLAS_StartBlock',
'SP_ICE_GLAS_EndBlock', 'Instance', 'Range_Bias',
'Instrument_State_Date', 'Instrument_State_Time', 'Range_Bias_Date',
'Range_Bias_Time', 'Timing_Bias_Date', 'Timing_Bias_Time',
'identifier_product_doi', 'identifier_file_uuid',
'identifier_product_doi_authority'
]
for att in global_attribute_list:
IS_gla12_tide_attrs[att] = fileID.attrs[att]
#-- add attributes for input GLA12 file
IS_gla12_tide_attrs['input_files'] = os.path.basename(INPUT_FILE)
#-- update geospatial ranges for ellipsoid
IS_gla12_tide_attrs['geospatial_lat_min'] = np.min(lat_40HZ)
IS_gla12_tide_attrs['geospatial_lat_max'] = np.max(lat_40HZ)
IS_gla12_tide_attrs['geospatial_lon_min'] = np.min(lon_40HZ)
IS_gla12_tide_attrs['geospatial_lon_max'] = np.max(lon_40HZ)
IS_gla12_tide_attrs['geospatial_lat_units'] = "degrees_north"
IS_gla12_tide_attrs['geospatial_lon_units'] = "degrees_east"
IS_gla12_tide_attrs['geospatial_ellipsoid'] = "WGS84"
#-- copy 40Hz group attributes
for att_name, att_val in fileID['Data_40HZ'].attrs.items():
IS_gla12_tide_attrs['Data_40HZ'][att_name] = att_val
#-- copy attributes for time, geolocation and geophysical groups
for var in ['Time', 'Geolocation', 'Geophysical']:
IS_gla12_tide['Data_40HZ'][var] = {}
IS_gla12_fill['Data_40HZ'][var] = {}
IS_gla12_tide_attrs['Data_40HZ'][var] = {}
for att_name, att_val in fileID['Data_40HZ'][var].attrs.items():
IS_gla12_tide_attrs['Data_40HZ'][var][att_name] = att_val
#-- J2000 time
IS_gla12_tide['Data_40HZ']['DS_UTCTime_40'] = DS_UTCTime_40HZ
IS_gla12_fill['Data_40HZ']['DS_UTCTime_40'] = None
IS_gla12_tide_attrs['Data_40HZ']['DS_UTCTime_40'] = {}
for att_name, att_val in fileID['Data_40HZ']['DS_UTCTime_40'].attrs.items(
):
if att_name not in ('DIMENSION_LIST', 'CLASS', 'NAME'):
IS_gla12_tide_attrs['Data_40HZ']['DS_UTCTime_40'][
att_name] = att_val
#-- record
IS_gla12_tide['Data_40HZ']['Time']['i_rec_ndx'] = rec_ndx_40HZ
IS_gla12_fill['Data_40HZ']['Time']['i_rec_ndx'] = None
IS_gla12_tide_attrs['Data_40HZ']['Time']['i_rec_ndx'] = {}
IS_gla12_tide_attrs['Data_40HZ']['Time']['i_rec_ndx']['coordinates'] = \
"../DS_UTCTime_40"
for att_name, att_val in fileID['Data_40HZ']['Time'][
'i_rec_ndx'].attrs.items():
if att_name not in ('DIMENSION_LIST', 'CLASS', 'NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Time']['i_rec_ndx'][
att_name] = att_val
#-- latitude
IS_gla12_tide['Data_40HZ']['Geolocation']['d_lat'] = lat_40HZ
IS_gla12_fill['Data_40HZ']['Geolocation']['d_lat'] = None
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lat'] = {}
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lat']['coordinates'] = \
"../DS_UTCTime_40"
for att_name, att_val in fileID['Data_40HZ']['Geolocation'][
'd_lat'].attrs.items():
if att_name not in ('DIMENSION_LIST', 'CLASS', 'NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lat'][
att_name] = att_val
#-- longitude
IS_gla12_tide['Data_40HZ']['Geolocation']['d_lon'] = lon_40HZ
IS_gla12_fill['Data_40HZ']['Geolocation']['d_lon'] = None
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lon'] = {}
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lon']['coordinates'] = \
"../DS_UTCTime_40"
for att_name, att_val in fileID['Data_40HZ']['Geolocation'][
'd_lon'].attrs.items():
if att_name not in ('DIMENSION_LIST', 'CLASS', 'NAME'):
IS_gla12_tide_attrs['Data_40HZ']['Geolocation']['d_lon'][
att_name] = att_val
#-- geophysical variables
#-- computed tide
IS_gla12_tide['Data_40HZ']['Geophysical'][variable] = tide
IS_gla12_fill['Data_40HZ']['Geophysical'][variable] = tide.fill_value
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][variable] = {}
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][variable][
'units'] = "meters"
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][variable][
'long_name'] = long_name
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][variable][
'description'] = description
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][variable][
'source'] = TIDE_MODEL
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][variable][
'reference'] = reference
IS_gla12_tide_attrs['Data_40HZ']['Geophysical'][variable]['coordinates'] = \
"../DS_UTCTime_40"
#-- close the input HDF5 file
fileID.close()
#-- print file information
print('\t{0}'.format(OUTPUT_FILE)) if VERBOSE else None
HDF5_GLA12_tide_write(IS_gla12_tide,
IS_gla12_tide_attrs,
FILENAME=os.path.join(DIRECTORY, OUTPUT_FILE),
FILL_VALUE=IS_gla12_fill,
CLOBBER=True)
#-- change the permissions mode
os.chmod(os.path.join(DIRECTORY, OUTPUT_FILE), MODE)
def plot_tide_forecasts(tide_dir, LON, LAT, DATE, TIDE_MODEL=''):
#-- select between tide models
if (TIDE_MODEL == 'CATS0201'):
grid_file = os.path.join(tide_dir, 'cats0201_tmd', 'grid_CATS')
model_file = os.path.join(tide_dir, 'cats0201_tmd', 'h0_CATS02_01')
reference = 'https://mail.esr.org/polar_tide_models/Model_CATS0201.html'
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'CATS2008'):
grid_file = os.path.join(tide_dir, 'CATS2008', 'grid_CATS2008a_opt')
model_file = os.path.join(tide_dir, 'CATS2008', 'hf.CATS2008.out')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
model_format = 'OTIS'
EPSG = 'CATS2008'
type = 'z'
elif (TIDE_MODEL == 'CATS2008_load'):
grid_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'grid_CATS2008a_opt')
model_file = os.path.join(tide_dir, 'CATS2008a_SPOTL_Load',
'h_CATS2008a_SPOTL_load')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/cats2008/')
model_format = 'OTIS'
EPSG = 'CATS2008'
type = 'z'
elif (TIDE_MODEL == 'TPXO9-atlas'):
model_directory = os.path.join(tide_dir, 'TPXO9_atlas')
grid_file = 'grid_tpxo9_atlas.nc.gz'
model_files = [
'h_q1_tpxo9_atlas_30.nc.gz', 'h_o1_tpxo9_atlas_30.nc.gz',
'h_p1_tpxo9_atlas_30.nc.gz', 'h_k1_tpxo9_atlas_30.nc.gz',
'h_n2_tpxo9_atlas_30.nc.gz', 'h_m2_tpxo9_atlas_30.nc.gz',
'h_s2_tpxo9_atlas_30.nc.gz', 'h_k2_tpxo9_atlas_30.nc.gz',
'h_m4_tpxo9_atlas_30.nc.gz', 'h_ms4_tpxo9_atlas_30.nc.gz',
'h_mn4_tpxo9_atlas_30.nc.gz', 'h_2n2_tpxo9_atlas_30.nc.gz'
]
reference = 'http://volkov.oce.orst.edu/tides/tpxo9_atlas.html'
model_format = 'netcdf'
type = 'z'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'TPXO9.1'):
grid_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'grid_tpxo9')
model_file = os.path.join(tide_dir, 'TPXO9.1', 'DATA', 'h_tpxo9.v1')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'TPXO8-atlas'):
grid_file = os.path.join(tide_dir, 'tpxo8_atlas',
'grid_tpxo8atlas_30_v1')
model_file = os.path.join(tide_dir, 'tpxo8_atlas',
'hf.tpxo8_atlas_30_v1')
reference = 'http://volkov.oce.orst.edu/tides/tpxo8_atlas.html'
model_format = 'ATLAS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'TPXO7.2'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'grid_tpxo7.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_tmd', 'h_tpxo7.2')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'TPXO7.2_load'):
grid_file = os.path.join(tide_dir, 'TPXO7.2_load', 'grid_tpxo6.2')
model_file = os.path.join(tide_dir, 'TPXO7.2_load', 'h_tpxo7.2_load')
reference = 'http://volkov.oce.orst.edu/tides/global.html'
model_format = 'OTIS'
EPSG = '4326'
type = 'z'
elif (TIDE_MODEL == 'AODTM-5'):
grid_file = os.path.join(tide_dir, 'aodtm5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aodtm5_tmd', 'h0_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aodtm-5/')
model_format = 'OTIS'
EPSG = '3996'
type = 'z'
elif (TIDE_MODEL == 'AOTIM-5'):
grid_file = os.path.join(tide_dir, 'aotim5_tmd', 'grid_Arc5km')
model_file = os.path.join(tide_dir, 'aotim5_tmd', 'h_Arc5km.oce')
reference = ('https://www.esr.org/research/polar-tide-models/'
'list-of-polar-tide-models/aotim-5/')
model_format = 'OTIS'
EPSG = '3996'
type = 'z'
elif (TIDE_MODEL == 'GOT4.7'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.7_load'):
model_directory = os.path.join(tide_dir, 'GOT4.7', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'GOT4.8'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.8_load'):
model_directory = os.path.join(tide_dir, 'got4.8', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 1000.0
elif (TIDE_MODEL == 'GOT4.10'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_oceantide')
model_files = [
'q1.d.gz', 'o1.d.gz', 'p1.d.gz', 'k1.d.gz', 'n2.d.gz', 'm2.d.gz',
's2.d.gz', 'k2.d.gz', 's1.d.gz', 'm4.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 100.0
elif (TIDE_MODEL == 'GOT4.10_load'):
model_directory = os.path.join(tide_dir, 'GOT4.10c', 'grids_loadtide')
model_files = [
'q1load.d.gz', 'o1load.d.gz', 'p1load.d.gz', 'k1load.d.gz',
'n2load.d.gz', 'm2load.d.gz', 's2load.d.gz', 'k2load.d.gz',
's1load.d.gz', 'm4load.d.gz'
]
c = ['q1', 'o1', 'p1', 'k1', 'n2', 'm2', 's2', 'k2', 's1', 'm4']
reference = ('https://denali.gsfc.nasa.gov/personal_pages/ray/'
'MiscPubs/19990089548_1999150788.pdf')
model_format = 'GOT'
SCALE = 1.0 / 1000.0
#-- calculate the modified Julian day from the calendar date
MJD = calc_modified_julian_day(DATE.tm_year, DATE.tm_mon, DATE.tm_mday)
TIME = np.arange(7 * 1440) / 1440.0
#-- read tidal constants and interpolate to grid points
if model_format in ('OTIS', 'ATLAS'):
amp, ph, D, c = extract_tidal_constants(np.array([LON]),
np.array([LAT]),
grid_file,
model_file,
EPSG,
type,
METHOD='spline',
GRID=model_format)
deltat = np.zeros_like(MJD)
elif (model_format == 'netcdf'):
amp, ph, D, c = extract_netcdf_constants(np.array([LON]),
np.array([LAT]),
model_directory,
grid_file,
model_files,
type,
METHOD='spline',
SCALE=SCALE)
deltat = np.zeros_like(MJD)
elif (model_format == 'GOT'):
amp, ph = extract_GOT_constants(np.array([LON]),
np.array([LAT]),
model_directory,
model_files,
METHOD='spline',
SCALE=SCALE)
delta_file = os.path.join(tide_dir, 'deltat.data')
deltat = calc_delta_time(delta_file, MJD + TIME)
#-- convert phase to radians
cph = -1j * ph * np.pi / 180.0
hc = amp * np.exp(cph)
#-- convert time from MJD to days relative to Jan 1, 1992 (48622 MJD)
#-- predict tidal elevations at time 1 and infer minor corrections
TIDE = predict_tidal_ts(MJD + TIME - 48622.0,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model_format)
TIDE += infer_minor_corrections(MJD + TIME - 48622.0,
hc,
c,
DELTAT=deltat,
CORRECTIONS=model_format)
#-- convert to centimeters
TIDE *= 100.0
#-- differentiate to calculate high and low tides
diff = np.zeros_like(TIME, dtype=np.float)
#-- forward differentiation for starting point
diff[0] = TIDE[1] - TIDE[0]
#-- backward differentiation for end point
diff[-1] = TIDE[-1] - TIDE[-2]
#-- centered differentiation for all others
diff[1:-1] = (TIDE[2:] - TIDE[0:-2]) / 2.0
#-- indices of high and low tides
htindex, = np.nonzero((np.sign(diff[0:-1]) >= 0) & (np.sign(diff[1:]) < 0))
ltindex, = np.nonzero((np.sign(diff[0:-1]) <= 0) & (np.sign(diff[1:]) > 0))
#-- create plot with tidal displacements, high and low tides and dates
fig, ax1 = plt.subplots(num=1)
ax1.plot(TIME * 24.0, TIDE, 'k')
ax1.plot(TIME[htindex] * 24.0, TIDE[htindex], 'r*')
ax1.plot(TIME[ltindex] * 24.0, TIDE[ltindex], 'b*')
for h in range(24, 192, 24):
ax1.axvline(h, color='gray', lw=0.5, ls='dashed', dashes=(11, 5))
ax1.set_xlim(0, 7 * 24)
ax1.set_ylabel('{0} Tidal Displacement [cm]'.format(TIDE_MODEL))
args = (DATE.tm_year, DATE.tm_mon, DATE.tm_mday)
ax1.set_xlabel(
'Time from {0:4d}-{1:02d}-{2:02d} UTC [Hours]'.format(*args))
ax1.set_title(u'{0:0.6f}\u00b0N {1:0.6f}\u00b0W'.format(LAT, LON))
fig.subplots_adjust(left=0.10, right=0.98, bottom=0.10, top=0.95)
plt.show()