def process_woa(config, decades):
'''
Download WOA 18 temperature and salinity, and remap them to the ISMIP6
grid
'''
try:
os.makedirs('woa')
except OSError:
pass
print('Processing World Ocean Atlas...')
woaDecades = ['95A4', 'A5B7']
woaWeights = [10., 13.]
for decade in woaDecades:
for fieldName, shortName in [('temperature', 't'), ('salinity', 's')]:
baseURL = 'https://data.nodc.noaa.gov/thredds/fileServer/ncei/' \
'woa/{}/{}/0.25/'.format(fieldName, decade)
fileNames = ['woa18_{}_{}00_04.nc'.format(decade, shortName)]
download_files(fileNames, baseURL, 'woa')
remap.remap_woa(config, woaDecades, woaWeights, decades)
print('Done.')
def process_meop(config):
'''
Download MEOP temperature and salinity, and bin them on the ISMIP6 grid
'''
try:
os.makedirs('meop')
except OSError:
pass
print('Processing Marine Mammals Exploring the Oceans Pole to Pole '
'(MEOP)...')
if not os.path.exists('meop/MEOP-CTD_2018-04-10'):
baseURL = 'https://www.seanoe.org/data/00343/45461/data'
fileNames = ['58202.zip']
download_files(fileNames, baseURL, 'meop')
print(' Decompressing MEOP data...')
args = ['unzip', 'meop/58202.zip', '-d', 'meop/']
returncode = subprocess.call(args)
if returncode not in [0, 1, 2]:
raise subprocess.CalledProcessError(returncode, args)
print(' Done.')
_bin_meop(config, 'TEMP', 'temperature')
_bin_meop(config, 'PSAL', 'salinity')
print('Done.')
def process_en4(config, startYear, endYear):
'''
Download EN4 temperature and salinity, and bin them on the ISMIP6 grid
'''
try:
os.makedirs('en4/zips')
except OSError:
pass
print('Processing UK Met Office EN4...')
if not os.path.exists('en4/profiles'):
baseURL = 'https://www.metoffice.gov.uk/hadobs/en4/data/en4-2-1/'
fileNames = [
'EN.4.2.1.profiles.g10.{}.zip'.format(year)
for year in range(startYear, endYear + 1)
]
download_files(fileNames, baseURL, 'en4/zips')
try:
os.makedirs('en4/profiles')
except OSError:
pass
print(' Decompressing EN4 data...')
widgets = [
' ',
progressbar.Percentage(), ' ',
progressbar.Bar(), ' ',
progressbar.ETA()
]
bar = progressbar.ProgressBar(widgets=widgets,
maxval=len(fileNames)).start()
for index, fileName in enumerate(fileNames):
with zipfile.ZipFile('en4/zips/{}'.format(fileName), 'r') as f:
f.extractall('en4/profiles')
bar.update(index + 1)
bar.finish()
res = get_res(config)
tempFileName = 'en4/en4_temperature_{}-{}_{}.nc'.format(
startYear, endYear, res)
salinFileName = 'en4/en4_salinity_{}-{}_{}.nc'.format(
startYear, endYear, res)
if not os.path.exists(salinFileName):
dsSalinity = _bin_en4(config, 'PSAL', 'salinity', startYear, endYear)
dsSalinity.to_netcdf(salinFileName)
dsSalinity.close()
if not os.path.exists(tempFileName):
dsSalinity = xarray.open_dataset(salinFileName)
dsPotTemp = _bin_en4(config, 'POTM', 'temperature', startYear, endYear)
dsTemp = potential_to_in_situ_temperature(dsPotTemp, dsSalinity)
dsTemp.to_netcdf(tempFileName)
print('Done.')
def _download_imbie():
'''
Download the geojson files that define the IMBIE basins
'''
if not os.path.exists(
'imbie/ANT_Basins_IMBIE2_v1.6/ANT_Basins_IMBIE2_v1.6.shp'):
# download
geojsonURL = 'http://imbie.org/wp-content/uploads/2016/09/'
fileNames = ['ANT_Basins_IMBIE2_v1.6.zip']
download_files(fileNames, geojsonURL, 'imbie')
print('Decompressing IMBIE2 data...')
# unzip
with zipfile.ZipFile('imbie/ANT_Basins_IMBIE2_v1.6.zip', 'r') as f:
f.extractall('imbie/ANT_Basins_IMBIE2_v1.6/')
print(' Done.')
def _bedmap2_bin_to_netcdf(outFileName):
if os.path.exists(outFileName):
return
fields = ['bed', 'surface', 'thickness', 'coverage', 'rockmask',
'grounded_bed_uncertainty', 'icemask_grounded_and_shelves']
allExist = True
for field in fields:
fileName = 'bedmap2/bedmap2_bin/bedmap2_{}.flt'.format(field)
if not os.path.exists(fileName):
allExist = False
break
if not allExist:
# download
baseURL = 'https://secure.antarctica.ac.uk/data/bedmap2'
fileNames = ['bedmap2_bin.zip']
download_files(fileNames, baseURL, 'bedmap2')
print('Decompressing Bedmap2 data...')
# unzip
with zipfile.ZipFile('bedmap2/bedmap2_bin.zip', 'r') as f:
f.extractall('bedmap2/')
print(' Done.')
print('Converting Bedmap2 to NetCDF...')
ds = xarray.Dataset()
x = numpy.linspace(-3333000., 3333000., 6667)
y = x
ds['x'] = ('x', x)
ds.x.attrs['units'] = 'meters'
ds['y'] = ('y', y)
ds.y.attrs['units'] = 'meters'
ds.attrs['Grid'] = "Datum = WGS84, earth_radius = 6378137., " \
"earth_eccentricity = 0.081819190842621, " \
"falseeasting = -3333000., " \
"falsenorthing = -3333000., " \
"standard_parallel = -71., central_meridien = 0, " \
"EPSG=3031"
ds.attrs['proj'] = "+proj=stere +lat_0=-90 +lat_ts=-71 +lon_0=0 +k=1 " \
"+x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs"
ds.attrs['proj4'] = "+init=epsg:3031"
# add Bedmap2 data
for fieldName in fields:
fileName = 'bedmap2/bedmap2_bin/bedmap2_{}.flt'.format(fieldName)
with open(fileName, 'r') as f:
field = numpy.fromfile(f, dtype=numpy.float32).reshape(6667, 6667)
# flip the y axis
field = field[::-1, :]
# switch invalid values to be NaN (as expected by xarray)
field[field == -9999.] = numpy.nan
if fieldName == 'rockmask':
# rock mask is zero where rock and -9999 (now NaN) elsewhere
field = numpy.array(numpy.isfinite(field), numpy.float32)
if fieldName == 'icemask_grounded_and_shelves':
# split into separate grounded and floating masks
ds['icemask_grounded'] = \
(('y', 'x'), numpy.array(field == 0, numpy.float32))
ds['icemask_shelves'] = \
(('y', 'x'), numpy.array(field == 1, numpy.float32))
ds['open_ocean_mask'] = \
(('y', 'x'), numpy.array(numpy.isnan(field), numpy.float32))
else:
ds[fieldName] = (('y', 'x'), field)
ds.to_netcdf(outFileName)
print(' Done.')