def __init__(self,
gribfile,
demfile,
grib='ECMWF',
humidity='Q',
demtype=np.int16,
demfmt='HGT',
verb=False,
Del='comb'):
'''
Initiates the data structure for atmos corrections in geocoded domain.
Args:
* gribfile (str) : Path to the weather model file.
* demfile (str) : Path to the SIM_nRLKS.hgt file.
Kwargs:
* grib (str) : Can be ECMWF, ERA, NARR or MERRA depending on the model.
* humidity (str) : Can be 'Q' or 'R' depdending on specific or relative humidity.
* demtype (dtype) : Data type of the DEM File.
* demfmt (str) : Can be 'HGT' or 'RMG' depending on type of file. If RMG, altitude is assumed to be second channel.
* Del (str) : Can be 'comb', 'dry' or 'wet'. Specifies which delay you want (both, dry or wet)
.. note ::
The DEMFile is only used to set up the geographic boundaries of the problem and the size of the output matrix during init. The GRIBfile is read and the 3D interpolation function is prepared.
'''
sanity_check(grib)
grib = grib.upper()
humidity = humidity.upper()
demfmt = demfmt.upper()
assert grib in ('ERA', 'NARR', 'ECMWF',
'MERRA'), 'PyAPS: Undefined grib file source.'
self.grib = grib
'''String with the name of the weather model.'''
assert humidity in ('Q', 'R'), 'PyAPS: Undefined humidity.'
self.humidity = humidity
if self.grib in ('NARR', 'MERRA'):
assert self.humidity in (
'Q'), 'PyAPS: Relative humidity not provided by NARR/MERRA.'
assert os.path.isfile(gribfile), 'PyAPS: GRIB File does not exist.'
self.gfile = gribfile
assert os.path.isfile(demfile), 'PyAPS: DEM file does not exist.'
self.hfile = demfile
assert demfmt in (
'RMG', 'HGT',
'VAR'), 'PyAPS: DEM Format can be RMG or HGT, VAR'
self.fmt = demfmt
self.demtype = demtype
self.dict = processor.initconst()
self.bufspc = 1.2 ####Hardcoded.
if grib in ('ERA', 'ECMWF'):
if GRIBflag:
self.hgtscale = (
(self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.703
else:
print('================================')
print('********************************')
print(' pyGrib needs to be installed ')
print(' No ECMWF or NARR possible ')
print('********************************')
print('================================')
sys.exit(1)
elif grib in ('NARR'):
if GRIBflag:
self.hgtscale = (
(self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.3
else:
print('================================')
print('********************************')
print(' pyGrib needs to be installed ')
print(' No ECMWF or NARR possible ')
print('********************************')
print('================================')
sys.exit(1)
elif grib in ('MERRA'):
if MERRAflag:
self.hgtscale = (
(self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.5
else:
print('================================')
print('********************************')
print(' pyHdf needs to be installed ')
print(' No MERRA possible ')
print('********************************')
print('================================')
sys.exit(1)
[lon, lat, nx, ny] = utils.geo_rsc(self.hfile, verbose=verb)
######Problems near the international dateline
if grib in ('MERRA'):
#MERRA's longtidue range -180~180.
#This is to correct the value from utils.geo_rsc() function. Cunren, OCT-2015
if (lon[0] > 180):
lon[0] = lon[0] - 360.0
if (lon[1] > 180):
lon[1] = lon[1] - 360.0
self.minlon = lon.min() - self.bufspc
self.maxlon = lon.max() + self.bufspc
self.minlat = lat.min() - self.bufspc
self.maxlat = lat.max() + self.bufspc
self.nx = nx
self.ny = ny
else:
lon[lon < 0.] += 360.0
self.minlon = lon.min() - self.bufspc
self.maxlon = lon.max() + self.bufspc
self.minlat = lat.min() - self.bufspc
self.maxlat = lat.max() + self.bufspc
self.nx = nx
self.ny = ny
if self.grib in ('ERA'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = era.get_era(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
humidity=self.humidity,
verbose=verb)
elif self.grib in ('ECMWF'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = era.get_ecmwf(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
humidity=self.humidity,
verbose=verb)
elif self.grib in ('NARR'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = narr.get_narr(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
verbose=verb)
elif self.grib in ('MERRA'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = merra.get_merra(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
verbose=verb)
lonlist[lonlist < 0.] += 360.0
hgt = np.linspace(self.dict['minAlt'], self.dict['maxAlt'],
self.dict['nhgt'])
[Pi, Ti, Vi] = processor.intP2H(lvls,
hgt,
gph,
tmp,
vpr,
self.dict,
verbose=verb)
[DDry, DWet] = processor.PTV2del(Pi,
Ti,
Vi,
hgt,
self.dict,
verbose=verb)
if Del in ('comb', 'Comb'):
Delfn = DDry + DWet
elif Del in ('dry', 'Dry'):
Delfn = DDry
elif Del in ('wet', 'Wet'):
Delfn = DWet
else:
print('Unrecognized delay type')
sys.exit(1)
if self.grib in ('NARR'):
[Delfn, latlist,
lonlist] = narr.intdel(hgt, latlist, lonlist, Delfn)
self.Delfn = Delfn
self.lonlist = lonlist
self.latlist = latlist
self.Pi = Pi
self.Vi = Vi
self.Ti = Ti
self.hgt = hgt
self.verb = verb
def merisfactor(self, dataobj, inc=0.0, wvl=4 * np.pi):
'''
Write pi-factor from Li et al 2012 to a matrix / HDF5 object or a file directly.
Args:
* dataobj (str or HDF5 or np.array): Final output. If str, output is written to file.
Kwargs:
* inc (np.float): Incidence angle in degrees. Default is vertical.
* wvl (np.float): Wavelength in meters. Default output results in delay in meters.
.. note::
If dataobj is string, output is written to the file.
If np.array or HDF5 object, it should be of size (ny,nx).
'''
minAltp = self.dict['minAltP']
# Incidence
cinc = np.cos(inc * np.pi / 180.0)
# Compute the two integrals
WonT = self.Vi / self.Ti
WonT2 = WonT / self.Ti
S1 = intg.cumtrapz(WonT, x=self.hgt, axis=-1)
val = 2 * S1[:, -1] - S1[:, -2]
val = val[:, None]
S1 = np.concatenate((S1, val), axis=-1)
del WonT
S2 = intg.cumtrapz(WonT2, x=self.hgt, axis=-1)
val = 2 * S2[:, -1] - S2[:, -2]
val = val[:, None]
S2 = np.concatenate((S2, val), axis=-1)
del WonT2
Tm = S1 / S2
self.Tm = Tm
# Reading in the DEM
if self.verb:
print('PROGRESS: READING DEM')
fin = open(self.hfile, 'rb')
if self.fmt in ('HGT'):
dem = np.fromfile(file=fin,
dtype=self.demtype,
count=self.nx * self.ny).reshape(
self.ny, self.nx)
elif self.fmt in ('RMG'):
dem = np.fromfile(file=fin,
dtype=self.demtype,
count=2 * self.nx * self.ny).reshape(
self.ny, 2 * self.nx)
dem = dem[:, self.nx:]
dem = np.round(dem).astype(np.int)
fin.close()
# check output, and open file if necessary
outFile = isinstance(dataobj, str)
if outFile:
fout = open(dataobj, 'wb')
dout = np.zeros((self.ny, self.nx))
else:
assert ((dataobj.shape[0] == self.ny) &
(dataobj.shape[1]
== self.nx)), 'PyAPS: Not a valid data object.'
dout = dataobj
# Create the lon/lat arrays
laty = np.linspace(self.maxlat - self.bufspc,
self.minlat + self.bufspc, self.ny)
lonx = np.linspace(self.minlon + self.bufspc,
self.maxlon - self.bufspc, self.nx)
# Create the 1d interpolator
if self.verb:
print('PROGRESS: FINE INTERPOLATION OF HEIGHT LEVELS')
intp_1d = si.interp1d(self.hgt, Tm, kind='cubic', axis=1)
# Interpolate the Tm variable every meter
dem[dem < minAltp] = minAltp
minH = dem.min()
maxH = dem.max() + 1
kh = np.arange(minH, maxH)
Tm_1m = intp_1d(kh)
self.alti = kh
# Reshape Tm
Lonu = np.unique(self.lonlist)
Latu = np.unique(self.latlist)
nLon = len(Lonu)
nLat = len(Latu)
Tm_1m = np.reshape(Tm_1m.T, (len(kh), nLat, nLon))
self.Tm_1m = Tm_1m
# Create the cube interpolator for the bilinear method
if self.verb:
print('PROGRESS: CREATE THE BILINEAR INTERPOLATION FUNCTION')
bilicube = processor.Bilinear2DInterpolator(Lonu,
Latu,
Tm_1m,
cube=True)
# Get the values from the dictionnary
k1 = self.dict['k1']
k2 = self.dict['k2']
k3 = self.dict['k3']
mmO = self.dict['mmO']
mmH = self.dict['mmH']
mma = self.dict['mma']
w = (2 * mmH + mmO) / mma
Rv = self.dict['Rv']
Rho = self.dict['Rho']
# Loop on the lines
if self.verb:
toto = utils.ProgressBar(maxValue=self.ny)
print('PROGRESS: MAPPING THE DELAY')
for m in range(self.ny):
if self.verb:
toto.update(m, every=5)
# Get Lon/Lat
loni = lonx
lati = laty[m] * np.ones((loni.shape))
# Make the bilinear interpolation
D = dem[m, :] - minH
val = bilicube(loni, lati, D)
val = 0.000001 * Rho * Rv * (
k3 / val + k2 - w * k1) * np.pi * 4.0 / (cinc * wvl)
if outFile:
resy = val.astype(np.float32)
resy.tofile(fout)
else:
dataobj[m, :] = val
if self.verb:
toto.close()
# Close if outfile
if outFile:
fout.close()
def __init__(self,
gribfile,
demfile,
grib='ECMWF',
humidity='Q',
demtype=np.int16,
demfmt='HGT',
verb=False,
Del='comb'):
'''
Initiates the data structure for atmos corrections in geocoded domain.
Args:
* gribfile (str) : Path to the weather model file.
* demfile (str) : Path to the SIM_nRLKS.hgt file.
Kwargs:
* grib (str) : Can be ECMWF, ERA, NARR or MERRA depending on the model.
* humidity (str) : Can be 'Q' or 'R' depdending on specific or relative humidity.
* demtype (dtype) : Data type of the DEM File.
* demfmt (str) : Can be 'HGT' or 'RMG' depending on type of file.
If RMG, altitude is assumed to be second channel.
* Del (str) : Can be 'comb', 'dry' or 'wet'. Specifies which delay you want (both, dry or wet)
.. note ::
The DEMFile is only used to set up the geographic boundaries of the problem and the size of the output matrix
during init. The GRIBfile is read and the 3D interpolation function is prepared.
'''
sanity_check(grib)
grib = grib.upper()
humidity = humidity.upper()
demfmt = demfmt.upper()
assert grib in ('ERA', 'NARR', 'ECMWF',
'MERRA'), 'PyAPS: Undefined grib file source.'
self.grib = grib
'''String with the name of the weather model.'''
assert humidity in ('Q', 'R'), 'PyAPS: Undefined humidity.'
self.humidity = humidity
if self.grib in ('NARR', 'MERRA'):
assert self.humidity in (
'Q'), 'PyAPS: Relative humidity not provided by NARR/MERRA.'
assert os.path.isfile(gribfile), 'PyAPS: GRIB File does not exist.'
self.gfile = gribfile
assert os.path.isfile(demfile), 'PyAPS: DEM file does not exist.'
self.hfile = demfile
assert demfmt in ('RMG', 'HGT',
'VAR'), 'PyAPS: DEM Format can be RMG or HGT, VAR'
self.fmt = demfmt
self.demtype = demtype
self.dict = processor.initconst()
self.bufspc = 1.2 ####Hardcoded.
if grib in ('ERA', 'ECMWF'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.703
elif grib in ('NARR'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.3
elif grib in ('MERRA'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.5
[lon, lat, nx, ny] = utils.geo_rsc(self.hfile, verbose=verb)
######Problems near the international dateline
if grib in ('MERRA'):
#MERRA's longtidue range -180~180.
#This is to correct the value from utils.geo_rsc() function. Cunren, OCT-2015
lon[lon > 180] -= 360.0
#if(lon[0] > 180):
# lon[0] = lon[0] - 360.0
#if(lon[1] > 180):
# lon[1] = lon[1] - 360.0
self.minlon = lon.min() - self.bufspc
self.maxlon = lon.max() + self.bufspc
self.minlat = lat.min() - self.bufspc
self.maxlat = lat.max() + self.bufspc
self.nx = nx
self.ny = ny
else:
lon[lon < 0] += 360.0
self.minlon = lon.min() - self.bufspc
self.maxlon = lon.max() + self.bufspc
self.minlat = lat.min() - self.bufspc
self.maxlat = lat.max() + self.bufspc
self.nx = nx
self.ny = ny
if self.grib in ('ERA'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = era.get_era(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
humidity=self.humidity,
verbose=verb)
elif self.grib in ('ECMWF'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = era.get_ecmwf(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
humidity=self.humidity,
verbose=verb)
elif self.grib in ('NARR'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = narr.get_narr(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
verbose=verb)
elif self.grib in ('MERRA'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = merra.get_merra(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
verbose=verb)
lonlist[lonlist < 0.] += 360.0
hgt = np.linspace(self.dict['minAlt'], self.dict['maxAlt'],
self.dict['nhgt'])
[Pi, Ti, Vi] = processor.intP2H(lvls,
hgt,
gph,
tmp,
vpr,
self.dict,
verbose=verb)
[DDry, DWet] = processor.PTV2del(Pi,
Ti,
Vi,
hgt,
self.dict,
verbose=verb)
if Del in ('comb', 'Comb'):
Delfn = DDry + DWet
elif Del in ('dry', 'Dry'):
Delfn = DDry
elif Del in ('wet', 'Wet'):
Delfn = DWet
else:
print('Unrecognized delay type')
sys.exit(1)
if self.grib in ('NARR'):
[Delfn, latlist, lonlist] = narr.intdel(hgt, latlist, lonlist,
Delfn)
self.Delfn = Delfn
self.lonlist = lonlist
self.latlist = latlist
self.Pi = Pi
self.Vi = Vi
self.Ti = Ti
self.hgt = hgt
self.verb = verb
def __init__(self,
gribfile,
dem,
lat,
lon,
inc=0.0,
mask=None,
grib='era5',
humidity='Q',
Del='comb',
model='ERA5',
verb=False):
'''Initiates the data structure for atmos corrections in geocoded domain.
Args:
* gribfile (str) : path to downloaded grib file
* dem (np.ndarray) : height in size of (length, width)
* lat (np.ndarray) : latitude in size of (length, width)
* lon (np.ndarray) : longitude in size of (length, width)
Kwargs:
* inc (number/np.ndarray) : incidence angle (in size of (length, width) for np.ndarray)
* mask (np.ndarray) : mask of valid pixels in size of (length, width)
* grib (str) : grib name in ['ERA5', 'ERAINT', 'HRES', 'NARR', 'MERRA']
* humidity (str) : ['Q', 'R']
* Del (str) : ['comb', 'wet', 'dry']
* model (str) : ECMWF dataset name in ['era5', 'eraint', 'hres']
* verb (bool) : True or False
.. note::
For ISCE products, lat/lon can be read from lat/lon.rdr file
For ROIPAC products, lat, lon = utils.get_lat_lon('radar_16rlks.hgt.rsc')
'''
#--------- Check files exist and we have what's needed for computation
# check grib type and import module
grib = grib.upper()
if grib in ['ERA5', 'ERAINT', 'HRES']:
from pyaps3 import era
elif grib == 'NARR':
from pyaps3 import narr
elif grib == 'MERRA':
from pyaps3 import merra
else:
raise ValueError(
'PyAPS: Undefined grib file source: {}'.format(grib))
self.grib = grib
# Check Humidity variable
humidity = humidity.upper()
assert humidity in ('Q', 'R'), 'PyAPS: Undefined humidity.'
self.humidity = humidity
if self.grib in ('NARR', 'MERRA'):
assert self.humidity in (
'Q'), 'PyAPS: Relative humidity not provided by NARR/MERRA.'
# Check the model for ECMWF
self.model = model
# Check grib file exists
assert os.path.isfile(gribfile), 'PyAPS: GRIB File does not exist.'
self.gfile = gribfile
# Get altitude, lon, lat, etc
self.dem = dem
self.lon = lon
self.lat = lat
self.inc = inc
if mask is None:
self.mask = np.ones(self.dem.shape)
else:
self.mask = mask
# Get size
self.ny, self.nx = self.dem.shape
assert self.lon.shape == (
self.ny, self.nx), 'PyAPS: Longitude array size mismatch'
assert self.lat.shape == (
self.ny, self.nx), 'PyAPS: Latitude array size mismatch'
assert self.mask.shape == (self.ny,
self.nx), 'PyAPS: Mask array size mismatch'
# check incidence angle size and type
if isinstance(self.inc, np.ndarray):
if verb:
print('INFO: INCIDENCE ANGLE AS AN ARRAY')
assert self.inc.shape == (
self.ny, self.nx), 'PyAPS: Incidence array size mismatch'
elif isinstance(self.inc, (int, float, np.float32, np.float64)):
if verb:
print('INFO: INCIDENCE ANGLE AS A NUMBER: {} DEG'.format(
self.inc))
else:
raise ValueError(
'PyAPS: unrecognized incidence data type: {}'.format(
type(self.inc)))
#--------- Initialize variables
self.dict = processor.initconst()
# Get some scales
if grib in ('ERA5', 'ERAINT', 'HRES'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.703
self.bufspc = 1.2
elif grib in ('NARR'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.3
self.bufspc = 1.2
elif grib in ('MERRA'):
self.hgtscale = ((self.dict['maxAlt'] - self.dict['minAlt']) /
self.dict['nhgt']) / 0.5
self.bufspc = 1.0
# Problems in isce when lon and lat arrays have weird numbers
self.lon[self.lon < 0.] += 360.0
self.minlon = np.nanmin(self.lon[self.mask]) - self.bufspc
self.maxlon = np.nanmax(self.lon[self.mask]) + self.bufspc
self.minlat = np.nanmin(self.lat[self.mask]) - self.bufspc
self.maxlat = np.nanmax(self.lat[self.mask]) + self.bufspc
if verb:
print(
'INFO: AREA COVERAGE IN SNWE: ({:.2f}, {:.2f}, {:.2f}, {:.2f})'
.format(self.maxlat, self.minlat, self.minlon, self.maxlon))
#--------- Extract infos from gribfiles
if self.grib in ('ERA'):
assert False, 'Need to modify get_era to fit with the new standards'
[lvls, latlist, lonlist, gph, tmp,
vpr] = era.get_era(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
humidity=self.humidity,
verbose=verb)
elif self.grib in ('ERA5', 'ERAINT', 'HRES'):
[lvls, latlist, lonlist, gph, tmp,
vpr] = era.get_ecmwf(self.model,
self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
humidity=self.humidity,
verbose=verb)
elif self.grib in ('NARR'):
assert False, 'Need to modify get_narr to fit with the new standards'
[lvls, latlist, lonlist, gph, tmp,
vpr] = narr.get_narr(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
verbose=verb)
elif self.grib in ('MERRA'):
assert False, 'Need to modify get_merra to fit with the new standards'
[lvls, latlist, lonlist, gph, tmp,
vpr] = merra.get_merra(self.gfile,
self.minlat,
self.maxlat,
self.minlon,
self.maxlon,
self.dict,
verbose=verb)
lonlist[lonlist < 0.] += 360.0
# Make a height scale
hgt = np.linspace(self.dict['minAltP'],
gph.max().round(), self.dict['nhgt'])
# Interpolate pressure, temperature and Humidity of hgt
[Pi, Ti, Vi] = processor.intP2H(lvls,
hgt,
gph,
tmp,
vpr,
self.dict,
verbose=verb)
# Calculate the delays
[DDry, DWet] = processor.PTV2del(Pi,
Ti,
Vi,
hgt,
self.dict,
verbose=verb)
if Del.lower() == 'comb':
Delfn = DDry + DWet
elif Del.lower() == 'dry':
Delfn = DDry
elif Del.lower() == 'wet':
Delfn = DWet
else:
raise ValueError('Unrecognized delay type: {}'.format(Del))
if self.grib in ('NARR'):
assert False, 'Need to check narr.intdel'
[Delfn, latlist, lonlist] = narr.intdel(hgt, latlist, lonlist,
Delfn)
#--------- Save things
self.Delfn = Delfn
self.latlist = latlist
self.lonlist = lonlist
self.lat = lat
self.lon = lon
self.hgt = hgt
self.Pi = Pi
self.Ti = Ti
self.Vi = Vi
self.verb = verb
# All done
return
