def read_ERA5(t0, dtRange, pre=False, vshift=0):
""" Generator reading the ERA5 data.
The loop is infinite; ERA5 data are called when required until the end of
the parcel loop.
The output contain a function that gives the pressure of the tropo^pause as
a function of lon and lat in the FullAMA domain"""
# initial time for internal loop
current_time = t0
while True:
try:
if (current_time in blacklist): raise BlacklistError()
# defining a new object is necessary to avoid messing dat if an error occurs
dat = ECMWF('FULL-EA', current_time)
dat._get_T()
dat._mkp()
dats = dat.shift2west(-179)
# extraction in a domain that encompasses FullAMA
datr0 = dats.extract(latRange=[-5, 55],
lonRange=[-15, 165],
varss=['P', 'T'])
del dat, dats
datr0._WMO()
datr0.fP = RegularGridInterpolator(
(np.arange(-5, 56), np.arange(-15, 166)),
datr0.d2d['pwmo'],
bounds_error=True)
print('get ERA5 tropopause for ', current_time)
try:
del datr
except:
pass # intended for the first pass when datr undefined
datr = datr0 # datr as a view of datr0
# We reproduce here the same sequence as for the satellite file
# although perhapsnot appropriate (the ERA5 data are instantaneous)
if pre:
datr.tf = current_time + dtRange
datr.ti = current_time
else:
datr.tf = current_time
datr.ti = current_time - dtRange
except BlacklistError:
print('blacklisted date for GridSat', current_time)
# extend the lease while keeping the old dat
datr.ti -= dtRange
except FileNotFoundError:
print('ERA5 file not found ', current_time)
# extend the lease while keeping the old dat
datr.ti -= dtRange
current_time -= dtRange
yield datr
def Pinterpol(date):
""" Read the ERA5 data and interpolate to the pressure levels. """
dat = ECMWF('FULL-EA', date, exp=['VOZ', 'QN'])
dat._get_T()
dat._get_var('O3')
dat._get_var('Q')
dat.close()
dat._mkp()
dat._mkz()
dat2 = dat.shift2west(-20)
dat3 = dat2.extract(lonRange=[-10, 160], latRange=[0, 50], varss='All')
dat3._WMO()
dat4 = dat3.interpolP(pressPa, varList=['Z', 'T', 'Q', 'O3'])
dat4.d2d = dat3.d2d
return (dat4)
if args.year is not None: year = args.year
if args.month1 is not None: month1 = args.month1
if args.month2 is not None: month2 = args.month2
if args.day1 is not None: day1 = args.day1
if args.day2 is not None: day2 = args.day2
if args.hour1 is not None: hour1 = args.hour1
if args.hour2 is not None: hour2 = args.hour2
date = datetime(year, month1, day1, hour1)
while date < datetime(year, month2, day2, hour2):
print('processing ', date)
outfile = date.strftime('TPP%y%m%d%H.hdf5')
fullname = os.path.join(maindir, date.strftime('%Y/%m'), outfile)
fdd = ECMWF('FULL-EA', date)
fdd._get_T()
fdd._mkp()
fdd.close()
fde = fdd.shift2west(-20)
fdf = fde.extract(lonRange=[-10, 160], latRange=[0, 50], varss='All')
fdf._CPT()
fdf._WMO()
tpp = {}
tpp['Twmo'] = fdf.d2d['Twmo']
tpp['pwmo'] = fdf.d2d['pwmo']
tpp['Tcold'] = fdf.d2d['Tcold']
tpp['pcold'] = fdf.d2d['pcold']
tpp['nlon'] = fdf.nlon
tpp['nlat'] = fdf.nlat
tpp['lats'] = fdf.attr['lats']
tpp['lons'] = fdf.attr['lons']
FAFfile = current_date.strftime('SAFNWC-PTOP-%Y-%m-%d-%H:%M.pkl')
fullname = os.path.join(SAF_dir,
current_date.strftime('%Y/%m/%Y-%m-%d'),
FAFfile)
# First try to get the SAFNWC file
try:
with gzip.open(fullname, 'rb') as file:
[ptop, cloud_flag] = pickle.load(file)
except IOError:
print('date', current_date, ' file not found ', FAFfile)
print(current_date, 'is skipped')
current_date += timedelta(hours=1)
continue
# The get the ECMWF data
data = ECMWF('STC', current_date)
data._get_T()
data._mkp()
data.close()
# find time
ir_start = int((current_date - date_beg).total_seconds())
# process the cloud tops above cut_level
ptop_temp = np.ma.masked_greater(ptop, cut_level)
ct = (cloud_flag >> 24) & 0xFF
if cloud_type == 'high':
filt = (ct == 8) | (ct == 9) | ((ct >= 11) & (ct <= 14))
elif cloud_type == 'meanhigh':
filt = (ct == 8) | (ct == 9) | (ct == 12) | (ct == 13)
elif cloud_type == 'veryhigh':
filt = (ct == 9) | (ct == 13)
ptop_temp[~filt] = np.ma.masked
# apply same mask to other fields
# out of the interval
date1 = datetime(mean_date.year,mean_date.month,mean_date.day,mean_date.hour - mean_date.hour%3)
date2 = date1 + timedelta(hours=3)
dtt = (mean_date-date1).total_seconds()/10800
# test whether the selected part of the orbit is totally in the interval
enter_date = ref_date + timedelta(seconds=data['time'][0])
exit_date = ref_date + timedelta(seconds=data['time'][-1])
if enter_date < date1:
print('beginning of orbit out by',date1-enter_date,dtt)
if exit_date > date2:
print('beginning of orbit out by',exit_date-date2,dtt)
# get ECMWF data for the orbit and generate a curtain over the retained segment
# read data for first bracketting date
dat1 = ECMWF('FULL-EI',date1)
dat1._get_T()
dat1._mkp()
dat1._mkz()
dat1.close()
# generate a curtain along the track for first date
sect1 = dat1.interpol_orbit(data['longitude'],data['latitude'],varList=['P','T','Z'])
del dat1
# read data for second bracketting date
dat2 = ECMWF('FULL-EI',date2)
dat2._get_T()
dat2._mkp()
dat2._mkz()
dat2.close()
# generate a curtain along the track for scond date
sect2 = dat2.interpol_orbit(data['longitude'],data['latitude'],varList=['P','T','Z'])
del dat2
from datetime import datetime
#import pickle,gzip
#import matplotlib.pyplot as plt
from os.path import join
from ECMWF_N import ECMWF
date = datetime(2017, 8, 23, 3)
dat = ECMWF('FULL-EA', date, exp='VOZ')
#date = datetime(2020,1,23,6)
#dat = ECMWF('OPZ',date)
#date = datetime(2017,8,10,0)
#dat = ECMWF('STC',date)
#%%
dat._get_T()
dat._get_var('VO')
dat._get_U()
dat._get_V()
dat._mkp()
dat._mkthet()
#%%
print('now call mkpv')
dat._mkpv()
#%%
#dats = dat.interpolPT([350,370,395,430],varList=['PV'],lonRange=(50,120),latRange=(0,50))
dats = dat.extract(varss='All', lonRange=(240, 330), latRange=(-80, -30))
part0['nact_lastNH'] = 0
part0['flag'] = np.empty(0,dtype=int)
part0['ir_start'] = np.empty(0,dtype=int)
part0['x'] = np.empty(0,dtype=float)
part0['y'] = np.empty(0,dtype=float)
part0['t'] = np.empty(0,dtype=float)
part0['p'] = np.empty(0,dtype=float)
part0['idx_back'] = np.empty(0,dtype=int)
numpart = 0
# Loop on the values of theta
for targetTheta in [theta-dTheta, theta, theta+dTheta]:
# get the first time
date1 = date + timedelta(hours=int(begSeq/3600))
predat = ECMWF('STC',date1)
predat._get_T()
predat._mkp()
predat._mkthet()
(fT1,fP1) = interp3d_thet(predat,targetTheta)
predat.close()
#for n in range(nInt):
# finds the boundary
id1 = np.where(utc == begSeq)[0][0]
id2 = np.where(utc == endSeq)[0][0]
# get lat, lon and release time
yy = data.var['Lat'][id1:id2+1]
xx = data.var['Long'][id1:id2+1]
ir_start = utc[id1:id2+1] - 86400
ir_start = ir_start.astype(np.int)
#weigthing factor
