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Commit 2d8b2212 authored by brunner's avatar brunner
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da/cosmo/icbc4ctdas.py
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......@@ -2,116 +2,132 @@ import sys
import numpy as np
from netCDF4 import Dataset
idir = '/store/empa/em05/parsenov/cosmo_input/icbc/'
odir = '/store/empa/em05/parsenov/cosmo_input/icbc/processed/ensemble/'
half_a=(0,7.367743,210.39389,855.361755,2063.779785,3850.91333,6144.314941,8802.356445,11632.75879,14411.12402,16899.46875,18864.75,20097.40234,20429.86328,19755.10938,18045.18359,15379.80566,12077.44629,8765.053711,6018.019531,3960.291504,1680.640259,713.218079,298.495789,95.636963,0)
half_b=(1,0.99401945,0.97966272,0.95182151,0.90788388,0.84737492,0.77159661,0.68326861,0.58616841,0.48477158,0.38389215,0.28832296,0.2024759,0.13002251,0.07353383,0.03412116,0.01114291,0.00181516,0.00007582,0,0,0,0,0,0,0)
date=str(sys.argv[1])
ifile = Dataset('CT2016.molefrac_glb3x2_'+date[:4]+'-'+date[4:6]+'-'+date[6:8]+'.nc', mode='r')
levs = ifile.variables['level'][:]
lats = ifile.variables['latitude'][:]
lons = ifile.variables['longitude'][:]
co2 = np.squeeze(ifile.variables['co2'][:])
p_bound = np.squeeze(ifile.variables['pressure'][:])
ifile.close()
lats_tf=(lats<=63.)&(lats>=35.)
lons_tf=(lons<=34.5)&(lons>=-10.5)
lats=lats[np.logical_and(lats>=35.,lats<=63.)]
lons=lons[np.logical_and(lons>=-10.5,lons<=34.5)]
co2=co2[:,:,lats_tf,:][:,:,:,lons_tf]*0.04401/0.02896 # * mmCO2/mmAir
p_bound=p_bound[:,:,lats_tf,:][:,:,:,lons_tf]
p=np.empty(shape=(8,25,15,16))
for i in range(0,24):
p[:,i,:,:]=(p_bound[:,i,:,:]+p_bound[:,i+1,:,:])/2.
sp=np.squeeze(p[:,0,:,:])
hyam=np.empty(25)
hybm=np.empty(25)
for i in range(0,25):
hyam[i]=(half_a[i]+half_a[i+1])/2.
hybm[i]=(half_b[i]+half_b[i+1])/2.
ttt=("00","03","06","09","12","15","18","21")
for ti,tt in enumerate(ttt):
ofile = Dataset(sys.argv[2]+'/ct_'+date[:4]+date[4:6]+date[6:8]+tt+'.nc', mode='w')
olev = ofile.createDimension('level', len(levs))
olat = ofile.createDimension('lat', len(lats))
olon = ofile.createDimension('lon', len(lons))
odate = ofile.createDimension('date', 1)
olat = ofile.createVariable('lat', np.float64, ('lat',))
olon = ofile.createVariable('lon', np.float64, ('lon',))
olev = ofile.createVariable('level', np.float64, ('level',))
otime = ofile.createVariable('time', np.float64, ('date',))
odate = ofile.createVariable('date', np.float64, ('date',))
ohyam = ofile.createVariable('hyam', np.float32, ('level',))
ohybm = ofile.createVariable('hybm', np.float32, ('level',))
oco2 = ofile.createVariable('CO2_BG', np.float32, ('date','level','lat','lon'),fill_value=-999.99)
op = ofile.createVariable('pressure', np.float32, ('date','level','lat','lon'),fill_value=-999.99)
osp = ofile.createVariable('PSURF', np.float32, ('date','lat','lon'),fill_value=-999.99)
op0 = ofile.createVariable('P0', np.float32, ('date'),fill_value=-999.99)
odate.comment = 'time-interval average, centered on times in the date axis'
odate.long_name = 'UTC dates and times'
odate.units = 'days since '+date[:4]+'-'+date[4:6]+'-'+date[6:8]+' 00:00:00'
# otime.dtype = 'double'
otime.units = 'seconds since '+date[:4]+'-'+date[4:6]+'-'+date[6:8]+' 00:00:00'
otime.calendar = 'proleptic_gregorian'
olat.standard_name = 'latitude'
olat.long_name = 'latitude'
olat.units = 'degree_north'
olat.axis = 'Y'
olon.standard_name = 'longitude'
olon.long_name = 'longitude'
olon.units = 'degree_east'
olon.axis = 'X'
ohyam.long_name = 'hybrid A coefficient at layer midpoints'
ohyam.units = 'Pa'
ohybm.long_name = 'hybrid B coefficient at layer midpoints'
ohybm.units = '1'
olev.positive = 'up'
olev.units = 'levels'
oco2.standard_name = 'mass_fraction_of_carbon_dioxide_in_air'
oco2.long_name = 'mass mixing ratio of CO2 from outside Europe'
oco2.units = 'kg kg-1'
op.long_name = 'pressure_at_center_levels'
op.units = 'Pa'
op.standard_name = 'air pressure'
op0.units = 'Pa'
osp.cell_methods = 'level:mean'
osp.units = 'Pa'
osp.long_name = 'surface pressure'
osp.table = '128'
osp.lev = '1'
olat[:] = lats
olon[:] = lons
olev[:] = levs
odate[:] = 3.*ti/24.
otime[:] = ti*3*3600
oco2[:] = co2[ti,:]
osp[:] = sp[ti,:]
op[:] = p[ti,:]
op0[:] = 1.
ohyam[:] = hyam
ohybm[:] = hybm
def ct(date, co2_bg):
date = str(date)
co2_bg = np.array(co2_bg)
ifile = Dataset(idir+'3d_molefractions_1x1_'+date+'.nc', mode='r')
levs = ifile.variables['levels'][:]
lats = ifile.variables['latitude'][:]
lons = ifile.variables['longitude'][:]
co2 = np.squeeze(ifile.variables['co2'][:])*(0.04401/0.02896)
p_bound = np.squeeze(ifile.variables['pressure'][:])
ifile.close()
lats_tf=(lats<=66.5)&(lats>=33.5)
lons_tf=(lons<=39.5)&(lons>=-13.5)
lats=lats[np.logical_and(lats>=33.5,lats<=66.5)]
lons=lons[np.logical_and(lons>=-13.5,lons<=39.5)]
#lats_tf=(lats<=63.)&(lats>=35.)
#lons_tf=(lons<=34.5)&(lons>=-10.5)
#lats=lats[np.logical_and(lats>=35.,lats<=63.)]
#lons=lons[np.logical_and(lons>=-10.5,lons<=34.5)]
p_bound=p_bound[:,:,lats_tf,:][:,:,:,lons_tf]
p=np.empty(shape=(8,25,34,54))
# p=np.empty(shape=(8,25,15,16)) # was like this before
for i in range(0,24):
p[:,i,:,:]=(p_bound[:,i,:,:]+p_bound[:,i+1,:,:])/2.
sp=np.squeeze(p[:,0,:,:])
co2=co2[:,:,lats_tf,:][:,:,:,lons_tf]
co2_ens = np.empty(shape=(co2_bg.size,8,25,34,54))
for i in range(0, co2_bg.size):
co2_ens[i,:,:,:,:] = co2[:,:,:,:]*co2_bg[i]
hyam=np.empty(25)
hybm=np.empty(25)
for i in range(0,25):
hyam[i]=(half_a[i]+half_a[i+1])/2.
hybm[i]=(half_b[i]+half_b[i+1])/2.
ttt=("00","03","06","09","12","15","18","21")
for ti,tt in enumerate(ttt):
ofile = Dataset(odir+'ct_'+date+tt+'.nc', mode='w')
olev = ofile.createDimension('level', len(levs))
olat = ofile.createDimension('lat', len(lats))
olon = ofile.createDimension('lon', len(lons))
odate = ofile.createDimension('date', 1)
olat = ofile.createVariable('lat', np.float64, ('lat',))
olon = ofile.createVariable('lon', np.float64, ('lon',))
olev = ofile.createVariable('level', np.float64, ('level',))
otime = ofile.createVariable('time', np.float64, ('date',))
odate = ofile.createVariable('date', np.float64, ('date',))
ohyam = ofile.createVariable('hyam', np.float32, ('level',))
ohybm = ofile.createVariable('hybm', np.float32, ('level',))
op = ofile.createVariable('pressure', np.float32, ('date','level','lat','lon'),fill_value=-999.99)
osp = ofile.createVariable('PSURF', np.float32, ('date','lat','lon'),fill_value=-999.99)
op0 = ofile.createVariable('P0', np.float32, ('date'),fill_value=-999.99)
odate.comment = 'time-interval average, centered on times in the date axis'
odate.long_name = 'UTC dates and times'
odate.units = 'days since '+date[:4]+'-'+date[4:6]+'-'+date[6:8]+' 00:00:00'
# otime.dtype = 'double'
otime.units = 'seconds since '+date[:4]+'-'+date[4:6]+'-'+date[6:8]+' 00:00:00'
otime.calendar = 'proleptic_gregorian'
olat.standard_name = 'latitude'
olat.long_name = 'latitude'
olat.units = 'degree_north'
olat.axis = 'Y'
olon.standard_name = 'longitude'
olon.long_name = 'longitude'
olon.units = 'degree_east'
olon.axis = 'X'
ohyam.long_name = 'hybrid A coefficient at layer midpoints'
ohyam.units = 'Pa'
ohybm.long_name = 'hybrid B coefficient at layer midpoints'
ohybm.units = '1'
olev.positive = 'up'
olev.units = 'levels'
op.long_name = 'pressure_at_center_levels'
op.units = 'Pa'
op.standard_name = 'air pressure'
op0.units = 'Pa'
osp.cell_methods = 'level:mean'
osp.units = 'Pa'
osp.long_name = 'surface pressure'
osp.table = '128'
osp.lev = '1'
olat[:] = lats
olon[:] = lons
olev[:] = levs
odate[:] = 3.*ti/24.
otime[:] = ti*3*3600
osp[:] = sp[ti,:]
op[:] = p[ti,:]
op0[:] = 1.
ohyam[:] = hyam
ohybm[:] = hybm
for e in range(0, co2_bg.size):
ens = str(e).zfill(3)
oco2 = ofile.createVariable('BG_'+ens, np.float64, ('date','level','lat','lon'),fill_value=-999.99)
oco2.standard_name = 'mass_fraction_of_carbon_dioxide_in_air'
oco2.long_name = 'mass mixing ratio of CO2 from outside Europe'
oco2.units = 'kg kg-1'
oco2[:] = co2_ens[e,ti,:,:,:]
ofile.close()
da/cosmo/observationoperator.py
View file @ 2d8b2212
......@@ -127,17 +127,19 @@ class ObservationOperator(object):
logging.info('Multiplying emissions with parameters for lag %d, date %s' % (lag, dt.strftime('%Y%m%d%H')))
for ens in range(0,self.forecast_nmembers):
dthh = dt.strftime('%H')
co2_bg=str((members[ens].param_values[-1]))
ens = str(ens).zfill(3)
cdo.setunit("'kg m-2 s-1' -expr,GPP_"+ens+"_F=CO2_GPP_F*parametermap -merge "+os.path.join(dacycle['da.bio.input'], 'gpp_%s.nc' % dt.strftime('%Y%m%d%H')), input = os.path.join(dacycle['restartmap.dir'],"parameters_gpp_lag"+str(lag)+"."+ens+".nc"), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "gpp_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
cdo.setunit("'kg m-2 s-1' -expr,RESP_"+ens+"_F=CO2_RESP_F*parametermap -merge "+os.path.join(dacycle['da.bio.input'], 'ra_%s.nc' % dt.strftime('%Y%m%d%H')), input = os.path.join(dacycle['restartmap.dir'],"parameters_resp_lag"+str(lag)+"."+ens+".nc"), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "ra_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
if dthh=='00' or dthh=='03' or dthh=='06' or dthh=='09' or dthh=='12' or dthh=='15' or dthh=='18' or dthh=='21':
cdo.setunit("'kg m-2 s-1' -expr,BG_"+ens+"=CO2_BG*"+co2_bg+" -merge "+os.path.join(dacycle['da.bg.input'], 'ct_%s.nc' % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bg.input'], 'ensemble', "ct_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
# co2_bg=str((members[ens].param_values[-1]))
co2_bg=str((members[:].param_values[-1]))
if dthh=='00':
icbc4ctdas(dt.strftime('%Y%m%d'), co2_bg)
#cdo.setunit("'kg m-2 s-1' -expr,BG_"+ens+"=CO2_BG*"+co2_bg+" -merge "+os.path.join(dacycle['da.bg.input'], 'ct_%s.nc' % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bg.input'], 'ensemble', "ct_"+ens+"_%s.nc" % dt.strftime('%Y%m%d%H')))
cdo.merge(input = os.path.join(dacycle['da.bio.input'], 'ensemble', "gpp_???_%s.nc" % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "gpp_%s.nc" % dt.strftime('%Y%m%d%H')))
cdo.merge(input = os.path.join(dacycle['da.bio.input'], 'ensemble', "ra_???_%s.nc" % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bio.input'], 'ensemble', "ra_%s.nc" % dt.strftime('%Y%m%d%H')))
if dthh=='00' or dthh=='03' or dthh=='06' or dthh=='09' or dthh=='12' or dthh=='15' or dthh=='18' or dthh=='21':
cdo.merge(input = os.path.join(dacycle['da.bg.input'], 'ensemble', "ct_???_%s.nc" % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bg.input'], 'ensemble', "ct_%s.nc" % dt.strftime('%Y%m%d%H')))
# if dthh=='00' or dthh=='03' or dthh=='06' or dthh=='09' or dthh=='12' or dthh=='15' or dthh=='18' or dthh=='21':
# cdo.merge(input = os.path.join(dacycle['da.bg.input'], 'ensemble', "ct_???_%s.nc" % dt.strftime('%Y%m%d%H')), output = os.path.join(dacycle['da.bg.input'], 'ensemble', "ct_%s.nc" % dt.strftime('%Y%m%d%H')))
os.chdir(dacycle['da.obsoperator.home'])
......
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