def fix_precip_attributes(path):
nc_file = NetCDF(path, mode='r+')
nc_file.history = ''
nc_file.variables['precip'].long_name = 'Daily Precipitation Rate at surface'
if 'Identification' in nc_file.ncattrs():
nc_file.Identification = ''
if 'Documentation' in nc_file.ncattrs():
nc_file.Documentation = ''
if 'About' in nc_file.ncattrs():
nc_file.About = ''
nc_file.close()
if l_interp_daily:
#
#print('LOLO: current time is rt =', rt)
for jtd in range(jr1, Nt_tot_daily - 1):
if vtime_d[jtd] <= rt and vtime_d[jtd + 1] > rt:
jr1 = jtd
jr2 = jtd + 1
break
#print('LOLO: what we found is:', vtime_d[jr1], vtime_d[jr2])
#
ivd = 0
for cvar in list_var_daily_expected:
# Linear interpolation !!!
rslope = (xdata_d[ivd, jr2] -
xdata_d[ivd, jr1]) / (vtime_d[jr2] - vtime_d[jr1])
ido_var[iv][jt, :, :] = xdata_d[
ivd, jr1] + rslope * (rt - vtime_d[jr1])
if cvar in list_temp_to_degC:
ido_var[iv][jt, :, :] = ido_var[iv][jt, :, :] - 273.15
iv = iv + 1
ivd = ivd + 1
for cvar in list_extra:
ido_var[iv][jt, :, :] = rval_extra[iv - nbfld_tot]
iv = iv + 1
id_fo.About = "Input file for 'STATION_ASF' NEMO test-case, generated with 'download_prepare_ERA5_for_SASF.py' of AeroBulk (https://github.com/brodeau/aerobulk)."
id_fi.close()
id_fo.close()
# Attributes
id_tim.units = cunt_time
#id_lat.long_name = clnm_lat
id_lat.units = cunt_lat
#id_lat.standard_name = csnm_lat
#id_lon.long_name = clnm_lon
id_lon.units = cunt_lon
#id_lon.standard_name = csnm_lon
id_tim.units = cunt_time
id_q2.long_name = 'Surface specific humidity at 2m, built from D2M and MSL'
id_q2.units = 'kg/kg'
id_q2.code = '133'
id_q2.table = '128'
f_out.About = 'Created by L. Brodeau using MSL and D2M corresponding fields'
# Filling variables:
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
id_tim[jt] = vtime[jt]
id_q2[jt, :, :] = xq2[:, :]
if jt == Nt - 1: f_out.close()
print 'Bye!'
id_lat.long_name = clnm_lat
id_lat.units = cunt_lat
id_lat.standard_name = csnm_lat
id_lon.long_name = clnm_lon
id_lon.units = cunt_lon
id_lon.standard_name = csnm_lon
id_tim.units = cunt_time
id_crl.long_name = 'Curl of vector ' + cv_Vx + ' and ' + cv_Vy
id_crl.units = CUNIT_CRL
id_crl.code = '???'
id_crl.table = '128'
f_out.About = 'Created by Barakuda using ' + cv_Vx + ' and ' + cv_Vy + '.'
# Filling variables:
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
for jt in range(Nt):
print ' *** jt = ', jt
xty = rmult * f_Vy_in.variables[cv_Vy][jt, :, :]
xtx = rmult * f_Vx_in.variables[cv_Vx][jt, :, :]
xtmp[:, :] = xtx[:, :] * xcosphi[:, :]
xcurl[1:nj-1,1:ni-1] = ( xty[1:nj-1,2:ni] - xty[1:nj-1,0:ni-2] ) / dlamx2 \
# Attributes
id_tim.units = cunt_time
#id_tim.calendar = ccal_time
id_lat.units = cunt_lat
id_lat.long_name = clnm_lat
#id_lat.standard_name = csnm_lat
id_lon.units = cunt_lon
id_lon.long_name = clnm_lon
#id_lon.standard_name = csnm_lon
id_q2.units = 'kg/kg'
id_q2.long_name = 'Surface specific humidity at 2m, built from ' + cv_d2 + ' and ' + cv_p0
id_q2.code = '133'
id_q2.table = '128'
f_out.About = 'Created with "build_q2_from_d2_slp.py" of AeroBulk, using ' + cv_p0 + ' and ' + cv_d2 + '. [https://github.com/brodeau/aerobulk]'
# Filling variables:
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
id_tim[jt] = vtime[jt]
id_q2[jt, :, :] = xq2[:, :]
if jt == Nt - 1: f_out.close()
print('Bye!')
if NbDim == 3:
id_msk = f_out.createVariable('mask',
'i1', (
cdim_z,
cdim_y,
cdim_x,
),
zlib=True,
complevel=8)
id_msk[:, :, :] = mask[:, :, :]
else:
id_msk = f_out.createVariable('mask',
'i1', (
cdim_y,
cdim_x,
),
zlib=True,
complevel=8)
id_msk[:, :] = mask[:, :]
id_msk.long_name = 'Land-Sea mask'
f_out.About = 'Land-sea mask built out of variable `' + cv_nc + '` of file `' + path.basename(
cf_nc) + '` !'
f_out.Author = 'Generated with `' + path.basename(
sys.argv[0]) + '` of `climporn` (https://github.com/brodeau/climporn)'
f_out.close()
print(cf_msk + ' created!!!')
if NbDim == 3: f_out.createDimension(cdim_z, nz)
#if l_fake_coor:
# id_lon = f_out.createVariable('lon0','f4',(cdim_x,))
# id_lat = f_out.createVariable('lat0','f4',(cdim_y,))
# id_lon[:] = vlon[:]
# id_lat[:] = vlat[:]
if NbDim == 3:
id_msk = f_out.createVariable('mask', 'i1', (
cdim_z,
cdim_y,
cdim_x,
))
id_msk[:, :, :] = mask[:, :, :]
else:
id_msk = f_out.createVariable('mask', 'i1', (
cdim_y,
cdim_x,
))
id_msk[:, :] = mask[:, :]
id_msk.long_name = 'Land-Sea mask'
f_out.About = 'Variable ' + cv_nc + ' converted to a mask...'
f_out.Author = 'Generated with image_to_netcdf.py of BARAKUDA (https://github.com/brodeau/barakuda)'
f_out.close()
print cf_msk + ' created!!!'
#id_lat.long_name = clnm_lat
id_lat.units = cunt_lat
#id_lat.standard_name = csnm_lat
#id_lon.long_name = clnm_lon
id_lon.units = cunt_lon
#id_lon.standard_name = csnm_lon
id_tim.units = cunt_time
id_q2.long_name = 'Surface specific humidity at 2m, built from D2M and MSL'
id_q2.units = 'kg/kg'
id_q2.code = '133'
id_q2.table = '128'
f_out.About = 'Created by L. Brodeau using MSL and D2M corresponding fields'
# Filling variables:
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
id_tim[jt] = vtime[jt]
id_q2[jt,:,:] = xq2[:,:]
if jt == Nt-1: f_out.close()
#id_lat.long_name = clnm_lat
id_lat.units = cunt_lat
#id_lat.standard_name = csnm_lat
#id_lon.long_name = clnm_lon
id_lon.units = cunt_lon
#id_lon.standard_name = csnm_lon
id_tim.units = cunt_time
#id_wm.long_name = 'Surface specific humidity at 2m, built from U10M, V10M and MSL'
#id_wm.units = 'kg/kg'
#id_wm.code = '133'
#id_wm.table = '128'
f_out.About = 'Created by L. Brodeau using MSL, U10M and V10M corresponding fields'
# Filling variables:
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
id_tim[jt] = vtime[jt]
id_wm[jt,:,:] = xwm[:,:]
id_ke[jt,:,:] = xke[:,:]
if jt == Nt-1: f_out.close()
#id_lat.long_name = clnm_lat
id_lat.units = cunt_lat
#id_lat.standard_name = csnm_lat
#id_lon.long_name = clnm_lon
id_lon.units = cunt_lon
#id_lon.standard_name = csnm_lon
id_tim.units = cunt_time
#id_wm.long_name = 'Surface specific humidity at 2m, built from U10M, V10M and MSL'
#id_wm.units = 'kg/kg'
#id_wm.code = '133'
#id_wm.table = '128'
f_out.About = 'Created by L. Brodeau using MSL, U10M and V10M corresponding fields'
# Filling variables:
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
id_tim[jt] = vtime[jt]
id_wm[jt, :, :] = xwm[:, :]
id_ke[jt, :, :] = xke[:, :]
if jt == Nt - 1: f_out.close()
print ' *** file ' + cf_wm + ' created !'
print 'Bye!'
# Attributes
id_tim.units = cunt_time
id_tim.calendar = ccal_time
id_lat.units = cunt_lat
id_lat.long_name = clnm_lat
#id_lat.standard_name = csnm_lat
id_lon.units = cunt_lon
id_lon.long_name = clnm_lon
#id_lon.standard_name = csnm_lon
id_out.units = cunt_in
id_out.long_name = clnm_in
#id_out.code = '133'
#id_out.table = '128'
f_out.About = cv_in + ' masked and deflated with "mask_field_ecmwf.py" of AeroBulk. [https://github.com/brodeau/aerobulk].'
# Filling variables:
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
id_tim[jt] = vtime[jt]
id_out[jt, :, :] = xfout[:, :]
if jt == Nt - 1: f_out.close()
print 'Bye!'
f_ice.createDimension(cv_tim, None)
# Variables
ido_lon = f_ice.createVariable(cv_lon, 'f4', (
'y',
'x',
), zlib=True)
ido_lat = f_ice.createVariable(cv_lat, 'f4', (
'y',
'x',
), zlib=True)
ido_tim = f_ice.createVariable(cv_tim, 'f4', (cv_tim, ), zlib=True)
# Attributes
ido_tim.units = cunt_time
ido_lat.units = cunt_lat
ido_lon.units = cunt_lon
f_ice.About = 'prepare_PAPA_forcing_STATION-ASF_ICE.py of AeroBulk for NEMO/STATION-ASF test-case. Gaps in time-series are filled by means of linear interpolation.'
# Filling variables:
ido_lat[:, :] = vlat[0]
ido_lon[:, :] = vlon[0]
for jt in range(Nt):
ido_tim[jt] = vtime[jt]
if list_real[iv] == 'atm':
id_atm = f_forc.createVariable(list_varo[iv],
'f4', (
cv_tim,
'y',
'x',
),
zlib=True)
#, fill_value=rmiss)
# Dimensions:
f_out.createDimension(cv_lon, ni)
f_out.createDimension(cv_lat, nj)
f_out.createDimension('time', None)
# Variables
id_lon = f_out.createVariable(cv_lon, 'f4', (cv_lon, ), zlib=True)
id_lat = f_out.createVariable(cv_lat, 'f4', (cv_lat, ), zlib=True)
id_tim = f_out.createVariable('time', 'f4', ('time', ), zlib=True)
# Attributes
id_tim.units = cunt_time
id_lat.units = cunt_lat
id_lon.units = cunt_lon
f_out.About = 'Created by L. Brodeau for AeroBulk. Gaps in time-series are filled by means of linear interpolation.'
# Filling variables:
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
for jt in range(Nt):
id_tim[jt] = vtime[jt]
id_out = f_out.createVariable(list_varo[iv],
'f4', (
'time',
cv_lat,
cv_lon,
),
zlib=True)
#, fill_value=rmiss)
'lon',
))
# Attributes
id_tim.units = cunt_time
id_lev.units = cunt_lev
id_lat.long_name = clnm_lat
id_lat.units = cunt_lat
id_lon.long_name = clnm_lon
id_lon.units = cunt_lon
id_R.long_name = 'Relative Humidity'
id_R.units = '%'
id_R.code = '157'
id_R.table = '128'
f_out.About = 'Created by L. Brodeau using Q, T and pressure from pressure levels!'
# Filling variables:
id_lev[:] = vlev[:]
id_lat[:] = vlat[:]
id_lon[:] = vlon[:]
for jt in range(nt):
id_tim[jt] = vtime[jt]
id_R[jt, :, :, :] = xR[jt, :, :, :]
f_out.close()
print cf_R + ' is created!'
print 'build_RH_new.py: Bye!'
ido_var.units = id_fi.variables[cvec].units
ido_var.long_name = id_fi.variables[cvec].long_name
# Filling coordinates:
ido_lon[:] = vlon[:]
ido_lat[:] = nmp.flipud(vlat[:])
# Filling fields
for jt in range(Nt):
print(' * "' + cvec + '" => jt = ', jt, ' /', Nt)
ido_tim[jt] = vtime[jt]
if jt == 0: Xvar = nmp.zeros((nj, ni))
Xvar[:, :] = id_fi.variables[cvec][jt, :, :]
Xvar[:, :] = nmp.flipud(Xvar[:, :])
ido_var[jt, :, :] = Xvar[:, :]
# Flux conversion ???
if cvec in list_flx:
idx = list_flx.index(cvec)
ido_var[jt, :, :] = ido_var[jt, :, :] * fact_flx[idx]
#
id_fo.About = "Generated with 'download_prepare_ERA5.py' of AeroBulk (https://github.com/brodeau/aerobulk)."
id_fo.close()
id_fi.close()
id_blue = f_out.createVariable('blue', 'f4', (
cdim_y,
cdim_x,
))
id_blue.long_name = 'Blue (of RGB)'
id_red[:, :] = nmp.flipud(xpic[:, :, 0])
id_green[:, :] = nmp.flipud(xpic[:, :, 1])
id_blue[:, :] = nmp.flipud(xpic[:, :, 2])
else:
#if l_nemo_like:
# id_bw = f_out.createVariable('bw','i1',('t',cdim_y,cdim_x,))
# id_bw.long_name = 'Grey scale'
# #id_bw[0,:,:] = nmp.flipud(xpic[:,:]) / idiv
# id_bw[0,:,:] = 1 - (nmp.flipud(xpic[:,:]) + 1)/idiv
#else:
id_bw = f_out.createVariable('bw', 'i1', (
cdim_y,
cdim_x,
))
id_bw.long_name = 'Grey scale'
id_bw[:, :] = 1 - (nmp.flipud(xpic[:, :]) + 1) / idiv
f_out.About = 'Image ' + cf_im + ' converted to netcdf.'
f_out.Author = 'Generated with `imageBW_to_NetCDF.py` of `climporn` (https://github.com/brodeau/climporn)'
f_out.close()
print(cf_nc + ' created!!!\n')
id_lat = f_out.createVariable('nav_lat', 'f4', (
'y',
'x',
))
id_lon[:, :] = nav_lon[:, :]
id_lat[:, :] = nav_lat[:, :]
jb = 0
jbt = 0
for cb in vbasins:
if vtreat[jb]:
#id_bas = f_out.createVariable(crout+cb,'i1',('y','x',))
id_bas = f_out.createVariable(crout + cb, 'f4', (
'y',
'x',
))
id_bas.long_name = vbnames[jb] + ' ' + vocesea[jb] + ' basin'
id_bas[:, :] = XBASINS[jbt, :, :] * mask[:, :]
jbt = jbt + 1
jb = jb + 1
f_out.About = 'ORCA025, masks for main ocean basins, created with orca_mesh_mask_to_bitmap.py, Gimp, and tiff_to_orca_mask.py, ' + cdate + '.'
f_out.Author = 'L. Brodeau (https://github.com/brodeau/barakuda)'
f_out.close()
print cf_bm + ' created!!!'
id_lon = f_out.createVariable('nav_lon','f4',('y','x',))
id_lat = f_out.createVariable('nav_lat','f4',('y','x',))
id_atl = f_out.createVariable('tmaskatl' ,'f4',('y','x',)) ; id_atl.long_name = 'Atlantic Basin'
id_pac = f_out.createVariable('tmaskpac' ,'f4',('y','x',)) ; id_pac.long_name = 'Pacific Basin'
id_ind = f_out.createVariable('tmaskind' ,'f4',('y','x',)) ; id_ind.long_name = 'Indian Basin'
id_soc = f_out.createVariable('tmasksoc' ,'f4',('y','x',)) ; id_soc.long_name = 'Southern Basin'
id_inp = f_out.createVariable('tmaskinp' ,'f4',('y','x',)) ; id_inp.long_name = 'Indo-Pacific Basin'
# Filling variables:
id_lat[:,:] = xlat[:,:]
id_lon[:,:] = xlon[:,:]
id_atl[:,:] = mask_atl[:,:]
id_pac[:,:] = mask_pac[:,:]
id_ind[:,:] = mask_ind[:,:]
id_soc[:,:] = mask_soc[:,:]
id_inp[:,:] = mask_inp[:,:]
f_out.About = 'ORCA1 main oceanic basin land-sea mask created from '+cf_mm
f_out.Author = ' Generated with "orca025_create_basin_mask_from_meshmask.py" of BaraKuda (https://github.com/brodeau/barakuda)'
f_out.close()
print cf_out+' sucessfully created!'
f_atm.createDimension(cv_tim, None)
# Variables
ida_lon = f_atm.createVariable(cv_lon, 'f4', (
'y',
'x',
), zlib=True)
ida_lat = f_atm.createVariable(cv_lat, 'f4', (
'y',
'x',
), zlib=True)
ida_tim = f_atm.createVariable(cv_tim, 'f4', (cv_tim, ), zlib=True)
# Attributes
ida_tim.units = cunt_time
ida_lat.units = cunt_lat
ida_lon.units = cunt_lon
f_atm.About = 'prepare_PAPA_forcing_STATION-ASF.py of AeroBulk for NEMO/STATION-ASF test-case. Gaps in time-series are filled by means of linear interpolation.'
# Filling variables:
ida_lat[:, :] = vlat[0]
ida_lon[:, :] = vlon[0]
for jt in range(Nt):
ida_tim[jt] = vtime[jt]
# Creating output file for ocean:
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
f_oce = Dataset(cf_oce, 'w', format='NETCDF4')
# Dimensions:
f_oce.createDimension('x', ni)
f_oce.createDimension('y', nj)
f_oce.createDimension(cv_tim, None)
# Variables
ido_lon = f_oce.createVariable(cv_lon, 'f4', (
