WRF-chem的後處理

strT=[''.join([i.decode('utf-8') for i in nc.variables['Times'][t,:]]) for t in range(nt)]
Times=[datetime.datetime.strptime(a,'%Y-%m-%d_%H:00:00') for a in strT]
tflag=[i.strftime('%Y%m%d%H') for i in Times]

import netCDF4
import numpy as np
import datetime

#for i in 03-3{0..1} 04-0{1..9};do nc=wrfout_d01_2018-${i}_00:00:00;ncks -v Times,DUST_1,DUST_2,DUST_2,DUST_3,DUST_4,DUST_5 -d bottom_top,0 $nc dust$i.nc;done
#ncrcat -O dust0*.nc a
#ncks -O -v Times,DUST_1 a dust.nc

fnames=subprocess.check_output('ls dust??-??.nc',shell=True).decode('utf8').strip('\n').split('\n')
nc = netCDF4.Dataset('dust.nc', 'r+')
binf={i:1 for i in range(1,4)};binf.update({4:0.87,5:0})
it=0
for fname in fnames:
  nc_in = netCDF4.Dataset(fname, 'r')
  nt,nz,ny,nx=nc_in['DUST_1'].shape
  dust=np.zeros(shape=(nt,nz,ny,nx))
  for i in range(1,6):
    dust+=nc_in['DUST_'+str(i)][:]*binf[i]
  nc['DUST_1'][it:it+nt,:,:,:]=dust[:,:,:,:]
  it+=nt

IX,IY=335-1,212-1
nt,nz,ny,nx=nc['DUST_1'].shape
strT=[''.join([i.decode('utf-8') for i in nc.variables['Times'][t,:]]) for t in range(nt)]
Times=[datetime.datetime.strptime(a,'%Y-%m-%d_%H:00:00') for a in strT]
tflag=[i.strftime('%Y%m%d%H') for i in Times]
zs=['WRFchem']
for z in zs:
  exec(z+'=nc["DUST_1"][:,0,IY,IX]*1.1839') #dens of air https://en.wikipedia.org/wiki/Density_of_air
DD={}
for z in zs+['tflag']:
  exec('DD.update({"'+z+'":'+z+'})')
df=DataFrame(DD)
df.set_index('tflag').to_csv('ntw.csv')

nc.close()