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############################################### meic2wrf ########################################################
# Authors: Fan Jin; Zhou Yong-long; Zhang Lei; Xu Xuan-ye; Jiang Pei-ya; Li Zhuo #
# Institution: Chengdu AeriDice Environment Technology Co., Ltd.; Chengdu University of Information & Technology; #
# Chinese Academy of Meteorological Sciences #
# E-mail: jin.fan@outlook.com #
# Environment: Python 3.7.7; pynio 1.5.5 #
###################################################################################################################
import Nio
import tkinter as tk
from tkinter import filedialog
import numpy as np
import os
from int_dis import *
from tkinter import messagebox
import fnmatch
import shutil
root=tk.Tk()
root.title('MEIC污染源清单向WRF-Chem模式网格插值分配程序')
lbl=tk.Label(root, text='1. 整合MEIC清单中各污染物不同部门的排放数据')
lbl.grid(row=0,column=0,sticky=tk.W)
lbl=tk.Label(root, text='MEIC清单数据所在文件夹路径:')
lbl.grid(row=1,column=0,sticky=tk.E)
ent_dir = tk.Entry(root, width=65)
ent_dir.grid(row=1,column=1)
def bws_meic():
dirname = filedialog.askdirectory()
ent_dir.delete(0,tk.END)
ent_dir.insert(0, dirname)
def merge_meic_dept():
if os.path.exists(ent_dir.get()+'/merged/'):
shutil.rmtree(ent_dir.get()+'/merged/')
os.mkdir(ent_dir.get()+'/merged/')
for i,j in zip(['*BC*','*CO[!2]*','*CO2*','*NH3*','*NOx*','*[!V]OC*','*PM2.5*','*PMcoarse*','*ALD*',\
'*CSL*','*ETH*','*GLY*','*HC3*','*HC5*','*HC8*','*HCHO*',\
'*ISO*','*KET*','*MACR*','*MGLY*','*MVK*','*NR*','*NVOL*',\
'*OL2*','*OLI*','*OLT*','*ORA1*','*ORA2*','*TOL*','*XYL*','*SO2*','*VOC*',], ['BC','CO','CO2','NH3','NOx','OC','PM2.5','PMcoarse','ALD',\
'CSL','ETH','GLY','HC3','HC5','HC8','HCHO',\
'ISO','KET','MACR','MGLY','MVK','NR','NVOL',\
'OL2','OLI','OLT','ORA1','ORA2','TOL','XYL','SO2','VOC',]):
fn_act=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*agr*nc')[0]
fn_idt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*ind*nc')[0]
fn_pwr=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*pow*nc')[0]
fn_rdt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*res*nc')[0]
fn_tpt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*tra*nc')[0]
f_act=Nio.open_file(fn_act)
f_idt=Nio.open_file(fn_idt)
f_pwr=Nio.open_file(fn_pwr)
f_rdt=Nio.open_file(fn_rdt)
f_tpt=Nio.open_file(fn_tpt)
act=f_act.variables['z'][:].reshape((200, 320),)[::-1]
act=np.where(act>0.0,act*1,0.0)
idt=f_idt.variables['z'][:].reshape((200, 320),)[::-1]
idt=np.where(idt>0.0,idt*1,0.0)
pwr=f_pwr.variables['z'][:].reshape((200, 320),)[::-1]
pwr=np.where(pwr>0.0,pwr*1,0.0)
rdt=f_rdt.variables['z'][:].reshape((200, 320),)[::-1]
rdt=np.where(rdt>0.0,rdt*1,0.0)
tpt=f_tpt.variables['z'][:].reshape((200, 320),)[::-1]
tpt=np.where(tpt>0.0,tpt*1,0.0)
lon=np.arange(70.125,150,0.25,dtype=np.float32)
lat=np.arange(10.125,60,0.25,dtype=np.float32)
lon,lat=np.meshgrid(lon,lat)
f=Nio.open_file(ent_dir.get()+'/merged/'+j+'.nc','c')
f.create_dimension('lon',320)
f.create_dimension('lat',200)
for var,val in zip(['act','idt','pwr','rdt','tpt','lon','lat'],[act,idt,pwr,rdt,tpt,lon,lat]):
f.create_variable(var,'f',('lat','lon',))
f.variables[var][:] = val
f.close()
else:
os.mkdir(ent_dir.get()+'/merged/')
for i,j in zip(['*BC*','*CO[!2]*','*CO2*','*NH3*','*NOx*','*[!V]OC*','*PM2.5*','*PMcoarse*','*ALD*',\
'*CSL*','*ETH*','*GLY*','*HC3*','*HC5*','*HC8*','*HCHO*',\
'*ISO*','*KET*','*MACR*','*MGLY*','*MVK*','*NR*','*NVOL*',\
'*OL2*','*OLI*','*OLT*','*ORA1*','*ORA2*','*TOL*','*XYL*','*SO2*','*VOC*',], ['BC','CO','CO2','NH3','NOx','OC','PM2.5','PMcoarse','ALD',\
'CSL','ETH','GLY','HC3','HC5','HC8','HCHO',\
'ISO','KET','MACR','MGLY','MVK','NR','NVOL',\
'OL2','OLI','OLT','ORA1','ORA2','TOL','XYL','SO2','VOC',]):
fn_act=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*agr*nc')[0]
fn_idt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*ind*nc')[0]
fn_pwr=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*pow*nc')[0]
fn_rdt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*res*nc')[0]
fn_tpt=ent_dir.get()+'/'+fnmatch.filter(fnmatch.filter(os.listdir(ent_dir.get()), i), '*tra*nc')[0]
f_act=Nio.open_file(fn_act)
f_idt=Nio.open_file(fn_idt)
f_pwr=Nio.open_file(fn_pwr)
f_rdt=Nio.open_file(fn_rdt)
f_tpt=Nio.open_file(fn_tpt)
act=f_act.variables['z'][:].reshape((200, 320),)[::-1]
act=np.where(act>0.0,act*1,0.0)
idt=f_idt.variables['z'][:].reshape((200, 320),)[::-1]
idt=np.where(idt>0.0,idt*1,0.0)
pwr=f_pwr.variables['z'][:].reshape((200, 320),)[::-1]
pwr=np.where(pwr>0.0,pwr*1,0.0)
rdt=f_rdt.variables['z'][:].reshape((200, 320),)[::-1]
rdt=np.where(rdt>0.0,rdt*1,0.0)
tpt=f_tpt.variables['z'][:].reshape((200, 320),)[::-1]
tpt=np.where(tpt>0.0,tpt*1,0.0)
lon=np.arange(70.125,150,0.25,dtype=np.float32)
lat=np.arange(10.125,60,0.25,dtype=np.float32)
lon,lat=np.meshgrid(lon,lat)
f=Nio.open_file(ent_dir.get()+'/merged/'+j+'.nc','c')
f.create_dimension('lon',320)
f.create_dimension('lat',200)
for var,val in zip(['act','idt','pwr','rdt','tpt','lon','lat'],[act,idt,pwr,rdt,tpt,lon,lat]):
f.create_variable(var,'f',('lat','lon',))
f.variables[var][:] = val
f.close()
b_btn = tk.Button(root, text='浏览', command=bws_meic, width=15)
b_btn.grid(row=1,column=2)
r_btn = tk.Button(root, text='运行', command=merge_meic_dept, width=15)
r_btn.grid(row=1,column=3)
lbl=tk.Label(root, text='2. 向WRF-Chem模式网格插值分配')
lbl.grid(row=2,column=0,sticky=tk.W)
lbl=tk.Label(root, text='wrfinput文件路径:')
lbl.grid(row=3,column=0,sticky=tk.E)
ent_inp = tk.Entry(root, width=65)
ent_inp.grid(row=3,column=1)
def bws_wrfipt():
wrfiptname = filedialog.askopenfilename()
ent_inp.delete(0,tk.END)
ent_inp.insert(0, wrfiptname)
b_btn = tk.Button(root, text='浏览', command=bws_wrfipt, width=15)
b_btn.grid(row=3,column=2)#padx=10,pady=10
agr_z_d=[1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000]
ind_z_d=[0.602,0.346,0.052,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000]
pow_z_d=[0.034,0.140,0.349,0.227,0.167,0.059,0.024,0.000,0.000,0.000,0.000]
res_z_d=[0.900,0.100,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000]
tra_z_d=[0.950,0.050,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000]
sec_z_d=[agr_z_d,ind_z_d,pow_z_d,res_z_d,tra_z_d,]
agr_t_d=[1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000,
1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000]
ind_t_d=[1.080, 1.632, 1.632, 1.632, 1.632, 1.632, 1.632, 1.632, 1.632, 1.080, 0.936, 0.792, 0.648, 0.504,
0.504, 0.504, 0.504, 0.504, 0.504, 0.504, 0.504, 0.648, 0.792, 0.936]
pow_t_d=[1.104, 1.200, 1.212, 1.200, 1.224, 1.236, 1.236, 1.224, 1.176, 1.104, 1.116, 1.128, 1.080, 1.008,
0.948, 0.720, 0.840, 0.708, 0.576, 0.600, 0.732, 0.804, 0.852, 0.972]
res_t_d=[1.224, 1.584, 2.736, 2.520, 0.984, 0.696, 0.552, 0.984, 1.680, 2.328, 1.488, 0.840, 0.264, 0.360,
0.336, 0.240, 0.336, 0.312, 0.408, 0.216, 0.408, 1.080, 1.176, 1.248]
tra_t_d=[1.536, 1.440, 1.392, 1.272, 1.212, 1.368, 1.380, 1.416, 1.428, 1.524, 1.380, 1.128, 1.068, 1.008,
0.864, 0.648, 0.480, 0.348, 0.252, 0.216, 0.192, 0.312, 0.720, 1.416]
sec_t_d=[agr_t_d,ind_t_d,pow_t_d,res_t_d,tra_t_d,]
state=tk.StringVar()
state.set('disable')
def disable():
ent_agr_z.config(state=state.get())
ent_ind_z.config(state=state.get())
ent_pow_z.config(state=state.get())
ent_res_z.config(state=state.get())
ent_tra_z.config(state=state.get())
ent_agr_t.config(state=state.get())
ent_ind_t.config(state=state.get())
ent_pow_t.config(state=state.get())
ent_res_t.config(state=state.get())
ent_tra_t.config(state=state.get())
def activate():
ent_agr_z.config(state=state.get())
ent_ind_z.config(state=state.get())
ent_pow_z.config(state=state.get())
ent_res_z.config(state=state.get())
ent_tra_z.config(state=state.get())
ent_agr_t.config(state=state.get())
ent_ind_t.config(state=state.get())
ent_pow_t.config(state=state.get())
ent_res_t.config(state=state.get())
ent_tra_t.config(state=state.get())
rdb_default = tk.Radiobutton(root, text='使用默认分配因子', variable=state, value='disable', command=disable)
rdb_default.grid(row=4,column=1,sticky=tk.W)
rdb_custom = tk.Radiobutton(root, text='自定义分配因子', variable=state, value='normal', command=activate)
rdb_custom.grid(row=4,column=1,sticky=tk.E)
lbl=tk.Label(root, text='农业垂直排放因子:')
lbl.grid(row=5,column=0,sticky=tk.E)
ent_agr_z=tk.Entry(root, state='disable',width=65)
ent_agr_z.grid(row=5,column=1,)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=5,column=2)
lbl=tk.Label(root, text='工业垂直排放因子:')
lbl.grid(row=6,column=0,sticky=tk.E)
ent_ind_z=tk.Entry(root, state='disable',width=65)
ent_ind_z.grid(row=6,column=1,)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=6,column=2)
lbl=tk.Label(root, text='电力垂直排放因子:')
lbl.grid(row=7,column=0,sticky=tk.E)
ent_pow_z=tk.Entry(root, state='disable',width=65)
ent_pow_z.grid(row=7,column=1,)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=7,column=2)
lbl=tk.Label(root, text='民用垂直排放因子:')
lbl.grid(row=8,column=0,sticky=tk.E)
ent_res_z=tk.Entry(root, state='disable',width=65)
ent_res_z.grid(row=8,column=1,)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=8,column=2)
lbl=tk.Label(root, text='交通垂直排放因子:')
lbl.grid(row=9,column=0,sticky=tk.E)
ent_tra_z=tk.Entry(root, state='disable',width=65)
ent_tra_z.grid(row=9,column=1,)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=9,column=2)
lbl=tk.Label(root, text='农业逐小时排放因子:')
lbl.grid(row=10,column=0,sticky=tk.E)
ent_agr_t=tk.Entry(root, state='disable',width=65)
ent_agr_t.grid(row=10,column=1,)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=10,column=2)
lbl=tk.Label(root, text='工业逐小时排放因子:')
lbl.grid(row=11,column=0,sticky=tk.E)
ent_ind_t=tk.Entry(root, state='disable',width=65)
ent_ind_t.grid(row=11,column=1,)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=11,column=2)
lbl=tk.Label(root, text='电力逐小时排放因子:')
lbl.grid(row=12,column=0,sticky=tk.E)
ent_pow_t=tk.Entry(root, state='disable',width=65)
ent_pow_t.grid(row=12,column=1)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=12,column=2)
lbl=tk.Label(root, text='民用逐小时排放因子:')
lbl.grid(row=13,column=0,sticky=tk.E)
ent_res_t=tk.Entry(root, state='disable',width=65)
ent_res_t.grid(row=13,column=1)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=13,column=2)
lbl=tk.Label(root, text='交通逐小时排放因子:')
lbl.grid(row=14,column=0,sticky=tk.E)
ent_tra_t=tk.Entry(root, state='disable',width=65)
ent_tra_t.grid(row=14,column=1)
lbl=tk.Label(root, text='输入格式: 0.34 0.56 ... ')
lbl.grid(row=14,column=2)
def itp_dis():
if state.get() == 'normal':
if fnmatch.fnmatch(ent_agr_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_ind_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_pow_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_res_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_tra_z.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_agr_t.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_ind_t.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_pow_t.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_res_t.get().replace(' ', '').replace('.',''), '*[!0-9]*') or fnmatch.fnmatch(ent_tra_t.get().replace(' ', '').replace('.',''), '*[!0-9]*'):
tk.messagebox.showerror(title='error',message='input format must be 0.23 0.34 ...')
elif not len(ent_agr_z.get().strip().split(' '))==len(ent_ind_z.get().strip().split(' '))==len(ent_pow_z.get().strip().split(' '))==len(ent_res_z.get().strip().split(' '))==len(ent_tra_z.get().strip().split(' ')):
tk.messagebox.showerror(title='error',message='number of z factor must be equal')
elif not len(ent_agr_t.get().strip().split(' '))==len(ent_ind_t.get().strip().split(' '))==len(ent_pow_t.get().strip().split(' '))==len(ent_res_t.get().strip().split(' '))==len(ent_tra_t.get().strip().split(' '))==24:
tk.messagebox.showerror(title='error',message='number of t factor must be 24')
else:
agr_z=[float(i) for i in ent_agr_z.get().strip().split(' ')]
ind_z=[float(i) for i in ent_ind_z.get().strip().split(' ')]
pow_z=[float(i) for i in ent_pow_z.get().strip().split(' ')]
res_z=[float(i) for i in ent_res_z.get().strip().split(' ')]
tra_z=[float(i) for i in ent_tra_z.get().strip().split(' ')]
sec_z=[agr_z,ind_z,pow_z,res_z,tra_z,]
agr_t=[float(i) for i in ent_agr_t.get().strip().split(' ')]
ind_t=[float(i) for i in ent_ind_t.get().strip().split(' ')]
pow_t=[float(i) for i in ent_pow_t.get().strip().split(' ')]
res_t=[float(i) for i in ent_res_t.get().strip().split(' ')]
tra_t=[float(i) for i in ent_tra_t.get().strip().split(' ')]
sec_t=[agr_t,ind_t,pow_t,res_t,tra_t,]
f_inp=Nio.open_file(ent_inp.get(),format='nc')
lon_inp=f_inp.variables['XLONG'][0,:]
lat_inp=f_inp.variables['XLAT'][0,:]
time_inp=f_inp.variables['Times'][:][0]
time_inp=''.join([i.decode('utf-8') for i in time_inp]).split('_')[0]
f_inp.close()
#put all the distributed meic species into meic_spec_emis:
meic_spec_emis=[]
#inorganic gas: ton/(grid.month) to mole/(km2.h)
for spec,M in zip(['CO','CO2','NH3','NOx','SO2',],[28,44,17,31.6,64]):
f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
lon=f_post.variables['lon'][:]
lat=f_post.variables['lat'][:]
section=[(f_post.variables[sec][:,:]*1e6)/(ll_area(lat,0.25)*30*24*M) for sec in ['act','idt','pwr','rdt','tpt',]]
f_post.close()
sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z,sec_t)]
c=sum(c)
meic_spec_emis.append(c)
#organic gas: million_mole/(grid.month) to mole/(km2.h)
for spec in ['ALD','CSL','ETH','GLY','HC3','HC5','HC8','HCHO','ISO','KET','MACR','MGLY','MVK','NR','NVOL',
'OL2','OLI','OLT','ORA1','ORA2','TOL','XYL',]:
f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
#lon=f_post.variables['lon'][:]
#lat=f_post.variables['lat'][:]
section=[(f_post.variables[sec][:,:]*1e6)/(ll_area(lat,0.25)*30*24) for sec in ['act','idt','pwr','rdt','tpt',]]
f_post.close()
sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z,sec_t)]
c=sum(c)
meic_spec_emis.append(c)
#aerosol: ton/(grid.month) to ug/(m2.s)
for spec in ['BC','OC','PM2.5','PMcoarse',]:
f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
#lon=f_post.variables['lon'][:]
#lat=f_post.variables['lat'][:]
section=[(f_post.variables[sec][:,:]*1e6)/(ll_area(lat,0.25)*30*24*3600) for sec in ['act','idt','pwr','rdt','tpt',]]
f_post.close()
sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z,sec_t)]
c=sum(c)
meic_spec_emis.append(c)
#meic emission to RADM2 chemistry scheme:
wrf_spec_emis=[np.zeros(meic_spec_emis[0][:].shape, dtype='float32')]*31
wrf_spec_emis[0]=meic_spec_emis[0] #wrf: CO
wrf_spec_emis[1]=meic_spec_emis[2] #wrf: NH3
wrf_spec_emis[2]=meic_spec_emis[3]*0.9 #wrf: NO
wrf_spec_emis[3]=meic_spec_emis[3]*0.1 #wrf: NO2
wrf_spec_emis[4]=meic_spec_emis[4]*0.9 #wrf: SO2
wrf_spec_emis[5]=meic_spec_emis[5] #wrf: ALD
wrf_spec_emis[6]=meic_spec_emis[6] #wrf: CSL
wrf_spec_emis[7]=meic_spec_emis[7] #wrf: ETH
wrf_spec_emis[8]=meic_spec_emis[9] #wrf: HC3
wrf_spec_emis[9]=meic_spec_emis[10] #wrf: HC5
wrf_spec_emis[10]=meic_spec_emis[11] #wrf: HC8
wrf_spec_emis[11]=meic_spec_emis[12] #wrf: HCHO
wrf_spec_emis[12]=meic_spec_emis[13] #wrf: ISO
wrf_spec_emis[13]=meic_spec_emis[14] #wrf: KET
wrf_spec_emis[14]=meic_spec_emis[20]*1.1 #wrf: OL2
wrf_spec_emis[15]=meic_spec_emis[21]*1.1 #wrf: OLI
wrf_spec_emis[16]=meic_spec_emis[22]*1.1 #wrf: OLT
wrf_spec_emis[17]=meic_spec_emis[24] #wrf: ORA2
wrf_spec_emis[18]=meic_spec_emis[25]*1.1 #wrf: TOL
wrf_spec_emis[19]=meic_spec_emis[26]*1.1 #wrf: XYL
wrf_spec_emis[20]=meic_spec_emis[27]*0.2 #wrf: ECi
wrf_spec_emis[21]=meic_spec_emis[27]*0.8 #wrf: ECj
wrf_spec_emis[22]=meic_spec_emis[28]*0.2 #wrf: ORGi
wrf_spec_emis[23]=meic_spec_emis[28]*0.8 #wrf: ORGj
wrf_spec_emis[24]=meic_spec_emis[29]-meic_spec_emis[28]-meic_spec_emis[27]*0.2 #wrf: PM25i
wrf_spec_emis[25]=meic_spec_emis[29]-meic_spec_emis[28]-meic_spec_emis[27]*0.8 #wrf: PM25j
wrf_spec_emis[26]=meic_spec_emis[30]*0.8 #wrf: PM10
wrf_spec_emis[27]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: SO4i
wrf_spec_emis[28]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: SO4j
wrf_spec_emis[29]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: NO3i
wrf_spec_emis[30]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: NO3j
#generate wrfchemi_00z_d01 anthropogenic emission data for wrf-chem model run:
if os.path.exists(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]):
os.remove(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1],'c',format='nc')
f_chem.create_dimension('Time',None)
f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
f_chem.create_dimension('DateStrLen',19)
f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
for i,time in enumerate([time_inp+'_00:00:00',time_inp+'_01:00:00',time_inp+'_02:00:00',time_inp+'_03:00:00',time_inp+'_04:00:00',
time_inp+'_05:00:00',time_inp+'_06:00:00',time_inp+'_07:00:00',time_inp+'_08:00:00',time_inp+'_09:00:00',time_inp+'_10:00:00',
time_inp+'_11:00:00',]):
f_chem.variables['Times'][i]=list(time) #split the string to char
for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
f_chem.variables[LL][:]=ll
radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]
for gas in radm_gas:
f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[gas].FieldType = np.int16(104)
f_chem.variables[gas].MemoryOrder = 'XYZ'
f_chem.variables[gas].description = 'EMISSIONS'
f_chem.variables[gas].units = 'mol km^-2 hr^-1'
f_chem.variables[gas].stagger = 'Z'
#f_chem.variables[gas].ordinates = 'XLONG XLAT'
for aerosol in radm_aerosol:
f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[aerosol].FieldType = np.int16(104)
f_chem.variables[aerosol].MemoryOrder = 'XYZ'
f_chem.variables[aerosol].description = 'EMISSIONS'
f_chem.variables[aerosol].units = 'ug/m3 m/s'
f_chem.variables[aerosol].stagger = 'Z'
#f_chem.variables[aerosol].ordinates = 'XLONG XLAT'
radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
'E_SO4J','E_NO3I','E_NO3J',]
for i,spec in enumerate(radm_spec):
f_chem.variables[spec][:] = wrf_spec_emis[i][0:12,:,:,:] #dimension need to be matched with the variable defination
f_chem.close()
os.rename(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
else:
f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1],'c',format='nc')
f_chem.create_dimension('Time',None)
f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
f_chem.create_dimension('DateStrLen',19)
f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
for i,time in enumerate([time_inp+'_00:00:00',time_inp+'_01:00:00',time_inp+'_02:00:00',time_inp+'_03:00:00',time_inp+'_04:00:00',
time_inp+'_05:00:00',time_inp+'_06:00:00',time_inp+'_07:00:00',time_inp+'_08:00:00',time_inp+'_09:00:00',time_inp+'_10:00:00',
time_inp+'_11:00:00',]):
f_chem.variables['Times'][i]=list(time) #split the string to char
for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
f_chem.variables[LL][:]=ll
radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]
for gas in radm_gas:
f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[gas].FieldType = np.int16(104)
f_chem.variables[gas].MemoryOrder = 'XYZ'
f_chem.variables[gas].description = 'EMISSIONS'
f_chem.variables[gas].units = 'mol km^-2 hr^-1'
f_chem.variables[gas].stagger = 'Z'
#f_chem.variables[gas].ordinates = 'XLONG XLAT'
for aerosol in radm_aerosol:
f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[aerosol].FieldType = np.int16(104)
f_chem.variables[aerosol].MemoryOrder = 'XYZ'
f_chem.variables[aerosol].description = 'EMISSIONS'
f_chem.variables[aerosol].units = 'ug/m3 m/s'
f_chem.variables[aerosol].stagger = 'Z'
#f_chem.variables[aerosol].ordinates = 'XLONG XLAT'
radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
'E_SO4J','E_NO3I','E_NO3J',]
for i,spec in enumerate(radm_spec):
f_chem.variables[spec][:] = wrf_spec_emis[i][0:12,:,:,:] #dimension need to be matched with the variable defination
f_chem.close()
os.rename(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
#generate wrfchemi_12z_d01 anthropogenic emission data for wrf-chem model run:
if os.path.exists(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]):
os.remove(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1],'c',format='nc')
f_chem.create_dimension('Time',None)
f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
f_chem.create_dimension('DateStrLen',19)
f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
for i,time in enumerate([time_inp+'_12:00:00',time_inp+'_13:00:00',time_inp+'_14:00:00',time_inp+'_15:00:00',time_inp+'_16:00:00',
time_inp+'_17:00:00',time_inp+'_18:00:00',time_inp+'_19:00:00',time_inp+'_20:00:00',time_inp+'_21:00:00',time_inp+'_22:00:00',
time_inp+'_23:00:00',]):
f_chem.variables['Times'][i]=list(time)
for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
f_chem.variables[LL][:]=ll
radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]
for gas in radm_gas:
f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[gas].FieldType = np.int16(104)
f_chem.variables[gas].MemoryOrder = 'XYZ'
f_chem.variables[gas].description = 'EMISSIONS'
f_chem.variables[gas].units = 'mol km^-2 hr^-1'
f_chem.variables[gas].stagger = 'Z'
#f_chem.variables[gas].ordinates = 'XLONG XLAT'
for aerosol in radm_aerosol:
f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[aerosol].FieldType = np.int16(104)
f_chem.variables[aerosol].MemoryOrder = 'XYZ'
f_chem.variables[aerosol].description = 'EMISSIONS'
f_chem.variables[aerosol].units = 'ug/m3 m/s'
f_chem.variables[aerosol].stagger = 'Z'
#f_chem.variables[aerosol].ordinates = 'XLONG XLAT'
radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
'E_SO4J','E_NO3I','E_NO3J',]
for i,spec in enumerate(radm_spec):
f_chem.variables[spec][:] = wrf_spec_emis[i][12:24,:,:,:] #dimension need to be matched with the variable defination
f_chem.close()
os.rename(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
else:
f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1],'c',format='nc')
f_chem.create_dimension('Time',None)
f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
f_chem.create_dimension('DateStrLen',19)
f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
for i,time in enumerate([time_inp+'_12:00:00',time_inp+'_13:00:00',time_inp+'_14:00:00',time_inp+'_15:00:00',time_inp+'_16:00:00',
time_inp+'_17:00:00',time_inp+'_18:00:00',time_inp+'_19:00:00',time_inp+'_20:00:00',time_inp+'_21:00:00',time_inp+'_22:00:00',
time_inp+'_23:00:00',]):
f_chem.variables['Times'][i]=list(time)
for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
f_chem.variables[LL][:]=ll
radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]
for gas in radm_gas:
f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[gas].FieldType = np.int16(104)
f_chem.variables[gas].MemoryOrder = 'XYZ'
f_chem.variables[gas].description = 'EMISSIONS'
f_chem.variables[gas].units = 'mol km^-2 hr^-1'
f_chem.variables[gas].stagger = 'Z'
#f_chem.variables[gas].ordinates = 'XLONG XLAT'
for aerosol in radm_aerosol:
f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[aerosol].FieldType = np.int16(104)
f_chem.variables[aerosol].MemoryOrder = 'XYZ'
f_chem.variables[aerosol].description = 'EMISSIONS'
f_chem.variables[aerosol].units = 'ug/m3 m/s'
f_chem.variables[aerosol].stagger = 'Z'
#f_chem.variables[aerosol].ordinates = 'XLONG XLAT'
radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
'E_SO4J','E_NO3I','E_NO3J',]
for i,spec in enumerate(radm_spec):
f_chem.variables[spec][:] = wrf_spec_emis[i][12:24,:,:,:] #dimension need to be matched with the variable defination
f_chem.close()
os.rename(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
elif state.get() =='disable':
f_inp=Nio.open_file(ent_inp.get(),format='nc')
lon_inp=f_inp.variables['XLONG'][0,:]
lat_inp=f_inp.variables['XLAT'][0,:]
time_inp=f_inp.variables['Times'][:][0]
time_inp=''.join([i.decode('utf-8') for i in time_inp]).split('_')[0]
f_inp.close()
#put all the distributed meic species into meic_spec_emis:
meic_spec_emis=[]
#inorganic gas: ton/(grid.month) to mole/(km2.h)
for spec,M in zip(['CO','CO2','NH3','NOx','SO2',],[28,44,17,31.6,64]):
f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
lon=f_post.variables['lon'][:]
lat=f_post.variables['lat'][:]
section=[(f_post.variables[sec][:,:]*1e6)/(ll_area(lat,0.25)*30*24*M) for sec in ['act','idt','pwr','rdt','tpt',]]
f_post.close()
sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z_d,sec_t_d)]
c=sum(c)
meic_spec_emis.append(c)
#organic gas: million_mole/(grid.month) to mole/(km2.h)
for spec in ['ALD','CSL','ETH','GLY','HC3','HC5','HC8','HCHO','ISO','KET','MACR','MGLY','MVK','NR','NVOL',
'OL2','OLI','OLT','ORA1','ORA2','TOL','XYL',]:
f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
#lon=f_post.variables['lon'][:]
#lat=f_post.variables['lat'][:]
section=[(f_post.variables[sec][:,:]*1e6)/(ll_area(lat,0.25)*30*24) for sec in ['act','idt','pwr','rdt','tpt',]]
f_post.close()
sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z_d,sec_t_d)]
c=sum(c)
meic_spec_emis.append(c)
#aerosol: ton/(grid.month) to ug/(m2.s)
for spec in ['BC','OC','PM2.5','PMcoarse',]:
f_post=Nio.open_file(ent_dir.get()+'/merged/'+spec+'.nc')
#lon=f_post.variables['lon'][:]
#lat=f_post.variables['lat'][:]
section=[(f_post.variables[sec][:,:]*1e6)/(ll_area(lat,0.25)*30*24*3600) for sec in ['act','idt','pwr','rdt','tpt',]]
f_post.close()
sections=[meic2wrf(lon_inp,lat_inp,lon,lat,emis,) for emis in section]
c=[sec2zt(i,j,k) for i,j,k in zip(sections,sec_z_d,sec_t_d)]
c=sum(c)
meic_spec_emis.append(c)
#meic emission to RADM2 chemistry scheme:
wrf_spec_emis=[np.zeros(meic_spec_emis[0][:].shape, dtype='float32')]*31
wrf_spec_emis[0]=meic_spec_emis[0] #wrf: CO
wrf_spec_emis[1]=meic_spec_emis[2] #wrf: NH3
wrf_spec_emis[2]=meic_spec_emis[3]*0.9 #wrf: NO
wrf_spec_emis[3]=meic_spec_emis[3]*0.1 #wrf: NO2
wrf_spec_emis[4]=meic_spec_emis[4]*0.9 #wrf: SO2
wrf_spec_emis[5]=meic_spec_emis[5] #wrf: ALD
wrf_spec_emis[6]=meic_spec_emis[6] #wrf: CSL
wrf_spec_emis[7]=meic_spec_emis[7] #wrf: ETH
wrf_spec_emis[8]=meic_spec_emis[9] #wrf: HC3
wrf_spec_emis[9]=meic_spec_emis[10] #wrf: HC5
wrf_spec_emis[10]=meic_spec_emis[11] #wrf: HC8
wrf_spec_emis[11]=meic_spec_emis[12] #wrf: HCHO
wrf_spec_emis[12]=meic_spec_emis[13] #wrf: ISO
wrf_spec_emis[13]=meic_spec_emis[14] #wrf: KET
wrf_spec_emis[14]=meic_spec_emis[20]*1.1 #wrf: OL2
wrf_spec_emis[15]=meic_spec_emis[21]*1.1 #wrf: OLI
wrf_spec_emis[16]=meic_spec_emis[22]*1.1 #wrf: OLT
wrf_spec_emis[17]=meic_spec_emis[24] #wrf: ORA2
wrf_spec_emis[18]=meic_spec_emis[25]*1.1 #wrf: TOL
wrf_spec_emis[19]=meic_spec_emis[26]*1.1 #wrf: XYL
wrf_spec_emis[20]=meic_spec_emis[27]*0.2 #wrf: ECi
wrf_spec_emis[21]=meic_spec_emis[27]*0.8 #wrf: ECj
wrf_spec_emis[22]=meic_spec_emis[28]*0.2 #wrf: ORGi
wrf_spec_emis[23]=meic_spec_emis[28]*0.8 #wrf: ORGj
wrf_spec_emis[24]=meic_spec_emis[29]-meic_spec_emis[28]-meic_spec_emis[27]*0.2 #wrf: PM25i
wrf_spec_emis[25]=meic_spec_emis[29]-meic_spec_emis[28]-meic_spec_emis[27]*0.8 #wrf: PM25j
wrf_spec_emis[26]=meic_spec_emis[30]*0.8 #wrf: PM10
wrf_spec_emis[27]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: SO4i
wrf_spec_emis[28]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: SO4j
wrf_spec_emis[29]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: NO3i
wrf_spec_emis[30]=np.zeros(meic_spec_emis[0][:].shape, dtype='float32') #wrf: NO3j
#generate wrfchemi_00z_d01 anthropogenic emission data for wrf-chem model run:
if os.path.exists(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]):
os.remove(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1],'c',format='nc')
f_chem.create_dimension('Time',None)
f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
f_chem.create_dimension('DateStrLen',19)
f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
for i,time in enumerate([time_inp+'_00:00:00',time_inp+'_01:00:00',time_inp+'_02:00:00',time_inp+'_03:00:00',time_inp+'_04:00:00',
time_inp+'_05:00:00',time_inp+'_06:00:00',time_inp+'_07:00:00',time_inp+'_08:00:00',time_inp+'_09:00:00',time_inp+'_10:00:00',
time_inp+'_11:00:00',]):
f_chem.variables['Times'][i]=list(time) #split the string to char
for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
f_chem.variables[LL][:]=ll
radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]
for gas in radm_gas:
f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[gas].FieldType = np.int16(104)
f_chem.variables[gas].MemoryOrder = 'XYZ'
f_chem.variables[gas].description = 'EMISSIONS'
f_chem.variables[gas].units = 'mol km^-2 hr^-1'
f_chem.variables[gas].stagger = 'Z'
#f_chem.variables[gas].ordinates = 'XLONG XLAT'
for aerosol in radm_aerosol:
f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[aerosol].FieldType = np.int16(104)
f_chem.variables[aerosol].MemoryOrder = 'XYZ'
f_chem.variables[aerosol].description = 'EMISSIONS'
f_chem.variables[aerosol].units = 'ug/m3 m/s'
f_chem.variables[aerosol].stagger = 'Z'
#f_chem.variables[aerosol].ordinates = 'XLONG XLAT'
radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
'E_SO4J','E_NO3I','E_NO3J',]
for i,spec in enumerate(radm_spec):
f_chem.variables[spec][:] = wrf_spec_emis[i][0:12,:,:,:] #dimension need to be matched with the variable defination
f_chem.close()
os.rename(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
else:
f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1],'c',format='nc')
f_chem.create_dimension('Time',None)
f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
f_chem.create_dimension('DateStrLen',19)
f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
for i,time in enumerate([time_inp+'_00:00:00',time_inp+'_01:00:00',time_inp+'_02:00:00',time_inp+'_03:00:00',time_inp+'_04:00:00',
time_inp+'_05:00:00',time_inp+'_06:00:00',time_inp+'_07:00:00',time_inp+'_08:00:00',time_inp+'_09:00:00',time_inp+'_10:00:00',
time_inp+'_11:00:00',]):
f_chem.variables['Times'][i]=list(time) #split the string to char
for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
f_chem.variables[LL][:]=ll
radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]
for gas in radm_gas:
f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[gas].FieldType = np.int16(104)
f_chem.variables[gas].MemoryOrder = 'XYZ'
f_chem.variables[gas].description = 'EMISSIONS'
f_chem.variables[gas].units = 'mol km^-2 hr^-1'
f_chem.variables[gas].stagger = 'Z'
#f_chem.variables[gas].ordinates = 'XLONG XLAT'
for aerosol in radm_aerosol:
f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[aerosol].FieldType = np.int16(104)
f_chem.variables[aerosol].MemoryOrder = 'XYZ'
f_chem.variables[aerosol].description = 'EMISSIONS'
f_chem.variables[aerosol].units = 'ug/m3 m/s'
f_chem.variables[aerosol].stagger = 'Z'
#f_chem.variables[aerosol].ordinates = 'XLONG XLAT'
radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
'E_SO4J','E_NO3I','E_NO3J',]
for i,spec in enumerate(radm_spec):
f_chem.variables[spec][:] = wrf_spec_emis[i][0:12,:,:,:] #dimension need to be matched with the variable defination
f_chem.close()
os.rename(ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_00z_'+ent_inp.get().split('_')[-1])
#generate wrfchemi_12z_d01 anthropogenic emission data for wrf-chem model run:
if os.path.exists(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]):
os.remove(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1],'c',format='nc')
f_chem.create_dimension('Time',None)
f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
f_chem.create_dimension('DateStrLen',19)
f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
for i,time in enumerate([time_inp+'_12:00:00',time_inp+'_13:00:00',time_inp+'_14:00:00',time_inp+'_15:00:00',time_inp+'_16:00:00',
time_inp+'_17:00:00',time_inp+'_18:00:00',time_inp+'_19:00:00',time_inp+'_20:00:00',time_inp+'_21:00:00',time_inp+'_22:00:00',
time_inp+'_23:00:00',]):
f_chem.variables['Times'][i]=list(time)
for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
f_chem.variables[LL][:]=ll
radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]
for gas in radm_gas:
f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[gas].FieldType = np.int16(104)
f_chem.variables[gas].MemoryOrder = 'XYZ'
f_chem.variables[gas].description = 'EMISSIONS'
f_chem.variables[gas].units = 'mol km^-2 hr^-1'
f_chem.variables[gas].stagger = 'Z'
#f_chem.variables[gas].ordinates = 'XLONG XLAT'
for aerosol in radm_aerosol:
f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[aerosol].FieldType = np.int16(104)
f_chem.variables[aerosol].MemoryOrder = 'XYZ'
f_chem.variables[aerosol].description = 'EMISSIONS'
f_chem.variables[aerosol].units = 'ug/m3 m/s'
f_chem.variables[aerosol].stagger = 'Z'
#f_chem.variables[aerosol].ordinates = 'XLONG XLAT'
radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
'E_SO4J','E_NO3I','E_NO3J',]
for i,spec in enumerate(radm_spec):
f_chem.variables[spec][:] = wrf_spec_emis[i][12:24,:,:,:] #dimension need to be matched with the variable defination
f_chem.close()
os.rename(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
else:
f_chem=Nio.open_file(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1],'c',format='nc')
f_chem.create_dimension('Time',None)
f_chem.create_dimension('emissions_zdim',wrf_spec_emis[0].shape[1])
f_chem.create_dimension('south_north',wrf_spec_emis[0].shape[2])
f_chem.create_dimension('west_east',wrf_spec_emis[0].shape[3])
f_chem.create_dimension('DateStrLen',19)
f_chem.create_variable('Times','S1',('Time','DateStrLen'),)
for i,time in enumerate([time_inp+'_12:00:00',time_inp+'_13:00:00',time_inp+'_14:00:00',time_inp+'_15:00:00',time_inp+'_16:00:00',
time_inp+'_17:00:00',time_inp+'_18:00:00',time_inp+'_19:00:00',time_inp+'_20:00:00',time_inp+'_21:00:00',time_inp+'_22:00:00',
time_inp+'_23:00:00',]):
f_chem.variables['Times'][i]=list(time)
for ll, LL in zip([lon_inp, lat_inp],['XLONG', 'XLAT']):
f_chem.create_variable(LL, 'f', ('south_north', 'west_east',),)
f_chem.variables[LL][:]=ll
radm_gas=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL',]
radm_aerosol=['E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I','E_SO4J','E_NO3I','E_NO3J',]
for gas in radm_gas:
f_chem.create_variable(gas,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[gas].FieldType = np.int16(104)
f_chem.variables[gas].MemoryOrder = 'XYZ'
f_chem.variables[gas].description = 'EMISSIONS'
f_chem.variables[gas].units = 'mol km^-2 hr^-1'
f_chem.variables[gas].stagger = 'Z'
#f_chem.variables[gas].ordinates = 'XLONG XLAT'
for aerosol in radm_aerosol:
f_chem.create_variable(aerosol,'f',('Time','emissions_zdim','south_north','west_east',))
f_chem.variables[aerosol].FieldType = np.int16(104)
f_chem.variables[aerosol].MemoryOrder = 'XYZ'
f_chem.variables[aerosol].description = 'EMISSIONS'
f_chem.variables[aerosol].units = 'ug/m3 m/s'
f_chem.variables[aerosol].stagger = 'Z'
#f_chem.variables[aerosol].ordinates = 'XLONG XLAT'
radm_spec=['E_CO','E_NH3','E_NO','E_NO2','E_SO2','E_ALD','E_CSL','E_ETH','E_HC3','E_HC5','E_HC8','E_HCHO','E_ISO','E_KET',
'E_OL2','E_OLI','E_OLT','E_ORA2','E_TOL','E_XYL','E_ECI','E_ECJ','E_ORGI','E_ORGJ','E_PM25I','E_PM25J','E_PM_10','E_SO4I',
'E_SO4J','E_NO3I','E_NO3J',]
for i,spec in enumerate(radm_spec):
f_chem.variables[spec][:] = wrf_spec_emis[i][12:24,:,:,:] #dimension need to be matched with the variable defination
f_chem.close()
os.rename(ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1]+'.nc', ent_dir.get()+'/merged/'+'wrfchemi_12z_'+ent_inp.get().split('_')[-1])
btn = tk.Button(root, text='运行', command=itp_dis, width=15)
btn.grid(row=15, column=3)
tk.mainloop()
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