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plot_aqm_smoke_dust.py
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###################################################################### CHJ #####
## Name : plot_rrfscmaq_emission.py
## Language : Python 3.7
## Usage : Plot an input file for smoke and dust
## Input files : GBBEPx_CRES.emissions.nc
## NOAA/EPIC
## History ===============================
## V000: 2024/09/09: Chan-Hoo Jeon : Preliminary version
###################################################################### CHJ #####
import os, sys
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import numpy as np
from netCDF4 import Dataset
from scipy.io import netcdf
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import cartopy
from mpl_toolkits.axes_grid1 import make_axes_locatable
# HPC machine ('hera','orion')
machine='hera'
print(' You are on', machine)
#### Machine-specific input data ==================================== CHJ =====
# cartopy.config: Natural Earth data for background
# out_fig_dir: directory where the output files are created
# mfdt_kwargs: mfdataset argument
if machine=='hera':
cartopy.config['data_dir']='/scratch2/NCEPDEV/fv3-cam/Chan-hoo.Jeon/tools/NaturalEarth'
out_fig_dir="/scratch2/NCEPDEV/fv3-cam/Chan-hoo.Jeon/tools/fv3sar_pre_plot/Fig/"
mfdt_kwargs={'parallel':False}
elif machine=='orion':
cartopy.config['data_dir']='/home/chjeon/tools/NaturalEarth'
out_fig_dir="/work/noaa/fv3-cam/chjeon/tools/Fig/"
mfdt_kwargs={'parallel':False,'combine':'by_coords'}
else:
sys.exit('ERROR: Required input data are NOT set !!!')
plt.switch_backend('agg')
# Case-dependent input =============================================== CHJ =====
# Domain name
domain_nm='RRFS_CONUS_3km'
dnm_in="/scratch2/NCEPDEV/naqfc/Chan-hoo.Jeon/srw_aqm_main/nco_dirs/test_smoke_dust/tmp/run_fcst_mem000.2019072206.66531816/INPUT/"
#dnm_in="/scratch1/BMC/acomp/Johana/rrfs-sd_v1/test_workflow_6hrs/stmp/2019072206/fcst_fv3lam/INPUT/"
fnm_input='SMOKE_RRFS_data.nc'
# Variables
vars_data=["frp_avg_hr","ebb_smoke_hr"]
#vars_data=["frp_avg_hr"]
# Select time step
l_time=10
# basic forms of title and file name
out_title_base='Smoke/Dust::'+domain_nm+'::'
out_fname_base='smoke_dust_'+domain_nm+'_'
# Resolution of background natural earth data ('10m' or '50m' or '110m')
back_res='50m'
# Main part (will be called at the end) ======================= CHJ =====
def main():
# ============================================================= CHJ =====
global ds,lon_o,lat_o
global extent,c_lon,c_lat
print(' ===== Input data ========================================')
# open the data file
fname=os.path.join(dnm_in,fnm_input)
# Check the variables in netcdf file
try: ds=Dataset(fname,'r')
except: raise Exception('Could NOT find the file',fname)
print(ds)
lon_o=ds.variables['geolon'][:]
lat_o=ds.variables['geolat'][:]
# =============================================================================
# lon_max=np.max(lon)
# Longitude 0:360 => -180:180
# if lon_max>180:
# lon=(lon+180)%360-180
# Highest and lowest longitudes and latitudes for plot extent
lon_min=np.min(lon_o)
lon_max=np.max(lon_o)
lat_min=np.min(lat_o)
lat_max=np.max(lat_o)
print(' lon_min=',lon_min,', lon_max=',lon_max)
print(' lat_min=',lat_min,', lat_max=',lat_max)
# Plot extent
esp=1
extent=[lon_min-esp,lon_max+esp,lat_min-esp,lat_max+esp]
c_lon=np.mean(extent[:2])
c_lat=np.mean(extent[2:])
# Variables
for svar in vars_data:
data_plot(svar)
# ===== plot ================================================== CHJ =====
def data_plot(svar):
# ============================================================= CHJ =====
print(' ===== '+svar+' ===== data ===============================')
# Extract data array
sfld=ds.variables[svar][:]
ndim_svar=sfld.ndim
if ndim_svar==2:
(nys,nxs)=sfld.shape
print(' 2D: nys=',nys,' nxs=',nxs)
sfld2d=sfld
elif ndim_svar==3:
(nts,nys,nxs)=sfld.shape
print(' time+2D: nts=',nts,' nys=',nys,' nxs=',nxs)
print(' time level=',l_time)
sfld2d=np.squeeze(sfld[l_time-1,:,:])
print(sfld.shape)
print(sfld2d.shape)
# Check if dimensions of grid and vars are matched
if sfld2d.shape==lon_o.shape:
print('Data and grid are matched !!!')
else:
sys.exit('ERROR: Size of data does NOT match with that of grid !!!')
# extract non-zero cells
lon_pts=lon_o[sfld2d>0]
lat_pts=lat_o[sfld2d>0]
sfld_pts=sfld2d[sfld2d>0]
print(lon_pts.shape)
print(lat_pts.shape)
print(sfld_pts.shape)
out_title_fld=out_title_base+svar
out_fname=out_fname_base+svar
nm_svar=svar
cs_cmap='gist_ncar_r'
lb_ext='neither'
tick_ln=1.5
tick_wd=0.45
tlb_sz=3
scat_sz=2
cmap_range='fixed'
cmap_fix_min=0.0
cmap_fix_max=100.0
# Max and Min of the field
fmax=np.max(sfld2d)
fmin=np.min(sfld2d)
print(' fld_max=',fmax)
print(' flx_min=',fmin)
# Make the colormap range symmetry
print(' cmap range=',cmap_range)
if cmap_range=='symmetry':
tmp_cmp=max(abs(fmax),abs(fmin))
cs_min=round(-tmp_cmp,n_rnd)
cs_max=round(tmp_cmp,n_rnd)
elif cmap_range=='round':
cs_min=round(fmin,n_rnd)
cs_max=round(fmax,n_rnd)
elif cmap_range=='real':
cs_min=fmin
cs_max=fmax
elif cmap_range=='fixed':
cs_min=cmap_fix_min
cs_max=cmap_fix_max
else:
sys.exit('ERROR: wrong colormap-range flag !!!')
print(' cs_max=',cs_max)
print(' cs_min=',cs_min)
# Plot field
if domain_nm[:7]=='RRFS_NA':
fig,ax=plt.subplots(1,1,subplot_kw=dict(projection=ccrs.Orthographic(
central_longitude=-107,central_latitude=53)))
else:
fig,ax=plt.subplots(1,1,subplot_kw=dict(projection=ccrs.Robinson(c_lon)))
ax.set_extent(extent, ccrs.PlateCarree())
back_plot(ax)
ax.set_title(out_title_fld,fontsize=9)
map_type='scatter'
if map_type == 'mesh':
cs=ax.pcolormesh(lon_o,lat_o,sfld2d,cmap=cs_cmap,rasterized=True,
vmin=cs_min,vmax=cs_max,transform=ccrs.PlateCarree())
else:
cs=ax.scatter(lon_pts,lat_pts,transform=ccrs.PlateCarree(),c=sfld_pts,cmap=cs_cmap,
vmin=cs_min,vmax=cs_max,s=scat_sz)
divider=make_axes_locatable(ax)
ax_cb=divider.new_horizontal(size="3%",pad=0.1,axes_class=plt.Axes)
fig.add_axes(ax_cb)
cbar=plt.colorbar(cs,cax=ax_cb,extend=lb_ext)
cbar.ax.tick_params(labelsize=6)
cbar.set_label(nm_svar,fontsize=6)
# Output figure
ndpi=300
out_file(out_fname,ndpi)
# Background plot ========================================== CHJ =====
def back_plot(ax):
# ========================================================== CHJ =====
fline_wd=0.5 # line width
falpha=0.3 # transparency
# natural_earth
# land=cfeature.NaturalEarthFeature('physical','land',back_res,
# edgecolor='face',facecolor=cfeature.COLORS['land'],
# alpha=falpha)
lakes=cfeature.NaturalEarthFeature('physical','lakes',back_res,
edgecolor='blue',facecolor='none',
linewidth=fline_wd,alpha=falpha)
coastline=cfeature.NaturalEarthFeature('physical','coastline',
back_res,edgecolor='blue',facecolor='none',
linewidth=fline_wd,alpha=falpha)
states=cfeature.NaturalEarthFeature('cultural','admin_1_states_provinces',
back_res,edgecolor='black',facecolor='none',
linewidth=fline_wd,linestyle=':',alpha=falpha)
borders=cfeature.NaturalEarthFeature('cultural','admin_0_countries',
back_res,edgecolor='red',facecolor='none',
linewidth=fline_wd,alpha=falpha)
# ax.add_feature(land)
ax.add_feature(lakes)
ax.add_feature(states)
ax.add_feature(borders)
ax.add_feature(coastline)
# Output file ============================================= CHJ =====
def out_file(out_file,ndpi):
# ========================================================= CHJ =====
# Output figure
plt.savefig(out_fig_dir+out_file+'.png',dpi=ndpi,bbox_inches='tight')
plt.close('all')
# Main call ================================================ CHJ =====
if __name__=='__main__':
main()