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maps_tctracks.py
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maps_tctracks.py
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#!/usr/bin/env python
# coding: utf-8
# ### Notebook to plot TC tracks
#
# James Ruppert
# 11/27/22
from netCDF4 import Dataset
import numpy as np
import matplotlib
matplotlib.use('pdf')
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from matplotlib import ticker, cm
import cartopy
import subprocess
import sys
# #### Variable selection
storm = 'haiyan'
# storm = 'maria'
# Tests to read and compare
# itest = 'ctl'
# itest = 'ncrf'
if storm == 'haiyan':
tests = ['ctl','ncrf36h']
elif storm == 'maria':
# tests = ['ctl','ncrf36h']
tests = ['ctl','ncrf48h']
# How many members
nmem = 10 # number of ensemble members (1-5 have NCRF)
# nmem = 1
# Starting member to read
memb0=1
# TC tracking
ptrack='600' # tracking pressure level
var_track = 'rvor' # variable
# #### Directories
figdir = "/home/jamesrup/figures/tc/ens/tracks/"
# main = "/ourdisk/hpc/radclouds/auto_archive_notyet/tape_2copies/wrfenkf/"
main = "/ourdisk/hpc/radclouds/auto_archive_notyet/tape_2copies/tc_ens/"
nums=np.arange(memb0,nmem+memb0,1)
nums=nums.astype(str)
nustr = np.char.zfill(nums, 2)
memb_all=np.char.add('memb_',nustr)
##### Get dimensions
itest=tests[0]
datdir = main+storm+'/'+memb_all[0]+'/'+itest+'/'
varfil_main = Dataset(datdir+'post/d02/T.nc')
nz = varfil_main.dimensions['level'].size
nx1 = varfil_main.dimensions['lat'].size
nx2 = varfil_main.dimensions['lon'].size#-xmin-1
pres = varfil_main.variables['pres'][:] # hPa
varfil_main.close()
process = subprocess.Popen(['ls '+datdir+'/wrfout_d02_*'],shell=True,
stdout=subprocess.PIPE,universal_newlines=True)
output = process.stdout.readline()
wrffil = output.strip() #[3]
varfil_main = Dataset(wrffil)
lat = varfil_main.variables['XLAT'][:][0] # deg
lon = varfil_main.variables['XLONG'][:][0] # deg
varfil_main.close()
lon1d=lon[0,:]
lat1d=lat[:,0]
# Function to account for crossing of the Intl Date Line
def dateline_lon_shift(lon_in, reverse):
if reverse == 0:
lon_offset = np.zeros(lon_in.shape)
lon_offset[np.where(lon_in < 0)] += 360
else:
lon_offset = np.zeros(lon_in.shape)
lon_offset[np.where(lon_in > 180)] -= 360
# return lon_in + lon_offset
return lon_offset
# Account for crossing of Date Line
if storm == 'haiyan':
offset = 180
else:
offset = 0
lon_offset = dateline_lon_shift(lon, reverse=0)
lon_offset_plt = lon + lon_offset
lon_offset_plt -= offset
# Create figure with all tracks
# ### Plotting routines ##############################################
font = {'family' : 'sans-serif',
'weight' : 'normal',
'size' : 16}
matplotlib.rc('font', **font)
# select plotting area
plt_area=[lon1d[0], lon1d[-1], lat1d[0], lat1d[-1]] # W,E,S,N
# ### Combined plot ##############################################
# for ktest in range(2):
for ktest in range(1):
itest = tests[ktest]
# create figure
fig = plt.figure(figsize=(20,10))
proj = cartopy.crs.PlateCarree(central_longitude=offset)
# box_proj = ccrs.PlateCarree(central_longitude=0)
ax = fig.add_subplot(111,projection=proj)
# ax.set_title(ptrack + '-hPa RVor, Ens Memb '+str(imemb+1), fontsize=20)
ax.set_title(storm.capitalize()+', '+itest.capitalize()+' ('+ptrack + '-hPa AVor, 10Memb)', fontsize=20)
ax.set_prop_cycle(color=[
'#1f77b4', '#1f77b4', '#aec7e8', '#aec7e8', '#ff7f0e', '#ff7f0e', '#ffbb78', '#ffbb78', '#2ca02c', '#2ca02c', '#98df8a', '#98df8a',
'#d62728', '#d62728', '#ff9896', '#ff9896', '#9467bd', '#9467bd', '#c5b0d5', '#c5b0d5'])#,
# '#e377c2', '#f7b6d2', '#7f7f7f', '#c7c7c7', '#bcbd22', '#dbdb8d',
# '#17becf', '#9edae5'])#,
# marker=["s"]*20)
for imemb in range(nmem):
# for imemb in range(nmem-1):
print('Running imemb: ',memb_all[imemb])
datdir = main+storm+'/'+memb_all[imemb]+'/'+itest+'/'
track_file = datdir+'track_'+var_track+'_'+ptrack+'hPa.nc'
print(track_file)
# Read track
ncfile = Dataset(track_file)
clon = ncfile.variables['clon'][:] # deg
clat = ncfile.variables['clat'][:] # deg
ncfile.close()
nt = clon.shape[0]
clon_shift = clon
if storm == 'haiyan':
clon_offset = dateline_lon_shift(clon, reverse=0)
clon_shift += clon_offset
clon_shift -= offset
# storm track
plt.plot(clon_shift, clat, linewidth=2, label=nustr[imemb])
skip=24
itim=np.arange(0,nt,skip)
plt.plot(clon_shift[itim], clat[itim], "s")
# add map features
ax.add_feature(cartopy.feature.LAND,facecolor="lightgray") #land color
# ax.add_feature(cartopy.feature.OCEAN) #ocean color
ax.add_feature(cartopy.feature.COASTLINE)
# ax.add_feature(cartopy.feature.STATES)
ax.gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False,
xlocs=np.arange(140,190,5), ylocs=np.arange(-10,20,5))
ax.set_extent(plt_area)
plt.legend(loc="upper right")
# plt.show()
# plt.savefig(figdir+storm+'_track_'+var_track+'_'+ptrack+'_'+memb_all[imemb]+'.png',dpi=200, facecolor='white', \
plt.savefig(figdir+storm+'_'+itest+'_track_'+var_track+'_'+ptrack+'.png',dpi=200, facecolor='white', \
bbox_inches='tight', pad_inches=0.2)
plt.close()
# ### Single member plots ##############################################
# for imemb in range(nmem):
# fig = plt.figure(figsize=(20,10))
# ax = fig.add_subplot(111,projection=proj)
# ax.set_title(ptrack + '-hPa RVor, Ens Memb '+str(imemb+1), fontsize=20)
# print('Running imemb: ',memb_all[imemb])
# for ktest in range(2):
# itest = tests[ktest]
# datdir = main+storm+'/'+memb_all[imemb]+'/'+itest+'/'
# track_file = datdir+'track_'+var_track+'_'+ptrack+'hPa.nc'
# print(track_file)
# # Read track
# ncfile = Dataset(track_file)
# clon = ncfile.variables['clon'][:] # deg
# clat = ncfile.variables['clat'][:] # deg
# ncfile.close()
# nt = clon.shape[0]
# clon_shift = clon
# if storm == 'haiyan':
# clon_offset = dateline_lon_shift(clon, reverse=0)
# clon_shift += clon_offset
# clon_shift -= offset
# if (imemb == 0) & (ktest == 0):
# print(clon[35])
# print(clat[35])
# # storm track
# plt.plot(clon_shift, clat, linewidth=2, label=nustr[imemb])#, color='k')
# skip=24
# itim=np.arange(0,nt,skip)
# if (imemb == 0) & (ktest == 0): itim = 35
# plt.plot(clon_shift[itim], clat[itim], "s", color='r')
# if storm == 'haiyan':
# xloc=np.arange(130,185,5)
# # add map features
# ax.add_feature(cartopy.feature.LAND,facecolor="lightgray") #land color
# # ax.add_feature(cartopy.feature.OCEAN) #ocean color
# ax.add_feature(cartopy.feature.COASTLINE)
# # ax.add_feature(cartopy.feature.STATES)
# ax.gridlines(draw_labels=True, dms=True, xlocs=xloc, x_inline=False, y_inline=False)
# ax.set_extent(plt_area)
# # plt.show()
# plt.savefig(figdir+storm+'_track_'+var_track+'_'+ptrack+'_'+memb_all[imemb]+'.png',dpi=200, facecolor='white', \
# bbox_inches='tight', pad_inches=0.2)
# plt.close()