'2003-03-22 00:00:00', '2003-03-22 04:00:00', freq='10min')
spath = '/home/guod/Documents/work/fig/density_cell/'\
'why_no_low_density_cell_at_high_latitude/lat_alt/'
outpdf_vert_wind = PdfFileMerger()
outpdf_rho_diff = PdfFileMerger()
outpdf_divrhov_rho_diff = PdfFileMerger()
outpdf_vert_divv_diff = PdfFileMerger()
outpdf_hozt_divv_diff = PdfFileMerger()
outpdf_vert_vgradrho_diff = PdfFileMerger()
outpdf_hozt_vgradrho_diff = PdfFileMerger()
for t in trange:
tstring = t.strftime('%H%M')
filename = glob.glob(
'/media/guod/wd2t/simulation_output/momentum_analysis/run_shrink_iondrift_4_c1'\
'/data/3DALL_t030322_%s*.bin' % tstring)[0]
g1a = gitm.GitmBin(filename)
filename = glob.glob(
'/media/guod/wd2t/simulation_output/momentum_analysis/run_no_shrink_iondrift_4_1'\
'/data/3DALL_t030322_%s*.bin' % tstring)[0]
g2a = gitm.GitmBin(filename)
# plot_vertical_wind(show=False, save=True)
# outpdf_vert_wind.append(PdfFileReader(open(spath+'02_vertical_wind_diff_%s.pdf' % tstring, 'rb')))
# plot_rho_diff(show=False, save=True)
# outpdf_rho_diff.append(PdfFileReader(open(spath+'01_rho_diff_%s.pdf' % tstring, 'rb')))
# plot_divrhov_rho_diff(show=False, save=True)
# outpdf_divrhov_rho_diff.append(PdfFileReader(open(spath+'03_divrhov_rho_diff_%s.pdf' % tstring, 'rb')))
# plot_vert_divv_diff(show=False, save=True)
# outpdf_vert_divv_diff.append(PdfFileReader(open(spath+'04_vert_divv_diff%s.pdf' % tstring, 'rb')))
# plot_hozt_divv_diff(show=False, save=True)
# outpdf_hozt_divv_diff.append(PdfFileReader(open(spath+'05_hozt_divv_diff%s.pdf' % tstring, 'rb')))
plot_vert_vgradrho_rho_diff(show=False, save=True)
import gitm
import gitm_gradient as gg
import gitm_divergence as gd
import gitm_3D_const_alt as g3ca
import gitm_create_coordinate as gcc
import cartopy.crs as ccrs
import numpy as np
import matplotlib.pyplot as plt
Re = 6371*1000
RR = Re+400000
g = gitm.GitmBin('/home/guod/big/raid4/guod/run_imfby/run2c/data/'
'3DALL_t100323_013000.bin', varlist=[
'Rho', 'V!Dn!N (north)', 'V!Dn!N (east)', 'V!Dn!N (up)'])
gg.calc_gradient(g, 'Rho', 'gradn', component='north')
gg.calc_gradient(g, 'Rho', 'grade', component='east')
gg.calc_gradient(g, 'Rho', 'gradr', component='radial')
gd.calc_divergence(g, neuion='neutral', name='divergence')
lon0, lat0, ewind0 = g3ca.contour_data('V!Dn!N (east)', g, alt=400)
lon0, lat0, nwind0 = g3ca.contour_data('V!Dn!N (north)', g, alt=400)
lon0, lat0, uwind0 = g3ca.contour_data('V!Dn!N (up)', g, alt=400)
ewind0 = ewind0 + ((2*np.pi)/(24*3600))*RR+np.cos(lat0*np.pi/180)
lon0, lat0, gradn0 = g3ca.contour_data('gradn', g, alt=400)
lon0, lat0, grade0 = g3ca.contour_data('grade', g, alt=400)
lon0, lat0, gradr0 = g3ca.contour_data('gradr', g, alt=400)
lon0, lat0, rho0 = g3ca.contour_data('Rho', g, alt=400)
lon0, lat0, div0 = g3ca.contour_data('divergence', g, alt=400)
hadvect = ewind0 * grade0 + nwind0 * gradn0
def animate_vert_divv(i):
g1 = gitm.GitmBin(fn1[i])
g2 = gitm.GitmBin(fn2[i])
alt_ind = np.argmin(
np.abs(g1['Altitude'][0, 0, 2:-2] / 1000 - which_alt)) + 2
# create axis
ax = list(range(2))
projection = ax.copy()
for ins in range(2):
nlat, slat = [90, 40] if ins == 0 else [-40, -90]
ax[ins], projection[ins] = gcc.create_map(
1,
2,
1 + ins,
'polar',
nlat=nlat,
slat=slat,
dlat=10,
centrallon=g3ca.calculate_centrallon(g1, 'polar', useLT=True),
coastlines=False)
alt1 = np.array(g1['Altitude'])
uwind1 = np.array(g1['V!Dn!N (up)'])
divv1 = cr.calc_div_vert(alt1, uwind1)
alt2 = np.array(g2['Altitude'])
uwind2 = np.array(g2['V!Dn!N (up)'])
divv2 = cr.calc_div_vert(alt2, uwind2)
g1['divv'] = divv1 - divv2
lon0, lat0, divv = g3ca.contour_data('divv', g1, alt=which_alt)
hc = ax[0].contourf(lon0,
lat0,
divv,
np.linspace(-1, 1, 21) * 1e-4,
transform=ccrs.PlateCarree(),
cmap='seismic',
extend='both')
ax[0].set_title(g1['time'].strftime('%d-%b-%y %H:%M') + ' UT', y=1.05)
hc = ax[1].contourf(lon0,
lat0,
divv,
np.linspace(-1, 1, 21) * 1e-4,
transform=ccrs.PlateCarree(),
cmap='seismic',
extend='both')
ax[1].set_title(g1['time'].strftime('%d-%b-%y %H:%M') + ' UT', y=1.05)
# low density center
lon3, lat3, zdata3 = g3ca.contour_data('Rho', g1, alt=which_alt)
lon4, lat4, zdata4 = g3ca.contour_data('Rho', g2, alt=which_alt)
diffrho = 100 * (zdata4 - zdata3) / zdata3
hc = [
ax[k].contour(lon0,
lat0,
diffrho, [-10],
transform=ccrs.PlateCarree(),
colors='g',
linestyles='-') for k in [0, 1]
]
# wind difference
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(g1,
'neutral',
alt=which_alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2,
'neutral',
alt=which_alt)
lon0, lat0, ewind, nwind = (lon1.copy(), lat1.copy(), ewind2 - ewind1,
nwind2 - nwind1)
for ins in [0, 1]:
lon0t, lat0t, ewindt, nwindt = g3ca.convert_vector(
lon0,
lat0,
ewind,
nwind,
plot_type='polar',
projection=projection[ins])
hq = ax[ins].quiver(lon0t,
lat0t,
ewindt,
nwindt,
scale=1500,
scale_units='inches',
color='k',
regrid_shape=20)
def animate_vgradrho_rho(i):
g1 = gitm.GitmBin(fn1[i])
g2 = gitm.GitmBin(fn2[i])
alt_ind = np.argmin(
np.abs(g1['Altitude'][0, 0, 2:-2] / 1000 - which_alt)) + 2
# create axis
ax = list(range(2))
projection = ax.copy()
for ins in range(2):
nlat, slat = [90, 40] if ins == 0 else [-40, -90]
ax[ins], projection[ins] = gcc.create_map(
1,
2,
1 + ins,
'polar',
nlat=nlat,
slat=slat,
dlat=10,
centrallon=g3ca.calculate_centrallon(g1, 'polar', useLT=True),
coastlines=False)
lon1 = np.array(g1['Longitude'])
lat1 = np.array(g1['Latitude'])
alt1 = np.array(g1['Altitude'])
nwind1 = np.array(g1['V!Dn!N (north)'])
RR = 6371 * 1000 + alt1
omega = (2 * np.pi) / (24 * 3600)
ewind1 = np.array(g1['V!Dn!N (east)']) + omega * RR * np.cos(lat1)
uwind1 = np.array(g1['V!Dn!N (up)'])
rho1 = np.array(g1['Rho'])
vgradrho1 = uwind1 * cr.calc_rusanov_alts_ausm(alt1, rho1) / rho1
lon2 = np.array(g2['Longitude'])
lat2 = np.array(g2['Latitude'])
alt2 = np.array(g2['Altitude'])
nwind2 = np.array(g2['V!Dn!N (north)'])
RR = 6371 * 1000 + alt2
omega = (2 * np.pi) / (24 * 3600)
ewind2 = np.array(g2['V!Dn!N (east)']) + omega * RR * np.cos(lat2)
uwind2 = np.array(g2['V!Dn!N (up)'])
rho2 = np.array(g2['Rho'])
vgradrho2 = uwind2 * cr.calc_rusanov_alts_ausm(alt2, rho2) / rho2
g1['vgradrho'] = vgradrho1 - vgradrho2
lon0, lat0, vgradrho = g3ca.contour_data('vgradrho', g1, alt=which_alt)
hc = ax[0].contourf(lon0,
lat0,
vgradrho,
np.linspace(-1, 1, 21) * 1e-4,
transform=ccrs.PlateCarree(),
cmap='seismic',
extend='both')
ax[0].set_title(g1['time'].strftime('%d-%b-%y %H:%M') + ' UT', y=1.05)
hc = ax[1].contourf(lon0,
lat0,
vgradrho,
np.linspace(-1, 1, 21) * 1e-4,
transform=ccrs.PlateCarree(),
cmap='seismic',
extend='both')
ax[1].set_title(g1['time'].strftime('%d-%b-%y %H:%M') + ' UT', y=1.05)
# low density center
lon3, lat3, zdata3 = g3ca.contour_data('Rho', g1, alt=which_alt)
lon4, lat4, zdata4 = g3ca.contour_data('Rho', g2, alt=which_alt)
diffrho = 100 * (zdata4 - zdata3) / zdata3
hc = [
ax[k].contour(lon0,
lat0,
diffrho, [-10],
transform=ccrs.PlateCarree(),
colors='g',
linestyles='-') for k in [0, 1]
]
# wind difference
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(g1,
'neutral',
alt=which_alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2,
'neutral',
alt=which_alt)
lon0, lat0, ewind, nwind = (lon1.copy(), lat1.copy(), ewind2 - ewind1,
nwind2 - nwind1)
for ins in [0, 1]:
lon0t, lat0t, ewindt, nwindt = g3ca.convert_vector(
lon0,
lat0,
ewind,
nwind,
plot_type='polar',
projection=projection[ins])
hq = ax[ins].quiver(lon0t,
lat0t,
ewindt,
nwindt,
scale=1500,
scale_units='inches',
color='k',
regrid_shape=20)
def animate_den_wind(i):
g1, g2 = [gitm.GitmBin(k[i]) for k in [fn1, fn2]]
# create axis
ax = [1, 2, 3, 4, 5, 6, 7, 8, 9]
projection = ax.copy()
for ialts in range(3):
for ird in range(2): # run2 or diff
centrallon = g3ca.calculate_centrallon(g1, 'polar', useLT=True)
ax[ialts * 2 + ird], projection[ialts * 2 +
ird] = gcc.create_map(
3,
2,
1 + ialts * 2 + ird,
'polar',
nlat=nlat,
slat=slat,
dlat=10,
centrallon=centrallon,
coastlines=False)
ax[ialts * 2 + ird].scatter(qlon,
qlat,
color='k',
transform=ccrs.PlateCarree())
ax[0].set_title(g1['time'].strftime('%d-%b-%y %H:%M') + ' UT', y=1.05)
ax[1].set_title(g1['time'].strftime('%d-%b-%y %H:%M') + ' UT', y=1.05)
#ax[2].set_title(g1['time'].strftime('%d-%b-%y %H:%M')+' UT', y=1.05)
# Density and diff
for ialt, alt in enumerate(alts):
lon1, lat1, zdata1 = g3ca.contour_data('Rho', g1, alt=alt)
lon2, lat2, zdata2 = g3ca.contour_data('Rho', g2, alt=alt)
diffzdata = 100 * (zdata2 - zdata1) / zdata1
hc = ax[ialt * 2].contourf(lon1,
lat1,
zdata2,
transform=ccrs.PlateCarree(),
levels=rholevels[ialt],
cmap='jet',
extend='both')
hc = ax[ialt * 2 + 1].contourf(lon2,
lat2,
diffzdata,
transform=ccrs.PlateCarree(),
levels=np.linspace(-20, 20, 21),
cmap='seismic',
extend='both')
# density change rate
# for ialt, alt in enumerate(alts):
# lon1 = np.array(g1['Longitude'])
# lat1 = np.array(g1['Latitude'])
# alt1 = np.array(g1['Altitude'])
# Re = 6371*1000 # Earth radius, unit: m
# RR = Re+alt1
# omega = 2*np.pi/(24*3600)
# rho1 = np.array(g1['Rho'])
# nwind1 = np.array(g1['V!Dn!N (north)'])
# ewind1 = np.array(g1['V!Dn!N (east)']) + omega*RR*np.cos(lat1)
# uwind1 = np.array(g1['V!Dn!N (up)'])
# div_rhov1 = \
# (cr.calc_div_hozt(lon1, lat1, alt1, rho1*nwind1, rho1*ewind1)\
# +cr.calc_div_vert(alt1, rho1*uwind1))/rho1
# lon2 = np.array(g2['Longitude'])
# lat2 = np.array(g2['Latitude'])
# alt2 = np.array(g2['Altitude'])
# Re = 6371*1000 # Earth radius, unit: m
# RR = Re+alt2
# omega = 2*np.pi/(24*3600)
# rho2 = np.array(g2['Rho'])
# nwind2 = np.array(g2['V!Dn!N (north)'])
# ewind2 = np.array(g2['V!Dn!N (east)']) + omega*RR*np.cos(lat2)
# uwind2 = np.array(g2['V!Dn!N (up)'])
# div_rhov2 = \
# (cr.calc_div_hozt(lon2, lat2, alt2, rho2*nwind2, rho2*ewind2)\
# +cr.calc_div_vert(alt2, rho2*uwind2))/rho2
# g1['divrhov_diff'] = div_rhov1-div_rhov2
# lon2, lat2, zdata2 = g3ca.contour_data('divrhov_diff', g1, alt=alt)
# hc = ax[ialt*3+2].contourf(
# lon2, lat2, zdata2, transform=ccrs.PlateCarree(),
# levels=np.linspace(-1,1,21)*1e-4, cmap='seismic', extend='both')
# wind
for ialt, alt in enumerate(alts):
lon1, lat1, ewind1, nwind1 = \
g3ca.vector_data(g1, 'neutral', alt=alt)
lon2, lat2, ewind2, nwind2 = \
g3ca.vector_data(g2, 'neutral', alt=alt)
lon0, lat0, ewind, nwind = (lon2.copy(), lat2.copy(),
ewind2.copy(), nwind2.copy())
lon0, lat0, ewind, nwind = g3ca.convert_vector(
lon0,
lat0,
ewind,
nwind,
plot_type='polar',
projection=projection[ialt * 2])
hq = ax[ialt * 2].quiver(lon0,
lat0,
ewind,
nwind,
scale=1500,
scale_units='inches',
color='k',
regrid_shape=20)
lon0, lat0, ewind, nwind = (lon1.copy(), lat1.copy(),
ewind2 - ewind1, nwind2 - nwind1)
lon0, lat0, ewind, nwind = g3ca.convert_vector(
lon0,
lat0,
ewind,
nwind,
plot_type='polar',
projection=projection[ialt * 2 + 1])
hq = ax[ialt * 2 + 1].quiver(lon0,
lat0,
ewind,
nwind,
scale=1500,
scale_units='inches',
color='k',
regrid_shape=20)
return
def animate_vert_wind(i):
g1, g2 = [gitm.GitmBin(k[i]) for k in [fn1, fn2]]
# create axis
ax = list(range(6))
projection = ax.copy()
for ins in range(2):
nlat, slat = [90, 40] if ins == 0 else [-40, -90]
for irun in range(3):
ax[ins +
irun * 2], projection[ins + irun * 2] = gcc.create_map(
3,
2,
1 + ins + irun * 2,
'polar',
nlat=nlat,
slat=slat,
dlat=10,
centrallon=g3ca.calculate_centrallon(g1,
'polar',
useLT=True),
coastlines=False)
# vertical wind
lon1, lat1, zdata1 = g3ca.contour_data('V!Dn!N (up)',
g1,
alt=which_alt)
lon2, lat2, zdata2 = g3ca.contour_data('V!Dn!N (up)',
g2,
alt=which_alt)
hc = [
ax[k].contourf(
lon1,
lat1,
zdata1,
21,
transform=ccrs.PlateCarree(),
levels=np.linspace(-20, 20, 21),
#levels=np.linspace(15e-13, 25e-13, 21),
cmap='seismic',
extend='both') for k in [0, 1]
]
ax[0].set_title(g1['time'].strftime('%d-%b-%y %H:%M') + ' UT', y=1.05)
ax[1].set_title(g1['time'].strftime('%d-%b-%y %H:%M') + ' UT', y=1.05)
hc = [
ax[k].contourf(lon2,
lat2,
zdata2,
21,
transform=ccrs.PlateCarree(),
levels=np.linspace(-20, 20, 21),
cmap='seismic',
extend='both') for k in [2, 3]
]
diffzdata = zdata2 - zdata1
hc = [
ax[k].contourf(lon2,
lat2,
diffzdata,
21,
transform=ccrs.PlateCarree(),
levels=np.linspace(-20, 20, 21),
cmap='seismic',
extend='both') for k in [4, 5]
]
# low density center
lon3, lat3, zdata3 = g3ca.contour_data('Rho', g1, alt=which_alt)
lon4, lat4, zdata4 = g3ca.contour_data('Rho', g2, alt=which_alt)
diffrho = 100 * (zdata4 - zdata3) / zdata3
hc = [
ax[k].contour(lon2,
lat2,
diffrho, [-10],
transform=ccrs.PlateCarree(),
colors='g',
linestyles='-') for k in [4, 5]
]
# wind
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(g1,
'neutral',
alt=which_alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2,
'neutral',
alt=which_alt)
for iax in range(6):
if iax == 0 or iax == 1:
lon0, lat0, ewind, nwind = (lon1.copy(), lat1.copy(),
ewind1.copy(), nwind1.copy())
lon0, lat0, ewind, nwind = g3ca.convert_vector(
lon0,
lat0,
ewind,
nwind,
plot_type='polar',
projection=projection[iax])
elif iax == 2 or iax == 3:
lon0, lat0, ewind, nwind = (lon2.copy(), lat2.copy(),
ewind2.copy(), nwind2.copy())
lon0, lat0, ewind, nwind = g3ca.convert_vector(
lon0,
lat0,
ewind,
nwind,
plot_type='polar',
projection=projection[iax])
elif iax == 4 or iax == 5:
lon0, lat0, ewind, nwind = (lon1.copy(), lat1.copy(),
ewind2 - ewind1, nwind2 - nwind1)
lon0, lat0, ewind, nwind = g3ca.convert_vector(
lon0,
lat0,
ewind,
nwind,
plot_type='polar',
projection=projection[iax])
hq = ax[iax].quiver(lon0,
lat0,
ewind,
nwind,
scale=1500,
scale_units='inches',
color='k',
regrid_shape=20)
# ax.quiverkey(hq, 0.93, 0, 1000, '1000 m/s')
# hc = plt.colorbar(hc, ticks=np.arange(3, 7)*1e-12)
# hc.set_label(r'$\rho$ (kg/m$^3$)')
# ax[iax].scatter(
# qlonn, qlatn, color='k', transform=ccrs.PlateCarree())
# ax[iax].scatter(
# qlons, qlats, color='k', transform=ccrs.PlateCarree())
return
import matplotlib.pyplot as plt
import gitm
import numpy as np
import seaborn as sns
import calc_rusanov as cr
sns.set('paper', 'whitegrid')
plt.close('all')
plt.figure(figsize=(6.5, 7.2))
fn1 = '/home/guod/simulation_output/momentum_analysis/'\
'run_shrink_iondrift_4_c1/data/3DALL_t030322_060000.bin'
fn2 = '/home/guod/simulation_output/momentum_analysis/'\
'run_no_shrink_iondrift_4_1/data/3DALL_t030322_060000.bin'
g1 = gitm.GitmBin(fn1)
g2 = gitm.GitmBin(fn2)
g1['diffrho'] = 100 * (g2['Rho'] - g1['Rho']) / g1['Rho']
color = ['b', 'r']
for ig, g in enumerate([g1, g2]):
lons, lats, alts = (g[k] for k in ['Longitude', 'Latitude', 'Altitude'])
rho = g['Rho']
nlat, slat = -30, -90
for i, alt in enumerate([130, 300, 600]):
ax1 = plt.subplot(3, 2, i * 2 + 1)
ax2 = plt.subplot(3, 2, i * 2 + 2)
lt = 6
ilt = np.argmin(np.abs(g['LT'][2:-2, 0, 0] - lt)) + 2
ialt = np.argmin(np.abs(alts[0, 0, 2:-2] / 1000 - alt)) + 2
ilat = (lats[0, :, 0] / np.pi * 180 <
nlat) & (lats[0, :, 0] / np.pi * 180 > slat)
ax1.plot(180 + lats[ilt, ilat, ialt] / np.pi * 180,
gdata[name] = dmarray(vort,
attrs={
'units':
'm/s^2',
'scale':
'linear',
'name':
neuion + ' velocity ' + component + ' vorticity'
})
return
#END
if __name__ == '__main__':
fn = '/home/guod/big/raid4/guod/run_imfby/run2c/data/3DALL_t100323_042000.bin'
gdata = gitm.GitmBin(fn)
calc_vorticity(gdata, 'neu', name='nvorticity', component='radial')
alt = 200
nlat = 90
slat = 50
centrallon = g3ca.calculate_centrallon(gdata, 'polar', useLT=True)
ax, projection = gcc.create_map(1,
1,
1,
plot_type='polar',
nlat=nlat,
slat=slat,
centrallon=centrallon,
coastlines=False,
dlat=10)
divvar = calc_rusanov_alts_ausm(alts, var)\
+ 2*var/rdist
return divvar
if __name__ == '__main__':
import gitm
import numpy as np
import gitm_create_coordinate as gcc
from cartopy.util import add_cyclic_point
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import gitm_divergence_new as gd
alt = 400
g1 = gitm.GitmBin(
'/home/guod/simulation_output/momentum_analysis/'
'run_shrink_iondrift_3_continue/data/3DALL_t030322_013000.bin')
alt_ind = np.argmin(np.abs(g1['Altitude'][0, 0, :] - alt * 1000))
lons, lats, alts = (g1[k] for k in ['Longitude', 'Latitude', 'Altitude'])
veln = g1['V!Dn!N (north)']
vele = g1['V!Dn!N (east)'] + (2 * np.pi) / (24 * 3600) * (
6371 * 1000 + alts) * np.cos(lats)
velu = g1['V!Dn!N (up)']
rho = g1['Rho']
zdata1 = calc_div_vert(alts, rho * velu) + calc_div_hozt(
lons, lats, alts, rho * veln, rho * vele)
dglat = np.array(g1['dLat'][0, 2:-2, 0])
dglon = np.array(g1['dLon'][2:-2, 0, 0])
zdata1, dglon = add_cyclic_point(zdata1[2:-2, 2:-2, alt_ind].T,
coord=dglon,