def plot_divrhov_rho(read=True):
if read:
divrhov = []
for fn1, fn2 in zip(fns1,fns2):
g1, g2 = gitm.read(fn1), gitm.read(fn2)
# density change (shrink)
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
# density change (no shrink)
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
div_rhov = div_rhov1 - div_rhov2
divrhov1 = []
for alt in alts:
ialt = np.argmin(np.abs(g1['Altitude'][0, 0, 2:-2]-alt*1000))+2
divrhov2 = []
for lt in lts:
ilt = np.argmin(np.abs(g1['LT'][2:-2, 0, 0]-lt))+2
divrhov2.append(
np.array(div_rhov[ilt, 2:-2, ialt]).reshape(1,1,1,-1))
divrhov2 = np.concatenate(divrhov2, axis=2)
divrhov1.append(divrhov2)
divrhov1 = np.concatenate(divrhov1, axis=1)
divrhov.append(divrhov1)
divrhov = np.concatenate(divrhov, axis=0)
lat = g1['dLat'][0, 2:-2, 0]
np.savez('/home/guod/tmp/divrhov_rho', divrhov=divrhov, lat=lat)
ldf = np.load('/home/guod/tmp/divrhov_rho.npz')
divrhov, lat = ldf['divrhov'], ldf['lat']
plt.close()
plt.contourf(
timeidx, lat, divrhov[:,3, 1, :].T, levels=np.linspace(-1,1,21)*1e-4,
cmap='seismic')
plt.ylim(-90, -40)
plt.show()
return
def plot_hozt_divv(read=True):
if read:
divv = []
for fn1, fn2 in zip(fns1,fns2):
g1, g2 = gitm.read(fn1), gitm.read(fn2)
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)
nwind1 = np.array(g1['V!Dn!N (north)'])
ewind1 = np.array(g1['V!Dn!N (east)']) + omega*RR*np.cos(lat1)
div_v1 = cr.calc_div_hozt(
g1['Longitude'], g1['Latitude'], g1['Altitude'],
nwind1, ewind1)
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)
nwind2 = np.array(g2['V!Dn!N (north)'])
ewind2 = np.array(g2['V!Dn!N (east)']) + omega*RR*np.cos(lat2)
div_v2 = cr.calc_div_hozt(
g2['Longitude'], g2['Latitude'], g2['Altitude'],
nwind2, ewind2)
div_v = div_v1 - div_v2
divv1 = []
for alt in alts:
ialt = np.argmin(np.abs(g1['Altitude'][0, 0, 2:-2]-alt*1000))+2
divv2 = []
for lt in lts:
ilt = np.argmin(np.abs(g1['LT'][2:-2, 0, 0]-lt))+2
divv2.append(
np.array(div_v[ilt, 2:-2, ialt]).reshape(1,1,1,-1))
divv2 = np.concatenate(divv2, axis=2)
divv1.append(divv2)
divv1 = np.concatenate(divv1, axis=1)
divv.append(divv1)
divv = np.concatenate(divv, axis=0)
lat = g1['dLat'][0, 2:-2, 0]
np.savez('/home/guod/tmp/hozt_divv', divv=divv, lat=lat)
ldf = np.load('/home/guod/tmp/hozt_divv.npz')
divv, lat = ldf['divv'], ldf['lat']
plt.close()
plt.contourf(
timeidx, lat, divv[:,3, 1, :].T, levels=np.linspace(-1,1,21)*1e-4,
cmap='seismic')
plt.ylim(-90, -40)
plt.show()
return
def plot_divrhov_rho_diff(show=True, save=False):
plt.close('all')
plt.figure()
# density change (shrink)
lon1 = np.array(g1a['Longitude'])
lat1 = np.array(g1a['Latitude'])
alt1 = np.array(g1a['Altitude'])
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt1
omega = 2*np.pi/(24*3600)
rho1 = np.array(g1a['Rho'])
nwind1 = np.array(g1a['V!Dn!N (north)'])
ewind1 = np.array(g1a['V!Dn!N (east)']) + omega*RR*np.cos(lat1)
uwind1 = np.array(g1a['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
# density change (no shrink)
lon2 = np.array(g2a['Longitude'])
lat2 = np.array(g2a['Latitude'])
alt2 = np.array(g2a['Altitude'])
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt2
omega = 2*np.pi/(24*3600)
rho2 = np.array(g2a['Rho'])
nwind2 = np.array(g2a['V!Dn!N (north)'])
ewind2 = np.array(g2a['V!Dn!N (east)']) + omega*RR*np.cos(lat2)
uwind2 = np.array(g2a['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
ilt = np.argmin(np.abs(g1a['LT'][2:-2, 0, 0]-whichlt))+2
divrhov1 = div_rhov1[ilt,2:-2,2:-2]
divrhov2 = div_rhov2[ilt,2:-2,2:-2]
ddivrhov = np.array(divrhov1-divrhov2).T
lat = np.array(g1a['dLat'][ilt, 2:-2, 2:-2]).T
alt = np.array(g1a['Altitude'][ilt, 2:-2, 2:-2]/1000).T
plt.contourf(lat, alt, ddivrhov, levels=np.linspace(-1, 1, 21)*1e-4,
cmap='seismic', extend='both')
plt.xlim(-90, -40)
plt.xlabel('Latitude')
plt.ylabel('Altitude')
plt.text(0.5, 0.95, 'Time: '+tstring, fontsize=15,
horizontalalignment='center', transform=plt.gcf().transFigure)
if show:
plt.show()
if save:
plt.savefig(spath+'03_divrhov_rho_diff_%s.pdf' % tstring)
return
def plot_hozt_divv_diff(show=True, save=False):
plt.close('all')
plt.figure()
lat1 = np.array(g1a['Latitude'])
alt1 = np.array(g1a['Altitude'])
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt1
omega = 2*np.pi/(24*3600)
nwind1 = np.array(g1a['V!Dn!N (north)'])
ewind1 = np.array(g1a['V!Dn!N (east)'])# + omega*RR*np.cos(lat1)
divv1 = cr.calc_div_hozt(
g1a['Longitude'], g1a['Latitude'], g1a['Altitude'], nwind1, ewind1)
lat2 = np.array(g2a['Latitude'])
alt2 = np.array(g2a['Altitude'])
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt2
omega = 2*np.pi/(24*3600)
nwind2 = np.array(g2a['V!Dn!N (north)'])
ewind2 = np.array(g2a['V!Dn!N (east)']) #+ omega*RR*np.cos(lat2)
divv2 = cr.calc_div_hozt(
g2a['Longitude'], g2a['Latitude'], g2a['Altitude'], nwind2, ewind2)
ilt = np.argmin(np.abs(g1a['LT'][2:-2, 0, 0]-whichlt))+2
divv1 = divv1[ilt,2:-2,2:-2]
divv2 = divv2[ilt,2:-2,2:-2]
ddivv = np.array(divv1-divv2).T
lat = np.array(g1a['dLat'][ilt, 2:-2, 2:-2]).T
alt = np.array(g1a['Altitude'][ilt, 2:-2, 2:-2]/1000).T
plt.contourf(lat, alt, ddivv, levels=np.linspace(-1, 1, 21)*1e-4,
cmap='seismic', extend='both')
plt.xlim(-90, -40)
plt.xlabel('Latitude')
plt.ylabel('Altitude')
plt.text(0.5, 0.95, 'Time: '+tstring, fontsize=15,
horizontalalignment='center', transform=plt.gcf().transFigure)
if show:
plt.show()
if save:
plt.savefig(spath+'05_hozt_divv_diff%s.pdf' % tstring)
return
gallfn = '/Users/guod/data/GITMOutput/run_shrink_notides_tmp/UA/data/3DALL_t030323_000004.bin'
gthmfn = '/Users/guod/data/GITMOutput/run_shrink_notides_tmp/UA/data/3DTHM_t030323_000004.bin'
gall = gitm.read(gallfn)
lontp = gall['Longitude']
lattp = gall['Latitude']
alttp = gall['Altitude']
Re = 6371 * 1000 # Earth radius, unit: m
RR = Re + alttp
omega = 2 * np.pi / (24 * 3600)
rhotp = gall['Rho']
nwindtp = gall['V!Dn!N (north)']
ewindtp = gall['V!Dn!N (east)'] + omega * RR * np.cos(lattp)
uwindtp = gall['V!Dn!N (up)']
gall['div_rhov'] = \
-(cr.calc_div_hozt(lontp, lattp, alttp, rhotp*nwindtp, rhotp*ewindtp)\
+cr.calc_div_vert(alttp, rhotp*uwindtp))/rhotp
gall['vert_divv'] = -cr.calc_div_vert(alttp, uwindtp)
gall['hozt_divv'] = -cr.calc_div_hozt(lontp, lattp, alttp, nwindtp, ewindtp)
gall['vert_vgradrho'] = -uwindtp * cr.calc_rusanov_alts_ausm(alttp,
rhotp) / rhotp
gall['hozt_vgradrho'] = \
-(nwindtp*cr.calc_rusanov_lats(lattp,alttp,rhotp)\
+ewindtp*cr.calc_rusanov_lons(lontp,lattp,alttp,rhotp))/rhotp
gp.calc_pressure(gall)
gthm = gitm.read(gthmfn)
gthm['total energy'] =\
gthm['EUV Heating'] + gthm['Conduction'] + \
gthm['Chemical Heating'] + gthm['Auroral Heating'] + \
gthm['Joule Heating'] - gthm['NO Cooling'] - gthm['O Cooling']
savepath = '/Users/guod/tmp/'
def animate_hozt_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)
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)'])
divv1 = cr.calc_div_hozt(lon1, lat1, alt1, nwind1, ewind1)
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)'])
divv2 = cr.calc_div_hozt(lon2, lat2, alt2, nwind2, ewind2)
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 plot_divrhov_rho_diff(show=True, save=True):
# density change (shrink)
lon1 = np.array(g1a['Longitude'])
lat1 = np.array(g1a['Latitude'])
alt1 = np.array(g1a['Altitude'])
Re = 6371 * 1000 # Earth radius, unit: m
RR = Re + alt1
omega = 2 * np.pi / (24 * 3600)
rho1 = np.array(g1a['Rho'])
nwind1 = np.array(g1a['V!Dn!N (north)'])
ewind1 = np.array(g1a['V!Dn!N (east)']) + omega * RR * np.cos(lat1)
uwind1 = np.array(g1a['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
# density change (no shrink)
lon2 = np.array(g2a['Longitude'])
lat2 = np.array(g2a['Latitude'])
alt2 = np.array(g2a['Altitude'])
Re = 6371 * 1000 # Earth radius, unit: m
RR = Re + alt2
omega = 2 * np.pi / (24 * 3600)
rho2 = np.array(g2a['Rho'])
nwind2 = np.array(g2a['V!Dn!N (north)'])
ewind2 = np.array(g2a['V!Dn!N (east)']) + omega * RR * np.cos(lat2)
uwind2 = np.array(g2a['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
g1a['divrhov_diff'] = div_rhov1 - div_rhov2
apex = Apex(date=2003)
qlat, qlon = apex.convert(-90, 0, source='apex', dest='geo', height=400)
plt.close('all')
plt.figure(figsize=(7.26, 9.25))
for ialt, alt in enumerate([130, 200, 300, 400, 500, 600]):
alt_ind = np.argmin(np.abs(g1a['Altitude'][0, 0, :] / 1000 - alt))
alt_str = '%6.2f' % (g1a['Altitude'][0, 0, alt_ind] / 1000)
ax, projection = gcc.create_map(3,
2,
ialt + 1,
'polar',
nlat=nlat,
slat=slat,
dlat=10,
centrallon=g3ca.calculate_centrallon(
g1a, 'polar', useLT=True),
coastlines=False)
lon0, lat0, zdata0 = g3ca.contour_data('divrhov_diff', g1a, alt=alt)
fp = (lat0[:, 0] > slat) & (lat0[:, 0] < nlat)
lon0, lat0, zdata0 = lon0[fp, :], lat0[fp, :], zdata0[fp, :]
hc = ax.contourf(lon0,
lat0,
zdata0,
np.linspace(-1, 1, 21) * 1e-4,
transform=ccrs.PlateCarree(),
cmap='seismic',
extend='both')
hc = plt.colorbar(hc, pad=0.17)
hc.formatter.set_powerlimits((0, 0))
hc.update_ticks()
hc.set_label(r'$-\frac{\nabla\cdot(\rho\vec{u})}{\rho}$')
# wind difference
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(g1a, 'neutral', alt=alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2a, 'neutral', alt=alt)
lon0, lat0 = lon1, lat1
lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(lon0,
lat0,
ewind2 - ewind1,
nwind2 - nwind1,
plot_type='polar',
projection=projection)
hq = ax.quiver(lon0,
lat0,
ewind0,
nwind0,
scale=1000,
scale_units='inches',
regrid_shape=20,
headwidth=5)
ax.quiverkey(hq, 0.93, -0.1, 500, '500 m/s')
ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
plt.title('%s km' % alt_str, y=1.05)
plt.text(0.5,
0.95,
'Time: ' + tstring,
fontsize=15,
horizontalalignment='center',
transform=plt.gcf().transFigure)
if show:
plt.show()
if save:
plt.savefig(spath + '08_divrhov_rho_diff_%s%s.pdf' %
(tstrday, tstring))
return
def animate_hozt_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)
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)'])
divv1 = cr.calc_div_hozt(lon1,lat1,alt1,nwind1,ewind1)
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)'])
divv2 = cr.calc_div_hozt(lon2,lat2,alt2,nwind2,ewind2)
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 plot_divrhov_rho_diff(show=True, save=True):
# density change (shrink)
lon1 = np.array(g1a['Longitude'])
lat1 = np.array(g1a['Latitude'])
alt1 = np.array(g1a['Altitude'])
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt1
omega = 2*np.pi/(24*3600)
rho1 = np.array(g1a['Rho'])
nwind1 = np.array(g1a['V!Dn!N (north)'])
ewind1 = np.array(g1a['V!Dn!N (east)']) + omega*RR*np.cos(lat1)
uwind1 = np.array(g1a['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
# density change (no shrink)
lon2 = np.array(g2a['Longitude'])
lat2 = np.array(g2a['Latitude'])
alt2 = np.array(g2a['Altitude'])
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt2
omega = 2*np.pi/(24*3600)
rho2 = np.array(g2a['Rho'])
nwind2 = np.array(g2a['V!Dn!N (north)'])
ewind2 = np.array(g2a['V!Dn!N (east)']) + omega*RR*np.cos(lat2)
uwind2 = np.array(g2a['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
g1a['divrhov_diff'] = div_rhov1-div_rhov2
apex = Apex(date=2003)
qlat, qlon = apex.convert(-90, 0, source='apex', dest='geo', height=400)
plt.close('all')
plt.figure(figsize=(7.26, 9.25))
for ialt, alt in enumerate([130, 200, 300, 400, 500, 600]):
alt_ind = np.argmin(np.abs(g1a['Altitude'][0, 0, :]/1000-alt))
alt_str = '%6.2f' % (g1a['Altitude'][0, 0, alt_ind]/1000)
ax, projection = gcc.create_map(
3, 2, ialt+1, 'polar', nlat=nlat, slat=slat, dlat=10,
centrallon=g3ca.calculate_centrallon(g1a, 'polar', useLT=True),
coastlines=False)
lon0, lat0, zdata0 = g3ca.contour_data('divrhov_diff', g1a, alt=alt)
fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
hc = ax.contourf(
lon0, lat0, zdata0, np.linspace(-1,1,21)*1e-4,
transform=ccrs.PlateCarree(), cmap='seismic', extend='both')
hc = plt.colorbar(hc, pad=0.17)
hc.formatter.set_powerlimits((0,0))
hc.update_ticks()
hc.set_label(r'$-\frac{\nabla\cdot(\rho\vec{u})}{\rho}$')
# wind difference
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(g1a, 'neutral', alt=alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2a, 'neutral', alt=alt)
lon0, lat0 = lon1, lat1
lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(
lon0, lat0, ewind2-ewind1, nwind2-nwind1, plot_type='polar',
projection=projection)
hq = ax.quiver(
lon0, lat0, ewind0, nwind0, scale=1000, scale_units='inches',
regrid_shape=20, headwidth=5)
ax.quiverkey(hq, 0.93, -0.1, 500, '500 m/s')
ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
plt.title('%s km' % alt_str, y=1.05)
plt.text(0.5, 0.95, 'Time: '+tstring, fontsize=15,
horizontalalignment='center', transform=plt.gcf().transFigure)
if show:
plt.show()
if save:
plt.savefig(spath+'08_divrhov_rho_diff_%s%s.pdf' % (tstrday,tstring))
return
gallfn = '/Users/guod/data/GITMOutput/run_shrink_notides_tmp/UA/data/3DALL_t030323_000004.bin'
gthmfn = '/Users/guod/data/GITMOutput/run_shrink_notides_tmp/UA/data/3DTHM_t030323_000004.bin'
gall = gitm.read(gallfn)
lontp = gall['Longitude']
lattp = gall['Latitude']
alttp = gall['Altitude']
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alttp
omega = 2*np.pi/(24*3600)
rhotp = gall['Rho']
nwindtp = gall['V!Dn!N (north)']
ewindtp = gall['V!Dn!N (east)'] + omega*RR*np.cos(lattp)
uwindtp = gall['V!Dn!N (up)']
gall['div_rhov'] = \
-(cr.calc_div_hozt(lontp, lattp, alttp, rhotp*nwindtp, rhotp*ewindtp)\
+cr.calc_div_vert(alttp, rhotp*uwindtp))/rhotp
gall['vert_divv'] = -cr.calc_div_vert(alttp, uwindtp)
gall['hozt_divv'] = -cr.calc_div_hozt(lontp, lattp, alttp, nwindtp, ewindtp)
gall['vert_vgradrho'] = -uwindtp*cr.calc_rusanov_alts_ausm(alttp,rhotp)/rhotp
gall['hozt_vgradrho'] = \
-(nwindtp*cr.calc_rusanov_lats(lattp,alttp,rhotp)\
+ewindtp*cr.calc_rusanov_lons(lontp,lattp,alttp,rhotp))/rhotp
gp.calc_pressure(gall)
gthm = gitm.read(gthmfn)
gthm['total energy'] =\
gthm['EUV Heating'] + gthm['Conduction'] + \
gthm['Chemical Heating'] + gthm['Auroral Heating'] + \
gthm['Joule Heating'] - gthm['NO Cooling'] - gthm['O Cooling']
savepath='/Users/guod/tmp/'
def figure5_7(alt=150):
times = pd.to_datetime([
'2003-03-22 00:00:00', '2003-03-22 00:30:00', '2003-03-22 01:00:00',
'2003-03-22 02:00:00', '2003-03-22 03:00:00', '2003-03-22 06:00:00'])
plt.close('all')
plt.figure(figsize=(9.5, 9.25))
xtitle = [
r'$-\nabla\cdot w$', r'$-\nabla\cdot u$',
r'$-\frac{w\cdot\nabla\rho}{\rho}$',
r'$-\frac{u\cdot\nabla\rho}{\rho}$',
r'$\frac{\partial \rho}{\rho\partial t}$',
r'$\delta\rho$ (%)']
ylabel = times.strftime('%H:%M')
qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
for itime, time in enumerate(times):
strtime = time.strftime('%y%m%d_%H%M')
fn1 = glob.glob(
'/home/guod/simulation_output/momentum_analysis/'\
'run_no_shrink_iondrift_4_1/data/3DALL_t%s*.bin' % strtime)
fn2 = glob.glob(
'/home/guod/simulation_output/momentum_analysis/'\
'run_shrink_iondrift_4_c1/data/3DALL_t%s*.bin' % strtime)
g1 = gitm.read(fn1[0])
g2 = gitm.read(fn2[0])
lon1 = g1['Longitude']
lat1 = g1['Latitude']
alt1 = g1['Altitude']
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt1
omega = 2*pi/(24*3600)
rho1 = np.array(g1['Rho'])
nwind1 = g1['V!Dn!N (north)']
ewind1 = g1['V!Dn!N (east)'] + omega*RR*np.cos(lat1)
uwind1 = 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
vert_divv1 = cr.calc_div_vert(alt1, uwind1)
hozt_divv1 = cr.calc_div_hozt(lon1, lat1, alt1, nwind1, ewind1)
vert_vgradrho1 = uwind1*cr.calc_rusanov_alts_ausm(alt1,rho1)/rho1
hozt_vgradrho1 = \
(nwind1*cr.calc_rusanov_lats(lat1,alt1,rho1)\
+ewind1*cr.calc_rusanov_lons(lon1,lat1,alt1,rho1))/rho1
dc1 = [
vert_divv1, hozt_divv1, vert_vgradrho1, hozt_vgradrho1,
div_rhov1, rho1]
lon2 = g2['Longitude']
lat2 = g2['Latitude']
alt2 = g2['Altitude']
Re = 6371*1000 # Earth radius, unit: m
RR = Re+alt2
omega = 2*pi/(24*3600)
rho2 = g2['Rho']
nwind2 = g2['V!Dn!N (north)']
ewind2 = g2['V!Dn!N (east)'] + omega*RR*np.cos(lat2)
uwind2 = 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
vert_divv2 = cr.calc_div_vert(alt2, uwind2)
hozt_divv2 = cr.calc_div_hozt(lon2, lat2, alt2, nwind2, ewind2)
vert_vgradrho2 = uwind2*cr.calc_rusanov_alts_ausm(alt2,rho2)/rho2
hozt_vgradrho2 = \
(nwind2*cr.calc_rusanov_lats(lat2,alt2,rho2)\
+ewind2*cr.calc_rusanov_lons(lon2,lat2,alt2,rho2))/rho2
dc2 = [
vert_divv2, hozt_divv2, vert_vgradrho2, hozt_vgradrho2,
div_rhov2, rho2]
alt_ind = np.argmin(np.abs(alt1[0, 0, :]/1000-alt))
alt_str = '%6.0f' % (alt1[0, 0, alt_ind]/1000)
for idc in range(6):
lonticklabel = [0, 0, 0, 0]
if idc == 0:
lonticklabel[3] = lonticklabel[-1]+1
if idc == 5:
lonticklabel[1] = lonticklabel[-1]+1
if itime == 0:
lonticklabel[0] = lonticklabel[-2]+1
if itime == 5:
lonticklabel[2] = lonticklabel[-2]+1
ax, projection = gcc.create_map(
6, 6, itime*6+idc+1, 'polar', nlat=nlat, slat=slat, dlat=10,
centrallon=g3ca.calculate_centrallon(g1, 'polar', useLT=True),
coastlines=False, lonticklabel=lonticklabel)
g1['temp'] = -(dc1[idc] - dc2[idc])
if idc==5:
g1['temp'] = 100*(dc1[idc] - dc2[idc])/dc2[idc]
lon0, lat0, zdata0 = g3ca.contour_data('temp', g1, alt=alt)
fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
levels = np.linspace(-8,8,21)*1e-5
if idc==5:
levels = np.linspace(-30,30,21)
hc = ax.contourf(
lon0, lat0, zdata0, levels,
transform=ccrs.PlateCarree(), cmap='seismic', extend='both')
# wind difference
alt_ind = np.argmin(np.abs(alt1[0, 0, :]/1000-alt))
alt_str = '%6.0f' % (alt1[0, 0, alt_ind]/1000)
lon1, lat1, ewind1, nwind1 = g3ca.vector_data(
g1, 'neutral', alt=alt)
lon2, lat2, ewind2, nwind2 = g3ca.vector_data(
g2, 'neutral', alt=alt)
lon0, lat0 = lon1, lat1
lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(
lon0, lat0, ewind1-ewind2, nwind1-nwind2,
plot_type='polar', projection=projection)
hq = ax.quiver(
lon0, lat0, ewind0, nwind0, scale=1500,
scale_units='inches', regrid_shape=20, headwidth=5)
ax.scatter(
qlon, qlat, s=10, color='k', transform=ccrs.PlateCarree())
ax.scatter(
0, -90, color='w', s=10, transform=ccrs.PlateCarree(),
zorder=1000)
if idc==0:
plt.text(
-0.3, 0.5, ylabel[itime], rotation=90,
transform=ax.transAxes, verticalalignment='center')
if itime==0:
plt.title(xtitle[idc], y=1.15, fontsize=14)
texts = ['(a)', '(b)', '(c)', '(d)', '(e)', '(f)']
plt.text(0.05,1,texts[idc],transform=plt.gca().transAxes,
color='r')
if itime==5:
axp = ax.get_position()
cax = [axp.x0, axp.y0-0.03, axp.x1-axp.x0, 1/20*(axp.y1-axp.y0)]
cax = plt.axes(cax)
ticks = np.arange(-8e-5, 8.1e-5, 4e-5) if idc<5 else \
np.arange(-30, 31, 15)
hcb = plt.colorbar(
hc, cax=cax, extendrect=True, orientation='horizontal',
ticks=ticks)
if idc<5:
hcb.formatter.set_powerlimits((0,0))
hcb.update_ticks()
plt.subplots_adjust(wspace=0, hspace=0)
if alt==300:
plt.savefig(savepath+'Figure5.eps')
plt.savefig(savepath+'Figure5.jpeg')
if alt==600:
plt.savefig(savepath+'Figure7.eps')
plt.savefig(savepath+'Figure7.jpeg')
return