def get_swath_coord(iC):
swath_x, swath_y = get_cs_coords(x_cs[iC], y_cs[iC], orientation_in + 90., X, Y, h = res, isPeriodic = True, max_r = swath_width/2.)
return swath_x, swath_y
y_c = 4*R_i # y-coordinate for the island centre
# Create the coordinate system for this data
<<<<<<< HEAD
dx = 1600.0
X, Y = np.meshgrid(np.arange(74)*dx, np.arange(20)*dx)
# Get coordinates of the cross section along the swath
h = dx*1. # Resolution in the along-swath direction
=======
X, Y = np.meshgrid(np.arange(0., 116000., 100.), np.arange(0., 31900., 100.))
# Get coordinates of the cross section along the swath
h = 100. # Resolution in the along-swath direction
>>>>>>> 62279a4ff074ba2a906de6d583e07e7c7ce0c696
x_cs, y_cs = get_cs_coords(x_c, y_c, orientation_in, X, Y, h = h)
# Truncate to one domain - i.e. remove points that exit a boundary
removal = []
for i in xrange(len(x_cs)):
if (np.min(X) > x_cs[i]) or (np.max(X) < x_cs[i]) or (np.min(Y) > y_cs[i]) or (np.max(Y) < y_cs[i]):
removal.append(i)
x_cs = np.delete(x_cs, removal)
y_cs = np.delete(y_cs, removal)
R_i /= 1000. # Convert the island radius to km
# Calculate the distance from the island centre in the along swath direction
R = -np.array([np.round(x, 0) for x in np.sign(x_cs - x_c)*np.sqrt((x_cs - x_c)**2 + (y_cs - y_c)**2)]) - R_i*1000.
def get_chunk_coord(iC):
print 'get_chunk_coord(' + str(iC) + ')'
iR = np.where(np.min(np.abs(R - chunk_Rs[chunk_keys[-1]][iC])) == np.abs(R - chunk_Rs[chunk_keys[-1]][iC]))[0][0]
chunks_x, chunks_y = get_cs_coords(x_cs[iR], y_cs[iR], wind_dir_0 + 90., X, Y, h = res, isPeriodic = True, max_r = chunk_width/2.)
return chunks_x, chunks_y
lsm = landseamask.variables['lsm'][0, 0, :, :] * 1.
y = landseamask.variables['latitude'][:] * 1.
x = landseamask.variables['longitude'][:] * 1.
# create 2D coordinate mesh
X, Y = np.meshgrid(x, y)
landseamask.close()
# We know from our domain definition where the centre of the island should be
R_i = 1000.0 * (50.0 / np.pi)**0.5 # island radius
x_c = 100000.0 + R_i
y_c = 4 * R_i
x_cs, y_cs = get_cs_coords(x_c, y_c, wind_dir_0, X, Y, h=100.)
hours = ["{0:02d}".format(h) for h in xrange(0, 24, 3)]
# use dictionaries to hold the stash codes for the variables
var_keys = {
'theta': u'STASH_m01s00i004',
'qv': u'STASH_m01s00i010',
'w': u'STASH_m01s00i150'
}
var_cmaps = {'theta': 'hot', 'qv': 'BrBG', 'w': 'bwr'}
var_factor = {'theta': 1., 'qv': 1000., 'w': 1.}
var_units = {'theta': '(K)', 'qv': r'(g kg$^{-1}$)', 'w': r'(m s^{-1}$)'}
# use dictionary to hold the hovmollers
hovmollers = {}
for key in var_keys.keys():
hovmollers[key] = np.zeros((18 * len(hours), len(x_cs)))
def get_cs(it):
# only need data to the height just above 3000 m
iz3000 = np.where(np.abs(z - 5000) == np.min(np.abs(z - 5000)))[0][0] + 1
# leave the rest of the levels = 0
my_kind = 2
d = 2000.
print('[' + dt.now().strftime("%H:%M:%S") +
'] Interpolating to the cross section coordinates...')
START = dt.now()
print('[' + dt.now().strftime("%H:%M:%S") + '] Starting interpolation...')
start = dt.now()
theta_cs = bilinear_interpolation(
X,
Y,
bouy_nc.variables[theta_key][it, :iz3000, :, :] * 1.,
x_cs,
y_cs,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating Theta, elapsed time: ' + str(end - start))
start = dt.now()
q_cs = bilinear_interpolation(X,
Y,
bouy_nc.variables[q_key][it, :iz3000, :, :] *
1.,
x_cs,
y_cs,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating q, elapsed time: ' + str(end - start))
start = dt.now()
w_cs = bilinear_interpolation(X,
Y,
bouy_nc.variables[w_key][it, :iz3000, :, :] *
1.,
x_cs,
y_cs,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating w, elapsed time: ' + str(end - start))
start = dt.now()
zi_cs = bilinear_interpolation(X,
Y,
zi_nc.variables[zi_key][:],
x_cs,
y_cs,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating zi, elapsed time: ' + str(end - start))
start = dt.now()
lcl_cs = bilinear_interpolation(X,
Y,
zi_nc.variables[lcl_key][:],
x_cs,
y_cs,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating lcl, elapsed time: ' + str(end - start))
END = dt.now()
print('[' + dt.now().strftime("%H:%M:%S") +
'] Completed interpolation in ' + str(END - START) + "...")
#================================= Section 4 ==================================#
# #
# Plot the cross section and anomalies #
# #
#==============================================================================#
#print('Starting section 4')
# Translate the cross section coordinates into the distance downwind of the island
R = np.sign(x_c - x_cs) * np.sqrt((x_cs - x_c)**2 + (y_cs - y_c)**2)
# Calculate the anomaly from the horizontal mean
theta_cs_anom = np.zeros_like(theta_cs)
q_cs_anom = np.zeros_like(q_cs)
theta_hm = np.nanmean(bouy_nc.variables[theta_key][it, :iz3000, :, :],
axis=(1, 2))
q_hm = np.nanmean(bouy_nc.variables[q_key][it, :iz3000, :, :], axis=(1, 2))
for i in xrange(theta_cs.shape[1]):
theta_cs_anom[:, i] = theta_cs[:, i] - theta_hm
q_cs_anom[:, i] = q_cs[:, i] - q_hm
# Plotting params
text_pos_x = -R_i / 1000. + R_i * 0.1 / 1000.
text_pos_y = 100.
fig_width = 10 # inches
fig = plt.figure()
fig.set_size_inches(fig_width, fig_width / 1.5)
ax = plt.subplot(311)
plt.contourf(R / 1000.,
z[:iz3000] / 1000.,
theta_cs_anom,
cmap='bwr',
levels=[l for l in np.linspace(-1., 1., 11) if l != 0.],
extend='both')
plt.colorbar(label=r'$\theta$ Anomaly (K)')
plt.title('Potential Temperature Anomaly (K) Cross Section')
plt.ylim([0, 5])
r_i = np.array([-R_i, R_i]) / 1000.
plt.plot(r_i, [0, 0], 'k', lw=5)
plt.text(text_pos_x, text_pos_y, 'Island')
plt.plot(R / 1000., zi_cs[it, :] / 1000., 'k', lw=2)
plt.plot(R / 1000., lcl_cs[it, :] / 1000., 'grey', lw=2)
plt.ylabel('Height (km)')
plt.setp(ax.get_xticklabels(), visible=False)
ax1 = plt.subplot(312, sharex=ax)
plt.contourf(R / 1000.,
z[:iz3000] / 1000.,
q_cs_anom * 1000.,
cmap='BrBG',
levels=[l for l in np.linspace(-2., 2., 11) if l != 0.],
extend='both')
plt.colorbar(label=r'q Anomaly (g kg$^{-1}$)')
plt.title('Specific Humidity Anomaly (g kg$^{-1}$) Cross Section')
plt.ylim([0, 5])
plt.plot(r_i, [0, 0], 'k', lw=5)
plt.text(text_pos_x, text_pos_y, 'Island')
plt.plot(R / 1000., zi_cs[it, :] / 1000., 'k', lw=2)
plt.plot(R / 1000., lcl_cs[it, :] / 1000., 'grey', lw=2)
plt.ylabel('Height (km)')
plt.setp(ax1.get_xticklabels(), visible=False)
plt.subplot(313, sharex=ax)
plt.contourf(R / 1000.,
z[:iz3000] / 1000.,
w_cs,
cmap='bwr',
levels=[l for l in np.linspace(-2.5, 2.5, 11) if l != 0.],
extend='both')
plt.colorbar(label=r'w (m s$^{-1}$)')
plt.title('Vertical Velocity (m s$^{-1}$) Cross Section')
plt.ylim([0, 5])
plt.plot(r_i, [0, 0], 'k', lw=5)
plt.text(text_pos_x, text_pos_y, 'Island')
plt.plot(R / 1000., zi_cs[it, :] / 1000., 'k', lw=2)
plt.plot(R / 1000., lcl_cs[it, :] / 1000., 'grey', lw=2)
plt.ylabel('Height (km)')
plt.xlabel('Distance from Island mid-point (km)')
plt.suptitle('Along-wind Cross Section, at T+' + str(int(times[it])) +
'mins',
fontsize=15)
plt.tight_layout()
fig.subplots_adjust(top=0.88)
plt.savefig('../AlongWind_interpolated_T' +
"{0:04d}".format(int(times[it])) + '.png',
dpi=100)
plt.close('all')
#plt.show()
#================================= Section 5 ==================================#
# #
# Calculate cross sections perpendicular to the flow and plot them #
# #
#==============================================================================#
# Choose distance from island mid-point to do the cross section
# e.g. 20 km
r_targets = [10000.0, 20000.0, 40000.0, 60000.0]
for r_target in r_targets:
# Find where the distance to the island is nearest to the target distance
R_pos = np.where((R > 0), R, np.nan)
iR = np.where(
np.abs(R_pos - r_target) == np.nanmin(np.abs(R_pos -
r_target)))[0][0]
x_cs2, y_cs2 = get_cs_coords(x_cs[iR],
y_cs[iR],
wind_dir_0 + 90.,
X,
Y,
h=100.0)
### Testing ###
if testing:
fig = plt.figure()
my_x = 12.
fig.set_size_inches(my_x, my_x * 32. / 116.)
plt.contourf(X / 1000.,
Y / 1000.,
lwp_data,
levels=[0, 1e-8, 1],
colors=['k', 'w'])
plt.contourf(X / 1000.,
Y / 1000.,
lsm,
levels=[0, 1e-16, 1],
colors=['w', 'b'],
alpha=0.5)
plt.plot(x_cs / 1000., y_cs / 1000., 'r', lw=3)
plt.plot(x_cs2 / 1000., y_cs2 / 1000., 'b', lw=3)
plt.ylabel('y (km)')
plt.xlabel('x (km)')
plt.text(x_cs[0], y_cs[0], 'A', fontsize=20)
plt.text(x_cs[-1], y_cs[-1], 'B', fontsize=20)
plt.text(x_cs2[0], y_cs2[0], 'C', fontsize=20)
plt.text(x_cs2[-1], y_cs2[-1], 'D', fontsize=20)
plt.title('Cross Section Path')
plt.tight_layout()
plt.savefig('../Cross_Section_location2.png', dpi=100)
plt.show()
f = open("output.txt", "a")
f.write('[' + dt.now().strftime("%H:%M:%S") +
'] Starting interpolation...\n')
f.close()
START = dt.now()
# Interpolate to cs2
start = dt.now()
theta_cs2 = bilinear_interpolation(
X,
Y,
bouy_nc.variables[theta_key][it, :iz3000, :, :],
x_cs2,
y_cs2,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating Theta, elapsed time: ' +
str(end - start))
start = dt.now()
q_cs2 = bilinear_interpolation(
X,
Y,
bouy_nc.variables[q_key][it, :iz3000, :, :],
x_cs2,
y_cs2,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating q, elapsed time: ' + str(end - start))
start = dt.now()
w_cs2 = bilinear_interpolation(
X,
Y,
bouy_nc.variables[w_key][it, :iz3000, :, :],
x_cs2,
y_cs2,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating w, elapsed time: ' + str(end - start))
END = dt.now()
start = dt.now()
zi_cs2 = bilinear_interpolation(X,
Y,
zi_nc.variables[zi_key][:],
x_cs2,
y_cs2,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating zi, elapsed time: ' + str(end - start))
END = dt.now()
start = dt.now()
lcl_cs2 = bilinear_interpolation(X,
Y,
zi_nc.variables[lcl_key][:],
x_cs2,
y_cs2,
kind=my_kind,
d=d)
end = dt.now()
print('Finished interpolating lcl, elapsed time: ' + str(end - start))
END = dt.now()
f = open('output.txt', 'a')
f.write('[' + dt.now().strftime("%H:%M:%S") +
'] Completed interpolation in ' + str(END - START) + "...\n")
f.close()
# Translate the cross section coordinates into the distance away from the island downwind mid-point
R2 = -np.sign(x_cs[iR] - x_cs2) * np.sqrt((x_cs2 - x_cs[iR])**2 +
(y_cs2 - y_cs[iR])**2)
# Calculate the anomaly from the horizontal mean
theta_cs2_anom = np.zeros_like(theta_cs2)
q_cs2_anom = np.zeros_like(q_cs2)
for i in xrange(theta_cs2.shape[1]):
theta_cs2_anom[:, i] = theta_cs2[:, i] - theta_hm
q_cs2_anom[:, i] = q_cs2[:, i] - q_hm
# Plotting params
text_pos_x = -R_i / 1000. + R_i * 0.1 / 1000.
text_pos_y = 100.
fig = plt.figure()
ax = plt.subplot(311)
plt.contourf(R2 / 1000.,
z[:iz3000] / 1000.,
theta_cs2_anom,
cmap='bwr',
levels=[l for l in np.linspace(-1., 1., 11) if l != 0.],
extend='both')
plt.colorbar()
plt.title('Potential Temperature Anomaly (K) Cross Section')
plt.ylim([0, 5])
r_i = np.array([-R_i, R_i]) / 1000.
plt.plot(r_i, [0, 0], 'k', lw=10)
plt.text(text_pos_x, text_pos_y, 'Island')
plt.plot(R2 / 1000., zi_cs2[it, :] / 1000., 'k', lw=2)
plt.plot(R2 / 1000., lcl_cs2[it, :] / 1000., 'grey', lw=2)
plt.ylabel('Height (m)')
plt.setp(ax.get_xticklabels(), visible=False)
ax1 = plt.subplot(312, sharex=ax)
plt.contourf(R2 / 1000.,
z[:iz3000] / 1000.,
q_cs2_anom * 1000.,
cmap='BrBG',
levels=[l for l in np.linspace(-2., 2., 11) if l != 0.],
extend='both')
plt.colorbar()
plt.title('Specific Humidity Anomaly (g kg$^{-1}$) Cross Section')
plt.ylim([0, 5])
plt.plot(r_i, [0, 0], 'k', lw=10)
plt.text(text_pos_x, text_pos_y, 'Island')
plt.plot(R2 / 1000., zi_cs2[it, :] / 1000., 'k', lw=2)
plt.plot(R2 / 1000., lcl_cs2[it, :] / 1000., 'grey', lw=2)
plt.ylabel('Height (m)')
plt.setp(ax1.get_xticklabels(), visible=False)
plt.subplot(313, sharex=ax)
plt.contourf(R2 / 1000.,
z[:iz3000] / 1000.,
w_cs2,
cmap='bwr',
levels=[l for l in np.linspace(-2.5, 2.5, 11) if l != 0.],
extend='both')
plt.colorbar()
plt.title('Vertical Velocity (m s$^{-1}$) Cross Section')
plt.ylim([0, 5])
plt.plot(r_i, [0, 0], 'k', lw=10)
plt.text(text_pos_x, text_pos_y, 'Island')
plt.plot(R2 / 1000., zi_cs2[it, :] / 1000., 'k', lw=2)
plt.plot(R2 / 1000., lcl_cs2[it, :] / 1000., 'grey', lw=2)
plt.ylabel('Height (m)')
plt.xlabel('Distance from Island mid-point (km)')
plt.suptitle('Cross-wind Cross Section (' +
str(int(r_target / 1000.)) + 'km downwind), at T+' +
str(int(times[it])) + 'mins',
fontsize=15)
plt.tight_layout()
fig.subplots_adjust(top=0.88)
plt.savefig('../CrossWind_smoothed_' + str(int(r_target / 1000.)) +
'km_T' + "{0:04d}".format(int(times[it])) + '.png',
dpi=100)
plt.close('all')
