def walker_vs_hadley(run, lonin=[370., 10.]):
data = xr.open_dataset('/disca/share/rg419/Data_moist/climatologies/' +
run + '.nc')
#walker_mag = walker_strength(data, lonin=[90.,180.])
walker_mag = walker_strength(data, lonin=[270., 360.], psi_min=False)
edge_loc, psi_max, psi_max_loc = get_edge_psi(data, lonin=lonin)
times = np.intersect1d(walker_mag.xofyear.values, psi_max.xofyear)
plt.plot(psi_max.sel(xofyear=times), walker_mag.sel(xofyear=times), 'x')
def get_max_overturning(data):
n = len(data)
psi_max = []
for i in range(n):
vars = get_edge_psi(data[i], lev=500.)
psi_max.append(vars[1])
return psi_max
def plot_bs_fig_9_moist(run, pentads=[35, 40, 45, 50], rotfac=1.):
plot_dir = '/scratch/rg419/plots/paper_2_figs/revisions/heatbudg_moist/'
mkdir = sh.mkdir.bake('-p')
mkdir(plot_dir)
rcParams['figure.figsize'] = 5.5, 7.
rcParams['font.size'] = 14
data = xr.open_dataset('/disca/share/rg419/Data_moist/climatologies/' +
run + '.nc')
data['precipitation'] = make_sym(data.precipitation)
precip_centroid(data) # Locate precipitation centroid
dpcentdt = gr.ddt(data.p_cent) * 86400.
p_cent_pos = np.abs(data.p_cent.where(dpcentdt >= 0.))
eq_time = p_cent_pos.xofyear[p_cent_pos.argmin('xofyear').values]
peak_rate_time = dpcentdt.xofyear[dpcentdt.argmax('xofyear').values]
max_lat_time = data.p_cent.xofyear[data.p_cent.argmax('xofyear').values]
edge_loc, psi_max, psi_max_loc = get_edge_psi(data,
lev=850.,
thresh=0.,
intdown=True)
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, sharex=True)
axes = [ax1, ax2, ax3, ax4]
pentads = [
eq_time.values, peak_rate_time.values,
np.floor((peak_rate_time.values + max_lat_time.values) / 2.),
max_lat_time.values
]
for i in range(4):
fig_9_moist(run, ax=axes[i], pentad=pentads[i])
edge = edge_loc.sel(xofyear=pentads[i])
axes[i].plot([edge, edge], [-250., 250.], 'k:')
axes[i].text(20, 240., 'Pentad ' + str(int(pentads[i])))
ax4.set_xlabel('Latitude')
#ax1.text(-55, 315., 'a)')
#ax2.text(-55, 315., 'b)')
#ax3.text(-55, 315., 'c)')
#ax4.text(-55, 315., 'd)')
plt.subplots_adjust(left=0.15, right=0.95, top=0.97, bottom=0.1)
plt.savefig(plot_dir + 'sb08_fig9_moist_' + run + '.pdf', format='pdf')
plt.close()
def set_vars(data, plottype=None, lonin=[-1.,361.], thresh=0.):
# Load up variables to plot, depending on plot type
edge_loc, psi_max, psi_max_loc = get_edge_psi(data, thresh=thresh, lev=lev, lonin=lonin, nh=True, sanity_check=True)
if plottype == 'mse':
data_mse = peak_mse(data, lonin=lonin)
vars_out = (data_mse.mse_max_loc, psi_max)
elif plottype == 'pcent':
data = precip_centroid(data,lonin=lonin)
vars_out = (data.p_cent, psi_max)
elif plottype == None:
vars_out = (edge_loc, psi_max)
return vars_out
def overturning_plot(data,
ax_in,
lonin=[-1., 361.],
do_xlabels=False,
month_labels=True,
thresh=0.,
nh=False):
lons = pick_lons(data, lonin)
psi = mass_streamfunction(data, a=6376.0e3, dp_in=50., lons=lons)
psi /= 1.e9
edge_loc, psi_max, psi_max_loc = get_edge_psi(data,
lonin=lonin,
lev=500.,
thresh=thresh,
nh=nh)
f1 = psi.sel(pfull=500.).plot.contourf(ax=ax_in,
x='xofyear',
y='lat',
levels=np.arange(-500., 510., 50.),
add_colorbar=False,
add_labels=False,
extend='both')
edge_loc.plot(color='k', ax=ax_in)
psi_max_loc.plot(color='k', ax=ax_in)
ax_in.set_ylabel('Latitude')
ax_in.set_ylim(-60, 60)
ax_in.set_yticks(np.arange(-60., 61., 30.))
ax_in.grid(True, linestyle=':')
if month_labels:
mn_dic = month_dic(1)
tickspace = list(range(13, 72, 18))
labels = [mn_dic[(k + 5) / 6] for k in tickspace]
ax_in.set_xlim((1, 72))
ax_in.set_xticks(tickspace)
if do_xlabels:
ax_in.set_xlabel('')
ax_in.set_xticklabels(labels, rotation=25)
return f1
def set_vars(data, type=None, lonin=[-1., 361.], thresh=0.):
edge_loc, psi_max, psi_max_loc = get_edge_psi(data,
thresh=thresh,
lev=lev,
lonin=lonin)
if type == 'mse':
data_mse = peak_mse(data, lonin=lonin)
vars_out = (data_mse.mse_max_loc, psi_max)
elif type == 'pcent':
data = precip_centroid(data, lonin=lonin)
vars_out = (data.p_cent, psi_max)
elif type == None:
vars_out = (edge_loc, psi_max)
return vars_out
def hadley_strength_plot(run, lonin=[370., 10.], c='C0'):
data = xr.open_dataset('/disca/share/rg419/Data_moist/climatologies/' +
run + '.nc')
edge_loc, hadley_mag, psi_max_loc = get_edge_psi(data, lonin=lonin)
plt.plot(hadley_mag.xofyear, hadley_mag, 's', color=c)
def pcent_vs_cell_edge(data, symbol='xk'):
precip_centroid(data)
edge_loc, psi_max, psi_max_loc = get_edge_psi(data, thresh=0.)
plt.plot(data.p_cent, edge_loc, symbol)
else:
plt.ylim([0, int(latmax) + 5])
plt.xlim([0, int(psimax) + 50])
plt.savefig('/scratch/rg419/plots/regime_fig/' + plotname + '.pdf',
format='pdf')
plt.close()
if __name__ == "__main__":
#vars_zs = get_edge_psi('zs_sst', thresh=thresh, lev=lev, sanity_check=True)
#vars_co2 = get_edge_psi('ap10_co2', thresh=thresh, lev=lev, sanity_check=True)
#vars_qflux = get_edge_psi('ap10_qflux', thresh=thresh, lev=lev, sanity_check=True)
#vars_ap2 = get_edge_psi('ap_2', thresh=thresh, lev=lev)
vars_ap10 = get_edge_psi('sn_1.000', thresh=thresh, lev=lev)
#vars_ap20 = get_edge_psi('ap_20', thresh=thresh, lev=lev)
#vars_full = get_edge_psi('full_qflux', thresh=thresh, lonin=[60.,150.], lev=lev)
vars_sn05 = get_edge_psi('sn_0.500', thresh=thresh, lev=lev)
vars_sn20 = get_edge_psi('sn_2.000', thresh=thresh, lev=lev)
#vars_rt05 = get_edge_psi('rt_0.500', thresh=0., lev=lev)
#vars_rt10 = get_edge_psi('sn_1.000', thresh=0., lev=lev)
#vars_rt20 = get_edge_psi('rt_2.000', thresh=0., lev=lev)
#vars = [vars_ap10]
#plot_multiple(vars, 'mlds_10', s=['o'], psimin=200, psimax=470, latmax=25)
#vars = [vars_ap10]
#plot_multiple(vars, 'mlds_10_line', s=['o'], ll=[True], lh=[True], psimin=200, psimax=470, latmax=25)
#vars = [vars_ap10, vars_co2, vars_qflux]