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fig7_rhi_freq.py
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fig7_rhi_freq.py
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import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.gridspec as gridspec
flno = [2,3,4,6,7,8]
maxlag = [0,0,5,10,10,20]
cmap = "YlGnBu"
def satppm(p,T):
Psat = np.exp(9.550426 - 5723.265/T + 3.53068 * np.log(T) - 0.00728332 * T) / 100.
return 1e6 * Psat / p
def rhi_temp_freq(dat):
fig = plt.figure(figsize=(24,12))
plt.rcParams.update({"font.size":25})
gs0 = gridspec.GridSpec(1,4,figure=fig,width_ratios=[10,10,10,1])
cax = fig.add_subplot(gs0[-1])
insts = ["ChiWIS","FLASH","FISH"]
# add cloudy flag
dat['CLOUDY'] = ((dat['NICE'] > 0) | (dat['MASBR'] >= 1.2)).astype(int)
for i,f in enumerate(flno):
for lag in np.arange(1,maxlag[i]):
dat.loc[(dat['FLIGHT'] == f),'CLOUDY'] = np.maximum(dat.loc[(dat['FLIGHT'] == f),'CLOUDY'],
dat[(dat['FLIGHT'] == f)].shift(periods=lag, fill_value=0.0)['CLOUDY'])
# add ascent/descent flag
dz = (dat['ALT'] - dat.shift(periods=1)['ALT'])*1e3
dt = dat['TIME'] - dat.shift(periods=1)['TIME']
vert = np.abs(dz / dt)
vert_avg = vert.rolling(window=20).mean()
dat['ASCENT_FLAG'] = ((vert_avg > 10) | (dat['ALT'] < 12)).astype(int)
# add chiwis flag
dat['CELL_FLAG'] = ((dat['PRES_CELL'] < 30.0) | (dat['PRES_CELL'] > 45.0) | (dat['FLAG'] == 1)).astype(int)
# FL7 dive flag
dat['F7_DIVE'] = ((dat['FLIGHT'] == 7) & (dat['TIME'] > 19.9e3) & (dat['TIME'] < 20.2e3)).astype('int')
h2othresh = 100
for i, inst in enumerate(insts):
gs00 = gridspec.GridSpecFromSubplotSpec(2,1,subplot_spec=gs0[i])
if i == 0:
ax1 = fig.add_subplot(gs00[0])
plt.setp(ax1.get_xticklabels(), visible=False)
axlt = ax1
ax2 = fig.add_subplot(gs00[1], sharex=ax1)
axlb = ax2
inst = "ChiWIS"
key = "H2O"
# chiwis clear-sky
dat0 = dat[(dat[key] < h2othresh) & (dat['CLOUDY'] == 0) & (dat['ASCENT_FLAG'] == 0) & (dat['CELL_FLAG'] == 0)]
# chiwis cloudy
dat1 = dat[(dat[key] < h2othresh) & (dat['CLOUDY'] == 1) & (dat['ASCENT_FLAG'] == 0) & (dat['CELL_FLAG'] == 0)]
h0 = np.sum(~np.isnan(dat0[key])) / 3600.
h1 = np.sum(~np.isnan(dat1[key])) / 3600.
print(inst)
print(h0, h1, " hrs (clear, cloudy)")
if i == 1:
ax1 = fig.add_subplot(gs00[0], sharey=axlt)
ax2 = fig.add_subplot(gs00[1], sharex=ax1, sharey=axlb)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax1.get_yticklabels(), visible=False)
plt.setp(ax2.get_yticklabels(), visible=False)
inst = "FLASH"
key = "FLH2O"
# flash clear-sky
dat0 = dat[(dat[key] < h2othresh) & (dat['FLIGHT'] != 1) & (dat['FLIGHT'] != 5)
& (dat['CLOUDY'] == 0) & (dat['ASCENT_FLAG'] == 0) & (dat['F7_DIVE'] == 0)]
# flash cloudy
dat1 = dat[(dat[key] < h2othresh) & (dat['FLIGHT'] != 1) & (dat['FLIGHT'] != 5)
& (dat['CLOUDY'] == 1) & (dat['ASCENT_FLAG'] == 0) & (dat['F7_DIVE'] == 0)]
h0 = np.sum(~np.isnan(dat0[key])) / 3600.
h1 = np.sum(~np.isnan(dat1[key])) / 3600.
print(inst)
print(h0, h1, " hrs (clear, cloudy)")
if i == 2:
ax1 = fig.add_subplot(gs00[0], sharey=axlt)
plt.setp(ax1.get_yticklabels(), visible=False)
inst = "FISH"
key = "FIH2O"
# fish clear-sky
dat0 = dat[(dat[key] < h2othresh) & (dat['CLOUDY'] == 0) & (dat['ASCENT_FLAG'] == 0)]
h0 = np.sum(~np.isnan(dat0[key])) / 3600.
print(inst)
print(h0, " hrs (clear)")
temp = dat0['TEMP']+273.15
rhi = dat0[key]/dat0['SATPPM']
print("clear ", inst, "mean = ", np.nanmean(rhi), "median = ", np.nanmedian(rhi))
m = ax1.hist2d(temp,rhi,bins=[120,40],range=[[180, 240],[0, 2]],
density=1,norm=mcolors.PowerNorm(gamma=0.5),vmin=0,vmax=1,
cmin=1e-10,cmap=cmap)
ax1.plot([175,240],[1.67,1.42],'k:', lw=3)
ax1.plot([175,240],[1,1],'k-', lw=2)
ax1.text(186,0.05,"{:.1f} hrs".format(h0))
if i < 2:
temp = dat1['TEMP']+273.15
rhi = dat1[key]/dat1['SATPPM']
print("cloudy ", inst, "mean = ", np.nanmean(rhi), "median = ", np.nanmedian(rhi))
m = ax2.hist2d(temp,rhi,bins=[120,40],range=[[180, 240],[0, 2]],
density=1,norm=mcolors.PowerNorm(gamma=0.5),vmin=0,vmax=1,
cmin=1e-10,cmap=cmap)
ax2.plot([175,240],[1.67,1.42],'k:', lw=3, label="Koop homogenous\nice nucleation threshold")
ax2.plot([175,240],[1,1],'k-',lw=2,label=r"saturation line, RH$_{ice} = 1$")
ax2.text(186,0.05,"{:.1f} hrs".format(h1))
# plot attributes
ax2.set_xlabel('Temperature (K)')
if i == 0:
ax1.set_ylabel(r'RH$_{ice}$')
ax2.set_ylabel(r'RH$_{ice}$')
ax1.set_title("clear-sky "+inst)
ax2.set_title("in-cloud "+inst)
ax1.grid(which='major',linestyle=':')
ax2.grid(which='major',linestyle=':')
ax1.set_xlim([185,225])
ax1.set_ylim([0,2])
ax2.set_xlim([185,225])
ax2.set_ylim([0,2])
if i == 1:
ax2.legend(loc=1,bbox_to_anchor=(2.25, 0.9))
let = ["a","b","c"]
ax1.set_title(let[i],loc="left",weight="bold")
let = ["d","e"]
ax2.set_title(let[i],loc="left",weight="bold")
else:
ax1.set_xlabel('Temperature (K)')
ax1.set_title("clear-sky "+inst)
ax1.grid(which='major',linestyle=':')
ax1.set_xlim([185,225])
ax1.set_ylim([0,2])
let = ["a","b","c"]
ax1.set_title(let[i],loc="left",weight="bold")
plt.colorbar(m[3], cax=cax, ticks=[0,0.1,0.3,0.6,1.0], label="Frequency")
plt.rcParams.update({"font.size":25})
plt.savefig("./Paper-Figures/fig7-rhi-freq.png",bbox_inches="tight",dpi=200)
plt.show()