def make_plot(df_result,df_sounding,interpPress):
""" return two plots with the vertical velocity and temperature profiles
Parameters
----------
df_result: dataframe
dataframe containing wvel (m/s) ,cloud_height (m) , thetae (K), rT (kg/kg) for assending parcel
df_sounding: pandas dataframe
: sounding columns are temperature (deg C), dewpoint (deg C), height (m), press (hPa)
interpPress: func
: interp1d function for presusure p(z)
Returns
-------
ax1,ax2: matplotlib axes
: plotting axis for the two figures
"""
plt.style.use('ggplot')
fig,ax1 = plt.subplots(1,1)
ax1.plot(df_result['wvel'], df_result['cloud_height'], label='wvel')
ax1.set_xlabel('vertical velocity (m/s)')
ax1.set_ylabel('height above surface (m)')
Tcloud = np.zeros_like(df_result['cloud_height'])
rvCloud = np.zeros_like(df_result['cloud_height'])
rlCloud = np.zeros_like(df_result['cloud_height'])
for i,row in enumerate(df_result.iterrows()):
the_press = interpPress(row[1]['cloud_height'])*100.
Tcloud[i], rvCloud[i], rlCloud[i] = tinvert_thetae(row[1]['thetae_cloud'],
row[1]['rT_cloud'], the_press)
Tadia= np.zeros_like(df_result['cloud_height'])
rvAdia = np.zeros_like(df_result['cloud_height'])
rlAdia = np.zeros_like(df_result['cloud_height'])
heights=df_result['cloud_height']
thetae_cloud0 = df_result.loc[0,'thetae_cloud']
rT_cloud0 = df_result.loc[0,'rT_cloud']
for i, height in enumerate(heights):
the_press = interpPress(height)*100.
Tadia[i], rvAdia[i], rlAdia[i] = tinvert_thetae(thetae_cloud0,
rT_cloud0, the_press)
fig,ax2=plt.subplots(1,1)
ax2.plot(Tcloud - c.Tc, df_result['cloud_height'], 'r-',label='cloud')
height = df_sounding['hght'].values
temp = df_sounding['temp'].values
ax2.plot(temp, height, 'g-',label='environment')
ax2.plot(Tadia - c.Tc, df_result['cloud_height'], 'b-',label='moist aidabat')
ax2.set_xlabel('temperature (deg C)')
ax2.set_ylabel('height above surface (m)')
ax2.legend(loc='best')
return ax1,ax2
def lift_sounding(rTotal,theThetae,press,):
#
# return temp,dewpoint and Tspeudo soundings for an rT,thetae sounding at pressure levels press
#
numPoints, = press.shape
for i in range(0, numPoints):
#find the actual temperature and dewpoint
Temp[i], rv, rl = tinvert_thetae(theThetae[i], rTotal[i], press[i] * hPa2pa)
Tdew[i] = find_Td(rv, press[i] * hPa2pa)
Tpseudo[i] = find_Tmoist(theThetae[i], press[i] * hPa2pa)
return Tdew,Temp,Tpseudo
def rv_diff(press,thetae_mix,rT_mix):
"""
the lcl is is the pressure where rv=rT_mix
we want a difference that changes sign at cloud base
so below cloud set rv = rsat(temp,press) and
rT_mix - rv will be negative below cloud base and
positive above cloud base
"""
Temp, rv, rl = tinvert_thetae(thetae_mix,rT_mix,press)
#
# below cloud rl ~ 0, so switch to rv=rsat
#
if rl < 1.e-5:
rv=find_rsat(Temp,press)
diff = rT_mix - rv
return diff
# In[7]:
plt.close('all')
from a405thermo.thermlib import tinvert_thetae
mix_level=np.searchsorted(clipped_press[::-1],700.e2)
index=len(clipped_press) - mix_level
mix_press = clipped_press[index]
print('pressure, {:5.3g} hPa dewpoint {:5.3g} K , temp {:5.3g} K' .format(clipped_press[index]*1.e-2,env_Td[index],env_temps[index]))
env_thetae = find_thetaep(env_Td[index],env_temps[index],clipped_press[index])
env_rvap = env_rvaps[index]
print('cloud thetae {:5.3f} K, env_thetae {:5.3f} K'.format(sfc_thetae,env_thetae))
fenv=np.linspace(0,1,100.)
logthetae_mix = fenv*np.log(env_thetae) + (1 - fenv)*np.log(sfc_thetae)
rTot_mix = fenv*env_rvap + (1 - fenv)*sfc_rvap
thetae_mix = np.exp(logthetae_mix)
pairs = zip(thetae_mix,rTot_mix)
Tvlist = []
for thetae,rtot in pairs:
temp,rv,rl = tinvert_thetae(thetae,rtot,mix_press)
Tvlist.append(find_Tv(temp,rv,rl))
fig,ax = plt.subplots(1,1,figsize=(10,8))
ax.plot(fenv,Tvlist)
title='cloud environment mixing at {:5.2f} hPa'.format(clipped_press[index]*1.e-2)
out=ax.set(xlabel='fraction of environmental air',ylabel='Mixture Tv (K)',title=title)
# In[ ]:
get_ipython().magic('matplotlib inline')
pa2hPa = 1.e-2
A_press = 1.e5 #Pa
B_press = 4.e4 #Pa
A_temp = 300 #K
RH = 0.8
e = find_esat(A_temp)*RH
A_rv = c.eps*e/(A_press - e)
A_Td = find_Td(A_rv,A_press)
print('tropical surface dewpoint: {} K'.format(A_Td))
A_thetae=find_thetaet(A_Td,A_rv,A_temp,A_press)
print('tropical surface thetae: {} K'.format(A_thetae))
A_temp,A_rv,A_rl = tinvert_thetae(A_thetae,A_rv,A_press)
fields=['id','temp','rv','rl','press']
A_dict = dict(zip(fields,('A',A_temp,A_rv,A_rl,A_press)))
A_tup = calc_enthalpy(A_dict)
print(format_tup(A_tup))
# ### B. Lift to 400 hPa and remove 80% of the liquied water
# In[201]:
plt.close('all')
fig,ax = plt.subplots(1,1,figsize=[10,8])
ax,skew = makeSkewWet(ax,corners=[-15,35])
lcl_temp, lcl_press = find_lcl(A_Td,A_tup.temp,A_tup.press)
import a405thermo.thermlib as tl
#
# set the lcl for 900 hPa to 860 hPa and thetae to 338 K
#
press=860.e2
thetae_900=338. #K
Temp_860=find_Tmoist(thetae_900,press)
rv_860=find_rsat(Temp_860,press)
rv_900 = rv_860 #vapor is conserved
Tdew_860=Temp_860
print("temp,Tdew,rv at LCL press: {} hPa {} C {} C {} kg/kg" .format(n(press*1.e-2),e(k2c(Temp_860)),e(k2c(Tdew_860)),e(rv_900)))
#
# now descend adiabatically to 900 hPa
#
press=900.e2
Temp_900,rv_900,rl_900=tinvert_thetae(thetae_900,rv_900,press)
Tdew_900=find_Td(rv_900,press)
print("temperature and dewpoint at {} hPa hPa = {} C {} C".format(n(press*1.e-2),e(k2c(Temp_900)), e(k2c(Tdew_900))))
#
# draw these on the sounding at 900 hPa as a red circle and blue diamond
#
xplot=convertTempToSkew(Temp_900 - c.Tc,press*pa2hPa,skew)
bot=ax.plot(xplot, press*pa2hPa, 'ro', markersize=14, markerfacecolor='r')
xplot=convertTempToSkew(Tdew_900 - c.Tc,press*pa2hPa,skew)
bot=ax.plot(xplot, press*pa2hPa, 'bd', markersize=14, markerfacecolor='b')
#
#now look at an LCL of 700 hPa -- with thetae = 332 K
#
press=700.e2
thetae_800=332. #K
Temp_700=find_Tmoist(thetae_800,press)
