RHs = np.zeros(len(domsizes))
Ps = np.zeros(len(domsizes))
delhs = np.zeros(len(domsizes))
delhseff = np.zeros(len(domsizes))
p_LCLs = np.zeros(len(domsizes))
q_BLms = np.zeros(len(domsizes))
omega_ms = np.zeros(len(domsizes))
T_BLcs = np.zeros(len(domsizes))
p_BLcs = np.zeros(len(domsizes))
theta_BLcs = np.zeros(len(domsizes))
q_sat = wsatnew(T_s, p_s) #mixing ratio above sea surface (100% saturated)
thetae0 = thermo.theta_e(T_s, p_s, q_sat, 0) #theta_e in moist region
#use surface temperature to get moist adiaba
T_BLtop = findTmoist(thetae0, p_BL) #temperature of boundary layer top
T_t = findTmoist(thetae0, p_t) #temperature of tropopause (outflow region)
#T_BL = (T_s + T_BLtop)/2. #temperature of boundary layer, consistent with well-mixed assumption (linear mixing)
T_BL = T_s
#T_BLtop = T_BL
q_BLsat = wsatnew(T_BL, (p_s + p_BL)/2.)
q_BLtopsat = wsatnew(T_BLtop, p_BL)
q_FA = wsatnew(T_t, p_t) #free troposphere water vapor mixing ratio
#q_FA = 0.01
#q_FAd = q_FA
#q_FA = 0.001
for i, zeta in enumerate(zeta_levs):
if (zeta < zeta_T):
Tphumb[i] = T_s - gamma_ph*zeta
else:
Tphumb[i] = T_s - gamma_ph*zeta_T
Told = np.zeros(plevs.shape)
Tnew = np.zeros(plevs.shape)
for i, p in enumerate(plevs[:-1]):
Tgm[i+1] = Tgm[i]*(1 + gamma_m*c.Rd*delp/p)
Tgd[i+1] = Tgd[i]*(1+ gamma_d*c.Rd*delp/p)
Told[i] = findTmoist.findTmoist(thetae0, p)
Tnew[i] = findTmoist_new.findTmoist(thetae0, p, q_sat, 0)
plt.figure(1)
plt.plot(Told[:-1], plevs[:-1]/100., color='r', label='Told - root finder moist adiabat')
plt.plot(Tnew[:-1], plevs[:-1]/100., color='b', label='Tnew - root finder moist adiabat')
plt.plot(Tgm[:-1], plevs[:-1]/100., 'g--', label='constant gamma_m')
plt.plot(Tgd[:-1], plevs[:-1]/100., 'k--', label='constant gamma_d')
plt.plot(Tphumb, plevs/100., color ='y', label='pierre humbert profile')
plt.legend()
#plt.gca().invert_yaxis()
plt.show()
for j, domsize in enumerate(domsizes):
l_d = domsize*1000
print l_d/1e3
r = np.linspace(0, l_d, 1e6)
q_sat = wsat(T_s, p_s) #mixing ratio above sea surface (100% saturated)
thetae0 = thermo.theta_e(T_s, p_s, q_sat, 0) #theta_e in moist region
#use surface temperature to get moist adiaba
T_BLtop = findTmoist(thetae0, p_BL) #temperature of boundary layer top
T_t = findTmoist(thetae0, p_t) #temperature of tropopause (outflow region)
#T_BL = (T_s + T_BLtop)/2. #temperature of boundary layer, consistent with well-mixed assumption (linear mixing)
T_BL = T_s
q_BLsat = wsat(T_BL, (p_s + p_BL)/2.)
#q_BLtopsat = wsat(T_BLtop, p_BL)
q_FA = wsat(T_t, p_t) #free troposphere water vapor mixing ratio
#q_FA = 0.01
#q_FAd = q_FA
#q_FA = 0.001
M_trop = (p_BL - p_t)/g #mass of troposphere in kg m^-2
zeta_T = 16
for i, zeta in enumerate(zeta_levs):
if (zeta < zeta_T):
Tphumb[i] = T_s - gamma_ph * zeta
else:
Tphumb[i] = T_s - gamma_ph * zeta_T
Told = np.zeros(plevs.shape)
Tnew = np.zeros(plevs.shape)
for i, p in enumerate(plevs[:-1]):
Tgm[i + 1] = Tgm[i] * (1 + gamma_m * c.Rd * delp / p)
Tgd[i + 1] = Tgd[i] * (1 + gamma_d * c.Rd * delp / p)
Told[i] = findTmoist.findTmoist(thetae0, p)
Tnew[i] = findTmoist_new.findTmoist(thetae0, p, q_sat, 0)
plt.figure(1)
plt.plot(Told[:-1],
plevs[:-1] / 100.,
color='r',
label='Told - root finder moist adiabat')
plt.plot(Tnew[:-1],
plevs[:-1] / 100.,
color='b',
label='Tnew - root finder moist adiabat')
plt.plot(Tgm[:-1], plevs[:-1] / 100., 'g--', label='constant gamma_m')
plt.plot(Tgd[:-1], plevs[:-1] / 100., 'k--', label='constant gamma_d')
plt.plot(Tphumb, plevs / 100., color='y', label='pierre humbert profile')
plt.legend()
#plt.gca().invert_yaxis()