def thetaEchange(Tguess, thetaE0, press):
"""
thetaEchange(Tguess, thetaE0, press)
Evaluates the equation and passes it back to brenth.
Parameters
- - - - - -
Tguess : float
Trial temperature value (K).
ws0 : float
Initial saturated mixing ratio (kg/kg).
press : float
Pressure (Pa).
Returns
- - - -
theDiff : float
The difference between the values of 'thetaEguess' and
'thetaE0'. This difference is then compared to the tolerance
allowed by brenth.
"""
q = wsat(Tguess, press)
#assume no liquid water
thetaEguess = thermo.theta_e(Tguess, press, q, 0);
#when this result is small enough we're done
theDiff = thetaEguess - thetaE0;
return theDiff
def plot_rt_vs_theta_alpha(p, T, r, rl, alpha):
theta_l = thermo.theta_l(p, T, r, rl)
theta_e = thermo.theta_e(p, T, r, rl)
theta_alpha = (1. - alpha)*theta_l + alpha*theta_e
rt = r + rl
ax = subplot(1,1,1)
ax.plot(theta_alpha, rt*1000)
yl = ax.get_ylim()
if yl[0] < yl[1]: ax.set_ylim([yl[1], yl[0]])
def make_skewT(tmin, tmax, pmax, pmin, skew=30.):
#make a blank skewT diagram
clf()
#get a dense range of p, t0 to contour
yplot = linspace(1050, 100, 100)
xplot = linspace(-50, 50, 100)
xplot, yplot = meshgrid(xplot, yplot)
#lay down a reference grid that labels xplot,yplot points
#in the new (skewT-lnP) coordinate system .
# Each value of the temp matrix holds the actual (data) temperature
# label (in deg C) of the xplot, yplot coordinate pairs
#note that we don't have to transform the y coordinate
#it's still the pressure
#use the real (data) value to get the potential temperature
T = xplot + skew*log(0.001*yplot)
Tk = T + 273.15 #convert from C to K for use in thermo functios
p = yplot*100. #convert from hPa to Pa
th = thermo.theta(p, Tk) #theta labels
#add the mixing ratio
rstar = thermo.r_star(p, Tk) #wsat labels
#saturated adiabat, so Tdew=Tk
thetaeVals = thermo.theta_e(p, Tk, rstar, 0.)
tempLabels = arange(-140., 50., 10.)
con1 = contour(xplot, yplot, T, levels = tempLabels, colors = 'k', linewidths=.5)
ax = gca()
ax.set_yscale('log')
lines = arange(100., 1100., 100.)
yticks(lines, ['100','200','300','400','500','600','700','800','900','1000'])
for line in lines:
axhline(line, ls=':', color='k', linewidth=.5)
thetaLabels = arange(200., 380., 10.)
con2 = contour(xplot, yplot, th, levels = thetaLabels, colors='b', linewidths=.5)
#rsLabels = [.1,.2,.4,.6, 1, 2, 3, 4, 5, 6, 8, 10, 15, 20, 25, 30, 40]
#con3 = contour(xplot, yplot, rstar*1.e3, levels=rsLabels, colors='g', linewidths=.5)
#thetaeLabels = linspace(200,400,21)
#con4 = contour(xplot, yplot, thetaeVals, levels = thetaeLabels, colors='r', linewidths=.5)
axis([tmin, tmax, pmax, pmin])
clabel(con1, inline = False, fmt = '%1.0f')
clabel(con2, inline = False, fmt = '%1.0f')
#clabel(con3, inline = False, fmt = '%1.1f')
#clabel(con4, inline = False, fmt = '%1.0f')
title('skew T - lnp chart')
ylabel('pressure (hPa)')
xlabel('temperature (black, degrees C)')
delhs = np.zeros(len(domsizes))
delhseff = np.zeros(len(domsizes))
p_LCLs = np.zeros(len(domsizes))
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
d = 100000e3 #
p_s = 1000e2 #surface pressure (Pa)
p_t = 200e2 #tropopause (Pa)
p_BL = 900e2 #boundary layer top (Pa)
T_s = 302
delz_BL = z[BLi]
c_E = 0.001
l_d = domsize*1e3*(1./np.sqrt(2))
#r = np.linspace(0, l_d, 1e6)
q_sat = wsat(T_s, p_s) #mixing ratio above sea surface (100% saturated)
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
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)
q_FA = wsat(T_t, p_t) #free troposphere water vapor mixing ratio
zhat = delz_BL/c_E
q_BL = q_sat + 2*zhat*(q_FA - q_sat)/(l_d**2 - rbin_centers**2)*(rbin_centers + zhat - (zhat + l_d)*np.exp((rbin_centers - l_d)/zhat))
RH_c = q_BL/q_sat
if varname == 'QV':
titlename = r'$q_v$'
if varname == 'RH':
import site
import sys
site.addsitedir('/Users/cpatrizio/Dropbox/research/code/thermlib/')
import findTmoist
import findTmoist_new
from wsat import wsat
from constants import constants
import numpy as np
import thermo
import matplotlib.pyplot as plt
T_s = 302
p_s = 1000e2
p_t = 200e2
q_sat = wsat(T_s, p_s)
thetae0 = thermo.theta_e(T_s, p_s, q_sat, 0)
plevs = np.linspace(p_t, p_s, 1000)[::-1]
delp = np.diff(plevs)[0]
c = constants()
gamma_m = 6.5/1000. #lapse rate in K m^-1
gamma_d = 9.8/1000. #lapse rate in K m^-1
Tgm = np.zeros(plevs.shape)
Tgd = np.zeros(plevs.shape)
Tgm[0] = T_s
import site
import sys
site.addsitedir('/Users/cpatrizio/Dropbox/research/code/thermlib/')
import findTmoist
import findTmoist_new
from wsat import wsat
from constants import constants
import numpy as np
import thermo
import matplotlib.pyplot as plt
T_s = 302
p_s = 1000e2
p_t = 200e2
q_sat = wsat(T_s, p_s)
thetae0 = thermo.theta_e(T_s, p_s, q_sat, 0)
plevs = np.linspace(p_t, p_s, 1000)[::-1]
delp = np.diff(plevs)[0]
c = constants()
gamma_m = 6.5 / 1000. #lapse rate in K m^-1
gamma_d = 9.8 / 1000. #lapse rate in K m^-1
Tgm = np.zeros(plevs.shape)
Tgd = np.zeros(plevs.shape)
Tgm[0] = T_s
Tgd[0] = T_s
