def find_derivs(var_vec, the_time, cloud_tup):
"""
calcuate derivatives of var_vec
Parameters
----------
var_vec: vector(float)
vector of values to be integrated
the_time: float
timestep
cloud_tup: namedtuple
tuple of necessary coefficients
Returns
-------
deriv_vec: vector(float)
derivatives of each of var_vec
"""
# print('inside: ',var_vec)
temp, press, height = var_vec[-3:]
numrads = len(var_vec) - 3
dry_radius = cloud_tup.dry_radius
rho = press / (c.Rd * temp)
#
# find the evironmental S by water balance
#
S = Scalc(var_vec, cloud_tup)
deriv_vec = np.zeros_like(var_vec)
# dropgrow notes equaton 18 (W&H p. 170)
for i in range(numrads):
m = cloud_tup.masses[i]
if var_vec[i] < dry_radius[i]:
var_vec[i] = dry_radius[i]
Seq = cloud_tup.koehler_fun(var_vec[i], m)
rhovr = (Seq * find_esat(temp)) / (c.Rv * temp)
rhovinf = S * find_esat(temp) / (c.Rv * temp)
# day 25 drop_grow.pdf eqn. 18
deriv_vec[i] = (c.D / (var_vec[i] * c.rhol)) * (rhovinf - rhovr)
#
# moist adiabat day 25 equation 21a
#
deriv_vec[-3] = find_lv(temp) / c.cpd * wlderiv(var_vec, deriv_vec, cloud_tup) - c.g0 / c.cpd * cloud_tup.wvel
#
# hydrostatic balance dp/dt = -rho g dz/dt
#
deriv_vec[-2] = -1.0 * rho * c.g0 * cloud_tup.wvel
#
# how far up have we traveled?
#
deriv_vec[-1] = cloud_tup.wvel
return deriv_vec
def Scalc(var_vec, cloud_tup):
"""
calculate the environmental saturation using conservation
of total water mixing ratio cloud_top.wt and the current
value of the liquid water mixing ratio wl
Parameters
----------
var_vec: vector(float)
vector of values to be integrated
cloud_top: namedtuple
tuple of necessary coefficients
Returns
-------
Sout: float
environmental saturation
"""
temp, press, height = var_vec[-3:]
wl = wlcalc(var_vec, cloud_tup)
wv = cloud_tup.wt - wl
e = wv * press / (c.eps + wv)
Sout = e / find_esat(temp)
return Sout
def find_rsat(temp,press):
"""
input: temp (K)
press (hPa)
output: rsat (kg/kg)
"""
esat = find_esat(temp)*0.01
rsat=c.eps*esat/(press - esat)
return rsat
def therm_calc(the_row):
rT = cloud_vars['wt']
S = the_row[-1]
temp, press,height = the_row[-4:-1]
esat = find_esat(temp)
e = S*esat
rv = c.eps*e/(press - e) #Thompkins eqn 2.20
Td = find_Td(rv,press)
thetae = find_thetaet(Td,rT,temp,press)
hm = c.cpd*temp + find_lv(temp)*rv + c.g0*height
return (thetae, hm)
def zero_rs(temp,rsat,press):
"""
find the saturation temperature for
a given rsat,press, by rootfinding this zero
input: temp (guess) (K)
rsat (kg/kg)
press (hPa)
output: residual
see thompkins 2.20
"""
esat=find_esat(temp)*0.01 #convert to hPa
residual=rsat - c.eps*esat/(press - esat)
return residual
def parse_data(data_text):
all_lines=data_text.strip().split('\n')
count=0
theLine=all_lines[count]
try:
while theLine.find('PRES HGHT TEMP DWPT') < 0:
count += 1
theLine = all_lines[count]
header_names=all_lines[count].lower().split()
except IndexError:
print("no column header line found in sounding")
sys.exit(1)
count += 1 #go to unit names
unit_names=all_lines[count].split()
count+=2 #skip a row of ------
data_list=[]
while True:
try:
the_line=all_lines[count]
dataFields = the_line.split()
if len(dataFields) == 11:
try:
dataFields = [float(number) for number in dataFields]
es = find_esat(dataFields[3] + 273.15)*0.01 #get vapor pressure from dewpoint in hPa
dataFields[5] = (con.eps*es/(dataFields[0] - es))*1.e3 #g/kg
except VauleError:
print('trouble converting dataFields to float')
print(dataFields)
sys.exit(1)
data_list.append(dataFields)
#
# get the next line
#
count += 1
theLine = all_lines[count]
except IndexError:
break
df_out=pd.DataFrame.from_records(data_list,columns=header_names)
return df_out,unit_names
numrads = len(initial_radius)
var_vec = np.empty(numrads + 3)
for i in range(numrads):
var_vec[i] = initial_radius[i]
#
# temp, press and height go at the end of the vector
#
var_vec[-3] = parcel.Tinit
var_vec[-2] = parcel.Pinit
var_vec[-1] = parcel.Zinit
cloud_tup = make_tuple(cloud_vars)
#calculate the total water (kg/kg)
wl=wlcalc(var_vec,cloud_tup);
e=parcel.Sinit*find_esat(parcel.Tinit);
wv=c.eps*e/(parcel.Pinit - e)
#save total water
cloud_vars['wt'] = wv + wl
cloud_vars['wvel'] = parcel.wvel
cloud_vars['wvel'] = 1.5
#
# pass this to the find_derivs function
#
cloud_tup= make_tuple(cloud_vars)
# ### use odeint to integrate the variable in var_vec from tinit to tfin with outputs every dt seconds
# In[43]:
# In[11]:
from a405thermo.thermlib import find_rsat, find_esat
from a405thermo.constants import constants as c
x,y,z,temp = get_var(the_file,'TABS')
x,y,z,press = get_var(the_file,'p')
vert_cross_sec = temp[:,row_number,:end_col]
plt.close('all')
fig,ax = plt.subplots(1,1,figsize=(10,10))
image=ax.pcolormesh(x[:end_col],z,vert_cross_sec[:,:end_col])
cax = plt.colorbar(image,ax=ax)
cax.set_label('temperature (K)')
ax.set_title('vertical temp cross section along y=2 km')
esat = find_esat(temp)
esat.shape
#
# add dimensions to the 1D pressure vectory so
# that it can be used in the denominator
#
press = press[:,np.newaxis,np.newaxis]*100. #convert to Pa
rsat = c.eps*esat/(press - esat)*1.e3 #convert to g/kg
rh = qv/rsat
fig,ax = plt.subplots(1,1,figsize=(10,10))
vert_cross_sec = rh[:,row_number,:end_col]
image=ax.pcolormesh(x[:end_col],z,vert_cross_sec[:,:end_col])
cax = plt.colorbar(image,ax=ax)
cax.set_label('relative humidity')
ax.set_title('relative humidity cross section along y=2 km')
def parse_data(data_text):
"""
Read a single sounding into a dataframe
Parameters
----------
data_text : str
sounding text
Returns
-------
df_out : dataframe
11 column data frame with sounding values
unit_name : list
list of strings with name of units of each column
"""
"""
read lines with 11 numbers and convert to dataframe
data_text looks like:
-----------------------------------------------------------------------------
PRES HGHT TEMP DWPT RELH MIXR DRCT SKNT THTA THTE THTV
hPa m C C % g/kg deg knot K K K
-----------------------------------------------------------------------------
1000.0 100
979.0 288 24.0 23.0 94 18.45 0 0 299.0 353.0 302.2
974.0 333 25.2 21.1 78 16.46 348 0 300.6 349.1 303.6
932.0 719 24.0 16.0 61 12.42 243 3 303.2 340.3 305.4
925.0 785 23.4 15.4 61 12.03 225 3 303.2 339.2 305.4
"""
all_lines=data_text.strip().split('\n')
count=0
theLine=all_lines[count]
try:
while theLine.find('PRES HGHT TEMP DWPT') < 0:
count += 1
theLine = all_lines[count]
header_names=all_lines[count].lower().split()
except IndexError:
print("no column header line found in sounding")
sys.exit(1)
count += 1 #go to unit names
unit_names=all_lines[count].split()
count+=2 #skip a row of ------
data_list=[]
while True:
try:
the_line=all_lines[count]
dataFields = the_line.split()
if len(dataFields) == 11:
try:
dataFields = [float(number) for number in dataFields]
es = find_esat(dataFields[3] + 273.15)*0.01 #get vapor pressure from dewpoint in hPa
dataFields[5] = (con.eps*es/(dataFields[0] - es))*1.e3 #g/kg
except ValueError:
print('trouble converting dataFields to float')
print(dataFields)
sys.exit(1)
data_list.append(dataFields)
#
# get the next line
#
count += 1
theLine = all_lines[count]
except IndexError:
break
df_out=pd.DataFrame.from_records(data_list,columns=header_names)
return df_out,unit_names
rv: {rv:6.3g} kg/kg
rl: {rl:6.3g} kg/kg
rt: {rt:6.3g} kg/kg
enthalpy: {enthalpy: 8.3g} J/kg
"""
return the_string.format_map(the_tup._asdict())
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]:
