def _create_profile(self):
""" Create a vertical profile that we can interpolate into later.
Integrating with the hydrostatic assumption.
"""
from pyclouds import parameterisations
parameterisation = parameterisations.SaturationVapourPressure()
dz = 100.
R_d = self.R_d
R_v = self.R_v
R_d = self.R_d
cp_d = self.c_p
cp_v = self.cp_v
z = 0.0
p = self.ps
# Cathy suggested using the liquid water potential temperature as the
# temperature in the first model level
T = self.theta_l(0.0)
profile = []
n = 0
while z < self.z_max:
qt = self.q_t(z)
# assume no liquid water
ql = 0.0
qv = qt
qd = 1.0 - qt
theta_l = self.theta_l(z)
R_l = R_d * qd + R_v * qv
c_l = cp_d * qd + cp_v * qv
T = theta_l / ((self.p0 / p)**(R_l / c_l))
# T = self.iteratively_find_temp(theta_l=theta_l, p=p, q_t=qt, q_l=ql, T_initial=T)
rho = 1.0 / (
(qd * R_d + qv * R_v) * T / p) # + 1.0/(ql/rho_l), ql = 0.0
profile.append((z, rho, p, T))
# integrate pressure
z += dz
p += -rho * self.g * dz
n += 1
self._profile = np.array(profile)
def rel_humidity(self, z):
q_v = self.q_t(z)
p = self.p(z)
T = self.temp(z)
from pyclouds import parameterisations
parameterisation = parameterisations.SaturationVapourPressure()
qv_sat = parameterisation.qv_sat(T=T, p=p)
return q_v / qv_sat
def _create_profile(self):
""" Create a vertical profile that we can interpolate into later.
Integrating with the hydrostatic assumption.
"""
try:
from pyclouds import parameterisations
except ImportError:
warnings.warn("pyclouds module couldn't be found, can't create"
"profile for interpolation of rho, T, RH and p")
return
parameterisation = parameterisations.SaturationVapourPressure()
# XXX: R_v and cp_v are not given in the RICO test definition on the
# the KNMI site I will use what I believe are standard values here
self.R_v = parameterisations.common.default_constants.get('R_v')
self.cp_v = parameterisations.common.default_constants.get('cp_v')
dz = 100.
R_d = self.R_d
R_v = self.R_v
R_d = self.R_d
cp_d = self.c_p
cp_v = self.cp_v
z = 0.0
p = self.ps
# Cathy suggested using the liquid water potential temperature as the
# temperature in the first model level
T = self.theta_l(0.0)
profile = []
n = 0
while z < self.z_max:
qt = self.q_t(z)
# assume no liquid water
ql = 0.0
qv = qt
qd = 1.0 - qt
theta_l = self.theta_l(z)
R_l = R_d * qd + R_v * qv
c_l = cp_d * qd + cp_v * qv
T = theta_l / ((self.p0 / p)**(R_l / c_l))
# T = self.iteratively_find_temp(theta_l=theta_l, p=p, q_t=qt, q_l=ql, T_initial=T)
rho = 1.0 / (
(qd * R_d + qv * R_v) * T / p) # + 1.0/(ql/rho_l), ql = 0.0
profile.append((z, rho, p, T))
# integrate pressure
z += dz
p += -rho * self.g * dz
n += 1
self._profile = np.array(profile)