def advance_parcel_vars(self):
dt = self.core.dt
qv = self['qv'][0]
T = self['T'][0]
p = self['p'][0]
t = self['t'][0]
rho = p / phys.R(qv) / T
pd = p * (1 - 1 / (1 + const.eps / qv))
# mid-point value for w
dz_dt = self.w(t + dt / 2)
# Explicit Euler for p,T (predictor step assuming dq=0)
dp_dt = -rho * const.g * dz_dt
dpd_dt = dp_dt # dq=0
dT_dt = dp_dt / rho / phys.c_p(qv)
self._tmp['t'][:] += dt
self._tmp['z'][:] += dt * dz_dt
self._tmp['rhod'][:] += dt * (dpd_dt / const.Rd / T +
-dT_dt * pd / const.Rd / T**2)
rhod_mean = (self._tmp['rhod'][0] + self["rhod"][0]) / 2
self.mesh.dv = self.mass_of_dry_air / rhod_mean
def rhod(self, zZ):
Z = self.size[1]
z = zZ * Z # :)
# hydrostatic profile
kappa = const.Rd / const.c_pd
arg = np.power(
self.p0 / const.p1000,
kappa) - z * kappa * const.g / self.th_std0 / phys.R(self.qv0)
p = const.p1000 * np.power(arg, 1 / kappa)
# density using "dry" potential temp.
pd = p * (1 - self.qv0 / (self.qv0 + const.eps))
rhod = pd / (np.power(p / const.p1000, kappa) * const.Rd *
self.th_std0)
return rhod