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Microphysics_Arctic_1M.pyx
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Microphysics_Arctic_1M.pyx
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#!python
#cython: boundscheck=False
#cython: wraparound=False
#cython: initializedcheck=False
#cython: cdivision=True
import numpy as np
cimport numpy as np
cimport Grid
cimport ReferenceState
cimport PrognosticVariables
cimport DiagnosticVariables
cimport TimeStepping
cimport Lookup
cimport Thermodynamics
import cython
from Thermodynamics cimport LatentHeat, ClausiusClapeyron
from NetCDFIO cimport NetCDFIO_Stats
cimport ParallelMPI
from libc.math cimport fmax, fmin, fabs
cdef extern from "microphysics_arctic_1m.h":
void sedimentation_velocity_rain(Grid.DimStruct *dims, double* density, double* nrain, double* qrain,
double* qrain_velocity) nogil
void sedimentation_velocity_snow(Grid.DimStruct *dims, double* density, double* nsnow, double* qsnow,
double* qsnow_velocity) nogil
void entropy_source_heating_rain(Grid.DimStruct *dims, double* T, double* Twet, double* qrain,
double* w_qrain, double* w, double* entropy_tendency) nogil
void entropy_source_heating_snow(Grid.DimStruct *dims, double* T, double* Twet, double* qsnow,
double* w_qsnow, double* w, double* entropy_tendency) nogil
void entropy_source_drag(Grid.DimStruct *dims, double* T, double* qprec, double* w_qprec,
double* entropy_tendency) nogil
void get_virtual_potential_temperature(Grid.DimStruct *dims, double* p0, double* T, double* qv,
double* ql, double* qi, double* thetav) nogil
void microphysics_sources(Grid.DimStruct *dims, Lookup.LookupStruct *LT, double (*lam_fp)(double),
double (*L_fp)(double, double), double* density, double* p0,
double* temperature, double* qt, double ccn, double n0_ice,
double* ql, double* qi, double* qrain, double* nrain,
double* qsnow, double* nsnow, double dt,
double* qrain_tendency_micro, double* qrain_tendency,
double* qsnow_tendency_micro, double* qsnow_tendency,
double* precip_rate, double* evap_rate, double* melt_rate) nogil
void qt_source_formation(Grid.DimStruct *dims, double* qt_tendency, double* precip_rate, double* evap_rate) nogil
void evaporation_snow_wrapper(Grid.DimStruct *dims, Lookup.LookupStruct *LT, double (*lam_fp)(double),
double (*L_fp)(double, double), double* density, double* p0, double* temperature,
double* qt, double* qsnow, double* nsnow, double* qsnow_tendency) nogil
void accretion_all_wrapper(Grid.DimStruct *dims, double* density, double* p0, double* temperature, double n0_ice, double ccn,
double* ql, double* qi, double* qrain, double* nrain, double* qsnow, double* nsnow,
double* ql_tendency, double* qi_tendency, double* qrain_tendency, double* qsnow_tendency) nogil
void autoconversion_snow_wrapper(Grid.DimStruct *dims, Lookup.LookupStruct *LT, double (*lam_fp)(double),
double (*L_fp)(double, double), double n0_ice, double* density, double* p0, double* temperature,
double* qt, double* qi, double* qsnow_tendency) nogil
void melt_snow_wrapper(Grid.DimStruct *dims, double* density, double* temperature, double* qsnow, double* nsnow,
double* qsnow_tendency) nogil
void autoconversion_rain_wrapper(Grid.DimStruct *dims, double* density, double ccn, double* ql, double* qrain,
double* nrain, double* qrain_tendency) nogil
void evaporation_rain_wrapper(Grid.DimStruct *dims, Lookup.LookupStruct *LT, double (*lam_fp)(double),
double (*L_fp)(double, double), double* density, double* p0, double* temperature,
double* qt, double* qrain, double* nrain, double* qrain_tendency) nogil
void get_rain_n0(Grid.DimStruct *dims, double* density, double* qrain, double* nrain) nogil
void get_snow_n0(Grid.DimStruct *dims, double* density, double* qsnow, double* nsnow) nogil
void entropy_source_evaporation(Grid.DimStruct *dims, Lookup.LookupStruct *LT, double (*lam_fp)(double),
double (*L_fp)(double, double), double* p0, double* temperature,
double* Twet, double* qt, double* qv, double* evap_rate, double* entropy_tendency)
void entropy_source_precipitation(Grid.DimStruct *dims, Lookup.LookupStruct *LT, double (*lam_fp)(double),
double (*L_fp)(double, double), double* p0, double* temperature,
double* qt, double* qv, double* precip_rate, double* entropy_tendency)
void entropy_source_melt(Grid.DimStruct *dims, double* temperature, double* melt_rate, double* entropy_tendency)
cdef extern from "microphysics.h":
void microphysics_wetbulb_temperature(Grid.DimStruct *dims, Lookup.LookupStruct *LT, double* p0, double* s,
double* qt, double* T, double* Twet )nogil
cdef extern from "advection_interpolation.h":
double interp_2(double phi, double phip1) nogil
cdef extern from "scalar_advection.h":
void compute_advective_fluxes_a(Grid.DimStruct *dims, double *rho0, double *rho0_half, double *velocity,
double *scalar, double* flux, int d, int scheme) nogil
cdef class Microphysics_Arctic_1M:
def __init__(self, ParallelMPI.ParallelMPI Par, LatentHeat LH, namelist):
self.thermodynamics_type = 'SA'
#Get namelist variables
try:
self.ccn = namelist['microphysics']['ccn']
except:
self.ccn = 100.0e6
try:
self.n0_ice_input = namelist['microphysics']['n0_ice']
Par.root_print('set n0_ice to be '+self.n0_ice_input)
except:
self.n0_ice_input = 1.0e7
Par.root_print('default n0_ice value 1.0e7')
try:
self.order = namelist['scalar_transport']['order_sedimentation']
except:
self.order = namelist['scalar_transport']['order']
try:
if namelist['microphysics']['phase_partitioning'] == 'liquid_only':
self.Lambda_fp = lambda_constant_Arctic
LH.Lambda_fp = lambda_constant_Arctic
Par.root_print('Using constant liquid fraction = 1.0! ')
elif namelist['microphysics']['phase_partitioning'] == 'Arctic':
self.Lambda_fp = lambda_Arctic
LH.Lambda_fp = lambda_Arctic
Par.root_print('Using Arctic specific liquid fraction by Kaul et al. 2015!')
elif namelist['microphysics']['phase_partitioning'] == 'Cesana':
self.Lambda_fp = lambda_Cesana
LH.Lambda_fp = lambda_Cesana
Par.root_print('Using liquid fraction by Greg Cesana for the Arctic!')
elif namelist['microphysics']['phase_partitioning'] == 'Hu2010':
self.Lambda_fp = lambda_Hu2010
LH.Lambda_fp = lambda_Hu2010
Par.root_print('Using CALIPSO derived liquid fraction by Hu et al. 2015!')
except:
self.Lambda_fp = lambda_logistic
LH.Lambda_fp = lambda_logistic
Par.root_print('Using default logistic function as liquid fraction!')
LH.L_fp = latent_heat_Arctic
self.L_fp = latent_heat_Arctic
# self.Lambda_fp = LH.Lambda_fp
self.CC = ClausiusClapeyron()
self.CC.initialize(namelist, LH, Par)
return
cpdef initialize(self, Grid.Grid Gr, PrognosticVariables.PrognosticVariables PV, DiagnosticVariables.DiagnosticVariables DV, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
self.precip_rate = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
self.evap_rate = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
self.melt_rate = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
#Add precipitation variables
PV.add_variable('qrain', 'kg kg^-1', r'q_r', 'rain water specific humidity', "sym", "scalar", Pa)
PV.add_variable('qsnow', 'kg kg^-1', r'q_s', 'snow water specific humidity', "sym", "scalar", Pa)
# add sedimentation velocities as diagnostic variables (the format has to be w_q)
DV.add_variables('w_qrain', 'm/s', r'w_{qr}', 'rain mass sedimentation veloctiy', 'sym', Pa)
DV.add_variables('w_qsnow', 'm/s', r'w_{qs}', 'snow mass sedimentation veloctiy', 'sym', Pa)
# add number concentrations as DV
DV.add_variables('nrain', '1/kg', r'n_r', 'rain droplet number concentration', 'sym', Pa)
DV.add_variables('nsnow', '1/kg', r'n_s', 'snow droplet number concentration', 'sym', Pa)
# add wet bulb temperature
DV.add_variables('temperature_wb', 'K', r'T_{wb}','wet bulb temperature', 'sym', Pa)
NS.add_profile('evap_rate', Gr, Pa)
NS.add_profile('precip_rate', Gr, Pa)
NS.add_profile('melt_rate', Gr, Pa)
NS.add_profile('rain_auto_mass', Gr, Pa)
NS.add_profile('snow_auto_mass', Gr, Pa)
NS.add_profile('rain_accr_mass', Gr, Pa)
NS.add_profile('snow_accr_mass', Gr, Pa)
NS.add_profile('rain_evap_mass', Gr, Pa)
NS.add_profile('snow_depo_mass', Gr, Pa)
NS.add_profile('snow_melt_mass', Gr, Pa)
NS.add_profile('rain_sedimentation_flux', Gr, Pa)
NS.add_profile('snow_sedimentation_flux', Gr, Pa)
NS.add_profile('micro_s_source_precipitation', Gr, Pa)
NS.add_profile('micro_s_source_evaporation', Gr, Pa)
NS.add_profile('micro_s_source_melt', Gr, Pa)
NS.add_profile('thetav_mean', Gr, Pa)
NS.add_profile('thetav_flux_z', Gr, Pa)
NS.add_ts('iwp', Gr, Pa)
NS.add_ts('rwp', Gr, Pa)
NS.add_ts('swp', Gr, Pa)
NS.add_profile('cloud_fraction_ice', Gr, Pa)
NS.add_profile('cloud_fraction_mixed_phase', Gr, Pa)
NS.add_ts('cloud_fraction_ice', Gr, Pa)
NS.add_ts('cloud_fraction_mixed_phase', Gr, Pa)
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, Th,
PrognosticVariables.PrognosticVariables PV, DiagnosticVariables.DiagnosticVariables DV,
TimeStepping.TimeStepping TS, ParallelMPI.ParallelMPI Pa):
#Get parameters
cdef:
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
Py_ssize_t w_shift = PV.get_varshift(Gr, 'w')
Py_ssize_t s_shift = PV.get_varshift(Gr, 's')
Py_ssize_t qt_shift = PV.get_varshift(Gr, 'qt')
Py_ssize_t qrain_shift = PV.get_varshift(Gr, 'qrain')
Py_ssize_t qsnow_shift = PV.get_varshift(Gr, 'qsnow')
Py_ssize_t nrain_shift = DV.get_varshift(Gr, 'nrain')
Py_ssize_t nsnow_shift = DV.get_varshift(Gr, 'nsnow')
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
Py_ssize_t ql_shift = DV.get_varshift(Gr, 'ql')
Py_ssize_t qi_shift = DV.get_varshift(Gr, 'qi')
Py_ssize_t qv_shift = DV.get_varshift(Gr, 'qv')
Py_ssize_t tw_shift = DV.get_varshift(Gr, 'temperature_wb')
Py_ssize_t wqrain_shift = DV.get_varshift(Gr, 'w_qrain')
Py_ssize_t wqsnow_shift = DV.get_varshift(Gr, 'w_qsnow')
double [:] qrain_tend_micro = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
double [:] qsnow_tend_micro = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
# Calculate sedimentation before anything else to get N0
get_rain_n0(&Gr.dims, &Ref.rho0_half[0], &PV.values[qrain_shift], &DV.values[nrain_shift])
get_snow_n0(&Gr.dims, &Ref.rho0_half[0], &PV.values[qsnow_shift], &DV.values[nsnow_shift])
# Microphysics source terms
microphysics_sources(&Gr.dims, &self.CC.LT.LookupStructC, self.Lambda_fp, self.L_fp, &Ref.rho0_half[0],
&Ref.p0_half[0], &DV.values[t_shift], &PV.values[qt_shift], self.ccn, self.n0_ice_input,
&DV.values[ql_shift], &DV.values[qi_shift], &PV.values[qrain_shift], &DV.values[nrain_shift],
&PV.values[qsnow_shift], &DV.values[nsnow_shift], TS.dt,
&qrain_tend_micro[0], &PV.tendencies[qrain_shift],
&qsnow_tend_micro[0], &PV.tendencies[qsnow_shift], &self.precip_rate[0], &self.evap_rate[0],
&self.melt_rate[0])
sedimentation_velocity_rain(&Gr.dims, &Ref.rho0_half[0], &DV.values[nrain_shift], &PV.values[qrain_shift],
&DV.values[wqrain_shift])
sedimentation_velocity_snow(&Gr.dims, &Ref.rho0_half[0], &DV.values[nsnow_shift], &PV.values[qsnow_shift],
&DV.values[wqsnow_shift])
qt_source_formation(&Gr.dims, &PV.tendencies[qt_shift], &self.precip_rate[0], &self.evap_rate[0])
#Entropy tendencies due to microphysics
microphysics_wetbulb_temperature(&Gr.dims, &self.CC.LT.LookupStructC, &Ref.p0_half[0], &PV.values[s_shift],
&PV.values[qt_shift], &DV.values[t_shift], &DV.values[tw_shift])
entropy_source_precipitation(&Gr.dims, &self.CC.LT.LookupStructC, self.Lambda_fp, self.L_fp, &Ref.p0_half[0],
&DV.values[t_shift], &PV.values[qt_shift], &DV.values[qv_shift],
&self.precip_rate[0], &PV.tendencies[s_shift])
entropy_source_evaporation(&Gr.dims, &self.CC.LT.LookupStructC, self.Lambda_fp, self.L_fp, &Ref.p0_half[0],
&DV.values[t_shift], &DV.values[tw_shift], &PV.values[qt_shift],
&DV.values[qv_shift], &self.evap_rate[0], &PV.tendencies[s_shift])
entropy_source_melt(&Gr.dims, &DV.values[t_shift], &self.melt_rate[0], &PV.tendencies[s_shift])
entropy_source_heating_rain(&Gr.dims, &DV.values[t_shift], &DV.values[tw_shift], &PV.values[qrain_shift],
&DV.values[wqrain_shift], &PV.values[w_shift], &PV.tendencies[s_shift])
entropy_source_heating_snow(&Gr.dims, &DV.values[t_shift], &DV.values[tw_shift], &PV.values[qsnow_shift],
&DV.values[wqsnow_shift], &PV.values[w_shift], &PV.tendencies[s_shift])
entropy_source_drag(&Gr.dims, &DV.values[t_shift], &PV.values[qrain_shift], &DV.values[wqrain_shift],
&PV.tendencies[s_shift])
entropy_source_drag(&Gr.dims, &DV.values[t_shift], &PV.values[qsnow_shift], &DV.values[wqsnow_shift],
&PV.tendencies[s_shift])
return
cpdef stats_io(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, Th, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
cdef:
Py_ssize_t qt_shift = PV.get_varshift(Gr, 'qt')
Py_ssize_t w_shift = PV.get_varshift(Gr, 'w')
Py_ssize_t qv_shift = DV.get_varshift(Gr, 'qv')
Py_ssize_t ql_shift = DV.get_varshift(Gr, 'ql')
Py_ssize_t qi_shift = DV.get_varshift(Gr, 'qi')
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
Py_ssize_t tw_shift = DV.get_varshift(Gr, 'temperature_wb')
double [:] tmp = np.zeros((Gr.dims.npg), dtype=np.double, order='c')
double [:] tmp_tendency = np.zeros((Gr.dims.npg), dtype=np.double, order='c')
Py_ssize_t qrain_shift = PV.get_varshift(Gr, 'qrain')
Py_ssize_t qsnow_shift = PV.get_varshift(Gr, 'qsnow')
Py_ssize_t wqrain_shift = DV.get_varshift(Gr, 'w_qrain')
Py_ssize_t wqsnow_shift = DV.get_varshift(Gr, 'w_qsnow')
Py_ssize_t nsnow_shift = DV.get_varshift(Gr, 'nsnow')
Py_ssize_t nrain_shift = DV.get_varshift(Gr, 'nrain')
double [:] dummy = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
double [:] dummy2 = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
double [:] dummy3 = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
double [:] dummy4 = np.zeros((Gr.dims.npg,), dtype=np.double, order='c')
tmp = Pa.HorizontalMean(Gr, &self.precip_rate[0])
NS.write_profile('precip_rate', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
tmp = Pa.HorizontalMean(Gr, &self.evap_rate[0])
NS.write_profile('evap_rate', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
tmp = Pa.HorizontalMean(Gr, &self.melt_rate[0])
NS.write_profile('melt_rate', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
autoconversion_rain_wrapper(&Gr.dims, &Ref.rho0_half[0], self.ccn, &DV.values[ql_shift], &PV.values[qrain_shift],
&DV.values[nrain_shift], &dummy[0])
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('rain_auto_mass', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
dummy[:] = 0.0
autoconversion_snow_wrapper(&Gr.dims, &self.CC.LT.LookupStructC, self.Lambda_fp, self.L_fp, self.n0_ice_input,
&Ref.rho0_half[0], &Ref.p0_half[0], &DV.values[t_shift], &PV.values[qt_shift],
&DV.values[qi_shift], &dummy[0])
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('snow_auto_mass', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
dummy[:] = 0.0
evaporation_rain_wrapper(&Gr.dims, &self.CC.LT.LookupStructC, self.Lambda_fp, self.L_fp, &Ref.rho0_half[0],
&Ref.p0_half[0], &DV.values[t_shift], &PV.values[qt_shift], &PV.values[qrain_shift],
&DV.values[nrain_shift], &dummy[0])
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('rain_evap_mass', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
dummy[:] = 0.0
evaporation_snow_wrapper(&Gr.dims, &self.CC.LT.LookupStructC, self.Lambda_fp, self.L_fp, &Ref.rho0_half[0],
&Ref.p0_half[0], &DV.values[t_shift], &PV.values[qt_shift], &PV.values[qsnow_shift],
&DV.values[nsnow_shift], &dummy[0])
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('snow_depo_mass', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
dummy[:] = 0.0
accretion_all_wrapper(&Gr.dims, &Ref.rho0_half[0], &Ref.p0_half[0], &DV.values[t_shift], self.n0_ice_input, self.ccn,
&DV.values[ql_shift], &DV.values[qi_shift], &PV.values[qrain_shift], &DV.values[nrain_shift],
&PV.values[qsnow_shift], &DV.values[nsnow_shift], &dummy2[0], &dummy3[0],
&dummy4[0], &dummy[0])
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('snow_accr_mass', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
tmp = Pa.HorizontalMean(Gr, &dummy4[0])
NS.write_profile('rain_accr_mass', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
dummy[:] = 0.0
melt_snow_wrapper(&Gr.dims, &Ref.rho0_half[0], &DV.values[t_shift], &PV.values[qsnow_shift],
&DV.values[nsnow_shift], &dummy[0])
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('snow_melt_mass', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
#compute sedimentation flux only of qrain and qsnow
compute_advective_fluxes_a(&Gr.dims, &Ref.rho0[0], &Ref.rho0_half[0], &DV.values[wqrain_shift],
&PV.values[qrain_shift], &dummy[0], 2, self.order)
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('rain_sedimentation_flux', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
compute_advective_fluxes_a(&Gr.dims, &Ref.rho0[0], &Ref.rho0_half[0], &DV.values[wqsnow_shift],
&PV.values[qsnow_shift], &dummy[0], 2, self.order)
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('snow_sedimentation_flux', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
get_virtual_potential_temperature(&Gr.dims, &Ref.p0_half[0], &DV.values[t_shift], &DV.values[qv_shift],
&DV.values[ql_shift], &DV.values[qi_shift], &dummy[0])
tmp = Pa.HorizontalMean(Gr, &dummy[0])
NS.write_profile('thetav_mean', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
tmp = Pa.HorizontalMeanofSquares(Gr, &PV.values[w_shift], &dummy[0])
NS.write_profile('thetav_flux_z', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
#Output entropy source terms due to microphysics
entropy_source_precipitation(&Gr.dims, &self.CC.LT.LookupStructC, self.Lambda_fp, self.L_fp, &Ref.p0_half[0],
&DV.values[t_shift], &PV.values[qt_shift], &DV.values[qv_shift],
&self.precip_rate[0], &tmp_tendency[0])
tmp = Pa.HorizontalMean(Gr, &tmp_tendency[0])
NS.write_profile('micro_s_source_precipitation', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
tmp_tendency[:] = 0.0
entropy_source_evaporation(&Gr.dims, &self.CC.LT.LookupStructC, self.Lambda_fp, self.L_fp, &Ref.p0_half[0],
&DV.values[t_shift], &DV.values[tw_shift], &PV.values[qt_shift],
&DV.values[qv_shift], &self.evap_rate[0], &tmp_tendency[0])
tmp = Pa.HorizontalMean(Gr, &tmp_tendency[0])
NS.write_profile('micro_s_source_evaporation', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
tmp_tendency[:] = 0.0
entropy_source_melt(&Gr.dims, &DV.values[t_shift], &self.melt_rate[0], &tmp_tendency[0])
tmp = Pa.HorizontalMean(Gr, &tmp_tendency[0])
NS.write_profile('micro_s_source_melt', tmp[Gr.dims.gw:-Gr.dims.gw], Pa)
self.ice_stats(Gr, Ref, PV, DV, NS, Pa)
return
cpdef ice_stats(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
cdef:
Py_ssize_t kmin = 0
Py_ssize_t kmax = Gr.dims.n[2]
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t pi, k
ParallelMPI.Pencil z_pencil = ParallelMPI.Pencil()
Py_ssize_t qi_shift = DV.get_varshift(Gr, 'qi')
Py_ssize_t qrain_shift = PV.get_varshift(Gr, 'qrain')
Py_ssize_t qsnow_shift = PV.get_varshift(Gr, 'qsnow')
Py_ssize_t ql_shift = DV.get_varshift(Gr, 'ql')
double[:, :] qi_pencils
double[:, :] qrain_pencils
double[:, :] qsnow_pencils
double[:, :] ql_pencils
# Cloud indicator
double[:] ci
double cb
double ct
# Weighted sum of local cloud indicator
double ci_weighted_sum = 0.0
double mean_divisor = np.double(Gr.dims.n[0] * Gr.dims.n[1])
double dz = Gr.dims.dx[2]
double[:] iwp
double[:] rwp
double[:] swp
double iwp_weighted_sum = 0.0
double rwp_weighted_sum = 0.0
double swp_weighted_sum = 0.0
double[:] cf_profile = np.zeros((Gr.dims.n[2]), dtype=np.double, order='c')
# Initialize the z-pencil
z_pencil.initialize(Gr, Pa, 2)
qi_pencils = z_pencil.forward_double( &Gr.dims, Pa, &DV.values[qi_shift])
qrain_pencils = z_pencil.forward_double( &Gr.dims, Pa, &PV.values[qrain_shift])
qsnow_pencils = z_pencil.forward_double( &Gr.dims, Pa, &PV.values[qsnow_shift])
ql_pencils = z_pencil.forward_double( &Gr.dims, Pa, &DV.values[ql_shift])
# Compute liquid, ice, rain, and snow water paths
iwp = np.empty((z_pencil.n_local_pencils), dtype=np.double, order='c')
rwp = np.empty((z_pencil.n_local_pencils), dtype=np.double, order='c')
swp = np.empty((z_pencil.n_local_pencils), dtype=np.double, order='c')
with nogil:
for pi in xrange(z_pencil.n_local_pencils):
iwp[pi] = 0.0
rwp[pi] = 0.0
swp[pi] = 0.0
for k in xrange(kmin, kmax):
iwp[pi] += Ref.rho0_half[k] * qi_pencils[pi, k] * dz
rwp[pi] += Ref.rho0_half[k] * qrain_pencils[pi, k] * dz
swp[pi] += Ref.rho0_half[k] * qsnow_pencils[pi, k] * dz
for pi in xrange(z_pencil.n_local_pencils):
iwp_weighted_sum += iwp[pi]
rwp_weighted_sum += rwp[pi]
swp_weighted_sum += swp[pi]
iwp_weighted_sum /= mean_divisor
rwp_weighted_sum /= mean_divisor
swp_weighted_sum /= mean_divisor
iwp_weighted_sum = Pa.domain_scalar_sum(iwp_weighted_sum)
NS.write_ts('iwp', iwp_weighted_sum, Pa)
rwp_weighted_sum = Pa.domain_scalar_sum(rwp_weighted_sum)
NS.write_ts('rwp', rwp_weighted_sum, Pa)
swp_weighted_sum = Pa.domain_scalar_sum(swp_weighted_sum)
NS.write_ts('swp', swp_weighted_sum, Pa)
# Compute cloud fraction for ice
with nogil:
for pi in xrange(z_pencil.n_local_pencils):
for k in xrange(kmin, kmax):
if qi_pencils[pi, k] > 0.0:
cf_profile[k] += 1.0 / mean_divisor
cf_profile = Pa.domain_vector_sum(cf_profile, Gr.dims.n[2])
NS.write_profile('cloud_fraction_ice', cf_profile, Pa)
# Compute all or nothing ice cloud fraction
ci = np.empty((z_pencil.n_local_pencils), dtype=np.double, order='c')
with nogil:
for pi in xrange(z_pencil.n_local_pencils):
for k in xrange(kmin, kmax):
if qi_pencils[pi, k] > 0.0:
ci[pi] = 1.0
break
else:
ci[pi] = 0.0
for pi in xrange(z_pencil.n_local_pencils):
ci_weighted_sum += ci[pi]
ci_weighted_sum /= mean_divisor
ci_weighted_sum = Pa.domain_scalar_sum(ci_weighted_sum)
NS.write_ts('cloud_fraction_ice', ci_weighted_sum, Pa)
# Compute mixed-phase cloud fraction
cf_profile = np.zeros((Gr.dims.n[2]), dtype=np.double, order='c')
with nogil:
for pi in xrange(z_pencil.n_local_pencils):
for k in xrange(kmin, kmax):
if (ql_pencils[pi, k]+qi_pencils[pi, k]) > 0.0:
cf_profile[k] += 1.0 / mean_divisor
cf_profile = Pa.domain_vector_sum(cf_profile, Gr.dims.n[2])
NS.write_profile('cloud_fraction_mixed_phase', cf_profile, Pa)
# Compute all or nothing mixed-phase cloud fraction
ci = np.empty((z_pencil.n_local_pencils), dtype=np.double, order='c')
with nogil:
for pi in xrange(z_pencil.n_local_pencils):
for k in xrange(kmin, kmax):
if (ql_pencils[pi, k]+qi_pencils[pi, k]) > 0.0:
ci[pi] = 1.0
break
else:
ci[pi] = 0.0
for pi in xrange(z_pencil.n_local_pencils):
ci_weighted_sum += ci[pi]
ci_weighted_sum /= mean_divisor
ci_weighted_sum = Pa.domain_scalar_sum(ci_weighted_sum)
NS.write_ts('cloud_fraction_mixed_phase', ci_weighted_sum, Pa)
return