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Surface.pyx
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Surface.pyx
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#!python
#cython: boundscheck=False
#cython: wraparound=False
#cython: initializedcheck=False
#cython: cdivision=True
cimport Grid
cimport ReferenceState
cimport PrognosticVariables
cimport DiagnosticVariables
cimport ParallelMPI
cimport TimeStepping
cimport Radiation
from Thermodynamics cimport LatentHeat,ClausiusClapeyron
from SurfaceBudget cimport SurfaceBudget
from NetCDFIO cimport NetCDFIO_Stats
import cython
from thermodynamic_functions import exner, cpm
from thermodynamic_functions cimport cpm_c, pv_c, pd_c, exner_c
from entropies cimport sv_c, sd_c
from libc.math cimport sqrt, log, fabs,atan, exp, fmax
cimport numpy as np
import numpy as np
include "parameters.pxi"
import cython
cdef extern from "advection_interpolation.h":
double interp_2(double phi, double phip1) nogil
cdef extern from "thermodynamic_functions.h":
double pd_c(double p0, double qt, double qv) nogil
double pv_c(double p0, double qt, double qv) nogil
double exner_c(const double p0) nogil
double theta_rho_c(double p0, double T,double qt, double qv) nogil
double cpm_c(double qt) nogil
cdef extern from "surface.h":
double compute_ustar(double windspeed, double buoyancy_flux, double z0, double z1) nogil
double entropyflux_from_thetaflux_qtflux(double thetaflux, double qtflux, double p0_b, double T_b, double qt_b, double qv_b) nogil
void compute_windspeed(Grid.DimStruct *dims, double* u, double* v, double* speed, double u0, double v0, double gustiness ) nogil
void exchange_coefficients_byun(double Ri, double zb, double z0, double* cm, double* ch, double* lmo) nogil
cdef extern from "entropies.h":
double sd_c(double pd, double T) nogil
double sv_c(double pv, double T) nogil
def SurfaceFactory(namelist, LatentHeat LH, ParallelMPI.ParallelMPI Par):
casename = namelist['meta']['casename']
if casename == 'SullivanPatton':
return SurfaceSullivanPatton(LH)
elif casename == 'Bomex':
return SurfaceBomex(LH)
elif casename == 'Gabls':
return SurfaceGabls(namelist,LH)
elif casename == 'DYCOMS_RF01':
return SurfaceDYCOMS_RF01(namelist, LH)
elif casename == 'DYCOMS_RF02':
return SurfaceDYCOMS_RF02(namelist, LH)
elif casename == 'Rico':
return SurfaceRico(LH)
elif casename == 'Isdac':
return SurfaceIsdac(namelist, LH)
elif casename == 'IsdacCC':
return SurfaceIsdacCC(namelist, LH)
elif casename == 'Mpace':
return SurfaceMpace(namelist, LH)
elif casename == 'Sheba':
return SurfaceSheba(LH)
elif casename == 'CGILS':
return SurfaceCGILS(namelist, LH, Par)
elif casename == 'ZGILS':
return SurfaceZGILS(namelist, LH, Par)
else:
return SurfaceNone()
cdef class SurfaceBase:
def __init__(self):
return
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
self.u_flux = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.v_flux = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.qt_flux = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.s_flux = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.obukhov_length = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.friction_velocity = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.shf = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.lhf = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.b_flux = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
# If not overridden in the specific case, set T_surface = Tg
self.T_surface = Ref.Tg
NS.add_ts('uw_surface_mean', Gr, Pa)
NS.add_ts('vw_surface_mean', Gr, Pa)
NS.add_ts('s_flux_surface_mean', Gr, Pa)
NS.add_ts('shf_surface_mean', Gr, Pa)
NS.add_ts('lhf_surface_mean', Gr, Pa)
NS.add_ts('obukhov_length_mean', Gr, Pa)
NS.add_ts('friction_velocity_mean', Gr, Pa)
NS.add_ts('buoyancy_flux_surface_mean', Gr, Pa)
return
cpdef init_from_restart(self, Restart):
self.T_surface = Restart.restart_data['surf']['T_surf']
return
cpdef restart(self, Restart):
Restart.restart_data['surf'] = {}
Restart.restart_data['surf']['T_surf'] = self.T_surface
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV, ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
cdef :
Py_ssize_t i, j, ijk, ij
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t imax = Gr.dims.nlg[0]-gw
Py_ssize_t jmax = Gr.dims.nlg[1] - gw
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
Py_ssize_t s_shift = PV.get_varshift(Gr, 's')
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
Py_ssize_t ql_shift, qt_shift
double [:] t_mean = Pa.HorizontalMean(Gr, &DV.values[t_shift])
double cp_, lam, lv, pv, pd, sv, sd
double dzi = 1.0/Gr.dims.dx[2]
double tendency_factor = Ref.alpha0_half[gw]/Ref.alpha0[gw-1]*dzi
if self.dry_case:
with nogil:
for i in xrange(gw, imax):
for j in xrange(gw, jmax):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.shf[ij] = self.s_flux[ij] * Ref.rho0_half[gw] * DV.values[t_shift+ijk]
self.b_flux[ij] = self.shf[ij] * g * Ref.alpha0_half[gw]/cpd/t_mean[gw]
self.obukhov_length[ij] = -self.friction_velocity[ij] *self.friction_velocity[ij] *self.friction_velocity[ij] /self.b_flux[ij]/vkb
PV.tendencies[u_shift + ijk] += self.u_flux[ij] * tendency_factor
PV.tendencies[v_shift + ijk] += self.v_flux[ij] * tendency_factor
PV.tendencies[s_shift + ijk] += self.s_flux[ij] * tendency_factor
else:
ql_shift = DV.get_varshift(Gr,'ql')
qt_shift = PV.get_varshift(Gr, 'qt')
with nogil:
for i in xrange(gw, imax):
for j in xrange(gw, jmax):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
lam = self.Lambda_fp(DV.values[t_shift+ijk])
lv = self.L_fp(DV.values[t_shift+ijk],lam)
self.lhf[ij] = self.qt_flux[ij] * Ref.rho0_half[gw] * lv
pv = pv_c(Ref.p0_half[gw], PV.values[ijk + qt_shift], PV.values[ijk + qt_shift] - DV.values[ijk + ql_shift])
pd = pd_c(Ref.p0_half[gw], PV.values[ijk + qt_shift], PV.values[ijk + qt_shift] - DV.values[ijk + ql_shift])
sv = sv_c(pv,DV.values[t_shift+ijk])
sd = sd_c(pd,DV.values[t_shift+ijk])
self.shf[ij] = (self.s_flux[ij] * Ref.rho0_half[gw] - self.lhf[ij]/lv * (sv-sd)) * DV.values[t_shift+ijk]
cp_ = cpm_c(PV.values[qt_shift+ijk])
self.b_flux[ij] = g * Ref.alpha0_half[gw]/cp_/t_mean[gw] * \
(self.shf[ij] + (eps_vi-1.0)*cp_*t_mean[gw]*self.lhf[ij]/lv)
self.obukhov_length[ij] = -self.friction_velocity[ij] *self.friction_velocity[ij] *self.friction_velocity[ij] /self.b_flux[ij]/vkb
PV.tendencies[u_shift + ijk] += self.u_flux[ij] * tendency_factor
PV.tendencies[v_shift + ijk] += self.v_flux[ij] * tendency_factor
PV.tendencies[s_shift + ijk] += self.s_flux[ij] * tendency_factor
PV.tendencies[qt_shift + ijk] += self.qt_flux[ij] * tendency_factor
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
cdef double tmp
tmp = Pa.HorizontalMeanSurface(Gr, &self.u_flux[0])
NS.write_ts('uw_surface_mean', tmp, Pa)
tmp = Pa.HorizontalMeanSurface(Gr, &self.v_flux[0])
NS.write_ts('vw_surface_mean', tmp, Pa)
tmp = Pa.HorizontalMeanSurface(Gr, &self.s_flux[0])
NS.write_ts('s_flux_surface_mean', tmp, Pa)
tmp = Pa.HorizontalMeanSurface(Gr,&self.b_flux[0])
NS.write_ts('buoyancy_flux_surface_mean', tmp, Pa)
tmp = Pa.HorizontalMeanSurface(Gr,&self.shf[0])
NS.write_ts('shf_surface_mean', tmp, Pa)
tmp = Pa.HorizontalMeanSurface(Gr,&self.lhf[0])
NS.write_ts('lhf_surface_mean', tmp, Pa)
tmp = Pa.HorizontalMeanSurface(Gr,&self.friction_velocity[0])
NS.write_ts('friction_velocity_mean', tmp, Pa)
tmp = Pa.HorizontalMeanSurface(Gr,&self.obukhov_length[0])
NS.write_ts('obukhov_length_mean', tmp, Pa)
return
cdef class SurfaceNone(SurfaceBase):
def __init__(self):
pass
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV, ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
return
cdef class SurfaceSullivanPatton(SurfaceBase):
def __init__(self, LatentHeat LH):
self.theta_flux = 0.24 # K m/s
self.z0 = 0.1 #m (Roughness length)
self.gustiness = 0.001 #m/s, minimum surface windspeed for determination of u*
self.L_fp = LH.L_fp
self.Lambda_fp = LH.Lambda_fp
self.dry_case = True
return
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.initialize(self,Gr,Ref,NS,Pa)
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV, ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
# Since this case is completely dry, the computation of entropy flux from sensible heat flux is very simple
if Pa.sub_z_rank != 0:
return
cdef:
Py_ssize_t i, j, ijk, ij
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t imax = Gr.dims.nlg[0]
Py_ssize_t jmax = Gr.dims.nlg[1]
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
Py_ssize_t temp_shift = DV.get_varshift(Gr, 'temperature')
double T0 = Ref.p0_half[Gr.dims.gw] * Ref.alpha0_half[Gr.dims.gw]/Rd
self.buoyancy_flux = self.theta_flux * exner(Ref.p0_half[Gr.dims.gw]) * g /T0
#Get the scalar flux (dry entropy only)
with nogil:
for i in xrange(imax):
for j in xrange(jmax):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.s_flux[ij] = cpd * self.theta_flux*exner_c(Ref.p0_half[gw])/DV.values[temp_shift+ijk]
cdef:
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
double [:] windspeed = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1],dtype=np.double,order='c')
compute_windspeed(&Gr.dims, &PV.values[u_shift], &PV.values[v_shift], &windspeed[0],Ref.u0, Ref.v0,self.gustiness)
# Get the shear stresses
with nogil:
for i in xrange(1,imax):
for j in xrange(1,jmax):
ij = i * istride_2d + j
self.friction_velocity[ij] = compute_ustar(windspeed[ij],self.buoyancy_flux,self.z0, Gr.dims.dx[2]/2.0)
for i in xrange(1,imax-1):
for j in xrange(1,jmax-1):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.u_flux[ij] = -interp_2(self.friction_velocity[ij], self.friction_velocity[ij+istride_2d])**2/interp_2(windspeed[ij], windspeed[ij+istride_2d]) \
* (PV.values[u_shift + ijk] + Ref.u0)
self.v_flux[ij] = -interp_2(self.friction_velocity[ij], self.friction_velocity[ij+1])**2/interp_2(windspeed[ij], windspeed[ij+1]) \
* (PV.values[v_shift + ijk] + Ref.v0)
SurfaceBase.update(self, Gr, Ref, PV, DV, Pa, TS)
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.stats_io(self, Gr, NS, Pa)
return
cdef class SurfaceBomex(SurfaceBase):
def __init__(self, LatentHeat LH):
self.L_fp = LH.L_fp
self.Lambda_fp = LH.Lambda_fp
self.dry_case = False
return
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.initialize(self,Gr,Ref,NS,Pa)
self.qt_flux = np.add(self.qt_flux,5.2e-5) # m/s
self.theta_flux = 8.0e-3 # K m/s
self.ustar_ = 0.28 #m/s
self.theta_surface = 299.1 #K
self.qt_surface = 22.45e-3 # kg/kg
self.buoyancy_flux = g * ((self.theta_flux + (eps_vi-1.0)*(self.theta_surface*self.qt_flux[0]
+ self.qt_surface *self.theta_flux))
/(self.theta_surface*(1.0 + (eps_vi-1)*self.qt_surface)))
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV,ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
if Pa.sub_z_rank != 0:
return
cdef :
Py_ssize_t i
Py_ssize_t j
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t ijk, ij
Py_ssize_t imax = Gr.dims.nlg[0]
Py_ssize_t jmax = Gr.dims.nlg[1]
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
Py_ssize_t temp_shift = DV.get_varshift(Gr, 'temperature')
Py_ssize_t s_shift = PV.get_varshift(Gr, 's')
Py_ssize_t qt_shift = PV.get_varshift(Gr, 'qt')
Py_ssize_t qv_shift = DV.get_varshift(Gr,'qv')
# Get the scalar flux
with nogil:
for i in xrange(imax):
for j in xrange(jmax):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.friction_velocity[ij] = self.ustar_
self.s_flux[ij] = entropyflux_from_thetaflux_qtflux(self.theta_flux, self.qt_flux[ij], Ref.p0_half[gw],
DV.values[temp_shift+ijk], PV.values[qt_shift+ijk], DV.values[qv_shift+ijk])
cdef:
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
double [:] windspeed = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
compute_windspeed(&Gr.dims, &PV.values[u_shift], &PV.values[v_shift], &windspeed[0], Ref.u0, Ref.v0, self.gustiness)
# Get the shear stresses
with nogil:
for i in xrange(1,imax-1):
for j in xrange(1,jmax-1):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.u_flux[ij] = -self.ustar_**2/interp_2(windspeed[ij], windspeed[ij+istride_2d]) * (PV.values[u_shift + ijk] + Ref.u0)
self.v_flux[ij] = -self.ustar_**2/interp_2(windspeed[ij], windspeed[ij+1]) * (PV.values[v_shift + ijk] + Ref.v0)
SurfaceBase.update(self, Gr, Ref, PV, DV, Pa, TS)
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.stats_io(self, Gr, NS, Pa)
return
cdef class SurfaceGabls(SurfaceBase):
def __init__(self, namelist, LatentHeat LH):
self.gustiness = 0.001
self.z0 = 0.1
# Rate of change of surface temperature, in K/hour
# GABLS1 IC (Beare et al) value is 0.25 (given as default)
try:
self.cooling_rate = namelist['surface']['cooling_rate']
except:
self.cooling_rate = 0.25
self.L_fp = LH.L_fp
self.Lambda_fp = LH.Lambda_fp
self.dry_case = True
return
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.initialize(self,Gr,Ref,NS,Pa)
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV,ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
if Pa.sub_z_rank != 0:
return
cdef:
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
Py_ssize_t s_shift = PV.get_varshift(Gr, 's')
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
Py_ssize_t th_shift = DV.get_varshift(Gr, 'theta')
double [:] windspeed = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
compute_windspeed(&Gr.dims, &PV.values[u_shift], &PV.values[v_shift], &windspeed[0], Ref.u0, Ref.v0, self.gustiness)
cdef:
Py_ssize_t i,j, ijk, ij
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t imax = Gr.dims.nlg[0]
Py_ssize_t jmax = Gr.dims.nlg[1]
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
double theta_rho_b, Nb2, Ri
double zb = Gr.dims.dx[2] * 0.5
double [:] cm= np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
double ch=0.0
self.T_surface = 265.0 - self.cooling_rate * TS.t/3600.0 # sst = theta_surface also
cdef double theta_rho_g = theta_rho_c(Ref.Pg, self.T_surface, 0.0, 0.0)
cdef double s_star = sd_c(Ref.Pg,self.T_surface)
with nogil:
for i in xrange(gw-1, imax-gw+1):
for j in xrange(gw-1,jmax-gw+1):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
theta_rho_b = DV.values[th_shift + ijk]
Nb2 = g/theta_rho_g*(theta_rho_b-theta_rho_g)/zb
Ri = Nb2 * zb* zb/(windspeed[ij] * windspeed[ij])
exchange_coefficients_byun(Ri,zb,self.z0, &cm[ij], &ch, &self.obukhov_length[ij])
self.s_flux[ij] = -ch * windspeed[ij] * (PV.values[s_shift+ijk] - s_star)
self.friction_velocity[ij] = sqrt(cm[ij]) * windspeed[ij]
for i in xrange(gw, imax-gw):
for j in xrange(gw, jmax-gw):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.u_flux[ij] = -interp_2(cm[ij], cm[ij+istride_2d])*interp_2(windspeed[ij], windspeed[ij+istride_2d]) * (PV.values[u_shift + ijk] + Ref.u0)
self.v_flux[ij] = -interp_2(cm[ij], cm[ij+1])*interp_2(windspeed[ij], windspeed[ij+1]) * (PV.values[v_shift + ijk] + Ref.v0)
SurfaceBase.update(self, Gr, Ref, PV, DV, Pa, TS)
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.stats_io(self, Gr, NS, Pa)
return
cdef class SurfaceDYCOMS_RF01(SurfaceBase):
def __init__(self,namelist, LatentHeat LH):
self.ft = 15.0
self.fq = 115.0
self.gustiness = 0.0
self.cm = 0.0011
self.L_fp = LH.L_fp
self.Lambda_fp = LH.Lambda_fp
sst = 292.5 # K
psurface = 1017.8e2 # Pa
theta_surface = sst/exner(psurface)
qt_surface = 13.84e-3 # qs(sst) using Teten's formula
density_surface = 1.22 #kg/m^3
theta_flux = self.ft/(density_surface*cpm(qt_surface)*exner(psurface))
qt_flux_ = self.fq/self.L_fp(sst,self.Lambda_fp(sst))
self.buoyancy_flux = g * ((theta_flux + (eps_vi-1.0)*(theta_surface*qt_flux_ + qt_surface * theta_flux))
/(theta_surface*(1.0 + (eps_vi-1)*qt_surface)))
self.dry_case = False
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.initialize(self,Gr,Ref,NS,Pa)
self.windspeed = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.T_surface = 292.5
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV,ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
if Pa.sub_z_rank != 0:
return
cdef:
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
Py_ssize_t s_shift = PV.get_varshift(Gr, 's')
Py_ssize_t qt_shift = PV.get_varshift(Gr, 'qt')
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
Py_ssize_t ql_shift = DV.get_varshift(Gr, 'ql')
compute_windspeed(&Gr.dims, &PV.values[u_shift], &PV.values[v_shift], &self.windspeed[0],Ref.u0, Ref.v0,self.gustiness)
cdef:
Py_ssize_t i,j, ijk, ij
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t imax = Gr.dims.nlg[0]
Py_ssize_t jmax = Gr.dims.nlg[1]
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
double lam, lv, pv, pd, sv, sd
double [:] windspeed = self.windspeed
with nogil:
for i in xrange(gw-1, imax-gw+1):
for j in xrange(gw-1, jmax-gw+1):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.friction_velocity[ij] = sqrt(self.cm) * self.windspeed[ij]
lam = self.Lambda_fp(DV.values[t_shift+ijk])
lv = self.L_fp(DV.values[t_shift+ijk],lam)
pv = pv_c(Ref.p0_half[gw], PV.values[ijk + qt_shift], PV.values[ijk + qt_shift] - DV.values[ijk + ql_shift])
pd = pd_c(Ref.p0_half[gw], PV.values[ijk + qt_shift], PV.values[ijk + qt_shift] - DV.values[ijk + ql_shift])
sv = sv_c(pv,DV.values[t_shift+ijk])
sd = sd_c(pd,DV.values[t_shift+ijk])
self.qt_flux[ij] = self.fq / lv / 1.22
self.s_flux[ij] = Ref.alpha0_half[gw] * (self.ft/DV.values[t_shift+ijk] + self.fq*(sv - sd)/lv)
for i in xrange(gw, imax-gw):
for j in xrange(gw, jmax-gw):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.u_flux[ij] = -self.cm * interp_2(windspeed[ij], windspeed[ij+istride_2d]) * (PV.values[u_shift + ijk] + Ref.u0)
self.v_flux[ij] = -self.cm * interp_2(windspeed[ij], windspeed[ij+1]) * (PV.values[v_shift + ijk] + Ref.v0)
SurfaceBase.update(self, Gr, Ref, PV, DV, Pa,TS)
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.stats_io(self, Gr, NS, Pa)
return
cdef class SurfaceDYCOMS_RF02(SurfaceBase):
def __init__(self,namelist, LatentHeat LH):
self.ft = 16.0
self.fq = 93.0
self.gustiness = 0.0
self.ustar = 0.25
self.L_fp = LH.L_fp
self.Lambda_fp = LH.Lambda_fp
sst = 292.5 # K
psurface = 1017.8e2 # Pa
theta_surface = sst/exner(psurface)
qt_surface = 13.84e-3 # qs(sst) using Teten's formula
density_surface = 1.22 #kg/m^3
theta_flux = self.ft/(density_surface*cpm(qt_surface)*exner(psurface))
qt_flux_ = self.fq/self.L_fp(sst,self.Lambda_fp(sst))
self.buoyancy_flux = g * ((theta_flux + (eps_vi-1.0)*(theta_surface*qt_flux_ + qt_surface * theta_flux))
/(theta_surface*(1.0 + (eps_vi-1)*qt_surface)))
self.dry_case = False
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.initialize(self,Gr,Ref,NS,Pa)
self.windspeed = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
self.T_surface = 292.5 # assuming same sst as DYCOMS RF01
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV,ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
if Pa.sub_z_rank != 0:
return
cdef:
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
Py_ssize_t qt_shift = PV.get_varshift(Gr, 'qt')
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
Py_ssize_t ql_shift = DV.get_varshift(Gr, 'ql')
compute_windspeed(&Gr.dims, &PV.values[u_shift], &PV.values[v_shift], &self.windspeed[0],Ref.u0, Ref.v0,self.gustiness)
cdef:
Py_ssize_t i,j, ijk, ij
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t imax = Gr.dims.nlg[0]
Py_ssize_t jmax = Gr.dims.nlg[1]
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
double tendency_factor = Ref.alpha0_half[gw]/Ref.alpha0[gw-1]/Gr.dims.dx[2]
double lam
double lv
double pv
double pd
double sv
double sd
double [:] windspeed = self.windspeed
with nogil:
for i in xrange(gw-1, imax-gw+1):
for j in xrange(gw-1, jmax-gw+1):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.friction_velocity[ij] = self.ustar
lam = self.Lambda_fp(DV.values[t_shift+ijk])
lv = self.L_fp(DV.values[t_shift+ijk],lam)
pv = pv_c(Ref.p0_half[gw], PV.values[ijk + qt_shift], PV.values[ijk + qt_shift] - DV.values[ijk + ql_shift])
pd = pd_c(Ref.p0_half[gw], PV.values[ijk + qt_shift], PV.values[ijk + qt_shift] - DV.values[ijk + ql_shift])
sv = sv_c(pv,DV.values[t_shift+ijk])
sd = sd_c(pd,DV.values[t_shift+ijk])
self.qt_flux[ij] = self.fq / lv / 1.21
self.s_flux[ij] = Ref.alpha0_half[gw] * (self.ft/DV.values[t_shift+ijk] + self.fq*(sv - sd)/lv)
for i in xrange(gw, imax-gw):
for j in xrange(gw, jmax-gw):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.u_flux[ij] = -self.ustar*self.ustar / interp_2(windspeed[ij], windspeed[ij+istride_2d]) * (PV.values[u_shift + ijk] + Ref.u0)
self.v_flux[ij] = -self.ustar*self.ustar / interp_2(windspeed[ij], windspeed[ij+1]) * (PV.values[v_shift + ijk] + Ref.v0)
SurfaceBase.update(self, Gr, Ref, PV, DV, Pa, TS)
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.stats_io(self, Gr, NS, Pa)
return
cdef class SurfaceRico(SurfaceBase):
def __init__(self, LatentHeat LH):
self.cm =0.001229
self.ch = 0.001094
self.cq = 0.001133
self.z0 = 0.00015
self.gustiness = 0.0
self.L_fp = LH.L_fp
self.Lambda_fp = LH.Lambda_fp
self.dry_case = False
return
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.initialize(self,Gr,Ref,NS,Pa)
self.cm = self.cm*(log(20.0/self.z0)/log(Gr.zl_half[Gr.dims.gw]/self.z0))**2
self.ch = self.ch*(log(20.0/self.z0)/log(Gr.zl_half[Gr.dims.gw]/self.z0))**2
self.cq = self.cq*(log(20.0/self.z0)/log(Gr.zl_half[Gr.dims.gw]/self.z0))**2
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV,ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
cdef double pv_star = pv_c(Ref.Pg, Ref.qtg, Ref.qtg)
cdef double pd_star = Ref.Pg - pv_star
self.s_star = (1.0-Ref.qtg) * sd_c(pd_star, Ref.Tg) + Ref.qtg * sv_c(pv_star,Ref.Tg)
if Pa.sub_z_rank != 0:
return
cdef:
Py_ssize_t i,j, ijk, ij
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t imax = Gr.dims.nlg[0]
Py_ssize_t jmax = Gr.dims.nlg[1]
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
Py_ssize_t s_shift = PV.get_varshift(Gr, 's')
Py_ssize_t qt_shift = PV.get_varshift(Gr, 'qt')
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
double [:] windspeed = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
double ustar_
double buoyancy_flux, theta_flux
double theta_surface = Ref.Tg * exner_c(Ref.Pg)
double cm_sqrt = sqrt(self.cm)
compute_windspeed(&Gr.dims, &PV.values[u_shift], &PV.values[v_shift], &windspeed[0],Ref.u0, Ref.v0,self.gustiness)
with nogil:
for i in xrange(gw, imax-gw):
for j in xrange(gw,jmax-gw):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
theta_flux = -self.ch * windspeed[ij] * (DV.values[t_shift + ijk]*exner_c(Ref.p0_half[gw]) - theta_surface)
self.s_flux[ij] = -self.ch * windspeed[ij] * (PV.values[s_shift + ijk] - self.s_star)
self.qt_flux[ij] = -self.cq * windspeed[ij] * (PV.values[qt_shift + ijk] - Ref.qtg)
buoyancy_flux = g * ((theta_flux + (eps_vi-1.0)*(theta_surface*self.qt_flux[ij] + Ref.qtg * theta_flux))/(theta_surface*(1.0 + (eps_vi-1)*Ref.qtg)))
self.u_flux[ij] = -self.cm * interp_2(windspeed[ij], windspeed[ij + istride_2d]) * (PV.values[u_shift + ijk] + Ref.u0)
self.v_flux[ij] = -self.cm * interp_2(windspeed[ij], windspeed[ij + 1])* (PV.values[v_shift + ijk] + Ref.v0)
ustar_ = cm_sqrt * windspeed[ij]
self.friction_velocity[ij] = ustar_
SurfaceBase.update(self, Gr, Ref, PV, DV, Pa, TS)
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.stats_io(self, Gr, NS, Pa)
return
cdef class SurfaceCGILS(SurfaceBase):
def __init__(self, namelist, LatentHeat LH, ParallelMPI.ParallelMPI Pa):
try:
self.loc = namelist['meta']['CGILS']['location']
if self.loc !=12 and self.loc != 11 and self.loc != 6:
Pa.root_print('Invalid CGILS location (must be 6, 11, or 12)')
Pa.kill()
except:
Pa.root_print('Must provide a CGILS location (6/11/12) in namelist')
Pa.kill()
try:
self.is_p2 = namelist['meta']['CGILS']['P2']
except:
Pa.root_print('Must specify if CGILS run is perturbed')
Pa.kill()
self.gustiness = 0.001
self.z0 = 1.0e-4
self.L_fp = LH.L_fp
self.Lambda_fp = LH.Lambda_fp
self.CC = ClausiusClapeyron()
self.CC.initialize(namelist, LH, Pa)
self.dry_case = False
return
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.initialize(self,Gr,Ref,NS,Pa)
# Find the scalar transfer coefficient consistent with the vertical grid spacing
cdef double z1 = Gr.dims.dx[2] * 0.5
cdef double cq = 1.2e-3
cdef double u10m=0.0, ct_ic=0.0, z1_ic=0.0
if self.loc == 12:
ct_ic = 0.0104
z1_ic = 2.5
elif self.loc == 11:
ct_ic = 0.0081
z1_ic = 12.5
elif self.loc == 6:
ct_ic = 0.0081
z1_ic = 20.0
u10m = ct_ic/cq * np.log(z1_ic/self.z0)**2/np.log(10.0/self.z0)**2
self.ct = cq * u10m * (np.log(10.0/self.z0)/np.log(z1/self.z0))**2
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV,ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
if Pa.sub_z_rank != 0:
return
cdef:
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
Py_ssize_t s_shift = PV.get_varshift(Gr, 's')
Py_ssize_t qt_shift = PV.get_varshift(Gr, 'qt')
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
double [:] windspeed = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
compute_windspeed(&Gr.dims, &PV.values[u_shift], &PV.values[v_shift], &windspeed[0], Ref.u0, Ref.v0, self.gustiness)
cdef:
Py_ssize_t i,j, ijk, ij
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t imax = Gr.dims.nlg[0]
Py_ssize_t jmax = Gr.dims.nlg[1]
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
double zb = Gr.dims.dx[2] * 0.5
double [:] cm = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
double pv_star = self.CC.LT.fast_lookup(self.T_surface)
double qv_star = eps_v * pv_star/(Ref.Pg + (eps_v-1.0)*pv_star)
double [:] t_mean = Pa.HorizontalMean(Gr, &DV.values[t_shift])
double buoyancy_flux, th_flux
double exner_b = exner_c(Ref.p0_half[gw])
double theta_0 = self.T_surface/exner_c(Ref.Pg)
with nogil:
for i in xrange(gw-1, imax-gw+1):
for j in xrange(gw-1,jmax-gw+1):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.qt_flux[ij] = self.ct * (0.98 * qv_star - PV.values[qt_shift + ijk])
th_flux = self.ct * (theta_0 - DV.values[t_shift + ijk]/exner_b )
buoyancy_flux = g * th_flux * exner_b/t_mean[gw] + g * (eps_vi-1.0)*self.qt_flux[ij]
self.friction_velocity[ij] = compute_ustar(windspeed[ij],buoyancy_flux,self.z0, zb)
self.s_flux[ij] = entropyflux_from_thetaflux_qtflux(th_flux, self.qt_flux[ij],
Ref.p0_half[gw], DV.values[t_shift + ijk],
PV.values[qt_shift + ijk], PV.values[qt_shift + ijk])
cm[ij] = (self.friction_velocity[ij]/windspeed[ij]) * (self.friction_velocity[ij]/windspeed[ij])
for i in xrange(gw, imax-gw):
for j in xrange(gw, jmax-gw):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.u_flux[ij] = -interp_2(cm[ij], cm[ij+istride_2d])*interp_2(windspeed[ij], windspeed[ij+istride_2d]) * (PV.values[u_shift + ijk] + Ref.u0)
self.v_flux[ij] = -interp_2(cm[ij], cm[ij+1])*interp_2(windspeed[ij], windspeed[ij+1]) * (PV.values[v_shift + ijk] + Ref.v0)
SurfaceBase.update(self, Gr, Ref, PV, DV, Pa, TS)
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.stats_io(self, Gr, NS, Pa)
return
cdef class SurfaceZGILS(SurfaceBase):
def __init__(self, namelist, LatentHeat LH, ParallelMPI.ParallelMPI Pa):
self.gustiness = 0.001
self.z0 = 1.0e-3
self.L_fp = LH.L_fp
self.Lambda_fp = LH.Lambda_fp
self.CC = ClausiusClapeyron()
self.CC.initialize(namelist, LH, Pa)
self.dry_case = False
try:
self.loc = namelist['meta']['ZGILS']['location']
if self.loc !=12 and self.loc != 11 and self.loc != 6:
Pa.root_print('SURFACE: Invalid ZGILS location (must be 6, 11, or 12) '+ str(self.loc))
Pa.kill()
except:
Pa.root_print('SURFACE: Must provide a ZGILS location (6/11/12) in namelist')
Pa.kill()
# Get the multiplying factor for current levels of CO2
# Then convert to a number of CO2 doublings, which is how forcings are rescaled
try:
co2_factor = namelist['radiation']['RRTM']['co2_factor']
except:
co2_factor = 1.0
n_double_co2 = int(np.log2(co2_factor))
try:
constant_sst = namelist['surface_budget']['constant_sst']
except:
constant_sst = False
# Set the initial sst value to the Fixed-SST case value (Tan et al 2016a, Table 1)
if self.loc == 12:
self.T_surface = 289.8
elif self.loc == 11:
self.T_surface = 292.2
elif self.loc == 6:
self.T_surface = 298.9
# adjust surface temperature for fixed-SST climate change experiments
if constant_sst:
self.T_surface = self.T_surface + 3.0 * n_double_co2
return
cpdef initialize(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.initialize(self,Gr,Ref,NS,Pa)
return
cpdef update(self, Grid.Grid Gr, ReferenceState.ReferenceState Ref, PrognosticVariables.PrognosticVariables PV,
DiagnosticVariables.DiagnosticVariables DV,ParallelMPI.ParallelMPI Pa, TimeStepping.TimeStepping TS):
if Pa.sub_z_rank != 0:
return
cdef:
Py_ssize_t u_shift = PV.get_varshift(Gr, 'u')
Py_ssize_t v_shift = PV.get_varshift(Gr, 'v')
Py_ssize_t s_shift = PV.get_varshift(Gr, 's')
Py_ssize_t qt_shift = PV.get_varshift(Gr, 'qt')
Py_ssize_t t_shift = DV.get_varshift(Gr, 'temperature')
Py_ssize_t th_shift = DV.get_varshift(Gr, 'theta_rho')
double [:] windspeed = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
compute_windspeed(&Gr.dims, &PV.values[u_shift], &PV.values[v_shift], &windspeed[0], Ref.u0, Ref.v0, self.gustiness)
cdef:
Py_ssize_t i,j, ijk, ij
Py_ssize_t gw = Gr.dims.gw
Py_ssize_t imax = Gr.dims.nlg[0]
Py_ssize_t jmax = Gr.dims.nlg[1]
Py_ssize_t istride = Gr.dims.nlg[1] * Gr.dims.nlg[2]
Py_ssize_t jstride = Gr.dims.nlg[2]
Py_ssize_t istride_2d = Gr.dims.nlg[1]
double ustar, t_flux, b_flux
double theta_rho_b, Nb2, Ri
double zb = Gr.dims.dx[2] * 0.5
double [:] cm = np.zeros(Gr.dims.nlg[0]*Gr.dims.nlg[1], dtype=np.double, order='c')
double ch=0.0
double pv_star = self.CC.LT.fast_lookup(self.T_surface)
double qv_star = eps_v * pv_star/(Ref.Pg + (eps_v-1.0)*pv_star)
# Find the surface entropy
double pd_star = Ref.Pg - pv_star
double theta_rho_g = theta_rho_c(Ref.Pg, self.T_surface, qv_star, qv_star)
double s_star = sd_c(pd_star,self.T_surface) * (1.0 - qv_star) + sv_c(pv_star, self.T_surface) * qv_star
double [:] t_mean = Pa.HorizontalMean(Gr, &DV.values[t_shift])
with nogil:
for i in xrange(gw-1, imax-gw+1):
for j in xrange(gw-1,jmax-gw+1):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
theta_rho_b = DV.values[th_shift + ijk]
Nb2 = g/theta_rho_g*(theta_rho_b-theta_rho_g)/zb
Ri = Nb2 * zb * zb/(windspeed[ij] * windspeed[ij])
exchange_coefficients_byun(Ri, zb, self.z0, &cm[ij], &ch, &self.obukhov_length[ij])
self.s_flux[ij] = -ch *windspeed[ij] * (PV.values[s_shift + ijk] - s_star)
self.qt_flux[ij] = -ch *windspeed[ij] * (PV.values[qt_shift + ijk] - qv_star)
ustar = sqrt(cm[ij]) * windspeed[ij]
self.friction_velocity[ij] = ustar
for i in xrange(gw, imax-gw):
for j in xrange(gw, jmax-gw):
ijk = i * istride + j * jstride + gw
ij = i * istride_2d + j
self.u_flux[ij] = -interp_2(cm[ij], cm[ij+istride_2d])*interp_2(windspeed[ij], windspeed[ij+istride_2d]) * (PV.values[u_shift + ijk] + Ref.u0)
self.v_flux[ij] = -interp_2(cm[ij], cm[ij+1])*interp_2(windspeed[ij], windspeed[ij+1]) * (PV.values[v_shift + ijk] + Ref.v0)
SurfaceBase.update(self, Gr, Ref, PV, DV, Pa, TS)
return
cpdef stats_io(self, Grid.Grid Gr, NetCDFIO_Stats NS, ParallelMPI.ParallelMPI Pa):
SurfaceBase.stats_io(self, Gr, NS, Pa)
return