def __init__(self, scheme='cam3', absorber_vmr=None, **kwargs):
super(CliMTRad, self).__init__(**kwargs)
self.r = climt.radiation(scheme=scheme)
self.param['climt_scheme'] = scheme
newinput = [
'q',
'flux_from_sfc',
'cldf',
'clwp',
'absorber_vmr',
]
self.add_input(newinput)
# absorbing gases
if absorber_vmr is None:
absorber_vmr = {
'CO2': 350.,
'N2O': 0.,
'CH4': 0.,
'CFC11': 0.,
'CFC12': 0.
}
self.absorber_vmr = absorber_vmr
# cloud input
self.cldf = 0. * self.Tatm
self.clwp = 0. * self.Tatm
# upwelling surface radiation... should be set by parent process
self.flux_from_sfc = 0. * self.Ts
newdiags = [
'flux_to_sfc',
'flux_to_space',
]
for name in newdiags:
self.init_diagnostic(name)
def __init__(self, scheme='cam3', absorber_vmr=None, **kwargs):
super(CliMTRad, self).__init__(**kwargs)
self.r = climt.radiation(scheme=scheme)
self.param['climt_scheme'] = scheme
newinput = ['q',
'flux_from_sfc',
'cldf',
'clwp',
'absorber_vmr',]
self.add_input(newinput)
# absorbing gases
if absorber_vmr is None:
absorber_vmr = {'CO2': 350.,
'N2O': 0.,
'CH4': 0.,
'CFC11': 0.,
'CFC12': 0.}
self.absorber_vmr = absorber_vmr
# cloud input
self.cldf = 0. * self.Tatm
self.clwp = 0. * self.Tatm
# upwelling surface radiation... should be set by parent process
self.flux_from_sfc = 0. * self.Ts
newdiags = ['flux_to_sfc',
'flux_to_space',]
for name in newdiags:
self.init_diagnostic(name)
def compute(scheme='cam3'):
r = climt.radiation(scheme=scheme)
r(**par)
print 'Zenith angle: %f' % r['zen']
print 'Insolation: %f' % r['solin']
print 'TOA SW CRF: %6.2f %6.2f' % (r['SwToa'], r['SwToaCf'])
print 'TOA LW CRF: %6.2f %6.2f' % (r['LwToa'], r['LwToaCf'])
# output
print "lev p T q O3 lwflx lwhr swflx swhr"
for i in range(r.nlev):
print "%3i %6.1f %6.1f %6.3f %10.3e %12.5f %12.5f %12.5f %12.5f" % \
(i, r['p'][i], r['T'][i], r['q'][i], r['o3'][i], \
r['lwflx'][i], r['lwhr'][i], r['swflx'][i], r['swhr'][i])
def compute(scheme='cam3'):
r=climt.radiation(scheme=scheme)
r(**par)
print 'Zenith angle: %f' % r['zen']
print 'Insolation: %f' % r['solin']
print 'TOA SW CRF: %6.2f %6.2f' % (r['SwToa'],r['SwToaCf'])
print 'TOA LW CRF: %6.2f %6.2f' % (r['LwToa'],r['LwToaCf'])
# output
print "lev p T q O3 lwflx lwhr swflx swhr"
for i in range(r.nlev):
print "%3i %6.1f %6.1f %6.3f %10.3e %12.5f %12.5f %12.5f %12.5f" % \
(i, r['p'][i], r['T'][i], r['q'][i], r['o3'][i], \
r['lwflx'][i], r['lwhr'][i], r['swflx'][i], r['swhr'][i])
def __init__(self,
Case1='uh0',
Case2='uh1',
FileNumber=0):
self.Case1 = Case1
self.Case2 = Case2
self.FileNumber = FileNumber
# init data server
self.data = DataServer(Case1,Case2,FileNumber)
# geometry
self.cosphi = cos(self.data.lat*pi/180.)
self.a = 6.37122e6
# radiation
self.r = climt.radiation(scheme='cam3')
# fixed params
self.Fixed={}
self.Fixed['ch4'] = 7.6e-7 * 1.e6
self.Fixed['n2o'] = 2.6e-7 * 1.e6
self.Fixed['cfc11'] = 1.e-32
self.Fixed['cfc12'] = 1.e-32
self.Fixed['scon'] = 1365.
# compute
self.compute()
# import pdb; pdb.set_trace()
# set whether this is a global average or not
global_average = True
# a useful function
def sigdig(x, digits=1):
if x: x = copysign(round(x, -int(floor(log10(abs(x)))) + (digits - 1)), x)
return x
sys.stderr.write(json.dumps(model_data))
# if it's a global average, make the first run a night-time case
if global_average:
lw_model = climt.radiation(scheme='rrtm', do_sw=0, **model_data)
fluxes = {
'swuflx': numpy.array(lw_model['swuflx']),
'swdflx': numpy.array(lw_model['swdflx']),
'lwuflx': numpy.array([sigdig(float(f), 3) for f in lw_model['lwuflx']]),
'lwdflx': numpy.array([sigdig(float(f), 3) for f in lw_model['lwdflx']]),
'LwToa': sigdig(float(lw_model['LwToa']), 3),
'SwToa': 0.
}
number_of_divisions = 20
for n in range(number_of_divisions):
model_data['zen'] = acos((n + .5)/number_of_divisions) * 180 / pi
sw_model = climt.radiation(scheme = 'rrtm', do_lw=0, **model_data)
fluxes['swuflx'] += numpy.array(sw_model['swuflx']) / (2 * number_of_divisions)
par['calday'] = 83.333333
par['lat'] = 0.
par['lon'] = 0.
par['Cpd'] = 1004.64
par['epsilon'] = 0.622
par['g'] = 9.80616
par['p'] = p
par['T'] = T
par['q'] = q * 1.e3
par['o3'] = o3
par['cldf'] = cldf
par['clwp'] = clwp
import climt
r=climt.radiation(scheme='ccm3')
r(**par)
print 'Zenith angle: %f' % r.State['zen']
print 'Insolation: %f' % r.State['solin']
# output
lw=r.lwflx
ql=r.lwhr*86400.
sw=r.swflx
qs=r.swhr*86400.
print "lev p T q O3 lwflx lwhr swflx swhr"
for i in range(r.nlev):
print "%3i %6.1f %6.1f %6.3f %10.3e %12.5f %12.5f %12.5f %12.5f" % (i, p[i], T[i], q[i], r.o3[i], lw[i], ql[i], sw[i], qs[i])
par['avg'] = 'inst'
par['calday'] = 83.333333
par['lat'] = 0.
par['lon'] = 0.
par['Cpd'] = 1004.64
par['epsilon'] = 0.622
par['g'] = 9.80616
par['p'] = p
par['T'] = T
par['q'] = q * 1.e3
par['o3'] = o3
par['cldf'] = cldf
par['clwp'] = clwp
import climt
r = climt.radiation(scheme='ccm3')
r(**par)
print 'Zenith angle: %f' % r.State['zen']
print 'Insolation: %f' % r.State['solin']
# output
lw = r.lwflx
ql = r.lwhr * 86400.
sw = r.swflx
qs = r.swhr * 86400.
print "lev p T q O3 lwflx lwhr swflx swhr"
for i in range(r.nlev):
print "%3i %6.1f %6.1f %6.3f %10.3e %12.5f %12.5f %12.5f %12.5f" % (
i, p[i], T[i], q[i], r.o3[i], lw[i], ql[i], sw[i], qs[i])
# Initial conditions can be specified in 2 ways: # 1) by specifying a restart file, whose format is identical to # that of an output file. If the file contains a time series, # the model will initialize from the last time step in the file. # If RestartFile and OutputFile are the same, then output will be # appended to the restart file (ie. a continuation run). #kwargs['RestartFile'] = 'radconv.nc' # 2) If RestartFile is not given, then initial values for prognostic # fields must be explicitly given, e.g. nlev = climt.get_nlev() kwargs['q'] = zeros(nlev) + 1.e-9 kwargs['T'] = zeros(nlev) + 250. #(kwargs['solin']/2./climt.parameters.Parameters()['stebol'])**0.25 kwargs['Ts'] = 250. # -- Instantiate components and federation rad = climt.radiation(UpdateFreq=kwargs['dt']*50) con = climt.convection(scheme='emanuel') dif = climt.turbulence() ice = climt.seaice() ins = climt.insolation(lat=85.,avg='daily') kwargs['Hslab']=50. kwargs['Pr']=100. #kwargs['do_srf_lat_flx']=0 #kwargs['do_srf_sen_flx']=0 T0,q0 = climt.thermodyn.moistadiabat(rad['p'],273.,273.-90,.1) kwargs['T'],kwargs['q'] = T0,q0 fed = climt.federation(dif, rad, ice, con, ins, **kwargs)
def __init__(self, scheme='cam3', **kwargs):
super(CliMTRad, self).__init__(**kwargs)
self.r = climt.radiation(scheme=scheme)
self.param['climt_scheme'] = scheme
# write x label only if subplot does not have other subplot underneath
if Subplot in ["111", "212", "223", "224"]:
pylab.xlabel(AxisName[1])
pylab.ylabel(AxisName[0])
self.handle.set_norm(None)
# Title
self.TitleTemplate = "%s [%s]" % (FieldKey, KnownFields[FieldKey][1]) + " %6.2f days"
if len(AxisName) == 2:
self.TitleTemplate = self.TitleTemplate + "\n min=%g max=%g"
day = Component.State.ElapsedTime / 86400.0
try:
TitleText = self.TitleTemplate % day
except:
TitleText = self.TitleTemplate % (day, min(ravel(Field)), max(ravel(Field)))
self.title = pylab.title(TitleText)
self.title.set_fontsize(12)
if __name__ == "__main__":
import climt
r = climt.radiation(lat=arange(0.0, 90.0, 10.0))
m = Monitor(r, MonitorFields=["T", "Ts"])
for i in range(10):
r.step()
m.refresh(r)
show()
import climt import pylab as pl import numpy as np from numpy import arange pl.ioff() # co2 = [0.,100.,1000.,10000.,100000.] c = 0. #--- instantiate radiation module r = climt.radiation(scheme='cam3') #--- initialise T,q # Surface temperature Ts = 273.15 + 30. # Strospheric temp Tst = 273.15 - 80. # Surface pressure ps = 1000. # Equispaced pressure levels p = ( arange(r.nlev)+ 0.5 )/r.nlev * ps # Return moist adiabat with 70% rel hum (T,q) = climt.thermodyn.moistadiabat(p, Ts, Tst, 1.) # # cam3 = climt.radiation(scheme='cam3') # cam3(co2=co2, p=p, ps=ps, T=T, Ts=Ts, q=q) # # pl.plot(cam3['lwdflx'], cam3['p']) # # chou = climt.radiation(scheme='chou')
Ndays = 5. # Total length of run (days)
kwargs={}
kwargs['lat'] = ['1.','2.']
kwargs['solin'] = ['300.','310.']
kwargs['dt'] = 60.*10.
#kwargs['RestartFile'] = 'two_column.nc'
kwargs['OutputFile'] = 'two_column.nc'
kwargs['OutputFreq'] = 60*10.
#kwargs['MonitorFields'] = ['U','T','q']
#kwargs['MonitorFreq'] = 60 *60.*4.
# Set up federation
dyn = climt.dynamics(scheme='two_column')
tur = climt.turbulence()
rad = climt.radiation(scheme='cam3')
con = climt.convection(scheme='hard')
oce = climt.ocean()
fed = climt.federation(dyn,tur,rad,con,oce, **kwargs)
# Run
fed.step(Ndays*86400.)
try:
from matplotlib.pylab import *
show()
except:
pass
# Initial conditions can be specified in 2 ways:
# 1) by specifying a restart file, whose format is identical to
# that of an output file. If the file contains a time series,
# the model will initialize from the last time step in the file.
# If RestartFile and OutputFile are the same, then output will be
# appended to the restart file (ie. a continuation run).
#kwargs['RestartFile'] = 'restart.nc'
# 2) If RestartFile is not given, then initial values for prognostic
# fields must be explicitly given, e.g.
nlev = climt.get_nlev()
stebol = climt.Parameters()['stebol']
kwargs['q'] = zeros(nlev) + 1.e-9
kwargs['T'] = zeros(nlev) + (kwargs['solin'] / 2. / stebol)**0.25
# -- Instantiate components and federation
rad = climt.radiation(UpdateFreq=kwargs['dt'] * 50, scheme='cam3')
con = climt.convection(scheme='emanuel')
dif = climt.turbulence()
oce = climt.ocean()
fed = climt.federation(dif, rad, oce, con, **kwargs)
# Main timestepping loop
RunLength = 2000. # Total length of run (days)
NSteps = int(RunLength * 86400. / fed['dt'])
for i in range(NSteps):
# With a line like the following, it is possible to manipulate
# field values each time step (the example here resets humidity
# to an almost dry value everywhere at each timestep)
#fed.State['q']=zeros(rad.nlev)+1.e-9
# The following code adds a uniform 1 K/day cooling rate to
# the internally-computed tendencies
## Automatically adapted for numpy.oldnumeric Feb 01, 2008 by -c
import climt,numpy.oldnumeric as Numeric
# instantiate radiation module
r=climt.radiation(scheme='gray')
# initialise T,q to moist adiabat with 70% RH
ps = 1020. # surface pressure
q0 = 15. # surface moisture
T0 = 300. # surface temp
the0 = climt.thetae(T0,ps,q0)
p = ( Numeric.arange(r.nlev,typecode='d')+ 0.5 ) * ps/r.nlev
T = Numeric.zeros(r.nlev,typecode='d')
q = Numeric.zeros(r.nlev,typecode='d')
for k in range(r.nlev):
T[k] = climt.tmoistadiab(the0,p[k])
if (T[k] < 273.15-80.): T[k]=273.15-80.
q[k] = climt.qsflatau(T[k],p[k],1)*0.7
if (p[k] < 100.): q[k]=1.e-9
# compute radiative fluxes and heating rates
r(p=p,ps=ps,T=T,Ts=T0,q=q)
# output
lw = r['lwflx']
ql = r['lwhr']
print '+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++'
print 'Testing grey gas radiation module ...'
cldf[:, i] = getProfile(nlayers, kcentral, 3, nz)
zen = arange(ny) * 5. + 5.
print zen
inputs = {}
inputs['Ts'] = zeros((ny, nx)) + Ts
inputs['ps'] = zeros((ny, nx)) + ps
inputs['solin'] = zeros((ny, nx)) + 400.
inputs['zen'] = zeros((ny, nx)) + zen[::-1, None]
inputs['p'] = zeros((nz, ny, nx)) + p[:, None, None]
inputs['T'] = zeros((nz, ny, nx)) + T[:, None, None]
inputs['q'] = zeros((nz, ny, nx)) + q[:, None, None]
inputs['clwp'] = zeros((nz, ny, nx)) + 15.
inputs['cldf'] = zeros((nz, ny, nx)) + cldf[:, None, :]
r = climt.radiation(scheme='cam3', do_lw=0)
LoCldf = 0.01
HiCldf = 0.99
LoTime = 1.
HiTime = 1.
LoWeight = LoTime / (LoTime + HiTime)
HiWeight = HiTime / (LoTime + HiTime)
Mean = LoCldf * LoWeight + HiCldf * HiWeight
inputs['cldf'] *= LoCldf
r(**inputs)
Lo = r['SwToaCf']
inputs['cldf'] *= HiCldf / LoCldf
## Automatically adapted for numpy.oldnumeric Feb 01, 2008 by -c
import climt, numpy.oldnumeric as Numeric
# instantiate radiation module
r = climt.radiation(scheme='chou')
# initialise T,q to moist adiabat with 70% RH
ps = 1020. # surface pressure
q0 = 15. # surface moisture
T0 = 300. # surface temp
the0 = climt.thetae(T0, ps, q0)
p = (Numeric.arange(r.nlev, typecode='d') + 0.5) * ps / r.nlev
T = Numeric.zeros(r.nlev, typecode='d')
q = Numeric.zeros(r.nlev, typecode='d')
for k in range(r.nlev):
T[k] = climt.tmoistadiab(the0, p[k])
if (T[k] < 273.15 - 80.): T[k] = 273.15 - 80.
q[k] = climt.qsflatau(T[k], p[k], 1) * 0.7
if (p[k] < 100.): q[k] = 1.e-9
# compute radiative fluxes and heating rates
r(p=p, ps=ps, T=T, Ts=T0, q=q)
# output
lw = r['lwflx']
ql = r['lwhr']
sw = r['swflx']
qs = r['swhr']
o3 = r['o3']
RH_control = 0 T0_RH = 20. + 273.15 Drop_size = 10. Cloud_frac_hi = 0. Cloud_frac_lo = 0. Cloud_water_hi = 0. Cloud_water_lo = 0. zen = 60. if Cloud_water_lo == 0.: Cloud_frac_lo = 0. if Cloud_water_hi == 0.: Cloud_frac_hi = 0. # instantiate radiation objects, get number of levels r=climt.radiation(scheme=scheme) nlev=r.nlev # define some fixed profiles SurfPres = 1000. Pressure = ( arange(nlev)+ 0.5 ) * SurfPres/nlev cldf = zeros( nlev, 'd') # Cloud frac clwp = zeros( nlev, 'd') # Cloud liquid water path cloud_lev_hi = int(nlev*0.2) # put high cloud roughly at 200 mb cloud_lev_lo = int(nlev*0.8) # put low cloud roughly at 800 mb cldf[cloud_lev_lo] = Cloud_frac_lo cldf[cloud_lev_hi] = Cloud_frac_hi clwp[cloud_lev_lo] = Cloud_water_lo clwp[cloud_lev_hi] = Cloud_water_hi # dictionary for input into rad call
if Subplot in ['111', '212', '223', '224']:
pylab.xlabel(AxisName[0])
pylab.ylabel(AxisName[1])
self.handle.set_norm(None)
# Title
self.TitleTemplate = '%s [%s]' % (
FieldKey, KnownFields[FieldKey][1]) + ' %6.2f days'
if len(AxisName) == 2:
self.TitleTemplate = self.TitleTemplate + '\n min=%g max=%g'
day = Component.State.ElapsedTime / 86400.
try:
TitleText = self.TitleTemplate % day
except:
TitleText = self.TitleTemplate % (day, min(
ravel(plot_field)), max(ravel(plot_field)))
self.title = pylab.title(TitleText)
self.title.set_fontsize(12)
if __name__ == '__main__':
import climt
r = climt.radiation(lat=arange(0., 90., 10.))
m = Monitor(r, MonitorFields=['T', 'Ts'])
for i in range(10):
r.step()
m.refresh(r)
show()
RH_control = 0 T0_RH = 20. + 273.15 Drop_size = 10. Cloud_frac_hi = 0. Cloud_frac_lo = 0. Cloud_water_hi = 0. Cloud_water_lo = 0. zen = 60. if Cloud_water_lo == 0.: Cloud_frac_lo = 0. if Cloud_water_hi == 0.: Cloud_frac_hi = 0. # instantiate radiation objects, get number of levels r = climt.radiation(scheme=scheme) nlev = r.nlev # define some fixed profiles SurfPres = 1000. Pressure = (arange(nlev) + 0.5) * SurfPres / nlev cldf = zeros(nlev, 'd') # Cloud frac clwp = zeros(nlev, 'd') # Cloud liquid water path cloud_lev_hi = int(nlev * 0.2) # put high cloud roughly at 200 mb cloud_lev_lo = int(nlev * 0.8) # put low cloud roughly at 800 mb cldf[cloud_lev_lo] = Cloud_frac_lo cldf[cloud_lev_hi] = Cloud_frac_hi clwp[cloud_lev_lo] = Cloud_water_lo clwp[cloud_lev_hi] = Cloud_water_hi # dictionary for input into rad call
# set whether this is a global average or not
global_average = True
# a useful function
def sigdig(x, digits=1):
if x: x = copysign(round(x, -int(floor(log10(abs(x)))) + (digits - 1)), x)
return x
sys.stderr.write(json.dumps(model_data))
# if it's a global average, make the first run a night-time case
if global_average:
lw_model = climt.radiation(scheme='rrtm', do_sw=0, **model_data)
fluxes = {
'swuflx': numpy.array(lw_model['swuflx']),
'swdflx': numpy.array(lw_model['swdflx']),
'lwuflx':
numpy.array([sigdig(float(f), 3) for f in lw_model['lwuflx']]),
'lwdflx':
numpy.array([sigdig(float(f), 3) for f in lw_model['lwdflx']]),
'LwToa': sigdig(float(lw_model['LwToa']), 3),
'SwToa': 0.
}
number_of_divisions = 20
for n in range(number_of_divisions):
model_data['zen'] = acos((n + .5) / number_of_divisions) * 180 / pi
## Automatically adapted for numpy.oldnumeric Feb 01, 2008 by -c
import climt, numpy.oldnumeric as Numeric
# instantiate radiation module
r = climt.radiation(scheme='gray')
# initialise T,q to moist adiabat with 70% RH
ps = 1020. # surface pressure
q0 = 15. # surface moisture
T0 = 300. # surface temp
the0 = climt.thetae(T0, ps, q0)
p = (Numeric.arange(r.nlev, typecode='d') + 0.5) * ps / r.nlev
T = Numeric.zeros(r.nlev, typecode='d')
q = Numeric.zeros(r.nlev, typecode='d')
for k in range(r.nlev):
T[k] = climt.tmoistadiab(the0, p[k])
if (T[k] < 273.15 - 80.): T[k] = 273.15 - 80.
q[k] = climt.qsflatau(T[k], p[k], 1) * 0.7
if (p[k] < 100.): q[k] = 1.e-9
# compute radiative fluxes and heating rates
r(p=p, ps=ps, T=T, Ts=T0, q=q)
# output
lw = r['lwflx']
ql = r['lwhr']
print '+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++'
print 'Testing grey gas radiation module ...'
Ndays = 5.0 # Total length of run (days)
kwargs = {}
kwargs["lat"] = ["1.", "2."]
kwargs["solin"] = ["300.", "310."]
kwargs["dt"] = 60.0 * 10.0
# kwargs['RestartFile'] = 'two_column.nc'
kwargs["OutputFile"] = "two_column.nc"
kwargs["OutputFreq"] = 60 * 10.0
# kwargs['MonitorFields'] = ['U','T','q']
# kwargs['MonitorFreq'] = 60 *60.*4.
# Set up federation
dyn = climt.dynamics(scheme="two_column")
tur = climt.turbulence()
rad = climt.radiation(scheme="cam3")
con = climt.convection(scheme="hard")
oce = climt.ocean()
fed = climt.federation(dyn, tur, rad, con, oce, **kwargs)
# Run
fed.step(Ndays * 86400.0)
try:
from matplotlib.pylab import *
show()
except:
pass
def __init__(self, scheme='cam3', **kwargs):
super(CliMTRad, self).__init__(**kwargs)
self.r = climt.radiation(scheme=scheme)
self.param['climt_scheme'] = scheme
## Automatically adapted for numpy.oldnumeric Feb 01, 2008 by -c
import climt,numpy.oldnumeric as Numeric
# instantiate radiation module
r=climt.radiation(scheme='chou')
# initialise T,q to moist adiabat with 70% RH
ps = 1020. # surface pressure
q0 = 15. # surface moisture
T0 = 300. # surface temp
the0 = climt.thetae(T0,ps,q0)
p = ( Numeric.arange(r.nlev,typecode='d')+ 0.5 ) * ps/r.nlev
T = Numeric.zeros(r.nlev,typecode='d')
q = Numeric.zeros(r.nlev,typecode='d')
for k in range(r.nlev):
T[k] = climt.tmoistadiab(the0,p[k])
if (T[k] < 273.15-80.): T[k]=273.15-80.
q[k] = climt.qsflatau(T[k],p[k],1)*0.7
if (p[k] < 100.): q[k]=1.e-9
# compute radiative fluxes and heating rates
r(p=p,ps=ps,T=T,Ts=T0,q=q)
# output
lw=r['lwflx']
ql=r['lwhr']
sw=r['swflx']
qs=r['swhr']
o3=r['o3']
extent=(xmin, xmax, ymin, ymax),\
interpolation='bilinear')
pylab.setp(pylab.gca(), 'xlim',[xmin,xmax], 'ylim',[ymin,ymax])
# write x label only if subplot does not have other subplot underneath
if Subplot in ['111','212','223','224']: pylab.xlabel(AxisName[1])
pylab.ylabel(AxisName[0])
self.handle.set_norm(None)
# Title
self.TitleTemplate = '%s [%s]' % (FieldKey,KnownFields[FieldKey][1]) + ' %6.2f days'
if len(AxisName) == 2: self.TitleTemplate = self.TitleTemplate + '\n min=%g max=%g'
day = Component.State.ElapsedTime/86400.
try:
TitleText = self.TitleTemplate % day
except:
TitleText = self.TitleTemplate % (day, min(ravel(Field)), max(ravel(Field)))
self.title = pylab.title(TitleText)
self.title.set_fontsize(12)
if __name__=='__main__':
import climt
r=climt.radiation(lat=arange(0.,90.,10.))
m=Monitor(r, MonitorFields=['T','Ts'])
for i in range(10):
r.step()
m.refresh(r)
show()
cldf[:,i] = getProfile(nlayers, kcentral, 3, nz)
zen = arange(ny)*5. + 5.
print zen
inputs = {}
inputs['Ts'] = zeros((ny,nx)) + Ts
inputs['ps'] = zeros((ny,nx)) + ps
inputs['solin'] = zeros((ny,nx)) + 400.
inputs['zen'] = zeros((ny,nx)) + zen[::-1,None]
inputs['p'] = zeros((nz,ny,nx)) + p[:,None,None]
inputs['T'] = zeros((nz,ny,nx)) + T[:,None,None]
inputs['q'] = zeros((nz,ny,nx)) + q[:,None,None]
inputs['clwp'] = zeros((nz,ny,nx)) + 15.
inputs['cldf'] = zeros((nz,ny,nx)) + cldf[:,None,:]
r = climt.radiation(scheme='cam3', do_lw=0)
LoCldf = 0.01
HiCldf = 0.99
LoTime =1.
HiTime =1.
LoWeight = LoTime/(LoTime+HiTime)
HiWeight = HiTime/(LoTime+HiTime)
Mean = LoCldf*LoWeight + HiCldf*HiWeight
inputs['cldf'] *= LoCldf
r(**inputs)
Lo = r['SwToaCf']
inputs['cldf'] *= HiCldf/LoCldf
# Initial conditions can be specified in 2 ways:
# 1) by specifying a restart file, whose format is identical to
# that of an output file. If the file contains a time series,
# the model will initialize from the last time step in the file.
# If RestartFile and OutputFile are the same, then output will be
# appended to the restart file (ie. a continuation run).
#kwargs['RestartFile'] = 'restart.nc'
# 2) If RestartFile is not given, then initial values for prognostic
# fields must be explicitly given, e.g.
nlev = climt.get_nlev()
stebol = climt.Parameters()['stebol']
kwargs['q'] = zeros(nlev) + 1.e-9
kwargs['T'] = zeros(nlev) + (kwargs['solin']/2./stebol)**0.25
# -- Instantiate components and federation
rad = climt.radiation(UpdateFreq=kwargs['dt']*50, scheme='cam3')
con = climt.convection(scheme='emanuel')
dif = climt.turbulence()
oce = climt.ocean()
fed = climt.federation(dif, rad, oce, con, **kwargs)
# Main timestepping loop
RunLength = 2000. # Total length of run (days)
NSteps = int( RunLength*86400./fed['dt'] )
for i in range(NSteps):
# With a line like the following, it is possible to manipulate
# field values each time step (the example here resets humidity
# to an almost dry value everywhere at each timestep)
#fed.State['q']=zeros(rad.nlev)+1.e-9
# The following code adds a uniform 1 K/day cooling rate to
# the internally-computed tendencies