def build_rcm(num_lev=30, water_depth=2.5):
# Temperatures in a single column
state = climlab.column_state(num_lev=num_lev, water_depth=water_depth)
# Initialize a nearly dry column (small background stratospheric humidity)
state['q'] = np.ones_like(state.Tatm) * 5.E-6
# ASYNCHRONOUS COUPLING -- the radiation uses a much longer timestep
short_timestep = climlab.constants.seconds_per_hour
# Radiation coupled to water vapor
rad = climlab.radiation.RRTMG(name='Radiation',
state=state,
specific_humidity=state.q,
albedo=0.2,
timestep=24*short_timestep)
# Convection scheme -- water vapor is a state variable
conv = climlab.convection.EmanuelConvection(name='Convection',
state=state,
timestep=short_timestep,
ALPHA=0.1,)
# Surface heat flux processes
shf = climlab.surface.SensibleHeatFlux(name='SHF',
state=state, Cd=0.5E-3, U=10.,
timestep=short_timestep)
lhf = climlab.surface.LatentHeatFlux(name='LHF',
state=state, Cd=0.5E-3, U=10.,
timestep=short_timestep)
# Couple all the submodels together
turb = climlab.couple([shf,lhf], name='Turbulent')
model = climlab.couple([rad, conv, turb], name='RadiativeConvectiveModel')
for proc in [rad, conv, shf, lhf]:
model.add_subprocess(proc.name, proc)
return model
def test_radiative_forcing():
'''Run a single-column radiative-convective model with RRTMG radiation
out to equilibrium. Clone the model, double CO2 and measure the instantaneous
change in TOA flux. It should be positive net downward flux.'''
# State variables (Air and surface temperature)
state = climlab.column_state(num_lev=30, water_depth=1.)
# Fixed relative humidity
h2o = climlab.radiation.ManabeWaterVapor(name='WaterVapor', state=state)
# Couple water vapor to radiation
# Set icld=0 for clear-sky only (no need to call cloud overlap routine)
rad = climlab.radiation.RRTMG(name='Radiation',
state=state,
specific_humidity=h2o.q,
icld=0)
# Convective adjustment
conv = climlab.convection.ConvectiveAdjustment(name='Convection',
state=state,
adj_lapse_rate=6.5)
# Couple everything together
rcm = climlab.couple([rad, h2o, conv], name='Radiative-Convective Model')
rcm.integrate_years(5.)
assert np.abs(rcm.ASR - rcm.OLR) < 0.1 # close to energy balance
rcm2 = climlab.process_like(rcm)
rcm2.subprocess['Radiation'].absorber_vmr['CO2'] *= 2.
rcm2.compute_diagnostics()
assert (rcm2.ASR - rcm2.OLR) > 1. # positive radiative forcing
# Test the xarray interface
to_xarray(rcm2)
def test_radiative_forcing():
'''Run a single-column radiative-convective model with RRTMG radiation
out to equilibrium. Clone the model, double CO2 and measure the instantaneous
change in TOA flux. It should be positive net downward flux.'''
# State variables (Air and surface temperature)
state = climlab.column_state(num_lev=30, water_depth=1.)
# Fixed relative humidity
h2o = climlab.radiation.ManabeWaterVapor(name='WaterVapor', state=state)
# Couple water vapor to radiation
# Set icld=0 for clear-sky only (no need to call cloud overlap routine)
rad = climlab.radiation.RRTMG(name='Radiation',
state=state,
specific_humidity=h2o.q,
icld=0)
# Convective adjustment
conv = climlab.convection.ConvectiveAdjustment(name='Convection',
state=state,
adj_lapse_rate=6.5)
# Couple everything together
rcm = climlab.couple([rad,h2o,conv], name='Radiative-Convective Model')
rcm.integrate_years(5.)
assert np.abs(rcm.ASR - rcm.OLR) < 0.1 # close to energy balance
rcm2 = climlab.process_like(rcm)
rcm2.subprocess['Radiation'].absorber_vmr['CO2'] *= 2.
rcm2.compute_diagnostics()
assert (rcm2.ASR - rcm2.OLR) > 1. # positive radiative forcing
# Test the xarray interface
to_xarray(rcm2)
def rcm():
# initial state (temperatures)
state = climlab.column_state(num_lev=40, num_lat=1, water_depth=5.)
## Create individual physical process models:
# fixed relative humidity
h2o = climlab.radiation.ManabeWaterVapor(state=state, name='H2O')
# Hard convective adjustment
convadj = climlab.convection.ConvectiveAdjustment(state=state, name='ConvectiveAdjustment',
adj_lapse_rate=6.5)
# RRTMG radiation with default parameters and interactive water vapor
rad = climlab.radiation.RRTMG(state=state, albedo=0.2, specific_humidity=h2o.q, name='Radiation')
# Couple the models
rcm = climlab.couple([h2o,convadj,rad], name='RCM')
return rcm
def rcm():
# initial state (temperatures)
state = climlab.column_state(num_lev=40, num_lat=1, water_depth=5.)
## Create individual physical process models:
# fixed relative humidity
h2o = climlab.radiation.ManabeWaterVapor(state=state, name='H2O')
# Hard convective adjustment
convadj = climlab.convection.ConvectiveAdjustment(state=state, name='ConvectiveAdjustment',
adj_lapse_rate=6.5)
# RRTMG radiation with default parameters and interactive water vapor
rad = climlab.radiation.RRTMG(state=state, albedo=0.2, specific_humidity=h2o.q, name='Radiation')
# Couple the models
rcm = climlab.couple([h2o,convadj,rad], name='RCM')
return rcm