def test_float():
'''Check that we can step forward the model after setting the state
variable with an ndarray of integers through 2 different methods'''
from climlab.domain import initial
from climlab.domain.field import Field
state = initial.surface_state()
sfc = climlab.domain.zonal_mean_surface(num_lat=4)
state.Ts = Field([10, 15, 15, 10], domain=sfc)
m = climlab.EBM(state=state)
m.step_forward()
k = climlab.EBM(num_lat=4)
k.set_state('Ts', Field([10, 15, 15, 10], domain=k.domains['Ts']))
k.step_forward()
def test_moist_EBM_creation():
'''See if we can swap a moist diffusion module for the dry diffusion
and just step forward once.'''
m = climlab.EBM()
m.remove_subprocess('diffusion')
diff = climlab.dynamics.MeridionalMoistDiffusion(state=m.state,
timestep=m.timestep)
m.add_subprocess('diffusion', diff)
m.step_forward()
assert hasattr(m, 'heat_transport')
def test_albedo():
'''Check that we can integrate forward a model after changing the albedo
subprocess and get the expected icelat'''
import numpy as np
m = climlab.EBM()
m.add_subprocess('albedo',
climlab.surface.ConstantAlbedo(state=m.state, **m.param))
m.integrate_years(1)
assert m.icelat == None
m.add_subprocess(
'albedo', climlab.surface.StepFunctionAlbedo(state=m.state, **m.param))
m.integrate_years(1)
assert np.all(m.icelat == np.array([-70., 70.]))
assert np.all(m.icelat == m.subprocess.albedo.subprocess.iceline.icelat)
def test_analytical():
'''Check to see if the the numerical solution converges to the analytical
steady-state solution of the simple EBM with constant albedo'''
param = {
'a0': 0.3,
'a2': 0.,
'ai': 0.3,
's2': -0.48,
'S0': 1360.,
'A': 210.,
'B': 2.,
'D': 0.55,
'Tf': -1000., # effectively makes albedo constant
}
m = climlab.EBM(**param)
m.integrate_years(5)
Tnumerical = np.squeeze(m.Ts)
delta = param['D'] / param['B']
x = np.sin(np.deg2rad(m.lat))
Tanalytical = ((1 - param['a0']) * param['S0'] / 4 *
(1 + param['s2'] * P2(x) /
(1 + 6 * delta)) - param['A']) / param['B']
assert Tnumerical == pytest.approx(Tanalytical, abs=2E-2)
import climlab
import matplotlib.pyplot as plt
# creating & integrating model
model = climlab.EBM()
model.step_forward()
# plot
fig = plt.figure( figsize=(6,4))
ax = fig.add_subplot(111)
ax.plot(model.lat, model.inferred_heat_transport())
ax.set_title('inferred heat transport')
ax.set_xlabel('latitude')
ax.set_xticks([-90,-60,-30,0,30,60,90])
ax.set_ylabel('energy (PW)')
plt.axhline(linewidth=2, color='grey', linestyle='dashed')
plt.show()