def test_get_diagnostics_with_real_component():
dummy = RRTMGLongwave()
state = get_default_state([dummy])
diag = dummy.create_state_dict_for('_climt_diagnostics', state)
for quantity in dummy._climt_diagnostics:
assert quantity in diag
def test_rrtmg_logging(self, caplog):
caplog.set_level(logging.INFO)
RRTMGLongwave(mcica=True, cloud_overlap_method='clear_only')
assert 'no clouds' in caplog.text
caplog.clear()
RRTMGLongwave(mcica=True, cloud_optical_properties='single_cloud_type')
assert "must be 'direct_input' or " \
"'liquid_and_ice_clouds'" in caplog.text
def test_get_inputs_with_real_component():
dummy = RRTMGLongwave()
state = get_default_state([dummy])
diag = dummy.create_state_dict_for('_climt_inputs', state)
for quantity in dummy._climt_inputs:
assert quantity in diag
assert diag[quantity].dims == state[quantity].dims
def test_extracting_arrays_from_real_component():
dummy = RRTMGLongwave()
state = get_default_state([dummy])
arrays = dummy.get_numpy_arrays_from_state('_climt_inputs', state)
for quantity in dummy._climt_inputs.keys():
units = dummy._climt_inputs[quantity]
state_values = state[quantity].to_units(units).values
assert np.all(arrays[quantity] == state_values)
def get_component_instance(self, state_modification_func=lambda x: x):
dycore = GFSDynamicalCore(number_of_longitudes=68,
number_of_latitudes=32)
radiation = RRTMGLongwave()
dycore.prognostics = [radiation]
return dycore
def get_component_instance(self):
# Create Radiation Prognostic
radiation = RRTMGLongwave()
# Create Convection Prognostic
convection = EmanuelConvection()
# Create a SimplePhysics Prognostic
boundary_layer = TimeDifferencingWrapper(SimplePhysics())
return GFSDynamicalCore([radiation, convection, boundary_layer])
def test_get_diagnostics_with_real_component_with_2d_coordinates():
dummy = RRTMGLongwave()
state = get_default_state([dummy],
x=dict(label='shore',
values=np.random.randn(2, 2),
units='km'),
y=dict(label='latitude',
values=np.random.randn(2, 2),
units='degrees east'))
diag = dummy.create_state_dict_for('_climt_diagnostics', state)
for quantity in dummy.diagnostics:
assert quantity in diag
assert 'shore' in diag[quantity].coords
assert 'latitude' in diag[quantity].coords
assert diag[quantity].coords['shore'].ndim == 2
assert diag[quantity].coords['latitude'].ndim == 2
def tests_dycore_with_prognostic_attrs_are_sane():
dycore = GFSDynamicalCore(number_of_longitudes=68, number_of_latitudes=32)
radiation = RRTMGLongwave()
dycore.prognostics = [radiation]
for quantity in radiation.diagnostics:
assert quantity in dycore.diagnostics
for quantity in radiation.inputs:
assert quantity in dycore.inputs
def test_piecewise_constant_component():
radiation = RRTMGLongwave()
radiation = radiation.piecewise_constant_version(timedelta(seconds=1000))
state = climt.get_default_state([radiation])
current_tendency, current_diagnostic = radiation(state)
# Perturb state
state['air_temperature'] += 3
new_tendency, new_diagnostic = radiation(state)
assert np.all(current_tendency['air_temperature'].values ==
new_tendency['air_temperature'].values)
state['time'] += timedelta(seconds=1500)
new_tendency, new_diagnostic = radiation(state)
assert np.any(current_tendency['air_temperature'].values !=
new_tendency['air_temperature'].values)
def get_3d_input_state(self):
component = self.get_component_instance()
prognostic = RRTMGLongwave()
state = climt.get_default_state(
[component, prognostic],
x=component.grid_definition['x'],
y=component.grid_definition['y'],
mid_levels=component.grid_definition['mid_levels'],
interface_levels=component.grid_definition['interface_levels'])
dcmip = climt.DcmipInitialConditions()
out = dcmip(state, add_perturbation=True)
state.update(out)
return state
Lsun = 3.828e26
AU = 149597870700.0
distance = distance * AU
return Lsun / (4 * math.pi * distance**2.0)
def getAU(lum):
Lsun = 3.828e26
AU = 149597870700.0
return math.sqrt(Lsun / (4 * math.pi * lum)) / AU
monitor = PlotFunctionMonitor(plot_function)
rad_sw = RRTMGShortwave(cloud_overlap_method=0,
solar_constant=solarConstant(0.65))
rad_lw = RRTMGLongwave(cloud_overlap_method=0)
time_stepper = AdamsBashforth([rad_sw, rad_lw])
timestep = timedelta(hours=1)
mid_levels = {'label': 'mid_level', 'values': np.arange(60), 'units': ''}
int_levels = {'label': 'interface_level', 'values': np.arange(61), 'units': ''}
state = get_default_state([rad_sw, rad_lw],
mid_levels=mid_levels,
interface_levels=int_levels)
tp_profiles = np.load('thermodynamic_profiles.npz')
mol_profiles = np.load('molecule_profiles.npz')
co2_input_array = mol_profiles["carbon_dioxide"]
state["g"] = 25.0
def get_component_instance(self):
return RRTMGLongwave(cloud_optical_properties='single_cloud_type')
def get_component_instance(self, state_modification_func=lambda x: x):
return RRTMGLongwave(cloud_optical_properties='single_cloud_type')
def get_component_instance(self, state_modification_func=lambda x: x):
return RRTMGLongwave(calculate_interface_temperature=False)
def get_component_instance(self, state_modification_func=lambda x: x):
return RRTMGLongwave()
state['air_pressure_on_interface_levels'].to_units(
'mbar').values.flatten(), '-o')
ax.set_title('Net Flux')
ax.axes.invert_yaxis()
ax.set_xlabel('W/m^2')
ax.grid()
plt.tight_layout()
monitor = PlotFunctionMonitor(plot_function)
timestep = timedelta(minutes=5)
convection = EmanuelConvection()
radiation_sw = RRTMGShortwave()
radiation_lw = RRTMGLongwave()
slab = SlabSurface()
simple_physics = SimplePhysics()
store_quantities = [
'air_temperature', 'air_pressure', 'specific_humidity',
'air_pressure_on_interface_levels',
'air_temperature_tendency_from_convection',
'air_temperature_tendency_from_longwave',
'air_temperature_tendency_from_shortwave'
]
netcdf_monitor = NetCDFMonitor('rad_conv_eq.nc',
store_names=store_quantities,
write_on_store=True)
convection.current_time_step = timestep
ax = fig.add_subplot(1, 2, 2)
ax.plot(state['air_temperature'].values.flatten(),
state['air_pressure'].values.flatten(), '-o')
ax.axes.invert_yaxis()
ax.set_yscale('log')
ax.set_ylim(1e5, 1.)
ax.set_title('Temperature')
ax.grid()
ax.set_xlabel('K')
ax.set_yticklabels([])
monitor = PlotFunctionMonitor(plot_function)
rad_sw = RRTMGShortwave()
rad_lw = RRTMGLongwave()
time_stepper = AdamsBashforth([rad_sw, rad_lw])
timestep = timedelta(hours=1)
mid_levels = {'label': 'mid_level', 'values': np.arange(60), 'units': ''}
int_levels = {'label': 'interface_level', 'values': np.arange(61), 'units': ''}
state = get_default_state([rad_sw, rad_lw],
mid_levels=mid_levels,
interface_levels=int_levels)
tp_profiles = np.load('thermodynamic_profiles.npz')
mol_profiles = np.load('molecule_profiles.npz')
state['air_pressure'].values[0, 0, :] = tp_profiles['air_pressure']
state['air_temperature'].values[0, 0, :] = tp_profiles['air_temperature']
def get_component_instance(self):
radiation = RRTMGLongwave()
return GFSDynamicalCore([radiation], moist=True)
def get_component_instance(self):
return RRTMGLongwave(mcica=True)
def get_component_instance(self):
return RRTMGLongwave(calculate_interface_temperature=False)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rcParams
from climt import RRTMGShortwave, RRTMGLongwave, get_default_state
from sympl import get_constant
prop_cycle = rcParams['axes.prop_cycle']
colors = prop_cycle.by_key()['color']
rad_sw = RRTMGShortwave(mcica=True)
state_sw = get_default_state([rad_sw])
rad_lw = RRTMGLongwave(mcica=True)
state_lw = get_default_state([rad_lw])
p = state_lw['air_pressure'][:]
p_interface = state_lw['air_pressure_on_interface_levels'][:]
T = state_lw['air_temperature'][:]
R = get_constant('gas_constant_of_dry_air', 'J kg^-1 K^-1')
g = get_constant('gravitational_acceleration', 'm s^-2')
density = p / (R * T)
dz = -np.diff(p_interface, axis=0) / (density * g) # [m]
z = np.cumsum(dz) * 10**-3 # [km]
ice_density = 0.5 * 10**-3 # [kg m^-3]
cloud_base = 10 # [km]
cloud_top = 15 # [km]
cloud_loc = np.where((z > cloud_base) & (z < cloud_top))
i = 0
for area_fraction in np.arange(0, 1.1, 0.25):
mass_ice_array = area_fraction * ice_density * dz
for state in state_sw, state_lw: