'value': 1200,
'units': 'W m^-2'
}})
model_time_step = timedelta(seconds=600)
# Create components
convection = climt.EmanuelConvection()
simple_physics = TimeDifferencingWrapper(climt.SimplePhysics())
constant_duration = 6
radiation_lw = UpdateFrequencyWrapper(climt.RRTMGLongwave(),
constant_duration * model_time_step)
radiation_sw = UpdateFrequencyWrapper(climt.RRTMGShortwave(),
constant_duration * model_time_step)
slab_surface = climt.SlabSurface()
insolation = climt.Instellation()
dycore = climt.GFSDynamicalCore(
[simple_physics, slab_surface, radiation_sw, radiation_lw, convection],
number_of_damped_levels=5)
grid = climt.get_grid(nx=128, ny=62)
# Create model state
my_state = climt.get_default_state([dycore], grid_state=grid)
# Set initial/boundary conditions
latitudes = my_state['latitude'].values
'stellar_irradiance': {'value': 200, 'units': 'W m^-2'}})
model_time_step = timedelta(seconds=600)
# Create components
convection = climt.EmanuelConvection()
simple_physics = TimeDifferencingWrapper(climt.SimplePhysics())
constant_duration = 6
radiation_lw = UpdateFrequencyWrapper(
climt.RRTMGLongwave(), constant_duration*model_time_step)
radiation_sw = UpdateFrequencyWrapper(
climt.RRTMGShortwave(), constant_duration*model_time_step)
slab_surface = climt.SlabSurface()
dycore = climt.GFSDynamicalCore(
[simple_physics, slab_surface, radiation_sw,
radiation_lw, convection], number_of_damped_levels=5
)
grid = climt.get_grid(nx=NUM_COLS, ny=NUM_ROWS)
# Create model state
my_state = climt.get_default_state([dycore], grid_state=grid)
# Set initial/boundary conditions
latitudes = my_state['latitude'].values
longitudes = my_state['longitude'].values
convection = climt.EmanuelConvection(
convective_momentum_transfer_coefficient=1)
simple_physics = climt.SimplePhysics()
simple_physics = simple_physics.prognostic_version()
simple_physics.current_time_step = model_time_step
convection.current_time_step = model_time_step
# run radiation once every hour
constant_duration = 3
radiation_lw = climt.RRTMGLongwave()
radiation_lw = radiation_lw.piecewise_constant_version(constant_duration *
model_time_step)
radiation_sw = climt.RRTMGShortwave(use_solar_constant_from_fortran=False)
radiation_sw = radiation_sw.piecewise_constant_version(constant_duration *
model_time_step)
slab_surface = climt.SlabSurface()
# Create model state
my_state = climt.get_default_state(
[
dycore, radiation_lw, radiation_sw, convection, simple_physics,
slab_surface
],
x=dycore.grid_definition['x'],
y=dycore.grid_definition['y'],
mid_levels=dycore.grid_definition['mid_levels'],
interface_levels=dycore.grid_definition['interface_levels'])
def init_radiative_state(self, atmosphere, surface):
climt.set_constants_from_dict({
"stellar_irradiance": {
"value": self.solar_constant,
"units": 'W m^-2'
}
})
if self._is_mcica:
overlap = 'maximum_random'
else:
overlap = 'random'
self._rad_lw = climt.RRTMGLongwave(
cloud_optical_properties=self._cloud_optical_properties,
cloud_ice_properties=self._cloud_ice_properties,
cloud_liquid_water_properties='radius_dependent_absorption',
cloud_overlap_method=overlap,
mcica=self._is_mcica)
self._rad_sw = climt.RRTMGShortwave(
ignore_day_of_year=True,
cloud_optical_properties=self._cloud_optical_properties,
cloud_ice_properties=self._cloud_ice_properties,
cloud_liquid_water_properties='radius_dependent_absorption',
cloud_overlap_method=overlap,
mcica=self._is_mcica)
state_lw = {}
state_sw = {}
plev = atmosphere['plev']
phlev = atmosphere['phlev']
numlevels = len(plev)
for state0 in state_lw, state_sw:
state0['mid_levels'] = DataArray(np.arange(0, numlevels),
dims=('mid_levels', ),
attrs={'label': 'mid_levels'})
state0['interface_levels'] = DataArray(
np.arange(0, numlevels + 1),
dims=('interface_levels', ),
attrs={'label': 'interface_levels'})
state0['air_pressure'] = DataArray(plev,
dims=('mid_levels', ),
attrs={'units': 'Pa'})
state0['air_pressure_on_interface_levels'] = DataArray(
phlev, dims=('interface_levels', ), attrs={'units': 'Pa'})
state0['time'] = datetime.datetime(2000, 1, 1)
### Aerosols ###
# TODO: Should all the aerosol values be zero?!
# Longwave specific
num_lw_bands = self._rad_lw.num_longwave_bands
state_lw['longwave_optical_thickness_due_to_aerosol'] = DataArray(
np.zeros((num_lw_bands, numlevels)),
dims=('num_longwave_bands', 'mid_levels'),
attrs={'units': 'dimensionless'})
state_lw['surface_longwave_emissivity'] = DataArray(
surface.longwave_emissivity * np.ones((num_lw_bands, )),
dims=('num_longwave_bands'),
attrs={'units': 'dimensionless'})
# Shortwave specific changes
num_sw_bands = self._rad_sw.num_shortwave_bands
num_aerosols = self._rad_sw.num_ecmwf_aerosols
state_sw['aerosol_optical_depth_at_55_micron'] = DataArray(
np.zeros((num_aerosols, numlevels)),
dims=('num_ecmwf_aerosols', 'mid_levels'),
attrs={'units': 'dimensionless'})
state_sw['solar_cycle_fraction'] = DataArray(
0, attrs={'units': 'dimensionless'})
state_sw['flux_adjustment_for_earth_sun_distance'] = DataArray(
1, attrs={'units': 'dimensionless'})
for surface_albedo in [
'surface_albedo_for_diffuse_near_infrared',
'surface_albedo_for_direct_near_infrared',
'surface_albedo_for_diffuse_shortwave',
'surface_albedo_for_direct_shortwave'
]:
state_sw[surface_albedo] = DataArray(
np.array(float(surface.albedo)),
attrs={'units': 'dimensionless'})
for quant in [
'shortwave_optical_thickness_due_to_aerosol',
'single_scattering_albedo_due_to_aerosol',
'aerosol_asymmetry_parameter'
]:
state_sw[quant] = DataArray(np.zeros((num_sw_bands, numlevels)),
dims=('num_shortwave_bands',
'mid_levels'),
attrs={'units': 'dimensionless'})
return state_lw, state_sw
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 14 22:44:38 2017
@author: zifan
"""
import climt
import matplotlib.pyplot as plt
import numpy as np
from sympl import AdamsBashforth
from datetime import timedelta
incoming_radiation = climt.RRTMGShortwave(
cloud_overlap_method=0,
solar_constant = 2500)
outgoing_radiation = climt.RRTMGLongwave(
cloud_overlap_method=0)
convection = climt.EmanuelConvection()
surface = climt.SlabSurface()
state = climt.get_default_state([incoming_radiation,
outgoing_radiation,
convection])
model_time_step = timedelta(hours=24)
model = AdamsBashforth([incoming_radiation,
outgoing_radiation,
convection])
for step in range(50):
diagnostics, new_state = model(state, model_time_step)
def get_component_instance(self):
return climt.RRTMGShortwave(mcica=True)
def init_radiative_state(self, atmosphere, surface):
climt.set_constants_from_dict({
"stellar_irradiance": {
"value": self.solar_constant,
"units": "W m^-2"
}
})
if self._is_mcica:
overlap = "maximum_random"
else:
overlap = "random"
self._rad_lw = climt.RRTMGLongwave(
cloud_optical_properties=self._cloud_optical_properties,
cloud_ice_properties=self._cloud_ice_properties,
cloud_liquid_water_properties="radius_dependent_absorption",
cloud_overlap_method=overlap,
mcica=self._is_mcica,
)
self._rad_sw = climt.RRTMGShortwave(
ignore_day_of_year=True,
cloud_optical_properties=self._cloud_optical_properties,
cloud_ice_properties=self._cloud_ice_properties,
cloud_liquid_water_properties="radius_dependent_absorption",
cloud_overlap_method=overlap,
mcica=self._is_mcica,
)
state_lw = {}
state_sw = {}
plev = atmosphere["plev"]
phlev = atmosphere["phlev"]
numlevels = len(plev)
for state0 in state_lw, state_sw:
state0["mid_levels"] = DataArray(
np.arange(0, numlevels),
dims=("mid_levels", ),
attrs={"label": "mid_levels"},
)
state0["interface_levels"] = DataArray(
np.arange(0, numlevels + 1),
dims=("interface_levels", ),
attrs={"label": "interface_levels"},
)
state0["air_pressure"] = DataArray(plev,
dims=("mid_levels", ),
attrs={"units": "Pa"})
state0["air_pressure_on_interface_levels"] = DataArray(
phlev, dims=("interface_levels", ), attrs={"units": "Pa"})
state0["time"] = datetime.datetime(2000, 1, 1)
### Aerosols ###
# TODO: Should all the aerosol values be zero?!
# Longwave specific
num_lw_bands = self._rad_lw.num_longwave_bands
state_lw["longwave_optical_thickness_due_to_aerosol"] = DataArray(
np.zeros((num_lw_bands, numlevels)),
dims=("num_longwave_bands", "mid_levels"),
attrs={"units": "dimensionless"},
)
state_lw["surface_longwave_emissivity"] = DataArray(
surface.longwave_emissivity * np.ones((num_lw_bands, )),
dims=("num_longwave_bands"),
attrs={"units": "dimensionless"},
)
# Shortwave specific changes
num_sw_bands = self._rad_sw.num_shortwave_bands
num_aerosols = self._rad_sw.num_ecmwf_aerosols
state_sw["aerosol_optical_depth_at_55_micron"] = DataArray(
np.zeros((num_aerosols, numlevels)),
dims=("num_ecmwf_aerosols", "mid_levels"),
attrs={"units": "dimensionless"},
)
state_sw["solar_cycle_fraction"] = DataArray(
0, attrs={"units": "dimensionless"})
state_sw["flux_adjustment_for_earth_sun_distance"] = DataArray(
1, attrs={"units": "dimensionless"})
for surface_albedo in [
"surface_albedo_for_diffuse_near_infrared",
"surface_albedo_for_direct_near_infrared",
"surface_albedo_for_diffuse_shortwave",
"surface_albedo_for_direct_shortwave",
]:
state_sw[surface_albedo] = DataArray(
np.array(float(surface.albedo)),
attrs={"units": "dimensionless"})
for quant in [
"shortwave_optical_thickness_due_to_aerosol",
"single_scattering_albedo_due_to_aerosol",
"aerosol_asymmetry_parameter",
]:
state_sw[quant] = DataArray(
np.zeros((num_sw_bands, numlevels)),
dims=("num_shortwave_bands", "mid_levels"),
attrs={"units": "dimensionless"},
)
return state_lw, state_sw
