def surface_state(num_lat=90, water_depth=10., T0=12., T2=-40.):
'''Set up a state variable dictionary for a zonal-mean surface model
(e.g. basic EBM). There is a single state variable `Ts`, the temperature
of the surface mixed layer.
'''
sfc = domain.zonal_mean_surface(num_lat=num_lat, water_depth=water_depth)
sinphi = np.sin(np.deg2rad(sfc.axes['lat'].points))
initial = T0 + T2 * legendre.P2(sinphi)
Ts = Field(initial, domain=sfc)
state = AttrDict()
state['Ts'] = Ts
return state
def surface_state(num_lat=90, water_depth=10.0, T0=12.0, T2=-40.0):
"""Set up a state variable dictionary for a zonal-mean surface model
(e.g. basic EBM). There is a single state variable `Ts`, the temperature
of the surface mixed layer.
"""
sfc = domain.zonal_mean_surface(num_lat=num_lat, water_depth=water_depth)
sinphi = np.sin(np.deg2rad(sfc.axes["lat"].points))
initial = T0 + T2 * legendre.P2(sinphi)
Ts = Field(initial, domain=sfc)
state = AttrDict()
state["Ts"] = Ts
return state
def __init__(self,
name='Untitled',
state=None,
domains=None,
subprocess=None,
lat=None,
lev=None,
num_lat=None,
num_levels=None,
input=None,
verbose=True,
**kwargs):
# verbose flag used to control text output at process creation time
self.verbose = verbose
self.name = name
# dictionary of domains. Keys are the domain names
self.domains = _make_dict(domains, _Domain)
# If lat is given, create a simple domains
if lat is not None:
sfc = zonal_mean_surface()
self.domains.update({'default': sfc})
# dictionary of state variables (all of type Field)
self.state = attr_dict.AttrDict()
states = _make_dict(state, Field)
for name, value in states.items():
self.set_state(name, value)
# dictionary of model parameters
self.param = kwargs
# dictionary of diagnostic quantities
#self.diagnostics = attr_dict.AttrDict()
#self._diag_vars = frozenset()
self._diag_vars = []
# dictionary of input quantities
#self.input = _make_dict(input, Field)
if input is None:
#self._input_vars = frozenset()
self._input_vars = []
else:
self.add_input(list(input.keys()))
for name, var in input:
self.__dict__[name] = var
self.creation_date = time.strftime("%a, %d %b %Y %H:%M:%S %z",
time.localtime())
# subprocess is a dictionary of any sub-processes
self.subprocess = attr_dict.AttrDict()
if subprocess is not None:
self.add_subprocesses(subprocess)
def __init__(
self,
num_lat=90,
S0=const.S0,
A=210.,
B=2.,
D=0.555, # in W / m^2 / degC, same as B
water_depth=10.0,
Tf=-10.,
a0=0.3,
a2=0.078,
ai=0.62,
timestep=const.seconds_per_year / 90.,
T_init_0=12.,
T_init_P2=-40.,
**kwargs):
super(EBM, self).__init__(timestep=timestep, **kwargs)
if not self.domains and not self.state: # no state vars or domains yet
sfc = domain.zonal_mean_surface(num_lat=num_lat,
water_depth=water_depth)
lat = sfc.axes['lat'].points
initial = T_init_0 + T_init_P2 * legendre.P2(
np.sin(np.deg2rad(lat)))
self.set_state('Ts', Field(initial, domain=sfc))
self.param['S0'] = S0
self.param['A'] = A
self.param['B'] = B
self.param['D'] = D
self.param['Tf'] = Tf
self.param['water_depth'] = water_depth
self.param['a0'] = a0
self.param['a2'] = a2
self.param['ai'] = ai
# create sub-models
self.add_subprocess('LW', AplusBT(state=self.state, **self.param))
self.add_subprocess('insolation',
P2Insolation(domains=sfc, **self.param))
self.add_subprocess(
'albedo', albedo.StepFunctionAlbedo(state=self.state,
**self.param))
# diffusivity in units of 1/s
K = self.param['D'] / self.domains['Ts'].heat_capacity
self.add_subprocess(
'diffusion',
MeridionalDiffusion(state=self.state, K=K, **self.param))
self.topdown = False # call subprocess compute methods first
def __init__(self,
num_lat=90,
S0=const.S0,
A=210.,
B=2.,
D=0.555, # in W / m^2 / degC, same as B
water_depth=10.0,
Tf=-10.,
a0=0.3,
a2=0.078,
ai=0.62,
timestep=const.seconds_per_year/90.,
T_init_0 = 12.,
T_init_P2 = -40.,
**kwargs):
super(EBM, self).__init__(timestep=timestep, **kwargs)
if not self.domains and not self.state: # no state vars or domains yet
sfc = domain.zonal_mean_surface(num_lat=num_lat,
water_depth=water_depth)
lat = sfc.axes['lat'].points
initial = T_init_0 + T_init_P2 * legendre.P2(np.sin(np.deg2rad(lat)))
self.set_state('Ts', Field(initial, domain=sfc))
self.param['S0'] = S0
self.param['A'] = A
self.param['B'] = B
self.param['D'] = D
self.param['Tf'] = Tf
self.param['water_depth'] = water_depth
self.param['a0'] = a0
self.param['a2'] = a2
self.param['ai'] = ai
# create sub-models
self.add_subprocess('LW', AplusBT(state=self.state, **self.param))
self.add_subprocess('insolation',
P2Insolation(domains=sfc, **self.param))
self.add_subprocess('albedo',
albedo.StepFunctionAlbedo(state=self.state,
**self.param))
# diffusivity in units of 1/s
K = self.param['D'] / self.domains['Ts'].heat_capacity
self.add_subprocess('diffusion', MeridionalDiffusion(state=self.state,
K=K,
**self.param))
self.topdown = False # call subprocess compute methods first
def __init__(
self,
state=None,
domains=None,
subprocess=None,
lat=None,
lev=None,
num_lat=None,
num_levels=None,
input=None,
**kwargs
):
# dictionary of domains. Keys are the domain names
self.domains = _make_dict(domains, _Domain)
# If lat is given, create a simple domains
if lat is not None:
sfc = zonal_mean_surface()
self.domains.update({"default": sfc})
# dictionary of state variables (all of type Field)
self.state = attr_dict.AttrDict()
states = _make_dict(state, Field)
for name, value in states.iteritems():
self.set_state(name, value)
# dictionary of model parameters
self.param = kwargs
# dictionary of diagnostic quantities
self.diagnostics = attr_dict.AttrDict()
# dictionary of input quantities
# self.input = _make_dict(input, Field)
if input is None:
self._input_vars = frozenset()
else:
self.add_input(input.keys())
for name, var in input:
self.__dict__[name] = var
self.creation_date = time.strftime("%a, %d %b %Y %H:%M:%S %z", time.localtime())
# subprocess is a dictionary of any sub-processes
if subprocess is None:
# self.subprocess = {}
# a dictionary whose items can be accessed as attributes
self.subprocess = attr_dict.AttrDict()
else:
self.add_subprocesses(subprocess)
def __init__(self, name='Untitled', state=None, domains=None, subprocess=None,
lat=None, lev=None, num_lat=None, num_levels=None,
input=None, verbose=True, **kwargs):
# verbose flag used to control text output at process creation time
self.verbose = verbose
self.name = name
# dictionary of domains. Keys are the domain names
self.domains = _make_dict(domains, _Domain)
# If lat is given, create a simple domains
if lat is not None:
sfc = zonal_mean_surface()
self.domains.update({'default': sfc})
# dictionary of state variables (all of type Field)
self.state = AttrDict()
states = _make_dict(state, Field)
for name, value in states.items():
self.set_state(name, value)
# dictionary of model parameters
self.param = kwargs
# dictionary of diagnostic quantities
#self.diagnostics = AttrDict()
#self._diag_vars = frozenset()
self._diag_vars = []
# dictionary of input quantities
#self.input = _make_dict(input, Field)
if input is None:
#self._input_vars = frozenset()
self._input_vars = []
else:
self.add_input(list(input.keys()))
for name, var in input:
self.__dict__[name] = var
self.creation_date = time.strftime("%a, %d %b %Y %H:%M:%S %z",
time.localtime())
# subprocess is a dictionary of any sub-processes
self.subprocess = AttrDict()
if subprocess is not None:
self.add_subprocesses(subprocess)
def surface_state(num_lat=90,
num_lon=None,
water_depth=10.,
T0=12.,
T2=-40.):
"""Sets up a state variable dictionary for a surface model
(e.g. :class:`~climlab.model.ebm.EBM`) with a uniform slab ocean depth.
The domain is either 1D (latitude) or 2D (latitude, longitude)
depending on whether the input argument num_lon is supplied.
Returns a single state variable `Ts`, the temperature of the surface
mixed layer (slab ocean).
The temperature is initialized to a smooth equator-to-pole shape given by
.. math::
T(\phi) = T_0 + T_2 P_2(\sin\phi)
where :math:`\phi` is latitude, and :math:`P_2` is the second Legendre
polynomial :class:`~climlab.utils.legendre.P2`.
**Function-call arguments** \n
:param int num_lat: number of latitude points [default: 90]
:param int num_lat: (optional) number of longitude points [default: None]
:param float water_depth: depth of the slab ocean in meters [default: 10.]
:param float T0: global-mean initial temperature in :math:`^{\circ} \\textrm{C}` [default: 12.]
:param float T2: 2nd Legendre coefficient for equator-to-pole gradient in
initial temperature, in :math:`^{\circ} \\textrm{C}` [default: -40.]
:returns: dictionary with temperature
:class:`~climlab.domain.field.Field`
for surface mixed layer ``Ts``
:rtype: dict
:Example:
::
>>> from climlab.domain import initial
>>> import numpy as np
>>> T_dict = initial.surface_state(num_lat=36)
>>> print np.squeeze(T_dict['Ts'])
[-27.88584094 -26.97777479 -25.18923361 -22.57456133 -19.21320344
-15.20729309 -10.67854785 -5.76457135 -0.61467228 4.61467228
9.76457135 14.67854785 19.20729309 23.21320344 26.57456133
29.18923361 30.97777479 31.88584094 31.88584094 30.97777479
29.18923361 26.57456133 23.21320344 19.20729309 14.67854785
9.76457135 4.61467228 -0.61467228 -5.76457135 -10.67854785
-15.20729309 -19.21320344 -22.57456133 -25.18923361 -26.97777479
-27.88584094]
"""
if num_lon is None:
sfc = domain.zonal_mean_surface(num_lat=num_lat,
water_depth=water_depth)
else:
sfc = domain.surface_2D(num_lat=num_lat,
num_lon=num_lon,
water_depth=water_depth)
if 'lon' in sfc.axes:
lon, lat = np.meshgrid(sfc.axes['lon'].points, sfc.axes['lat'].points)
else:
lat = sfc.axes['lat'].points
sinphi = np.sin(np.deg2rad(lat))
initial = T0 + T2 * legendre.P2(sinphi)
Ts = Field(initial, domain=sfc)
#if num_lon is None:
# Ts = Field(initial, domain=sfc)
#else:
# Ts = Field([[initial for k in range(num_lon)]], domain=sfc)
state = AttrDict()
state['Ts'] = Ts
return state
def surface_state(num_lat=90,
num_lon=None,
water_depth=10.,
T0=12.,
T2=-40.):
"""Sets up a state variable dictionary for a surface model
(e.g. :class:`~climlab.model.ebm.EBM`) with a uniform slab ocean depth.
The domain is either 1D (latitude) or 2D (latitude, longitude)
depending on whether the input argument num_lon is supplied.
Returns a single state variable `Ts`, the temperature of the surface
mixed layer (slab ocean).
The temperature is initialized to a smooth equator-to-pole shape given by
.. math::
T(\phi) = T_0 + T_2 P_2(\sin\phi)
where :math:`\phi` is latitude, and :math:`P_2` is the second Legendre
polynomial :class:`~climlab.utils.legendre.P2`.
**Function-call arguments** \n
:param int num_lat: number of latitude points [default: 90]
:param int num_lat: (optional) number of longitude points [default: None]
:param float water_depth: depth of the slab ocean in meters [default: 10.]
:param float T0: global-mean initial temperature in :math:`^{\circ} \\textrm{C}` [default: 12.]
:param float T2: 2nd Legendre coefficient for equator-to-pole gradient in
initial temperature, in :math:`^{\circ} \\textrm{C}` [default: -40.]
:returns: dictionary with temperature
:class:`~climlab.domain.field.Field`
for surface mixed layer ``Ts``
:rtype: dict
:Example:
::
>>> from climlab.domain import initial
>>> import numpy as np
>>> T_dict = initial.surface_state(num_lat=36)
>>> print np.squeeze(T_dict['Ts'])
[-27.88584094 -26.97777479 -25.18923361 -22.57456133 -19.21320344
-15.20729309 -10.67854785 -5.76457135 -0.61467228 4.61467228
9.76457135 14.67854785 19.20729309 23.21320344 26.57456133
29.18923361 30.97777479 31.88584094 31.88584094 30.97777479
29.18923361 26.57456133 23.21320344 19.20729309 14.67854785
9.76457135 4.61467228 -0.61467228 -5.76457135 -10.67854785
-15.20729309 -19.21320344 -22.57456133 -25.18923361 -26.97777479
-27.88584094]
"""
if num_lon is None:
sfc = domain.zonal_mean_surface(num_lat=num_lat,
water_depth=water_depth)
else:
sfc = domain.surface_2D(num_lat=num_lat,
num_lon=num_lon,
water_depth=water_depth)
if 'lon' in sfc.axes:
lon, lat = np.meshgrid(sfc.axes['lon'].points, sfc.axes['lat'].points)
else:
lat = sfc.axes['lat'].points
sinphi = np.sin(np.deg2rad(lat))
initial = T0 + T2 * legendre.P2(sinphi)
Ts = Field(initial, domain=sfc)
#if num_lon is None:
# Ts = Field(initial, domain=sfc)
#else:
# Ts = Field([[initial for k in range(num_lon)]], domain=sfc)
state = AttrDict()
state['Ts'] = Ts
return state
