def column_state(num_lev=30, num_lat=1, lev=None, lat=None, water_depth=1.0):
'''Set up a state variable dictionary consisting of temperatures
for atmospheric column (`Tatm`) and surface mixed layer (`Ts`).
'''
if lat is not None:
num_lat = np.array(lat).size
if lev is not None:
num_lev = np.array(lev).size
if num_lat is 1:
sfc, atm = domain.single_column(water_depth=water_depth,
num_lev=num_lev,
lev=lev)
else:
sfc, atm = domain.zonal_mean_column(water_depth=water_depth,
num_lev=num_lev,
lev=lev,
num_lat=num_lat,
lat=lat)
num_lev = atm.lev.num_points
Ts = Field(288. * np.ones(sfc.shape), domain=sfc)
Tinitial = np.tile(np.linspace(200., 288. - 10., num_lev), sfc.shape)
Tatm = Field(Tinitial, domain=atm)
state = AttrDict()
state['Ts'] = Ts
state['Tatm'] = Tatm
return state
def initial_state(num_lev, num_lat, lev, lat, water_depth):
if num_lat is 1:
sfc, atm = domain.single_column(water_depth=water_depth, num_lev=num_lev, lev=lev)
else:
sfc, atm = domain.zonal_mean_column(water_depth=water_depth, num_lev=num_lev, lev=lev, num_lat=num_lat, lat=lat)
num_lev = atm.lev.num_points
Ts = Field(288.0 * np.ones(sfc.shape), domain=sfc)
Tinitial = np.tile(np.linspace(288.0 - 10.0, 200.0, num_lev), sfc.shape)
Tatm = Field(Tinitial, domain=atm)
state = {"Ts": Ts, "Tatm": Tatm}
return state
def initial_state(num_lev, num_lat, lev, lat, water_depth):
if num_lat is 1:
sfc, atm = domain.single_column(water_depth=water_depth,
num_lev=num_lev,
lev=lev)
else:
sfc, atm = domain.zonal_mean_column(water_depth=water_depth,
num_lev=num_lev,
lev=lev,
num_lat=num_lat,
lat=lat)
num_lev = atm.lev.num_points
Ts = Field(288. * np.ones(sfc.shape), domain=sfc)
Tinitial = np.tile(np.linspace(288. - 10., 200., num_lev), sfc.shape)
Tatm = Field(Tinitial, domain=atm)
state = {'Ts': Ts, 'Tatm': Tatm}
return state
def make_column(lev=None, ps=1013, tmp=None, ts=None):
state = climlab.column_state(lev=lev)
num_lev = np.array(lev).size
lev = state.Tatm.domain.lev
lev_values = lev.points
lev_dfs = np.zeros(num_lev)
lev_dfs[1:] = np.diff(lev_values)
lev_dfs[0] = lev_values[0]
lev_dfs = lev_dfs / 2.
lev.bounds = np.full(num_lev + 1, ps)
lev.bounds[:-1] = lev_values - lev_dfs
lev.delta = np.abs(np.diff(lev.bounds))
sfc, atm = domain.single_column(lev=lev)
state['Ts'] = Field(ts, domain=sfc)
state['Tatm'] = Field(tmp, domain=atm)
return state
def column_state(num_lev=30, num_lat=1, lev=None, lat=None, water_depth=1.0):
"""Set up a state variable dictionary consisting of temperatures
for atmospheric column (`Tatm`) and surface mixed layer (`Ts`).
"""
if lat is not None:
num_lat = np.array(lat).size
if lev is not None:
num_lev = np.array(lev).size
if num_lat is 1:
sfc, atm = domain.single_column(water_depth=water_depth, num_lev=num_lev, lev=lev)
else:
sfc, atm = domain.zonal_mean_column(water_depth=water_depth, num_lev=num_lev, lev=lev, num_lat=num_lat, lat=lat)
num_lev = atm.lev.num_points
Ts = Field(288.0 * np.ones(sfc.shape), domain=sfc)
Tinitial = np.tile(np.linspace(200.0, 288.0 - 10.0, num_lev), sfc.shape)
Tatm = Field(Tinitial, domain=atm)
state = AttrDict()
state["Ts"] = Ts
state["Tatm"] = Tatm
return state
def column_state(num_lev=30,
num_lat=1,
lev=None,
lat=None,
water_depth=1.0):
"""Sets up a state variable dictionary consisting of temperatures
for atmospheric column (``Tatm``) and surface mixed layer (``Ts``).
Surface temperature is always 288 K. Atmospheric temperature is initialized
between 278 K at lowest altitude and 200 at top of atmosphere according to
the number of levels given.
**Function-call arguments** \n
:param int num_lev: number of pressure levels
(evenly spaced from surface to top of atmosphere)
[default: 30]
:param int num_lat: number of latitude points on the axis
[default: 1]
:param lev: specification for height axis (optional)
:type lev: :class:`~climlab.domain.axis.Axis`
or pressure array
:param array lat: size of array determines dimension of latitude
(optional)
:param float water_depth: *irrelevant*
:returns: dictionary with two temperature
:class:`~climlab.domain.field.Field`
for atmospheric column ``Tatm`` and
surface mixed layer ``Ts``
:rtype: dict
:Example:
::
>>> from climlab.domain import initial
>>> T_dict = initial.column_state()
>>> print T_dict
{'Tatm': Field([ 200. , 202.68965517, 205.37931034, 208.06896552,
210.75862069, 213.44827586, 216.13793103, 218.82758621,
221.51724138, 224.20689655, 226.89655172, 229.5862069 ,
232.27586207, 234.96551724, 237.65517241, 240.34482759,
243.03448276, 245.72413793, 248.4137931 , 251.10344828,
253.79310345, 256.48275862, 259.17241379, 261.86206897,
264.55172414, 267.24137931, 269.93103448, 272.62068966,
275.31034483, 278. ]), 'Ts': Field([ 288.])}
"""
if lat is not None:
num_lat = np.array(lat).size
if lev is not None:
num_lev = np.array(lev).size
if num_lat == 1:
sfc, atm = domain.single_column(water_depth=water_depth,
num_lev=num_lev,
lev=lev)
else:
sfc, atm = domain.zonal_mean_column(water_depth=water_depth,
num_lev=num_lev,
lev=lev,
num_lat=num_lat,
lat=lat)
num_lev = atm.lev.num_points
Ts = Field(288.*np.ones(sfc.shape), domain=sfc)
Tinitial = np.tile(np.linspace(200., 288.-10., num_lev), sfc.shape)
Tatm = Field(Tinitial, domain=atm)
state = AttrDict()
state['Ts'] = Ts
state['Tatm'] = Tatm
return state
def column_state(num_lev=30,
num_lat=1,
lev=None,
lat=None,
water_depth=1.0):
"""Sets up a state variable dictionary consisting of temperatures
for atmospheric column (``Tatm``) and surface mixed layer (``Ts``).
Surface temperature is always 288 K. Atmospheric temperature is initialized
between 278 K at lowest altitude and 200 at top of atmosphere according to
the number of levels given.
**Function-call arguments** \n
:param int num_lev: number of pressure levels
(evenly spaced from surface to top of atmosphere)
[default: 30]
:param int num_lat: number of latitude points on the axis
[default: 1]
:param lev: specification for height axis (optional)
:type lev: :class:`~climlab.domain.axis.Axis`
or pressure array
:param array lat: size of array determines dimension of latitude
(optional)
:param float water_depth: *irrelevant*
:returns: dictionary with two temperature
:class:`~climlab.domain.field.Field`
for atmospheric column ``Tatm`` and
surface mixed layer ``Ts``
:rtype: dict
:Example:
::
>>> from climlab.domain import initial
>>> T_dict = initial.column_state()
>>> print T_dict
{'Tatm': Field([ 200. , 202.68965517, 205.37931034, 208.06896552,
210.75862069, 213.44827586, 216.13793103, 218.82758621,
221.51724138, 224.20689655, 226.89655172, 229.5862069 ,
232.27586207, 234.96551724, 237.65517241, 240.34482759,
243.03448276, 245.72413793, 248.4137931 , 251.10344828,
253.79310345, 256.48275862, 259.17241379, 261.86206897,
264.55172414, 267.24137931, 269.93103448, 272.62068966,
275.31034483, 278. ]), 'Ts': Field([ 288.])}
"""
if lat is not None:
num_lat = np.array(lat).size
if lev is not None:
num_lev = np.array(lev).size
if num_lat is 1:
sfc, atm = domain.single_column(water_depth=water_depth,
num_lev=num_lev,
lev=lev)
else:
sfc, atm = domain.zonal_mean_column(water_depth=water_depth,
num_lev=num_lev,
lev=lev,
num_lat=num_lat,
lat=lat)
num_lev = atm.lev.num_points
Ts = Field(288.*np.ones(sfc.shape), domain=sfc)
Tinitial = np.tile(np.linspace(200., 288.-10., num_lev), sfc.shape)
Tatm = Field(Tinitial, domain=atm)
state = AttrDict()
state['Ts'] = Ts
state['Tatm'] = Tatm
return state
