column

Object-oriented code for radiative-convective models with grey-gas radiation.

Code developed by Brian Rose, University at Albany brose@albany.edu

Note that the column models by default represent global, time averages. Thus the insolation is a prescribed constant.

Here is an example to implement seasonal insolation at 45 degrees North

Example:

import climlab

#  create the column model object
col = climlab.GreyRadiationModel()

#  create a new latitude axis with a single point
lat = climlab.domain.Axis(axis_type='lat', points=45.)

#  add this new axis to the surface domain
col.Ts.domain.axes['lat'] = lat

#  create a new insolation process using this domain
Q = climlab.radiation.insolation.DailyInsolation(domains=col.Ts.domain, **col.param)

#  replace the fixed insolation subprocess in the column model
col.add_subprocess('insolation', Q)

This model is now a single column with seasonally varying insolation calculated for 45N.

class climlab.model.column.BandRCModel(**kwargs)[source]

Bases: RadiativeConvectiveModel

Attributes:

current_time
depth: Depth at grid centers (m)
depth_bounds: Depth at grid interfaces (m)
diagnostics: Dictionary access to all diagnostic variables
elapsed_time
input: Dictionary access to all input variables
lat: Latitude of grid centers (degrees North)
lat_bounds: Latitude of grid interfaces (degrees North)
lev: Pressure levels at grid centers (hPa or mb)
lev_bounds: Pressure levels at grid interfaces (hPa or mb)
lon: Longitude of grid centers (degrees)
lon_bounds: Longitude of grid interfaces (degrees)
timestep: The amount of time over which step_forward() is integrating in unit seconds.
timestep_in_seconds: Return a float value representing the timestep in units of seconds

Methods

`add_diagnostic`(name[, value])	Create a new diagnostic variable called `name` for this process and initialize it with the given `value`.
`add_input`(name[, value])	Create a new input variable called `name` for this process and initialize it with the given `value`.
`add_subprocess`(name, proc[, verbose])	Adds a single subprocess to this process.
`add_subprocesses`(procdict)	Adds a dictionary of subproceses to this process.
`compute`()	Computes the tendencies for all state variables given current state and specified input.
`compute_diagnostics`([num_iter])	Compute all tendencies and diagnostics, but don't update model state.
`declare_diagnostics`(diaglist)	Add the variable names in `inputlist` to the list of diagnostics.
`declare_input`(inputlist)	Add the variable names in `inputlist` to the list of necessary inputs.
`do_diagnostics`()	Set all the diagnostics from long and shortwave radiation.
`integrate_converge`([crit, verbose])	Integrates the model until model states are converging.
`integrate_days`([days, verbose])	Integrates the model forward for a specified number of days.
`integrate_years`([years, verbose])	Integrates the model by a given number of years.
`remove_diagnostic`(name)	Removes a diagnostic from the `process.diagnostic` dictionary and also delete the associated process attribute.
`remove_subprocess`(name[, verbose])	Removes a single subprocess from this process.
`set_state`(name, value)	Sets the variable `name` to a new state `value`.
`step_forward`()	Updates state variables with computed tendencies.
`to_xarray`([diagnostics, timeave])	Convert process variables to `xarray.Dataset` format.

do_diagnostics()[source]: Set all the diagnostics from long and shortwave radiation. Here we need to sum over the spectral bands.

class climlab.model.column.GreyRadiationModel(num_lev=30, num_lat=1, lev=None, lat=None, water_depth=1.0, albedo_sfc=0.299, timestep=86400, Q=341.3, abs_coeff=0.0001229, **kwargs)[source]

Bases: TimeDependentProcess

Attributes:

current_time
depth: Depth at grid centers (m)
depth_bounds: Depth at grid interfaces (m)
diagnostics: Dictionary access to all diagnostic variables
elapsed_time
input: Dictionary access to all input variables
lat: Latitude of grid centers (degrees North)
lat_bounds: Latitude of grid interfaces (degrees North)
lev: Pressure levels at grid centers (hPa or mb)
lev_bounds: Pressure levels at grid interfaces (hPa or mb)
lon: Longitude of grid centers (degrees)
lon_bounds: Longitude of grid interfaces (degrees)
timestep: The amount of time over which step_forward() is integrating in unit seconds.
timestep_in_seconds: Return a float value representing the timestep in units of seconds

Methods

`add_diagnostic`(name[, value])	Create a new diagnostic variable called `name` for this process and initialize it with the given `value`.
`add_input`(name[, value])	Create a new input variable called `name` for this process and initialize it with the given `value`.
`add_subprocess`(name, proc[, verbose])	Adds a single subprocess to this process.
`add_subprocesses`(procdict)	Adds a dictionary of subproceses to this process.
`compute`()	Computes the tendencies for all state variables given current state and specified input.
`compute_diagnostics`([num_iter])	Compute all tendencies and diagnostics, but don't update model state.
`declare_diagnostics`(diaglist)	Add the variable names in `inputlist` to the list of diagnostics.
`declare_input`(inputlist)	Add the variable names in `inputlist` to the list of necessary inputs.
`do_diagnostics`()	Set all the diagnostics from long and shortwave radiation.
`integrate_converge`([crit, verbose])	Integrates the model until model states are converging.
`integrate_days`([days, verbose])	Integrates the model forward for a specified number of days.
`integrate_years`([years, verbose])	Integrates the model by a given number of years.
`remove_diagnostic`(name)	Removes a diagnostic from the `process.diagnostic` dictionary and also delete the associated process attribute.
`remove_subprocess`(name[, verbose])	Removes a single subprocess from this process.
`set_state`(name, value)	Sets the variable `name` to a new state `value`.
`step_forward`()	Updates state variables with computed tendencies.
`to_xarray`([diagnostics, timeave])	Convert process variables to `xarray.Dataset` format.

do_diagnostics()[source]: Set all the diagnostics from long and shortwave radiation.

class climlab.model.column.RadiativeConvectiveModel(adj_lapse_rate=6.5, **kwargs)[source]

Bases: GreyRadiationModel

Attributes:

current_time
depth: Depth at grid centers (m)
depth_bounds: Depth at grid interfaces (m)
diagnostics: Dictionary access to all diagnostic variables
elapsed_time
input: Dictionary access to all input variables
lat: Latitude of grid centers (degrees North)
lat_bounds: Latitude of grid interfaces (degrees North)
lev: Pressure levels at grid centers (hPa or mb)
lev_bounds: Pressure levels at grid interfaces (hPa or mb)
lon: Longitude of grid centers (degrees)
lon_bounds: Longitude of grid interfaces (degrees)
timestep: The amount of time over which step_forward() is integrating in unit seconds.
timestep_in_seconds: Return a float value representing the timestep in units of seconds

Methods

`add_diagnostic`(name[, value])	Create a new diagnostic variable called `name` for this process and initialize it with the given `value`.
`add_input`(name[, value])	Create a new input variable called `name` for this process and initialize it with the given `value`.
`add_subprocess`(name, proc[, verbose])	Adds a single subprocess to this process.
`add_subprocesses`(procdict)	Adds a dictionary of subproceses to this process.
`compute`()	Computes the tendencies for all state variables given current state and specified input.
`compute_diagnostics`([num_iter])	Compute all tendencies and diagnostics, but don't update model state.
`declare_diagnostics`(diaglist)	Add the variable names in `inputlist` to the list of diagnostics.
`declare_input`(inputlist)	Add the variable names in `inputlist` to the list of necessary inputs.
`do_diagnostics`()	Set all the diagnostics from long and shortwave radiation.
`integrate_converge`([crit, verbose])	Integrates the model until model states are converging.
`integrate_days`([days, verbose])	Integrates the model forward for a specified number of days.
`integrate_years`([years, verbose])	Integrates the model by a given number of years.
`remove_diagnostic`(name)	Removes a diagnostic from the `process.diagnostic` dictionary and also delete the associated process attribute.
`remove_subprocess`(name[, verbose])	Removes a single subprocess from this process.
`set_state`(name, value)	Sets the variable `name` to a new state `value`.
`step_forward`()	Updates state variables with computed tendencies.
`to_xarray`([diagnostics, timeave])	Convert process variables to `xarray.Dataset` format.

climlab.model.column.compute_layer_absorptivity(abs_coeff, dp)[source]: Compute layer absorptivity from a constant absorption coefficient.