external_forcing

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class climlab.process.external_forcing.ExternalForcing(**kwargs)

Bases: TimeDependentProcess

A Process class for user-defined tendencies of state variables. Useful for combining some prescribed external forcing with an interactive model.

Example:

The user can invoke the process on a dicionary of state variables mystate like this:

myforcing = climlab.process.ExternalForcing(state=mystate)

and then set the desired tendencies in the dictionary myforcing.forcing_tendencies, in units of [state variable unit] per second.

Attributes:

depth

Depth at grid centers (m)

depth_bounds

Depth at grid interfaces (m)

diagnostics

Dictionary access to all diagnostic variables

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.

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)	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.
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.
set_timestep([timestep, num_steps_per_year])	Calculates the timestep in unit seconds and calls the setter function of timestep()
step_forward()	Updates state variables with computed tendencies.
to_xarray([diagnostics])	Convert process variables to xarray.Dataset format.