limiter

class climlab.process.limiter.Limiter(bounds={}, **kwargs)

Bases: TimeDependentProcess

A process that implements strict bounds on the allowable range of values of state variables. Values outside the given bounds are adjusted back to the bounding value at each timestep.

Bounding values are stored in a dictionary .bounds which has identical keys to .state

Each item in the .bounds dict is another dict containing the keys 'minimum' and 'maximum'. By default these are initialized to None and np.inf respectively, which means the process produces zero adjustment.

The user needs to specify desired minimum and/or maximum values for each state variable. These can be specified at process creation time using the keyword argument bounds, or modified in-place (see example below).

For diagnostic purposes, we can always access the adjustments (in state variable units) and the tendencies (in state variable units per second) produced by the Limiter just like any other process (see example below)

Example use: an EBM with surface temperature limited to <= 25 degrees C:

import climlab
ebm = climlab.EBM()
#  Create the Limiter process, and make sure it has a matching timestep
mylimiter = climlab.process.Limiter(state=ebm.state, timestep=ebm.timestep)
#  Now set our desired upper bound on the temperature
mylimiter.bounds['Ts']['maximum'] = 25.
#  And couple it to the rest of the model
ebm.add_subprocess('TempLimiter', mylimiter)
#  Take a step forward and verify that surface temperatures do not exceed 25 degrees C
ebm.step_forward()
assert np.all(ebm.Ts<=25)
#  Examine the tendencies (in degrees C / second) produced by the Limiter:
#  They should be zero everywhere the temperaure is less than 25 degrees: 
print(ebm.subprocess['TempLimiter'].tendencies)

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.
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.

_compute()

Where the tendencies are actually computed…

Needs to be implemented for each daughter class

Returns a dictionary with same keys as self.state