energy_budget

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class climlab.process.energy_budget.EnergyBudget(**kwargs)[source]

Bases: TimeDependentProcess

A parent class for explicit energy budget processes.

This class solves equations that include a heat capacitiy term like \(C \\frac{dT}{dt} = \\textrm{flux convergence}\)

In an Energy Balance Model with model state \(T\) this equation will look like this:

\[\begin{split}C \\frac{dT}{dt} = R\downarrow - R\uparrow - H \n \\frac{dT}{dt} = \\frac{R\downarrow}{C} - \\frac{R\uparrow}{C} - \\frac{H}{C}\end{split}\]

Every EnergyBudget object has a heating_rate dictionary with items corresponding to each state variable. The heating rate accounts the actual heating of a subprocess, namely the contribution to the energy budget of \(R\\downarrow, R\\uparrow\) and \(H\) in this case. The temperature tendencies for each subprocess are then calculated through dividing the heating rate by the heat capacitiy \(C\).

Initialization parameters n

An instance of EnergyBudget is initialized with the forwarded keyword arguments **kwargs of the corresponding children classes.

Object attributes n

Additional to the parent class TimeDependentProcess following object attributes are generated or modified during initialization:

Variables:

  • time_type (str) – is set to 'explicit'

  • heating_rate (dict) – energy share for given subprocess in unit \(\\textrm{W}/ \\textrm{m}^2\) stored in a dictionary sorted by model states

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.
class climlab.process.energy_budget.ExternalEnergySource(**kwargs)[source]

Bases: EnergyBudget

A fixed energy source or sink to be specified by the user.

Object attributes

Additional to the parent class EnergyBudget the following object attribute is modified during initialization:

Variables:

heating_rate (dict) – energy share dictionary for this subprocess is set to zero for every model state.

After initialization the user should modify the fields in the heating_rate dictionary, which contain heating rates in unit \(\textrm{W}/ \textrm{m}^2\) for all state variables.

Example:

Creating an Energy Balance Model with a uniform external energy source of \(10 \ \textrm{W}/ \textrm{m}^2\) for all latitudes:

>>> import climlab
>>> from climlab.process.energy_budget import ExternalEnergySource
>>> import numpy as np

>>> # create model & external energy subprocess
>>> model = climlab.EBM(num_lat=36)
>>> ext_en = ExternalEnergySource(state= model.state,**model.param)

>>> # modify external energy rate
>>> ext_en.heating_rate.keys()
['Ts']

>>> np.squeeze(ext_en.heating_rate['Ts'])
Field([-0., -0., -0., -0., -0., -0., -0., -0., -0.,  0.,  0.,  0.,  0.,
        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
        0., -0., -0., -0., -0., -0., -0., -0., -0., -0.])

>>> ext_en.heating_rate['Ts'][:]=10

>>> np.squeeze(ext_en.heating_rate['Ts'])
Field([ 10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,
        10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,
        10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,  10.,
        10.,  10.,  10.])

>>> # add subprocess to model
>>> model.add_subprocess('ext_energy',ext_en)

>>> print model
climlab Process of type <class 'climlab.model.ebm.EBM'>.
State variables and domain shapes:
  Ts: (36, 1)
The subprocess tree:
top: <class 'climlab.model.ebm.EBM'>
   diffusion: <class 'climlab.dynamics.diffusion.MeridionalDiffusion'>
   LW: <class 'climlab.radiation.AplusBT.AplusBT'>
   ext_energy: <class 'climlab.process.energy_budget.ExternalEnergySource'>
   albedo: <class 'climlab.surface.albedo.StepFunctionAlbedo'>
      iceline: <class 'climlab.surface.albedo.Iceline'>
      cold_albedo: <class 'climlab.surface.albedo.ConstantAlbedo'>
      warm_albedo: <class 'climlab.surface.albedo.P2Albedo'>
   insolation: <class 'climlab.radiation.insolation.P2Insolation'>
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.