ConvectiveAdjustment

Inheritance diagram of climlab.convection.ConvectiveAdjustment
class climlab.convection.convadj.ConvectiveAdjustment(adj_lapse_rate=None, **kwargs)[source]

Bases: climlab.process.time_dependent_process.TimeDependentProcess

Hard Convective Adjustment to a prescribed lapse rate.

This process computes the instantaneous adjustment to conservatively remove any instabilities in each column.

Instability is defined as a temperature decrease with height that exceeds the prescribed critical lapse rate. This critical rate is set by input argument adj_lapse_rate, which can be either a numerical or string value.

Numerical values for adj_lapse_rate are given in units of K / km. Both array and scalar values are valid. For scalar values, the assumption is that the critical lapse rate is the same at every level.

If an array is given, it is assumed to represent the in-situ critical lapse rate (in K/km) at every grid point.

Alternatively, string arguments can be given as follows:

  • 'DALR' or 'dry adiabat': critical lapse rate is set to g/cp = 9.8 K / km

  • 'MALR' or 'moist adiabat' or 'pseudoadiabat': critical lapse rate follows the in-situ moist pseudoadiabat at every level

Adjustment includes the surface if 'Ts' is included in the state dictionary. This implicitly accounts for turbulent surface fluxes. Otherwise only the atmospheric temperature is adjusted.

If adj_lapse_rate is an array, its size must match the number of vertical levels of the adjustment. This is number of pressure levels if the surface is not adjusted, or number of pressure levels + 1 if the surface is adjusted.

This process implements the conservative adjustment algorithm described in Akmaev (1991) Monthly Weather Review.

Attributes
Tcol
adj_lapse_rate
ccol
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)

pcol
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.

Tcol
adj_lapse_rate
ccol
pcol