exo_k.atm_evolution.atm_evol

@author: jeremy leconte

Module Contents

class exo_k.atm_evolution.atm_evol.Atm_evolution(bg_vmr=None, verbose=False, **kwargs)

Bases: object

Model of atmospheric evolution.

Uses exo_k.Atm class to compute radiative transfer

Initializes atmospheric profiles.

Most arguments are passed directly to exo_k.Atm class through **kwargs

Warning

Layers are counted from the top down (increasing pressure order). All methods follow the same convention.

property time

Yields current time in seconds

property time_hist

Yields the array of the times for the last call to evolve (in seconds)

set_options(reset_rad_model=False, check_keys=True, Kzz=None, cp=None, verbose=False, **kwargs)

This method is used to store the global options in the Settings object.

Arguments are all passed through **kwargs.

Sometimes, one needs to reset the radiative model to take into account some modifications (like the databases). Normally, this should be automatic, but you can force it with reset_rad_model=True

initialize_condensation(condensing_species=None, **kwargs)

This method initializes the condensation module by listing all the condensing vapors and linking them to their condensed form.

For each vapor-condensate pair, a Condensible_species object is created with the thermodynamical data provided.

Here is an example of dictionary to provide as input to include CH4 condensation ``` condensing_species={‘ch4’:{‘Latent_heat_vaporization’: 5.25e5, ‘cp_vap’: 2.232e3, ‘Mvap’: 16.e-3,

‘T_ref’: 90., ‘Psat_ref’: 0.11696e5}}

```

setup_radiative_model(k_database=None, k_database_stellar=None, cia_database=None, cia_database_stellar=None, gas_vmr=None, **kwargs)

This method initializes the exo_k.Atm object that will be used to carry out radiative transfer calculations.

This is where the radiative data used are chosen and transmitted to the radiative transfer module, along with many other parameters including the incoming stellar flux (flux_top_dw), the blackbody temperature of the star (Tstar), the

If a k_database_stellar is provided, then this is this database that will be used to treat the scattering and absorption of incoming radiation. In that case, k_database will be used to treat the emission of the atmosphere. The effective cos(zenith angle) for the incoming stellar radiation can then be specified independently with the mu0_stellar keyword.

If no k_database_stellar is provided, k_database will be used to treat both the atmospheric emission and the stellar radiation. Running a model with k_database_stellar=k_database yields the same results at twice the cost.

Parameters:

• k_database (exo_k.Kdatabase objects) – radiative database for the molecules in the atmospheres.

• k_database_stellar (exo_k.Kdatabase objects) – radiative database for the molecules in the atmospheres.

• cia_database (exo_k.CIA_database object) – radiative database for the CIA ofmolecules in the atmospheres.

• cia_database_stellar (exo_k.CIA_database object) – radiative database for the CIA ofmolecules in the atmospheres.

compute_average_fluxes()

Use the averaged heating rates to compute the various fluxes (W/m^2) at the level interfaces. These fluxes are positive when the energy flows upward.

To be consistent with radiative fluxes, the first array value corresponds to the top of atmosphere and should be 0 in most cases. The last value corresponds to the flux between the deepest layer (considered to be the surface) and the layer just above.

evolve(N_timestep=1, N_kernel=10000, timestep_factor=1.0, dT_max=100.0, verbose=False, check_cons=False, **kwargs)

The time variable used in the model is tau=t/cp. The equation we are solving in each layer is thus

\[c_p \frac{d T}{d t}= \frac{d T}{d tau} = \sum_i H_i\]

For a given timestep dtau, the physical time elapsed in second can be computed using dt=dtau*cp

To work, the heating rates (H) must be computed in W/kg.

This also means that if one needs the physical rate of change of another quantity (like dq/dt) from the delta q over a time step, one needs to do dq/dt = delta q / (timestep * cp)

Parameters:

• N_timestep (int) – Number of timesteps to perform.

• N_kernel (int) – Maximal number of timesteps between two computations of the radiative kernel.

• timestep_factor (float) – Multiplicative factor applied to timestep computed automatically by the radiative module. timestep_factor > 1 can lead to unstabilities.

• dT_max (float) – Maximum temperature increment in a single timestep.

equilibrate(Fnet_tolerance=None, N_iter_max=10, N_timestep_ini=100, N_timestep_max=1000000, verbose=False, **kwargs)

Evolves an atmosphere until it is at equilibrium.

Equilibrium is assumed to be reached when the net top of atmosphere flux remains within +-Fnet_tolerance of the internal flux for a whole evolution step.

The number of timesteps per evolution step in multiplied by two at each iteration, starting from N_timestep_ini, until the limit of N_timestep_max is reached.

Parameters:

• Fnet_tolerance (float) – Tolerance on net flux in W/m^2 to identify convergence.

• N_iter_max (int) – Max number of successive calls to evolve

• N_timestep_ini (int) – Initial number of timesteps in a single evolution step

• N_timestep_max (int) – Max number of timesteps in a single evolution step

moist_convective_adjustment(timestep, Htot, moist_inhibition=True, verbose=False)

This method computes the vapor and temperature tendencies do to moist convectoin in saturated layers.

The tracer array in modified in place.

Parameters:

• timestep (float) – physical timestep of the current step (in s/cp).

• Htot (array, np.ndarray) – Total heating rate (in W/kg) of all physical processes already computed

Returns:

H_madj: array, np.ndarray

Heating rate due to large scale condensation (W/kg)

molecular_diffusion(timestep, Htot, atm, cp)

Mixes energy following a diffusion equation with a constant Dmol parameter (self.Dmol in m^2/s).

Parameters:

• timestep (float) – physical timestep of the current step (in s/cp). (needs to be converted before it is sent to `turbulent diffusion)

• Htot (array, np.ndarray) – Total heating rate (in W/kg) of all physical processes already computed

• atm (Atm object) – The Atm object used in the radiative transfer which contains many state variables.

condensation(timestep, Htot, verbose=False)

This method computes the vapor and temperature tendencies do to large scale condensation in saturated layers.

The tracer array in modified in place.

Parameters:

• timestep (float) – physical timestep of the current step (in s/cp).

• Htot (array, np.ndarray) – Total heating rate (in W/kg) of all physical processes already computed

Returns:

H_cond: array, np.ndarray

Heating rate due to large scale condensation (W/kg)

rainout(timestep, Htot, verbose=False)

This method computes rainout.

Condensates are carried down and reevaporated whenever there is “room” in an unsaturated layer.

The option evap_coeff acts has an efficiency factor. evap_coeff=1 is the efficient evaporation limit. When evap_coeff<1 the maximum amount of condensates that can be reevaporated in a single layer is multiplied by evap_coeff

All condensates are finaly evaporated in the last layer or when T > Tboil.

The tracer array is modified in place.

Parameters:

• timestep (float) – physical timestep of the current step (in s/cp).

• Htot (array, np.ndarray) – Total heating rate (in W/kg) of all physical processes already computed

Returns:

H_rain: array, np.ndarray

Heating rate due to re evaporation (W/kg)

compute_hybrid_coordinates()

Compute hybrid coordinates as in GCM.

This will be used when surface pressure changes.

Convention : sigma = (p-ptop)/(psurf-ptop) For each layer/level, the pressure is p = sigma * psurf + gamma

compute_mass_flux(dvapor_mass, sum_dvapor_mass)

Computes the mass flux through the hybrid coordinate interfaces (kg/s/m^2; positive upward). (see Methods in Leconte et al. (2013))

W[k] is the mass flux between layer k-1 et k.

Parameters:

• sum_dvapor_mass (float) – Total mass of vapor added to the atmosphere in the last timestep.

• dvapor_mass (array, np.ndarray) – mass of vapor added to each layer.

For the moment, W[0] = W[Nlay]

mass_redistribution(qarray_before_condensation)

Update new mass and new pressure of a layer due to the evaporation and condensation of a given species, for more details see Methods, Leconte et al., 2013 (Nature)

radiative_acceleration(timestep=0.0, acceleration_mode=0, verbose=False, **kwargs)

“Computes an acceleration factor and a new heating rate to speed up convergence

Parameters:

acceleration_mode (int) – 0: no acceleration 1 or 3: acceleration limited to radiative zones. 2 or 4: acceleration in convective zones as well.

• 1: acceleration limited to radiative zones. The largest radiative timescale in non-radiative zones is used as reference radiative timsescale to compute acceleration.

• 2: Same as mode 1 + acceleration in convective zones

• 3 acceleration limited to radiative zones. The smallest radiative timescale in radiative zones is used as reference radiative timsescale to compute acceleration.

• 4: Same as mode 3 + acceleration in convective zones

heating_rate(physical_process)

Returns heating rates in W/kg per layer averaged over last call to evolve. Possible physical_processes are rad, cond, conv, rain, madj, tot

net_flux(physical_process)

Returns net_flux in W/m^2 averaged over last call to evolve. Possible physical_processes are rad, cond, conv, rain, madj, tot

qsat(mol)

Returns the saturation specific concentration of molecule mol (kg/kg)

write_pickle(filename, data_reduction_level=1)

Saves the instance in a pickle file

Parameters:

• filename (str) – Path to pickle file

• data_reduction_level (int) – Level of data to delete. 0: keep everything (results in big files). 1: removes some arrays, should not affect subsequent evolution. 2: removes the k and cia databases. The radiative model will need to be reset. This can be done with set_options(k_database=, cia_database=, reset_rad_model=True) after re-loading the Atm_evolution instance.