exo_k.atm_evolution.convection

@author: jeremy leconte

Module Contents

exo_k.atm_evolution.convection.dry_convective_adjustment_numba(timestep, Nlay, t_lay, exner, dmass, tracer_array, Mgas, verbose=False)[source]

Computes the heating rates needed to adjust unstable regions of a given atmosphere to a convectively neutral T profile on a given timestep.

Parameters:

  • timestep (float) – Duration of the adjustment. If given in seconds, H=dT/timestep is in K/s. In the current model, timestep is in second over cp. This ensures that H=dT/timestep is in W/kg.

  • Nlay (int) – Number of atmospheric layers

  • t_lay (array, np.ndarray) – Temperatures of the atmospheric layers (K)

  • exner (array, np.ndarray) –

    Exner function computed at the layer centers ((p/psurf)**rcp)

    \[\Pi=(p / p_{s})^{R/c_p}\]

  • dmass (array, np.ndarray) – Mass of gas in each layer (kg/m^2)

Returns:

array

Heating rate in each atmospheric layer (W/kg).

exo_k.atm_evolution.convection.convective_acceleration_numba(timestep, Nlay, H_rad, rad_layers, tau_rad, tau_rads, dmass, convective_acceleration_mode=0, verbose=False)[source]

Computes a heating rate for the whole convective region to accelerate convergence

Parameters:

  • timestep (float) – Duration of the adjustment. If given in seconds, H=dT/timestep is in K/s. In the current model, timestep is in second over cp. This ensures that H=dT/timestep is in W/kg.

  • Nlay (int) – Number of atmospheric layers

  • H_rad (array, np.ndarray) – Radiative heating rate

  • rad_layers (array, np.ndarray of bool) – Elements in the array are true if layer is purely radiative

  • tau_rad (array, np.ndarray) – Baseline radiative timescale for the atmosphere. (e.g. the min of tau_rads) Should use the same units as timestep.

  • tau_rads (array, np.ndarray) – Radiative timescale for each layer. Should use the same units as timestep.

  • dmass (array, np.ndarray) – Mass of gas in each layer (kg/m^2)

  • convective_acceleration_mode (int) – convective_acceleration_mode=0 is the default mode =1 emulates an old (and bad) behavior.

Returns:

array

Heating rate in each atmospheric layer (W/kg).

exo_k.atm_evolution.convection.turbulent_diffusion_numba(timestep, Nlay, p_lay, p_lev, dmass, t_lay_ov_mu, g, Kzz, tracer_array, verbose=False)[source]

Solves turbulent diffusion equation:

\[\rho frac{\partial q}{\partial t} = \frac{\partial F_{diff}}{\partial z}\]

with a diffusive flux given by

\[F_{diff} = - \rho K_{zz} \frac{\partial q}{\partial z}\]

The equation is solved with an implicit scheme assuming that there is no flux at the top and bottom boundaries (evaporation must be treated separately for now).

Parameters:

  • timestep (float) – Time step in seconds.

  • Nlay (int) – Number of atmospheric layers

  • t_lay_ov_mu (array, np.ndarray) – Temperatures of the atmospheric layers divided by the molar_mass in kg/mol

  • p_lay (array, np.ndarray) – Pressure at the layer centers (Pa)

  • p_lev (array, np.ndarray) – Presure at the Nlay+1 level boundaries (Pa)

  • dmass (array, np.ndarray) – Mass of gas in each layer (kg/m^2)

  • g (float) – Gravity (m/s^2)

  • Kzz (float) – Eddy mixing coefficient (m^2/s)

  • tracer_array (array, np.ndarray (Ntrac, Nlay)) – Array containing the mass mixing ratio of all tracers at each layer before the mixing

Returns:

new_tracers: array, np.ndarray (Ntrac, Nlay)

Array containing the mass mixing ratio of all tracers at each layer after the mixing

exo_k.atm_evolution.convection.compute_condensation_numba(timestep, Nlay, tlay, play, cp, Mgas, qarray, idx_vap, idx_cond, thermo_parameters, latent_heating=True, condensation_timestep_reducer=None, verbose=False)[source]

Computes the heating rates needed to bring sursaturated regions back to saturation

Parameters:

  • timestep –

  • Nlay (float) – Number of layers

  • tlay (array, np.ndarray) – Layer temperatures

  • cp (float) – Specific heat capacity

  • Mgas (array, np.ndarray) – Layer molar mass

  • qarray (array, np.ndarray) – Array of tracer specific concentrations

  • idx_vap (int) – Indices for condensing species in tracer array

  • idx_cond (int) – Indices for condensing species in tracer array

  • thermo_parameters (array, np.ndarray) – Array of thermodynamical paramaters for condensing species. See :class:`~exo_k.atm_evolution.condensation.Condensation_Thermodynamical_Parameters

  • latent_heating (bool) – Whether latent heating should be taken into account

Returns:

H_cond: array, np.ndarray

Heating rate in W/kg

exo_k.atm_evolution.convection.moist_convective_adjustment_numba(timestep, Nlay, tlay, play, dmass, cp, Mgas, q_array, i_vap, i_cond, thermo_parameters, moist_inhibition=True, verbose=False)[source]

Computes the heating rates needed to adjust unstable regions of a given atmosphere to a moist adiabat.

Parameters:

  • timestep –

  • Nlay (float) – Number of layers

  • tlay (array, np.ndarray) – Layer temperatures

  • play (array) – Pressure at layer centers

  • dmass (array, np.ndarray) – mass of layers in kg/m^2

  • cp (float) – specific heat capacity at constant pressure

  • q_array (array, np.ndarray) – mass mixing ratio of tracers

  • i_vap (int) – index of vapor tracer in qarray

  • i_cond (int) – index of condensate tracer in qarray

  • qsat (array, np.ndarray) – Saturation mmr for each layer

  • dqsat_dt (array, np.ndarray) – d qsat / dT in each layer

  • Lvap (array, np.ndarray) – Latent heat of vaporization (can have different values in each layer if Lvap=f(T))

  • dlnt_dlnp_moist (array, np.ndarray) – threshold thermal gradient (d ln T / d ln P) for a moist atmosphere computed at the layer centers.

  • q_crit (array, np.ndarray) – Critical mass mixing ratio for the inhibition of moist convection (Eq. 17 of Leconte et al. 2017)

Returns:

H_madj: array, np.ndarray

Heating rate in each atmospheric layer (W/kg).

new_q: array, np.ndarray

tracer mmr array after adjustment.

new_t: array, np.ndarray

Temperature of layers after adjustment.

exo_k.atm_evolution.convection.compute_rainout_numba(timestep, Nlay, tlay, play, dmass, cp, Mgas, qarray, idx_vap, idx_cond, thermo_parameters, evap_coeff, qvap_deep, q_cloud=0.0, latent_heating=False, verbose=False)[source]

Computes the heating rates needed to adjust unstable regions of a given atmosphere to a moist adiabat.

Parameters:

  • timestep –

  • Nlay (float) – Number of layers

  • tlay (array, np.ndarray) – Layer temperatures

exo_k.atm_evolution.convection.molecular_diffusion_numba(timestep, Nlay, p_lay, p_lev, dmass, tlay, mu, g, Dmol, verbose=False)[source]

Solves turbulent diffusion equation:

\[\rho frac{\partialT}{\partial t} = \frac{\partial F_{diff}}{\partial z}\]

with a diffusive flux given by

\[F_{diff} = - \rho D_{mol} \frac{\partial T}{\partial z}\]

The equation is solved with an implicit scheme assuming that there is no flux at the top and bottom boundaries (evaporation must be treated separately for now).

Parameters:

  • timestep (float) – Time step in seconds.

  • Nlay (int) – Number of atmospheric layers

  • t_lay_ov_mu (array, np.ndarray) – Temperatures of the atmospheric layers divided by the molar_mass in kg/mol

  • p_lay (array, np.ndarray) – Pressure at the layer centers (Pa)

  • p_lev (array, np.ndarray) – Presure at the Nlay+1 level boundaries (Pa)

  • dmass (array, np.ndarray) – Mass of gas in each layer (kg/m^2)

  • g (float) – Gravity (m/s^2)

  • Dmol (float) – molecular diffusion coefficient (m^2/s)

Returns:

new_tlay: array, np.ndarray (Nlay)

Array containing the temperature at each layer after the mixing

exo_k.atm_evolution.convection.DTRIDGL(L, AF, BF, CF, DF)[source]

! GCM2.0 Feb 2003

! DOUBLE PRECISION VERSION OF TRIDGL

DIMENSION AF(L),BF(L),CF(L),DF(L),XK(L) DIMENSION AS(2*L),DS(2*L)

!* THIS SUBROUTINE SOLVES A SYSTEM OF TRIDIAGIONAL MATRIX !* EQUATIONS. THE FORM OF THE EQUATIONS ARE: !* A(I)*X(I-1) + B(I)*X(I) + C(I)*X(I+1) = D(I)

!======================================================================!