Atmospheric convection plays a key role in the climate of tidally-locked planets:

insights from high-resolution simulations

NASA GISS journal club | 21 April 2020

Denis Sergeev

University of Exeter, UK

This presentation is available at slides.com/denissergeev/2020-04-21-nasa-giss

Exeter Exoplanet Theory Group

Group leader: Nathan Mayne

Staff: Eric Hebrard, F. Hugo Lambert

Postdocs: Duncan Christie, Denis Sergeev,   Maria Zamyatina

PhD students: Michelle Bieger, Jake Eager, Robert Ridgway

IT support: Krisztian Kohary

UK Met Office collaborators: Ian Boutle, James Manners, Benjamin Drummond

Exeter Exoplanet Theory Group

Group leader: Nathan Mayne

Staff: Eric Hebrard, F. Hugo Lambert

Postdocs: Duncan Christie, Denis Sergeev,   Maria Zamyatina

PhD students: Michelle Bieger, Jake Eager, Robert Ridgway

IT support: Krisztian Kohary

UK Met Office collaborators: Ian Boutle, James Manners, Benjamin Drummond

Talk outline

  1. Challenges and importance of simulating convection on exoplanets
  2. Global simulations of Trappist-1e and Proxima Centauri b
  3. Regional high-resolution simulations and implications for the global climate

Introduction

Why are we interested in terrestrial tidally locked planets?

  • Habitable ~ have surface liquid water 
  • M-dwarf are relatively cool
  • Potentially habitable planets around M-dwarfs have to orbit closer
  • Strong tidal forces
  • Planet can become tidally locked
  • Orbital period = rotation period
  • Permanent day-side and night-side

 

Credit: ESA/Hubble

Credit: Engine House Animation Studio

Climate of Earth-like tidally locked exoplanets

Climate of Earth-like tidally locked exoplanets

Climate of Earth-like tidally locked exoplanets

Challenges in convection modeling

  • Wide scale separation between convection and planetary-scale circulation 
  • Computationally expensive
  • Convection is subgrid-scale and parameterized
  • All existing parameterizations are tested against observations on Earth and still are a big uncertainty for future climate projections
  • No in-situ measurements on exoplanets

Modeling framework

Met Office Unified Model

  • Full deep-atmosphere non-hydrostatic Navier-Stokes equations
  • Full suite of parameterizations
  • Seamless modeling: the same model is used for global climate & local high-res modeling
  • Adapted for exoplanet atmospheres

Mayne+ (2014)

Drummond+ (2018)

Lines+ (2019)

Boutle+ (2017)

Adaptation of the dynamical core

Climate modeling of a terrestrial exoplanet

Chemistry on Hot Jupiters 

Clouds on Hot Jupiters 

  • Orbital parameters of Trappist-1e and Proxima Centauri b
  • Planets are tidally locked to M-dwarf stars
  • \(N_2\)-dominated atmosphere with traces of \(CO_2\) and \(H_2O\)
  • Mean surface pressure of 1 bar
  • Aquaplanet regime (a slab ocean)
  • Two modes
    • Global coarse-resolution model with parameterized convection
    • Regional high-resolution model with explicit convection

Credit: ESA

Credit: ESA/Hubble

Credit: NASA/JPL-Caltech

Representation of convection in our global simulations

  • Standard operational scheme in the UM
  • Most sophisticated class of convection schemes
  • Involves a lot of "tuning" parameters
  • Convective adjustment to a reference state
  • Only 2 free parameters
  • Using a setup similar to Way+ (2018)

NoCnvPm

Adjust

MassFlux (Control)

  • Convection parameterization switched off

Mean global climate and its sensitivity to the convection parameterization

Global simulation of Trappist-1e

Shown are:

  • Surface temperature
  • Cloud condensate
  • Upper troposphere wind vectors

Surface temperature (\(T_s\))

  • \(T_s\) day-night contrast larger on Proxima b than on Trappist-1e

MassFlux

Surface temperature (\(T_s\))

  • \(T_s\) day-night contrast larger on Proxima b than on Trappist-1e

MassFlux

  • \(T_s\) increases globally, especially in cold traps on the night side
  • \(\Delta T_{s,dn}\) reduces

Adjust

Adjust minus MassFlux

Adjust minus MassFlux

Surface temperature (\(T_s\))

  • \(T_s\) day-night contrast larger on Proxima b than on Trappist-1e

MassFlux

  • \(T_s\) increases globally, especially in cold traps on the night side
  • \(\Delta T_{s,dn}\) reduces

NoCnvPm

Adjust

  • Small global-mean change
  • Different response on Trappist1-e vs Proxima b

NoCnvPm minus MassFlux

NoCnvPm minus MassFlux

Adjust minus MassFlux

Adjust minus MassFlux

Surface temperature (\(T_s\)) and free troposphere winds

  • \(T_s\) day-night contrast larger on Proxima b than on Trappist-1e
  • \(T_s\) increases globally, especially in cold traps on the night side
  • \(\Delta T_{s,dn}\) reduces

NoCnvPm

Adjust

MassFlux

  • Small global-mean change
  • Different response on Trappist1-e vs Proxima b

NoCnvPm minus MassFlux

NoCnvPm minus MassFlux

Adjust minus MassFlux

Adjust minus MassFlux

Circulation regime (eddy components)

  • Planetary-scale equatorial Rossby wave-like pattern

MassFlux

Circulation regime (eddy components)

  • Planetary-scale equatorial Rossby wave-like pattern

MassFlux

Circulation regime (eddy components)

  • Planetary-scale equatorial Rossby wave-like pattern

MassFlux

Circulation regime (eddy components)

  • Planetary-scale equatorial Rossby wave-like pattern

MassFlux

  • Almost a mirror-opposite of the MassFlux
  • Dominated by extratropical baroclinic gyres

Adjust

Circulation regime (eddy components)

  • Planetary-scale equatorial Rossby wave-like pattern
  • Almost a mirror-opposite of the MassFlux
  • Dominated by extratropical baroclinic gyres

NoCnvPm

Adjust

MassFlux

  • Broadly similar response as in Adjust

Circulation regime (eddy components)

  • Planetary-scale equatorial Rossby wave-like pattern
  • Almost a mirror-opposite of the MassFlux
  • Dominated by extratropical baroclinic gyres

NoCnvPm

Adjust

MassFlux

  • Broadly similar response as in Adjust

Clouds and precipitation

MassFlux

Clouds and precipitation

MassFlux

Clouds and precipitation

MassFlux

Clouds and precipitation

  • Large reduction of clouds on the day side
  • More clouds in polar regions of Trappist-1e

Adjust

MassFlux

Clouds and precipitation

  • Large reduction of clouds on the day side
  • More clouds in polar regions of Trappist-1e

NoCnvPm

Adjust

  • Day side: closer to MassFlux
  • Night side: closer to Adjust

MassFlux

Summary of global simulations: the effects of convection parameterization

  • The global climate of TL exoplanets is altered (and not just the day side!)
  • The effect is planet-dependent
  • Caution should be taken when interpreting results of GCMs with one parameterization or another.

Extra

Circulation regime

\lambda_{Rh} = \frac{\text{Rhines length}}{\text{planet's radius}}
\lambda_{Ro} = \frac{ \text{equatorial radius of deformation} }{ \text{planet's radius} }

Differences in circulation regimes

  • Leconte+ (2013)
  • Haqq-Misra+ (2017)

Energy redistribution

  • Using the horizontal divergence of the MSE flux, \(\int_0^{z_{top}} \rho \nabla\cdot\left(\vec u (c_p T + g z + L_v q) \right)dz\)
  • The largest difference is in the moist component (\(Lq\))
  • Adjust results in a more intense energy transport

Vertical profiles of temperature and humidity

Vertical cross-sections of heat fluxes at \(90^\circ E\)

High-resolution simulations

"global" (MassFlux)

"HighRes"

Nested grid setup

Spatial variability: top-of-atmosphere outgoing LW radiation

Spatial variability: top-of-atmosphere outgoing LW radiation

Spatial variability: top-of-atmosphere outgoing LW radiation

Spatial variability: top-of-atmosphere outgoing LW radiation

Histograms of instantaneous TOA OLR

Spatial variability: top-of-atmosphere outgoing LW radiation

Histograms of instantaneous TOA OLR

Vertical cloud structure (averaged profiles)

Vertical cloud structure (averaged profiles)

Vertical cloud structure (averaged profiles)

  • Biases in liquid water clouds
  • Thicker layer of mixed-phase clouds
  • Smaller bias in ice clouds

Latent heating (averaged profiles)

  • Latent heating is stronger in the global model, compared to HighRes
  • Impact on the upper-level flow divergence?

Extra

Global impact of resolved convection

  • Caveat: one-way nesting of the model
  • How to assess the impact of HighRes simulations on the global climate?
  • Caveat: one-way nesting of the model
  • How to assess the impact of HighRes simulations on the global climate?
  1. Run an ensemble of global experiments with perturbed convection parameters
  1. Run an ensemble of global experiments with perturbed convection parameters
  2. Integrate a metric of convection strength over the substellar region
  • Caveat: one-way nesting of the model
  • How to assess the impact of HighRes simulations on the global climate?
  1. Run an ensemble of global experiments with perturbed convection parameters
  2. Integrate a metric of convection strength over the substellar region
  3. Correlate with a metric of day-night heat redistribution
  • Caveat: one-way nesting of the model
  • How to assess the impact of HighRes simulations on the global climate?
  1. Run an ensemble of global experiments with perturbed convection parameters
  2. Integrate a metric of convection strength over the substellar region
  3. Correlate with a metric of day-night heat redistribution
  4. Extrapolate for the convection metric from HighRes simulations
  • Caveat: one-way nesting of the model
  • How to assess the impact of HighRes simulations on the global climate?
  1. Run an ensemble of global experiments with perturbed convection parameters
  2. Integrate a metric of convection strength over the substellar region
  3. Correlate with a metric of day-night heat redistribution
  4. Extrapolate for the convection metric from HighRes simulations
  • Caveat: one-way nesting of the model
  • How to assess the impact of HighRes simulations on the global climate?
  1. Run an ensemble of global experiments with perturbed convection parameters
  2. Integrate a metric of convection strength over the substellar region
  3. Correlate with a metric of day-night heat redistribution
  4. Extrapolate for the convection metric from HighRes simulations
  • Caveat: one-way nesting of the model
  • How to assess the impact of HighRes simulations on the global climate?

Summary

  • Representation of convection is important for the global climate of exoplanets
  • Using a simpler adjustment scheme leads to
    • on the day side: reduction of clouds, decrease in albedo (by ~60%)
    • on the night side: warming of 20-30 K
    • reduction in the day-night temperature contrast
    • change in the global circulation
  • The sensitivity to convection scheme is planet-dependent
  • The choice of convection scheme does not push the simulated climate out of habitable state
  • A potential global convection-permitting simulation may enhance the day-night temperature contrast

Future work

  • Extending this analysis to different planetary parameters and stellar spectra
  • Exploring the sensitivity to the lower boundary condition, e.g. a presence of a continent on the day side
  • Coupling the high-resolution simulation with chemical kinetics and space weather
  • Global resolved convection (LFRic project at the Met Office)

Thank you!

My twitter: meteodenny

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