Explicit convection
on tidally locked rocky exoplanets

simulated with the UM nesting suite

UM workshop | Met Office | 10 November 2020

Denis Sergeev

+ Ian Boutle, Hugo Lambert, James Manners, Nathan Mayne

This presentation is available at slides.com/denissergeev/2020-11-10-um-workshop-sergeev

Exeter Exoplanet Theory Group

Group leader: Nathan Mayne

Staff: Eric Hebrard, Hugo Lambert

Postdocs: Duncan Christie, Arwen Nicholson, Denis Sergeev, Maria Zamyatina

PhD students: Michelle Bieger, Jake Eager, Alex Loader, Robert Ridgway

IT support: Krisztian Kohary

UK Met Office collaborators:

  • Ian Boutle
  • James Manners
  • Benjamin Drummond
  • Stefan Lines

Adapted for extraterrestrial atmospheres!

Mayne+ (2014)

Drummond+ (2018)

Lines+ (2019)

Boutle+ (2017)

Adaptation of the dynamical core

Climate modelling of a terrestrial exoplanet

Chemistry on Hot Jupiters 

Clouds on Hot Jupiters 

UM for exoplanet atmospheres

Motivation

Exoplanets

  • >4000 exoplanets discovered
  • Most detected are gas giants (like Jupiter)
  • More rocky planets are detected too

... are awesome!

Credit: ESO

Rocky planets

Hot Jupiters

Tidally locked exoplanets

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

 

Credit: Engine House Animation Studio

Credit: ESA/Hubble

Climate of Earth-like tidally locked exoplanets

Climate of Earth-like tidally locked exoplanets

Climate of Earth-like tidally locked exoplanets

Challenges in convection modelling

  • Wide scale separation between convection and planetary-scale circulation 
  • Convection is subgrid-scale and parameterised
  • All existing parameterisations are tested against observations on Earth
  • No in-situ measurements on exoplanets

GCM grid size

Sergeev+ (2020)

Arakawa+ (2004)

Modelling setup

and global climate simulations

  • 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 (\(2^\circ\times 2.5^\circ\)) model with parameterised convection
    • Regional high-resolution (4 km) model with explicit convection

Credit: NASA/JPL-Caltech

Credit: ESA

Trappist-1e

Proxima b

Global simulation of Trappist-1e

Shown are:

  • Surface temperature
  • Cloud condensate
  • Upper troposphere wind vectors

The effects of convection parameterisation on global simulations

  • "MassFlux" (Gregory-Rowntree) vs "Adjust" (Lambert-Lewis) convection schemes
  • The global climate of TL exoplanets is altered (and not just the day side!)
  • The effect is planet-dependent: the climate regime on Trappist-1e is more sensitive
  • More detailed analysis of these runs is given in Sergeev+ (2020)

Adjust minus MassFlux

Adjust minus MassFlux

MassFlux

MassFlux

Surface temperature (\(T_s\)), and

free-troposphere winds

Trappist-1e

Proxima b

High-resolution simulations

"global" (MassFlux)

"HighRes"

RA-1T 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?

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
  • The sensitivity to convection scheme is planet-dependent
  • Global UM is biased in the cloud structure and cloud radiative feedbacks w.r.t. to HighRes
  • A hypothetical global convection-permitting simulation may enhance the day-night temperature contrast
  • Valuable cases for idealised convection modelling, providing "stress-tests" for the UM

Future work

  • Extending this analysis to broader range of planetary and stellar configurations (Sergeev et al., in prep.)
  • Explore the effects of lightning on exoplanets
  • Global resolved convection on tidally locked exoplanets (LFRic)

Thank you!

Any feedback is very welcome!

My twitter: meteodenny

UM workshop talk

By Denis Sergeev