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
- First adaptation of dynamical core: Mayne+ (2014a,b)
- First adaptation of the radiative transfer (RT), and implementation of overlap scheme: Amundsen+ (2014, 2017)
- First use of RT&dynamics for hot Jupiters: Amundsen+ (2016)
- First use of Gibbs minimisation chemical equilibrium scheme: Drummond+ (2018a)
- First use of chemical relaxation scheme: Drummond+ (2018b)
- First use of cloud model (DIHRT) for hot Jupiters: Lines+ (2018)
- First application of climate model (GA7.0) to rocky exoplanets: Boutle+ (2017)
- First use of land surface model: Lewis+ (2018)
- Exploring the role of mineral dust: Boutle+ (2020)
- Exploring the role of stellar spectra: Eager+ (2020)
- First use of the nesting suite: Sergeev+ (2020)
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?
- Run an ensemble of global experiments with perturbed convection parameters
- Run an ensemble of global experiments with perturbed convection parameters
- 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?
- Run an ensemble of global experiments with perturbed convection parameters
- Integrate a metric of convection strength over the substellar region
- 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?
- Run an ensemble of global experiments with perturbed convection parameters
- Integrate a metric of convection strength over the substellar region
- Correlate with a metric of day-night heat redistribution
- 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?
- Run an ensemble of global experiments with perturbed convection parameters
- Integrate a metric of convection strength over the substellar region
- Correlate with a metric of day-night heat redistribution
- 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?
- Run an ensemble of global experiments with perturbed convection parameters
- Integrate a metric of convection strength over the substellar region
- Correlate with a metric of day-night heat redistribution
- 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 website: dennissergeev.github.io
Code for figures: github.com/dennissergeev/exoconvection-apj-2020
My twitter: meteodenny
This presentation: slides.com/denissergeev/2020-11-10-um-workshop-sergeev
Published paper: https://doi.org/10.3847/1538-4357/ab8882
UM workshop talk
By Denis Sergeev
UM workshop talk
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