Thread by @meteodenny

#TRAPPIST-1 Habitable Atmosphere Intercomparison (#THAI) trilogy is submitted to @AAS_PSJ and arXiv, check it out!
- arxiv.org/abs/2109.11457 - The Fellowship of the GCMs
- arxiv.org/abs/2109.11459 - The Two Waterworlds
- arxiv.org/abs/2109.11460 - The Return of the Spectrum

This has been a great international project with the aim to compare 4 state-of-the-art 3D global climate models (GCMs) for the case of a confirmed rocky exoplanet, linking model output to simulated observations giphy.com/clips/hamlet-t…

Lots of people made this hapen: @Nonomamades, Ian Boutle, @tsigarid, Michael Way, @storyofthewolf1, @shawndgoldman, François Forget, @haqqmisra, @ravi_kopparapu, Hugo Lambert, James Manners, @exoclimatology, @gerolvillanueva, and of course our leader @ThomasFauchez

The 4 GCMs included in the project so far are (more are welcome to join!):
- @storyofthewolf1 ExoCAM,
- @CNRS & @IPSL_outreach LMD-G,
- @NASAGISS ROCKE-3D, and
- @MetOffice_Sci Unified Model

Part 1 of the trilogy (arxiv.org/abs/2109.11457) led by @Nonomamades focused on dry/benchmark experiments with N2 and CO2-dominated atmospheres, to highlight inter-model differences in the dynamics, radiative transfer and turbulence parameterizations.

In these dry cases, the THAI GCMs generally agree quite well, but differ in the circulation regime, because #TRAPPIST-1e is at the tipping point between two regimes: fast and Rhines rotators. Plus there are substantial differences in the upper atmospheric winds.

Of course more inter-GCM differences come from moist physics, which is the focus of Part 2: arxiv.org/abs/2109.11459. LMD-G is the least cloudy, ExoCAM is the warmest and wettest, ROCKE-3D is the cloudiest. The UM tends to be colder, especially in the N2-dominated case.

In the moist aquaplanet Hab1/Hab2 cases we again find a dichotomy of the circulation regimes: 3 GCMs produce a slow/Rhines-rotator pattern, while ROCKE-3D shows a fast-rotator regime.

While the inter-GCM spread in the surface temperature is ~14 and 24K in Hab1 (N2) and Hab2 (CO2-dom.) cases, respectively, the TRAPPIST-1e climate stays within habitable* limits.

*with obvious caveats

Interestingly, our models exhibit different amplitude and periodicity of atmospheric variability - despite no variability in the stellar forcing. E.g. ExoCAM has a higher amplitude, and a longer period of cloud variability.

Which brings us to the THAI's final part led by @ThomasFauchez - focusing on simulated observables produced by the GCMs and inter-transit variability induced by weather patterns and changes of terminator cloudiness between transits.

In part 3 (arxiv.org/abs/2109.11460) we look at simulated #JWST transmission spectra using the Planetary Spectrum Generator and the output of the 4 GCMs. For dry cases, the spectra are similar and the detectability of the atmosphere agrees within 1 to 3 JWST transits.

However, with water and clouds, differences in cloud deck altitude and thickness strongly impact the continuum level leading to 35-40% in the number of predicted transits for a 5 sigma detection with #JWST.

Thus, for the first time, this work provides "GCM uncertainty error bars" for simulated atmospheric characterization which is crucial for both, planning and interpreting future observations. This would hopefully be useful for the whole #exoplanet community!

THAI showed the importance of exoplanet multi-model studies, more of them will be done in the the Climates Using Interactive Suites of Intercomparisons Nested for Exoplanet Studies (CUISINES) framework.
The 1st CUISINES workshop (BUFFET) will happen virtually next week!

Finally, all our GCM THAI data are openly available here: ckan.emac.gsfc.nasa.gov/organization/t… and you can use these scripts to reproduce the figures: github.com/projectcuisine… which would be impossible w/o python packages incl. @ProjectJupyter @numpy_team @matplotlib @xarray_dev @scitools_iris