# A roadmap to the efficient and robust characterization of temperate
terrestrial planet atmospheres with JWST

TRAPPIST-1 JWST Community Initiative Julien de Wit${}^{\ref{miteaps},*}$ René
Doyon${}^{\ref{udem},\ref{trot},*}$ Benjamin V.
Rackham${}^{\ref{miteaps},\ref{mitkav}}$ Olivia
Lim${}^{\ref{udem},\ref{trot}}$ Elsa Ducrot${}^{\ref{paris_region},\ref{cea}}$
Laura Kreidberg${}^{\ref{mpia}}$ Björn Benneke${}^{\ref{udem},\ref{trot}}$
Ignasi Ribas${}^{\ref{ICECSIC},\ref{IEEC}}$ David Berardo${}^{\ref{miteaps}}$
Prajwal Niraula${}^{\ref{miteaps}}$ Aishwarya Iyer${}^{\ref{ASU}}$ Alexander
Shapiro${}^{\ref{mpis}}$ Nadiia Kostogryz${}^{\ref{mpis}}$ Veronika
Witzke${}^{\ref{mpis}}$ Michaël Gillon${}^{\ref{uliege1}}$ Eric
Agol${}^{\ref{washAA},\ref{washN}}$ Victoria
Meadows${}^{\ref{washAA},\ref{washN}}$ Adam J. Burgasser${}^{\ref{san_diego}}$
James E. Owen${}^{\ref{ICL}}$ Jonathan J. Fortney${}^{\ref{UCSC}}$ Franck
Selsis${}^{\ref{UBord}}$ Aaron Bello-Arufe${}^{\ref{JPL}}$ Emeline
Bolmont${}^{\ref{ObsGen},\ref{CVGen}}$ Nicolas
Cowan${}^{\ref{mcgillE},\ref{mcgillP}}$ Chuanfei Dong${}^{\ref{BU}}$ Jeremy J.
Drake${}^{\ref{CfA}}$ Lionel Garcia${}^{\ref{uliege1}}$ Thomas
Greene${}^{\ref{NASAAmes}}$ Thomas Haworth${}^{\ref{QMUL}}$ Renyu
Hu${}^{\ref{JPL},\ref{CalTechG}}$ Stephen R. Kane${}^{\ref{UCR}}$ Pierre
Kervella${}^{\ref{LESIA}}$ Daniel Koll${}^{\ref{PekU}}$ Joshua Krissansen-
Totton${}^{\ref{UWE}}$ Pierre-Olivier Lagage${}^{\ref{cea}}$ Tim
Lichtenberg${}^{\ref{UGron}}$ Jacob Lustig-Yaeger${}^{\ref{JHU}}$ Manasvi
Lingam${}^{\ref{FIT},\ref{UTA}}$ Martin Turbet${}^{\ref{UBord},\ref{Sorbo}}$
Sara Seager${}^{\ref{miteaps},\ref{mitkav},\ref{mitAA}}$ Khalid
Barkaoui${}^{\ref{uliege1},\ref{miteaps},\ref{IAC}}$ Taylor J.
Bell${}^{\ref{NASAAmesB},\ref{NASAAmesSSAD}}$ Artem
Burdanov${}^{\ref{miteaps}}$ Charles Cadieux${}^{\ref{trot}}$ Benjamin
Charnay${}^{\ref{LESIA}}$ Ryan Cloutier${}^{\ref{McMU}}$ Neil J.
Cook${}^{\ref{trot}}$ Alexandre C. M. Correia${}^{\ref{CFisUC},\ref{IMCCE}}$
Lisa Dang${}^{\ref{trot}}$ Tansu Daylan${}^{\ref{Princ}}$ Laetitia
Delrez${}^{\ref{uliege1},\ref{uliege2}}$ Billy Edwards${}^{\ref{SRON}}$ Thomas
J. Fauchez${}^{\ref{NASAGo},\ref{AmUn}}$ Laura Flagg${}^{\ref{Corn}}$ Federico
Fraschetti${}^{\ref{CfA},\ref{LPL}}$ Jacob Haqq-Misra${}^{\ref{BlueM}}$ Ziyu
Huang${}^{\ref{BU}}$ Nicolas Iro${}^{\ref{DLR}}$ Ray
Jayawardhana${}^{\ref{Corn}}$ Emmanuel Jehin${}^{\ref{uliege2}}$ Meng
Jin${}^{\ref{Lockh}}$ Edwin Kite${}^{\ref{UChi}}$ Daniel
Kitzmann${}^{\ref{UBern}}$ Quentin Kral${}^{\ref{LESIA}}$ David
Lafrenière${}^{\ref{trot}}$ Anne-Sophie Libert${}^{\ref{UNam}}$ Beibei
Liu${}^{\ref{UZhej}}$ Subhanjoy Mohanty${}^{\ref{ICL}}$ Brett M.
Morris${}^{\ref{STScI}}$ Catriona A. Murray${}^{\ref{UCol}}$ Caroline
Piaulet${}^{\ref{trot}}$ Francisco J. Pozuelos${}^{\ref{IAA}}$ Michael
Radica${}^{\ref{trot}}$ Sukrit Ranjan${}^{\ref{LPL}}$ Alexander
Rathcke${}^{\ref{DTU}}$ Pierre-Alexis Roy${}^{\ref{trot}}$ Edward W.
Schwieterman${}^{\ref{UCR}}$ Jake D. Turner${}^{\ref{Corn}}$ Amaury
Triaud${}^{\ref{UBirm}}$ Michael J. Way${}^{\ref{NASAGISS},\ref{UUpp}}$

###### Abstract

Ultra-cool dwarf stars are abundant, long-lived, and uniquely suited to enable
the atmospheric study of transiting terrestrial companions with JWST. Amongst
them, the most prominent is the M8.5V star TRAPPIST-1 and its seven planets,
which have been the favored targets of eight JWST Cycle 1 programs. While
Cycle 1 observations have started to yield preliminary insights into the
planets[1, 2], they have also revealed that their atmospheric exploration
requires a better understanding of their host star[3]. Here, we propose a
roadmap to characterize the TRAPPIST-1 system—and others like it—in an
efficient and robust manner. We notably recommend that—although more
challenging to schedule—multi-transit windows[4, 5] be prioritized to
constrain stellar heterogeneities and gather up to 2$\times$ more transits per
JWST hour spent. We conclude that in such systems planets cannot be studied in
isolation by small programs, thus large-scale community-supported programs
should be supported to enable the efficient and robust exploration of
terrestrial exoplanets in the JWST era.

∗These authors contributed equally to this work.

Department of Earth, Atmospheric and Planetary Science, Massachusetts
Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA

Department of Physics, Université de Montréal, Montreal, QC, Canada

Trottier Institute for Research on Exoplanets, Université de Montréal,
Montreal, QC, Canada

Kavli Institute for Astrophysics and Space Research, Massachusetts Institute
of Technology, Cambridge, MA 02139, USA

Paris Region Fellow, Marie Sklodowska-Curie Action

AIM, CEA, CNRS, Université Paris-Saclay, Université de Paris, F-91191 Gif-sur-
Yvette, France

Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg, Germany

Institut de Ciències de l’Espai (ICE, CSIC), Campus UAB, c/ Can Magrans s/n,
08193 Bellaterra, Barcelona, Spain

Institut d’Estudis Espacials de Catalunya (IEEC), c/ Gran Capità 2–4, 08034
Barcelona, Spain

School of Earth and Space Exploration, Arizona State University, 525 E.
University Dr., Tempe AZ 85281

Max Planck Institute for Solar System Research, Göttingen, Germany

Astrobiology Research Unit, Université de Liège, 19C Allée du 6 Août, 4000
Liège, Belgium

Department of Astronomy and Astrobiology Program, University of Washington,
Box 351580, Seattle, Washington 98195, USA

NASA Nexus for Exoplanet System Science, Virtual Planetary Laboratory Team,
Box 351580, University of Washington, Seattle, Washington 98195, USA

Center for Astrophysics and Space Sciences, UC San Diego, UCSD Mail Code 0424,
9500 Gilman Drive, La Jolla, CA 92093-0424, USA

Astrophysics Group, Imperial College London, Blackett Laboratory, Prince
Consort Road, London SW7 2AZ, UK

Department of Astronomy and Astrophysics, University of California, Santa
Cruz, Santa Cruz, 95064, CA, USA.

Laboratoire d’astrophysique de Bordeaux, Univ. Bordeaux, CNRS, B18N, allée
Geoffroy Saint-Hilaire, 33615 Pessac, France

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA,
USA

Observatoire astronomique de l’université de Genève, Chemin Pegasi 51,
CH-1290, Versoix, Switzerland

Centre Vie dans l’Univers, Faculté des sciences, Université de Genève, Quai
Ernest-Ansermet 30, 1211 Genève 4, Switzerland

Department of Earth & Planetary Sciences, McGill University, 3450 rue
University, Montréal, QC H3A 0E8, Canada

Department of Physics, McGill University, 3600 rue University, Montréal, QC
H3A 2T8, Canada

Department of Astronomy, Boston University, Boston, Massachusetts 02215, USA

Center for Astrophysics — Harvard & Smithsonian, 60 Garden Street, Cambridge
MA 02138

NASA Ames Research Center, Space Science and Astrobiology Division, MS 245-6,
Moffett Field, CA, 94035 USA

Astronomy Unit, School of Physics and Astronomy, Queen Mary University of
London, London E1 4NS, UK

Division of Geological and Planetary Sciences, California Institute of
Technology, Pasadena, CA, USA.

Department of Earth and Planetary Sciences, University of California,
Riverside, CA, USA

LESIA, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université,
Université de Paris, 5 place Jules Janssen, 92195 Meudon, France

Department of Atmospheric and Oceanic Sciences, Peking University, Beijing,
China

Department of Earth and Space Sciences/Astrobiology Program, University of
Washington, Seattle, WA 98195, USA.

Kapteyn Astronomical Institute, University of Groningen, P.O. Box 800, NL-9700
AV Groningen, The Netherlands

The Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins
Rd, Laurel, MD, 20723, USA

Department of Physics and Institute for Fusion Studies, The University of
Texas at Austin, Austin, TX 78712, USA

Laboratoire de Météorologie Dynamique/IPSL, CNRS, Sorbonne Université, Ecole
Normale Supérieure, Université PSL, Ecole Polytechnique, Institut
Polytechnique de Paris, 75005 Paris, France ;

Department of Aeronautics and Astronautics, MIT, 77 Massachusetts Avenue,
Cambridge, MA 02139, USA

Instituto de Astrofísica de Canarias (IAC), Calle Vía Láctea s/n, 38200, La
Laguna, Tenerife, Spain

BAER Institute, NASA Ames Research Center, Moffet Field, CA, USA

Space Science and Astrobiology Division, NASA Ames Research Center, Moffett
Field, CA, USA

Department of Physics & Astronomy, McMaster University, 1280 Main St W,
Hamilton, ON, L8S 4L8, Canada

CFisUC, Departamento de Física, Universidade de Coimbra, 3004-516 Coimbra,
Portugal

IMCCE, UMR8028 CNRS, Observatoire de Paris, PSL Université, 77 Av. Denfert-
Rochereau, 75014 Paris, France

Department of Astrophysical Sciences, Princeton University, 4 Ivy Lane,
Princeton, NJ 08544

Space sciences, Technologies and Astrophysics Research (STAR) Institute,
Université de Liège, Allée du 6 Août 19C, 4000 Liège, Belgium

SRON, Netherlands Institute for Space Research, Niels Bohrweg 4, NL-2333 CA,
Leiden, The Netherlands

NASA Goddard Space Flight Center, Greenbelt, MD, USA

Integrated Space Science and Technology Institute, Department of Physics,
American University, Washington DC, USA

Department of Astronomy and Carl Sagan Institute, Cornell University, Ithaca,
New York 14853, USA

Lunar & Planetary Laboratory/Department of Planetary Sciences, University of
Arizona, Tucson, AZ, USA

Blue Marble Space Institute of Science, 600 1st Avenue, 1st Floor, Seattle,
Washington 98104, USA

Institute of Planetary Research, German Aerospace Center (DLR),
Rutherfordstrasse 2, D-12489 Berlin, Germany

Lockheed Martin Solar and Astrophysics Lab (LMSAL), Palo Alto, CA 94304, USA

Department of the Geophysical Sciences, University of Chicago, 5734 S Ellis
Ave., Chicago, IL 60637

Center for Space and Habitability, University of Bern, Gesellschaftsstrasse 6,
3012 Bern, Switzerland

naXys Research Institute, Department of Mathematics, University of Namur, 61
Rue de Bruxelles, Namur, Belgium

Department of Aerospace, Physics and Space Sciences, Florida Institute of
Technology, Melbourne, FL 32901

Institute for Astronomy, School of Physics, Zhejiang University, Hangzhou
310027, China

Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD
21218-2410, USA

Department of Astrophysical & Planetary Sciences, University of Colorado
Boulder, Boulder, CO, USA

Instituto de Astrofísica de Andalucía (IAA-CSIC), Glorieta de la Astronomía
s/n, 18008 Granada, Spain

DTU Space, National Space Institute, Technical University of Denmark,
Elektrovej 328, DK-2800 Kgs. Lyngby, Denmark

School of Physics & Astronomy, University of Birmingham, Edgbaston,
Birmingham, B15 2TT, UK

NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY USA

Department of Physics and Astronomy, Theoretical Astrophysics, Uppsala
University, Uppsala, Sweden

##  1 Milky Way’s terrestrial temperate population: habitable oases or airless
rocks?

Terrestrial planets within the temperate zones—defined as receiving a flux
between $4\times$ and $0.25\times$ that of the Earth[6]—surrounding M dwarfs
are abundant [7, 8, 9]. As these stars dominate the galactic population [10],
planetary systems around M dwarfs can be viewed as windows on the galactic
terrestrial-planet population (Figure 1.a.). Unfortunately, temperate
terrestrial exoplanets are only amenable for atmospheric studies with JWST
when found around late M dwarfs (Figure 1.b.), specifically ultra-cool dwarf
stars (UCDs, with effective temperature less than 3000 K). The small sizes of
UCDs yield favorable planet-to-star radius ratios that enable the
detectability of terrestrial planet atmospheres via transmission spectroscopy.

If temperate planets around UCDs are able to acquire a moderate amount of
atmospheric volatiles during planet formation[11], and preserve it during
their star’s extended pre-main-sequence phase[12, 13], our galaxy may be host
to billions of habitable oases. Alternative scenarios, depending on volatile
inventories and age, may include scorched desert, runaway greenhouse, or
frigid, ice-locked ocean worlds[14, 15, 16, 17, 18, 19, 20]. Other factors
such as large XUV fluxes, stellar winds, flares, and coronal mass ejections
can evaporate and erode planetary atmospheres and remain at high levels on Gyr
timescales, thus supporting the former fate [21, 22, 23, 24]. In addition,
after the protoplanetary-disk phase collisions with planetesimals may deliver
volatiles to the outermost planets but erode the atmospheres of the innermost
ones[25]. As the observational constraints on both the effectiveness of these
processes and the planets’ original volatile reservoirs are limited, reliable
predictions are poorly constraining. In some instances even H2-dominated
atmospheres can be sustained by a balance between outgassing and escape[26].
The presence of an atmosphere on terrestrial UCD planets must therefore be
established empirically, an endeavor for which JWST is uniquely suited.

##  2 TRAPPIST-1: an opportunity and a test case.

Figure 1.b. highlights that a handful of systems with transiting terrestrial
exoplanets amenable for atmospheric characterization with JWST have already
been discovered (incl., L 98-59 [27], LHS 1140 [28], LHS 3844 [29], LP 791-18
[30, 31], LP 890-9[32], TOI-540 [33], and TRAPPIST-1 [34, 35]). Understanding
how planets form, assemble, and evolve around UCDs is a fundamental question
of planet formation, and the TRAPPIST-1 system provides a benchmark for such
studies[36]. Being able to study how the presence or absence of an atmosphere
or how the properties of such an atmosphere vary over seven planetary
configurations within a single system will be considerably more informative
than a similar number of configurations in distinct systems with different
histories and properties (incl. stellar activity). Similarly, comparative
studies leveraging planets within the same system are key to enable
habitability assessment[6].

While multiplanetary systems are expected and indeed found in ‘peas-in-a-pod’
architectures[37, 38, 39, 40, 41], only the TRAPPIST-1 system has been
identified with three or more transiting terrestrial planets and at least two
temperate ones—despite dedicated surveys such as SPECULOOS [42, 43] EDEN [44],
and PINES[45] searching for such systems around 20 times more UCDs than the
original TRAPPIST survey [46]. TRAPPIST-1 can thus be seen as both a unique
opportunity and test case in paving the way towards the characterization of
terrestrial exoplanets with JWST, in fact there may be no better target[47].

The radii of the seven TRAPPIST-1 planets have been measured to a precision of
a few % [48]. Their masses have been constrained to the same precision via
transit-timing variations. Pilot surveys with transmission spectroscopy from
HST/WFC3 and the mass–radius relationship of the planets have independently
ruled out the presence of large hydrogen-dominated atmospheres for all the
planets [4, 5, 49, 50, 51, 52, 53]. The planets adhere to a single rocky
mass–radius relation that can notably correspond to an iron depletion relative
to Earth[51], or an Earth-like composition enhanced in volatiles[11, 17, 18]
possibly splitting the climatic evolution of the planets in- and outside of
the long-lasting runaway greenhouse irradiation limit[54]. The next step in
the characterization of these planets is to assess the presence of secondary
cloud-free atmospheres, and—if present—to plan their detailed study. This
opportunity has already motivated eight Cycle 1 programs and one Cycle 2
program totaling over 280 JWST hrs.

##  3 Lessons from Cycle 1.

As the first insights into the system gained from Cycle 1 observations are
becoming public, we gather below key lessons that may help guide future
programs targeting terrestrial exoplanetary systems.

###  3.1 Planets.

To this date, only observations relative to the inner planets of the system
have been made public: in emission[1] and in transmission[3] for planet b and
in emission only for planet c[2]. The transmission spectrum of planet b
appears dominated by stellar contamination (next section) while its emission
reveals a very hot dayside, consistent with zero heat redistribution. On the
other hand, planet c has a slightly cooler dayside, possibly indicative of a
thin atmosphere or a higher surface albedo. However, with planet flux measured
in just one photometric bandpass, the interpretation of these measurements is
ambiguous.

###  3.2 Star.

JWST Cycle 1 programs targeting transits of planets around K- and M-type stars
including TRAPPIST-1 have shown that a key limitation stems from the effects
of stellar activity in the time domain (e.g., flares[55]) and in the
wavelength domain (e.g., stellar contamination) [56, 3].

Cycle 1 observations of TRAPPIST-1 have shown that flare events occur during
most transit observations and have intensities up to several thousands of ppm
in the near infrared (Figure 2). Flares constitute a significant source of
time- and wavelength-dependent continuum flux that contaminate transit depth
measurements by affecting the out-of-transit baseline and/or the in-transit
data. A mini-flare can also be mistaken for a spot-crossing event as was
observed on July 20th 2022, just before the egress of TRAPPIST-1 b[3].

The chromatic transit depth, or “transmission spectrum,” of a planet contains
only information related to the wavelength-dependent opacity of a planet’s
atmosphere if its star is a limb-darkened but otherwise featureless disk. As
most stars do show surface features in the form of spots and faculae, the
transmission spectrum also contains a stellar contribution due to the
difference between the hemisphere-averaged emission spectrum of the star and
the transit-chord-averaged one (Figure 2.a.), a phenomenon known as the
“transit light source” (TLS) effect[57, 58]. In addition, spectra of magnetic
features are not well described by 1D models which is expected to affect the
interpretation of derived transit depths impacted by the TLS effect[59, 60].

Prior to JWST, studies already highlighted the effect of stellar contamination
for the TRAPPIST-1 system [61, 49, 48, 52]. Space- and ground-based data
showed that stellar contamination in the system perturbs the apparent transit
depth of each planet by up to 10% (Figure 3.a.), resulting in spectral signals
of up to $\sim$700 p.p.m. in amplitude, larger than the $\sim$200-p.p.m.
signals expected from secondary atmospheres. The first JWST observations of
the system confirm that stellar contamination can be as high as 600 ppm,
although it is not consistent from visit to visit and planet to planet[3].
Prior to JWST, studies already highlighted the effect of stellar contamination
for the TRAPPIST-1 system [61, 49, 48, 52]. Space- and ground-based data
showed that stellar contamination in the system perturbs the apparent transit
depth of each planet by up to 10% (Figure 3.a.), resulting in spectral signals
of up to $\sim$700 p.p.m. in amplitude, larger than the $\sim$200-p.p.m.
signals expected from secondary atmospheres (Figure 1.b.). The first JWST
observations of the system confirm that stellar contamination can be as high
as 600 ppm, although it is not consistent from visit to visit and planet to
planet[3].

###  3.3 Transit frequency.

The TRAPPIST-1 system is tightly packed, which results in many windows with
back-to-back transits. In fact, for $\sim$46% of the transit events another
transit happens within 5 hours (Figure 4.a.), which is the typical duration
for transit observations of the system in Cycle 1. This means that one can
target back-to-back transits and, in many cases, observe two transits for the
observational cost of one. Figure 4.b. shows the example of a partial transit
of planet b observed serendipitously during a planned transit observation of
planet g (GO 2589, PI Lim). Unfortunately, partial transits are challenging to
fully utilize.

##  4 Considerations to turn lemons into lemonade

The detailed atmospheric study of terrestrial planet atmospheres with JWST is
a multi-step process that will likely require hundreds of transit or
occultation observations spread over $>$5 cycles, even with the most favorable
case to date, TRAPPIST-1 [62, 63]. For each planet, the first step is to
assess the presence of an atmosphere and perform a preliminary
characterization, which may warrant a detailed study over a second step aimed
at deriving tighter and more informative constraints on the atmospheric
properties (e.g., composition, temperature, and pressure profiles). For
TRAPPIST-1, if planets harbor atmospheres that are not cloudy/hazy, the first
step necessitates anywhere between a few to several dozen transits for CO2-,
CO-, H2O-, O2, or N2-dominated atmospheres, depending on bulk abundances [62,
64, 63, 65, 66, 67]. Assessing the presence of secondary atmospheres in the
TRAPPIST-1 system would thus require upwards of 46 transits or $\sim$276 JWST
hrs at the average Cycle-1 cost of 6 hr per transit for this system. The
second, in-depth, characterization step would require a similar level of
commitment for each atmosphere to study, notably for assessing their
atmospheric carbon depletion[6]. These estimates assume that the stellar
effects mentioned above can be fully mitigated.

To this end, the continuum jitter associated with flare activity must be
corrected and so must the TLS effect. This is an inescapable prerequisite to
reliably extracting and interpreting $\leq$200-ppm atmospheric signals
expected for this system. This situation is akin to the precision radial
velocity field that, about one decade ago, had to learn how to extract
Keplerian signals significantly smaller than those generated by stellar
activity. Thanks to various activity indicators and novel analysis methods,
Keplerian signals smaller than those generated by stellar activity are now
routinely detected close to the photon-noise limit (e.g., as for Proxima d
[68]).

###  4.1 Flares: approach and insights

Deriving a better understanding of a UCD’s flares requires monitoring and
characterizing its activity over a long period of time. Doing so will yield
empirical calibrations between H$\alpha$, recombination lines, and the
variable, wavelength-dependent continuum flux. Indeed, flares are detected in
H$\alpha$ along with several other recombination lines of the Paschen and
Brackett series (Figure 2). As TRAPPIST-1’s dtectable flares occur every 5 to
10 hours, a full stellar rotation curve can yield a sufficient sample to
inform these relationships. The frequencies of flares also support the need
for extended baselines when performing transit observations. Indeed, the
signatures of flares typically last between one and three hours, which is the
typical duration of the pre- or post-transit observation. In other words,
flares have a $\sim$30% chance of significantly biasing the out-of-transit
baseline of a standard 6-hr transit observation of TRAPPIST-1.

The flaring activity and likely associated coronal mass ejection of a UCD has
important implications for the atmospheres of its planets [69, 22, 70].
Insights into their position/directionality, intensity, and frequency [71, 72,
73, 74] will help update current atmospheric evolution models for UCD planets
[75, 76] and help answer crucial questions relative to the potential
habitability of their planets (incl., abiogenesis zone[77]). In particular, if
the activity of a UCD emerges primarily from its poles and thus leaves their
ecliptic untouched it has important implications for the sustainability and
evolution of atmospheres and biospheres around its planets.

###  4.2 Stellar contamination: approach and insights

Correcting for the TLS effect utilizes the out-of-transit stellar spectrum to
derive the temperatures and covering fractions of different components to
correct for their contributions to the stellar contamination [61, 49, 52].
Doing so requires reliable stellar spectral models to break otherwise-limiting
degeneracies[78]. Figure 3 presents the out-of-transit JWST/NIRISS spectra of
the G8V star WASP-39 and of the M8.5V star TRAPPIST-1 with their respective
best fit, highlighting the significant model inaccuracy for TRAPPIST-1, which
are primarily due to stellar models being streched beyond their intended usage
to approximate spots and faculae.

Little is currently known about properties of UCDs, their surface
heterogeneities, and their environments. Following the recommendation from the
NASA SAG21 Report on stellar contamination [79], simulations of magnetic
features on UCDs (e.g., with the 3D MHD code MURaM [80]) and calculations of
their spectra (e.g., with MPS-ATLAS [59]) are under way. Modelling of such
cool stars relies on a number of crucial steps, including accurate treatment
of molecular opacity and the equation of state. Fortunately, tight constraints
on the emission spectra of heterogeneities can also be derived empirically
from a full stellar rotation via time-resolved spectroscopy[81], thereby
providing a unique opportunity to benchmark a new generation of stellar
models. In the meantime, we advocate to perform first-order corrections of the
TLS effect by leveraging multi-transit windows with at least one planet
expected to have a marginal atmospheric signature in transmission, thereby
constraining the TLS signal at that epoch (see Section 5).

Constraints on the timescales of temporal variability of the covering
fractions will in turn provide constraints on whether the variability arises
from rotational modulation of active regions, physical evolution of active
regions, or both. Two puzzles of TRAPPIST-1’s variability [82] could then be
explored: (1) the existence of bright spots of line emission producing the
$\sim$1% variability seen in the Kepler band but not in Spitzer’s, and (2) the
coincidence of flares and the steepest rise in the spot flux observed with
Kepler.

##  5 A roadmap for JWST’s exploration of TRAPPIST-1-like systems

With the previous considerations in mind, we propose the following roadmap to
the exploration of a terrestrial planet system with JWST:

  1. 1.

Gather MIRI/LRS emission observations of the inner planets to assess the
presence of an atmosphere ($\sim$10 eclipses or 60hrs per planet and/or a
joint phase curve, $\leq$70 hr). This step has been planned for the TRAPPIST-1
system (PIDs 1177, 1279, 2304, and 3077 with Greene, Lagage, Kreidberg, and
Gillon as PI, respectively) ;

  2. 2.

If one of the inner planets does have a “featureless” atmosphere such that its
transmission spectrum primarily records the TLS effect at that epoch, the
presence of atmosphere around the other planets in the system can be supported
via a first-order TLS correction anchored by contemporaneous NIRSpec/GRISM
transit of that planet ($\leq$10 transit per planets for a total of $\sim$300
hr for the system thanks to multi-transit windows);

  3. 3.

If all inner planets appear to have an atmosphere, it will only be possible to
correct for TLS via empirical constraints on the stellar models. Therefore, a
full NIRISS/SOSS stellar rotation curve would be needed to search for the
presence of atmosphere around the other planets ($\sim$80 hr in addition to
the $\sim$300 hr mentioned at point 2).

  4. 4.

If an atmosphere is detected, its in-depth characterization may take upwards
of $\sim$300 hr (see section 3 and Ref.[6] and will require the empirical
emission spectra of the stellar heterogeneities mentioned at point 3 to ensure
a thorough correction of TLS.

Thermal emission spectra for the inner planets should be prioritized at the
beginning of the TRAPPIST-1 roadmap[1, 2]. These measurements are not
sensitive to stellar heterogeneity, and the results will provide important
context for the other planets in the system. If an atmosphere has survived at
the relatively high irradiation incident on planet b or c, that would be an
encouraging prospect that the cooler planets have atmospheres too. However, an
absence of atmosphere around the innermost planets has limited to no
implications on the odds of outer planets retaining substantial
atmospheres[83]. The inner planets are both the least likely to have retained
their atmospheres and the ones with the shortest period (i.e., with the
greatest probability of having consecutive transits) and thus may offer a
valuable opportunity to support preliminary correction of TLS when gathering
multi-transit observations (Figure 5). Such preliminary corrections would be
sufficiently precise (to within $\leq$50ppm) to support revealing secondary
atmospheres around other planets, but would not support a later in-depth
exploration which would require stellar models of sufficient fidelity. The TLS
associated with an atmosphereless planet is not identical to the one recorded
by other planets in quasi-contemporaneous transits due to their different
timings, impact parameters, and sizes.

To assess the presence of atmosphere amenable to in-depth characterization
with JWST around the other TRAPPIST-1 planets, we recommend leveraging multi-
transit windows as successfully implemented during the reconnaissance of the
system with HST (PIDs 14500&14873, PI de Wit) for the following three reasons
(highlighted in Figure 5). First, multi-transit windows decrease the overhead
per transit and can yield up to 2${\times}$ more transits per JWST hour spent,
thereby allowing us to save hundreds of JWST hours on this system alone.
Second, multi-transit windows provide an extended baseline, thereby mitigating
the relative effect of flare events. Third, back-to-back transits provide a
quasi-contemporaneous scan of the star, increasing substantially the
information content of the dataset and supporting notably better constraints
on the stellar contamination. Consecutive transits of adjacent chords will
sweep up to 60% of the visible stellar hemisphere, facilitating searches for
active regions from the stellar equator to stellar latitudes of $35^{\circ}$
[42, 51] and helping map the star [72, 73, 74], thereby informing the possible
evolution of atmospheres and biospheres (Section 4). Finally, stellar scans
will help constrain their mutual inclinations of the planets (i.e., on which
side of the ecliptic each planet is) by comparing their in-transit spot-
crossing patterns (Figure 5.e.).

Following the approved Cycle 1 programs and Ref.[63], we find that ten of such
multi-transit windows are needed to complement the Cycle 1 programs and
reliably assess the presence of atmospheres around each of the TRAPPIST-1
planets. These windows typically spread over two cycles due to their
scheduling constraints and require $\sim$80–100 hr in total. NIRSpec/PRISM is
best suited for this search as it covers a wide wavelength coverage suitable
for TLS correction and atmospheric-component identification[6].

If signs of a planetary atmosphere are found, we recommend acquiring a full
stellar rotation curve with a maximum number of contemporaneous transits. We
have identified at least four windows per Cycle offering nine bonus planetary
transits during a full rotation (Figure 5.a.). This full rotation curve will
not only yield the empirical emission spectra, enabling the reliable
correction of the TLS effect and thus unlocking the atmospheric
characterization of the TRAPPIST-1 planets[81], it will also yield the
empirical calibrations to support the corrections for flares (Section 3.1.).
NIRISS/SOSS is the optimal set up for this task owing to its spectral coverage
and resolving power, allowing to constrain key molecular features and spectral
lines while preventing full saturation.

Before concluding, we note that long-term parallel monitoring from the ground
can complement space-based monitoring providing independent constraints on the
activity state of a star. Joint physical modelling of photometry and activity
indicators from high-precision spectroscopy can reconstruct the surface
distribution of active regions on the face of the star and their time
evolution [84], therefore providing other means to correct for stellar
contamination during transits [85]. Multi-technique and multi-band
observations, covering the widest possible wavelength range, make it possible
to disentangle most of the parameter degeneracies of stellar active regions
[86] and render the inverse problem possible. Therefore, the present roadmap
should aim to bracket JWST transit observations of TRAPPIST-1 with
contemporaneous ground-based monitoring to ensure that we can attain the best
possible understanding of the stellar surface heterogeneities at the relevant
epoch and reliably disentangle between the stellar and planetary signals in
transit.

As the steps towards an efficient characterization of a TRAPPIST-1-like system
with JWST will require tight scheduling constraints, a significant time
commitment, and a wide range of expertise, we argue that a single, coherent,
cross-disciplinary observational program is needed per UCD system of interest.

##  6 Captions of Figures

Figure 1: The Ultra-Cool Dwarf Stars Opportunity. Ultra-cool dwarf stars
(UCDs) are the most abundant, long-lived, and amenable for transit study of
terrestrial worlds. a. Histogram of spectral types of all stars within 10 pc
observed by Gaia[87] together with the main-sequence lifetime (orange) and
expected transit depth for a terrestrial planet for each type (blue). The
region of UCDs is shaded in purple. The difference between expectations from
the stellar initial mass function (gray dotted line) and known detections owes
to observational bias. b. Most promising terrestrial planets for atmospheric
characterization. Planets transiting late-M, early-M, and other hosts are
shown as stars, squares, and triangles, respectively. Colors illustrate the
transmission spectroscopy metric[88], and marker sizes are proportional to
planet sizes. The region of temperature planets with instellations between
0.25 and 4 $S_{\oplus}$ is highlighted, and planets of particular interest are
labelled.  Figure 2: On the time-dependent contributions of flares to
TRAPPIST-1’s spectrum. a. White-light NIRSpec/PRISM light-curve showing
multiple flares and a planetary transit. b. Integrated flux in the H$\alpha$
stellar line during this observation. c. Extracted emission spectrum of the
flare (black points), consistent with a 3000 K blackbody. Models for 2500 K,
3000 K, and 3500 K blackbodies are shown in blue, orange, and green,
respectively. Purple, teal, and red dashed lines indicate locations of Balmer,
Paschen, and Brackett recombination lines, respectively. Adapted from
Ref.[55].  Figure 3: Challenges in performing spectral analysis of M-dwarf
systems stemming from their heterogeneous photospheres. a. Model transmission
spectra of TRAPPIST-1 b for an O2-dominated atmosphere in the case of no
stellar contamination (grey), unocculted spots (blue), and unocculted faculae
(orange). Spot and facula parameters are drawn from ref. [52]. Observations
are simulated for NIRISS/SOSS (solid lines) and NIRSpec/PRISM (dashed lines),
the latter of which does not have sufficient resolution to sample stellar
lines. b. G-dwarf WASP-39’s NIRISS/SOSS spectrum (black) is in excellent
agreement with stellar models (purple). c. Normalized residuals between the
WASP-39 data and model. d. M-dwarf TRAPPIST-1’s NIRISS/SOSS spectrum (black)
is poorly fitted by stellar models (purple). e. Normalized residuals between
the TRAPPIST-1 data and model.  Figure 4: On the frequency of planetary
transits in the TRAPPIST-1 system. a. Histogram of time-to-closest-transit for
each TRAPPIST-1 transit event between 2015–2025. b. Serendipitous partial
transit of TRAPPIST-1 b during the first GO-2589 observation of TRAPPIST-1 g.
Figure 5: Constraining the surface heterogeneities of a host star. a. A
simulated 3.3-d full rotation curve of TRAPPIST-1 (black line) featuring nine
transits of six planets (coloured lines). b. A snapshot of the spot
distribution at the last rotational phase of the simulation shown in panel a,
with the transit chords of planets b, c, d, and e. c. Contaminated
transmission spectra for the same transit train of planets b–e (coloured
lines). A nominal planet radius of 1 $R_{\oplus}$ (dashed gray line) is used
for each planet to ease comparisons of the TLS effect for each planet. d. The
residual stellar contamination signals for the simulated transits of planets
c–e (coloured lines), after correcting for the TLS effect using the in-transit
signal from planet b. A median-subtracted model of an atmosphere (see Figure
2) is shown for comparison (gray dashed line). e. Close-up view of the transit
profiles for the four-planet transit train, highlighting repeated occultations
of the same active regions by planets b and d as well as c and e, whose
transit chords overlap in this simulation.

.

The authors declare that they have no competing financial interests.

The light curve model in Figure 5 was generated with fleck[89].

Correspondence and requests for materials should be addressed to
<EMAIL_ADDRESS>
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