Exoplanet winds: Modelling atmospheric dynamics via resolved spectral lines

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Thesis

Reference

Exoplanet winds: Modelling atmospheric dynamics via resolved spectral lines

SEIDEL, Julia Victoria

Abstract

This thesis benchmarked a new probe of atmospheric dynamics in exoplanet atmospheres by resolving the spectral lines stemming from these far atmospheres and then modelling their line shape taking into account the broadening from atmospheric winds. This gives us a window into atmospheric winds for these far away worlds only limited by the depths of the resolved lines. I resolved the sodium doublet for a wide array of exoplanets and applied the novel modelling technique to the hot Jupiter HD189733b and the ultra hot Jupiter WASP-76b.

I found that both are dominated by zonal winds in the lower, and vertical winds in the intermediate atmosphere, a first to date. This novel approach pushes the limits of high-resolution transit spectroscopy, which is evolving from an element detection technique to a more holistic atmospheric characterisation technique.

SEIDEL, Julia Victoria. Exoplanet winds: Modelling atmospheric dynamics via resolved spectral lines. Thèse de doctorat : Univ. Genève, 2021, no. Sc. 5567

DOI : 10.13097/archive-ouverte/unige:152927 URN : urn:nbn:ch:unige-1529276

Available at:

http://archive-ouverte.unige.ch/unige:152927

Disclaimer: layout of this document may differ from the published version.

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Universit´e deGeneve` Facult´e desSciences Département d’Astronomie Professeur David Ehrenreich Professeur Vincent Bourrier

Exoplanet winds –

Modelling atmospheric dynamics via resolved spectral lines

Th` ese

présentée à la Faculté des Sciences de l’Université de Genève pour obtenir le grade de Docteur ès sciences,

mention Astronomie et Astrophysique

par

Julia Victoria SEIDEL

de

Kassel (Allemagne)

Thèse N^o5567

Gen`eve

Observatoire Astronomique de l’Université de Genève 2021

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iii La science des exoplanètes est allée plus loin que ce que ses pionniers auraient pu imaginer il y a près de trente ans. Depuis la première découverte d’une atmosphère d’exoplanète, des techniques ont été développées pour déterminer si une atmosphère est nuageuse, quelles sont les températures, et même les premiers pas ont été faits dans le domaine de la caractérisation chimique. Un des groupes d’exoplanètes les plus intrigants sont les Géantes chaudes, des planètes semblables à Jupiter qui reçoivent un rayonnement accru de leur étoile en raison de leur proximité surprenante. Ces conditions n’existent pas pour les planètes du système solaire et nous donnent un aperçu des conditions atmosphériques les plus extrêmes. Une technique de détection et d’étude des atmosphères planétaires est la spectroscopie de transmission, dans laquelle les éléments de l’atmosphère de l’exoplanète absorbent de la lumière, permetant de les détecter en fonction de leur position dans l’atmosphère, à l’instar des raies de Fraunhofer. Les Géantes chaudes sont les cibles parfaites pour cette technique car ils sont suffisamment chauds pour que les atomes avec leurs raies spectrales distinctes restent dans leur état neutre et ne se condensent pas en molécules plus complexes. J’ai étudié plusieurs de ces planètes de la taille de Neptune et Jupiter, en tenant compte des diverses sources de contamination de l’atmosphère terrestre et de l’étoile elle-même. Ceci a conduit à une lim- ite supérieure pour la détection du sodium dans le spectre de transmission de la Neptune chaude WASP-127 b, plus tard détectée dans ces limites par ESPRESSO, et à des détec- tions de sodium pour la Neptune chaude WASP-166 b et la Jupiter ultra chaude WASP-76 b.

Cette dernière, en raison du fort élargissement du doublet de sodium, a soulevée la question de savoir quelle est l’ampleur de cet élargissement par rapport à la fonction de diffusion des raies du spectrographe HARPS, et d’où il vient ? En supposant que l’interaction de la lumière avec l’atmosphère est la seule source possible de l’élargissement, la cause la plus probable est l’effet Doppler dû à l’interaction de la lumière avec les particules en mouvement transportées par les fortes circulations atmosphériques. Mais quels vents dominent les atmosphères de ces mondes extrêmes ? Et à quelles altitudes et longitudes ? Pour répondre à ces questions cruciales pour la compréhension de la circulation atmosphérique, j’ai développé l’algorithme MERC. Il met en œuvre un modèle éprouvé avec un élargissement Doppler supplémentaire en combinaison avec une technique d’échantillonnage adaptative. MERC permet non seule- ment d’adapter les différentes configurations de vent aux données, mais aussi de faire la distinction entre les configurations de vent en utilisant des preuves bayésiennes. Ce travail sert de première validation pour cette technique et illustre la grande quantité d’informations encodées dans la forme résolue des raies spectrales. Dans une première application, MERC a déterminé des vents homogènes sans tenir compte de la rotation planétaire pour la chaude Jupiter HD 189733 b. En raison de ces limitations, les vitesses du vent ne peuvent être con- sidérées que comme des limites supérieures, mais nous avons pu distinguer les différentes configurations du vent. Plus tard, la version mise à jour du MERC avec une approche quasi- 3D a été appliquée à WASP-76 b. Grâce au traitement supplémentaire de la dépendance de la latitude des configurations de vent et à la quantification de la rotation planétaire, les vitesses de vent ont été estimées avec beaucoup plus de précision, comme le montre la confirmation d’un vent latéral de 5 km s⁻¹du point sub-stellaire au point anti-stellaire estimé avec une technique alternative. MERC a montré que les raies de sodium élargies dans les Jupiters chaudes sont dominées par de forts vents verticaux sous la thermosphère, très probablement dirigés vers l’extérieur dans l’expansion de la thermosphère (ou de la haute atmosphère), alors que la basse atmosphère est dominée par des vents de rotation. En résumé, ce travail a établi une nouvelle référence pour l’étude de la dynamique atmosphérique, limitée uniquement par la profondeur des raies résolues. Elle a repoussé les limites de la spectroscopie de transit à haute résolution, qui évolue d’une technique de détection élémentaire à une caractérisation holistique de l’atmosphère.

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In the short time the field of exoplanet sciences has existed, it has already come farther than its pioneers might have imagined nearly thirty years ago. Since the first detection of an exoplanet atmosphere, we have developed techniques to understand whether an atmosphere is cloudy, what kind of temperatures dominate it and where, and even ventured into the realm of chemical characterisation. One of the most intriguing group of exoplanets are hot Giants, planets like Jupiter which receive increased irradiation from their host star due to a surpris- ing proximity. These systems are unlike any conditions witnessed in the Solar System and give us a first-hand observational glimpse into the most extreme conditions atmospheres can experience. One technique to detect and study the atmosphere of these planets is transmission spectroscopy, where elements in the atmosphere of the exoplanet absorb light, allowing us to detect their presence as a function of their position in the atmosphere, similarly to the widely known Fraunhofer lines. Hot Giants are the perfect targets for this technique, because they are hot enough for atoms, with distinct spectral lines, to remain in their neutral states and not condensate into more complex molecules. I studied multiple highly irradiated Neptune- and Jupiter-sized planets, accounting for various contamination sources from the Earth’s atmosphere and the star itself. This lead to an upper limit for sodium in the warm Neptune WASP-127 b, later confirmed as a detection within these limits with ESPRESSO, and sodium detections for the warm Neptune WASP-166 b and the ultra hot Jupiter WASP- 76 b. The result for the ultra hot Jupiter WASP-76 b raised an interesting question due to the large broadening of the sodium doublet, much larger than the line spread function of the HARPS spectrograph. Where could this line broadening come from? Assuming an interaction of the light with the atmosphere as the only possible source of broadening, the most likely avenue for a broadening of the lines is Doppler-broadening due to interactions of the light with moving particles, carried by strong atmospheric circulation. But which winds dominate the atmospheres of these extreme worlds? And at which altitudes and longitudes along the terminator? To answer these crucial questions in understanding atmospheric circulation, the MERC retrieval algorithm was created. It re-implements a well-established forward model for increased computational speed with added Doppler-broadening and com- bines it with a nested sampling technique. MERC not only fits different wind patterns to the data, but discriminates between the wind patterns via Bayesian evidence. This thesis serves as a benchmark for this technique, highlighting the vast amount of information encoded in the resolved line shape of spectral lines. In a first application, MERC retrieved homogeneous winds without taking planetary rotation into account for the hot Jupiter HD 189733 b. Due to these caveats, the wind speeds can only be seen as upper limits, however, we were able to distinguish the different wind patterns. Later, the updated version of MERC with a quasi-3D approach was applied to WASP-76 b. With the additional treatment of latitude dependency of the wind patterns and the quantification of planetary rotation the wind speeds were estimated far more accurately, as highlighted by the confirmation of a day-to-night side wind of 5 km s⁻¹estimated from an alternative technique. MERC showed that the broadened sodium lines in hot Jupiters stem from strong vertical wind patterns below the thermosphere, most likely outwards pointing and feeding into atmospheric escape in the thermosphere (and upper atmosphere), while the lower atmosphere is dominated by zonal winds. Summarising, this thesis benchmarked a new probe of atmospheric dynamics, giving us a window into atmospheric winds for these far away worlds only limited by the depths of the resolved lines. It pushed the limits of high-resolution transit spectroscopy, which is evolving from an element detection technique to a more holistic atmospheric characterisation technique.

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v Seit die Exoplanetenforschung existiert ist sie bereits weiter gekommen als sich ihre Pio- niere vor fast dreißig Jahren wohl hätten vorstellen können. Seit der ersten Entdeckung einer Exoplanetenatmosphäre wurden Techniken entwickelt, um festzustellen, ob eine At- mosphäre bewölkt ist, welche Temperaturen dort herrschen und wo, und sogar erste Schritte in den Bereich der chemischen Charakterisierung getan. Eine der faszinierendsten Gruppen von Exoplaneten sind die heißen Gasriesen, Jupiter-ähnliche Planeten, die aufgrund ihrer überraschenden Nähe eine erhöhte Strahlung von ihrem Stern erhalten. Diese Konditionen existieren nicht im Sonnensystem und geben uns einen Einblick in die extremsten Atmo- sphärenbedingungen. Eine Technik zum Nachweis und zur Untersuchung der Planetenat- mosphäre ist die Transmissionsspektroskopie, bei der Elemente in der Atmosphäre des Exo- planeten Licht absorbieren, so dass wir sie in Abhängigkeit der Position in der Atmosphäre nachweisen können, ähnlich wie bei den weithin bekannten Fraunhofer-Linien. Heiße Gas- riesen sind die perfekten Ziele für diese Technik, denn sie sind heiß genug, dass die Atome mit ihren ausgeprägten Spektrallinien in ihrem neutralen Zustand bleiben und nicht zu kom- plexeren Molekülen kondensieren. Ich untersuchte mehrere dieser Planeten von Neptun- bis Jupitergröße, wobei ich verschiedene Kontaminationsquellen aus der Erdatmosphäre und dem Stern selbst berücksichtigte. Dies führte zu einer oberen Grenze für Natrium im warmen Neptun WASP-127 b, was später innerhalb dieser Grenzen mit ESPRESSO gefunden wurde, und zu Natriumnachweisen für den warmen Neptun WASP-166 b und den ultraheißen Jupiter WASP-76 b. Letzteres warf aufgrund der starken Verbreiterung des Natrium-Doubletts die Frage auf, wie weit die Verbreiterung im Vergleich mit der Linienstreuungsfunktion des HARPS-Spektrographen ist und woher sie kommt? Geht man von einer Wechselwirkung des Lichts mit der Atmosphäre als einzig möglicher Quelle für die Verbreiterung aus, so ist die wahrscheinlichste Ursache der Doppler-Effekt aufgrund der Wechselwirkung des Lichts mit bewegten Teilchen, die von starken atmosphärischen Zirkulationen getragen werden.

Aber welche Winde dominieren die Atmosphären dieser extremen Welten? Und in welchen Höhen und Längengraden? Um diese entscheidenden Fragen zum Verständnis der atmo- sphärischen Zirkulation zu beantworten, entwickelte ich den MERC-Algorithmus. Er imple- mentiert ein bewährtes Modell mit zusätzlicher Doppler-Verbreiterung in Kombination mit einer verschachtelten Sampling-Technik. MERC passt nicht nur verschiedene Windmuster an die Daten an, sondern diskriminiert zwischen den Windmustern mittels Bayes’scher Ev- idenz. Diese Arbeit dient als Testbett für diese Technik und verdeutlicht die große Menge an Informationen, die in der aufgelösten Linienform von Spektrallinien kodiert ist. In einer ersten Anwendung ermittelte MERC homogene Winde ohne Berücksichtigung der Planeten- rotation für den heißen Jupiter HD 189733 b. Aufgrund dieser Einschränkungen können die Windgeschwindigkeiten nur als obere Grenzen angesehen werden, jedoch konnten wir die verschiedenen Windmuster unterscheiden. Später wurde die aktualisierte Version von MERC mit einem Quasi-3D-Ansatz auf WASP-76 b angewendet. Mit der zusätzlichen Behand- lung der Breitenabhängigkeit der Windmuster und der Quantifizierung der planetaren Rota- tion wurden die Windgeschwindigkeiten wesentlich genauer geschätzt, wie die Bestätigung eines Tag-zu-Nacht-Seitenwindes von 5 km s⁻¹, der mit einer alternativen Technik geschätzt wurde, zeigt. MERC zeigte, dass die verbreiterten Natriumlinien in heißen Jupitern von starken vertikalen Windmustern unterhalb der Thermosphäre dominiert werden, die höchst- wahrscheinlich nach außen gerichtet sind und in die Expandierung der oberen Atmosphäre einfließen, während die untere Atmosphäre von Rotationswinden dominiert wird. Zusam- menfassend lässt sich sagen, dass diese Arbeit einen neuen Maßstab für die Erforschung von Atmosphärendynamik gesetzt hat, der nur durch die Tiefe der aufgelösten Linien räumlich begrenzt ist. Sie hat die Grenzen der hochauflösenden Transitspektroskopie erweitert, die sich von einer Technik zur Erkennung von Elementen zu einer ganzheitlichen Charakter- isierung der Atmosphäre entwickelt.

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Acknowledgements

I’d like to thank my supervisors David and Vincent for their unwavering scientific support, their open ear to issues outside their life experience, their willingness to take a chance on me, their endless patience, use of resources to shape me into a budding scientist, and last but not least their support to somehow finish this thesis despite lockdowns, telework, and terrible Wifi. I hope the gray hairs I caused were worth it.

Additionally, I would like to extend my gratitude to my committee for taking the time to read this thesis, the Studienstiftung des deutschen Volkes for financing and supporting my entire education during my Bachelor and Master, to PlanetS and the SSAA for financing part of my conference travels, and to the Swiss government for not annoying the European Union enough to kick them out of their science funding schemes - the only reason I was able to do this PhD in the first place. My special thanks to everyone in Geneva and Chile who keeps the Euler telescope alive and everyone I had the pleasure of sharing a fondue in Chile with. You made the last four years truly outstanding.

My deepest gratitude to my father for nurturing my inner scientist for as long as I can remember, from putting up with my various collections and hobbies, over logging flights of a toy aircraft, to impromptu French vocabulary lessons while hiking, without you and your patience, I would not be here. Similarly, my wholehearted gratitude goes to my mother for shaping me into a braver person and subsequently for her unconditional support of crazy interests, my constant moves around the globe, abandoned pets and furniture, as well as for putting up with the constant presence of physics in her life. Thank you to my entire family, who have always been nothing short of supportive, even if they had no idea what I was planning on doing. Sometimes, neither do I.

To the people who made all of this at times bearable, at times truly fun and my favourite conference people: Louise, Emily, Leo, Manu, Nico, Karina, Helen, Lorenzo, Heather, Jens, Alejandro, JP, Andrea, John, you know what you did. To Christian and Evelyn, I don’t remember most of what we did, but I know it will be repeated often. Here is to many more memories, my lovelies. To all my friends accumulated during the journey from Darmstadt, Paris, Geneva, London, Bogota, and again to Geneva, thank you for making my life so colour- ful, and for always welcoming me back with open arms whenever we meet, especially Mar- cella, Elissar, Alex, Efraim, and my favourite flatmate, Mohanty. Gracias por todo to Juan, for following me anywhere and always reminding me that there is more to life than academia.

To Marian, thank you, for everything.

Lastly, I’d like to express my gratitude to my mentors and/or role models, Barbara Drossel, Corinne Charbonneau, Heather Cegla, and Monika Lendl, for walking this path before me and making me believe that the glass ceiling is penetrable.

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ix

Introduction

"Wir leben auf einem blauen Planeten Der sich um einen Feuerball dreht Mit ’nem Mond, der die Meere bewegt Und du glaubst nicht an Wunder?"

Marteria, Welt der Wunder

1.1 The importance of studying winds

Meteorology, or the studies of local and global weather, is as old as humanity. One of the first instances of recorded meteorological history stems from tortoise shells engraved with observations of the local weather in the Shang Dynasty in China (∼ sixteenth - eleventh century B. C.) (Di,2016). However, observations of the local weather cycles are not enough to truly understand the nature of weather and the climate but observations of the large scale phenomena governing atmospheres are key. One of the oldest recordings of winds on a larger scale, also from China, are catalogues of Earth’s trade winds dating back to the fourth century (Di,2016). Winds are of particular interest because they mix the atmosphere globally, and as a consequence, they also facilitate air and sea travel. The power of understanding the dynamical structure of Earth winds was clear early on when Greek and Arab sailors frequented the Arabian Sea and tracked their journeys, winds, and currents as early as 50 A.D. (Ramanathan, 2016). These records were later used by Vasco da Gama in 1499 to harness the monsoon winds and travel from Portugal to Calicut in Kerala, India in three weeks (Ramanathan,2016), an impressive feat at the time. Later on, in 1716, the Qing government in China employed surveying flags nationwide to monitor wind speeds and directions in what can be considered the first modern surveying network (Di,2016).

Since then, the global satellite network surveying every aspect of our planet, especially its winds, has given us unparalleled detail, tracking storms and local weather (e.g. Rinehart and Garvey,1978; Shao and Dong, 2006; Bell et al.,2008). Additionally, it gives us real-time data on the impact of the climate emergency on global (and local) circulation patterns (e.g.

Lu, Vecchi, and Reichler, 2007 and Seidel et al., 2008on general circulation, as well as Cohen et al.,2014highlighting the fragile nature of the jet stream). Considering that we are able to track our world in meticulous detail, we know little about Earth’s climate in a wider context, how it came to be or what will happen to it given a change in external parameters, such as irradiation from the sun or concentration of elements in the atmosphere.

And while the study of our climate was used in the past to shed light on whether astronomical phenomena like the Milky Way in the night sky are of terrestrial or cosmological origin (Mc- Peak,2016), we have now progressed to question atmospheres in a larger context and aim to understand our current atmospheric circulation as one point in a whole population of possible

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atmospheric circulation patterns. This thesis hopes to add its part to this endeavour by in- terpreting observations of exoplanet winds, thus adding a piece to the puzzle of atmospheric dynamics.

1.2 A review of atmospheric circulation patterns in the Solar Sys- tem

1.2.1 Earth’s atmosphere

Figure1.1: Overview of Earth’s dynamical atmospheric structure during summer on the Northern Hemisphere focussed on the Americas. Adapted from Rees (1989).

Compared to other planets in the Solar System, Earth has considerable water coverage and subsequently a high water vapour content in its atmosphere. Assuming summer in the North- ern Hemisphere, and its increased irradiation from the sun, heating is intensified most at the subsolar point (about 20^◦latitude north). This heating induces convective circulation, while the water vapour increases the air buoyancy, letting air rise to the upper layers of the troposphere (Rees,1989). Once it reaches the higher layers the hot stream of air separates into two streams facing north and south. The stream moves until 30^◦in latitude southwards where it descends back to the lower atmosphere on the cool branch of the cycle, thus closing the convective cell, known as a ‘Hadley cell’ (Lindzen and Hou,1988). Curiously, the Hadley cells expand with time (∼ 2^◦since 1979, Hu and Fu, 2007), highlighting the knowledge gaps in the understanding of global wind dynamics even for our planet. The expansion, and weaken- ing, of the Hadley cells accelerates further due to climate change and will, in turn, move the world’s deserts and subtropical dry zones, located at the down-welling stream of the Hadley cells (Lu, Vecchi, and Reichler,2007; Seidel et al.,2008). Since the Hadley cell air motion happens under the influence of the Coriolis force, the easterly component of this motion in- troduces trade winds streaming westward along the ground. These trade winds are typically

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1.2. A review of atmospheric circulation patterns in the Solar System 3 disrupted by air turbulences created by a topographic barrier, such as the Andean mountain chain, as depicted in Figure1.1(Rees,1989). The region encompassed by the Hadley cells is usually called the tropical region. Moving farther away from the equator, circulation is not dominated by the thermally produced Hadley cells, but by Ferrell cells, which are created indirectly (Huang and McElroy,2014). The Ferrell cells, corresponding to a heat pump, cre- ate the westerly winds which dominate the zonal circulation of Earth’s atmosphere at lower altitudes, such as the Atlantic jet stream. These rather familiar processes take place in the convection dominated part of the atmosphere, the troposphere and stratosphere (see Figure 1.2).

0 100 200 300 400

Altitude (km)

Troposphere Stratosphere Mesosphere Thermosphere

Exosphere

Satellites

Aurora

Airglow

Weather balloons

10⁴ 10⁵ 10⁶ Electron Density (#/cm³) Ionosphere

Homopause Exobase

Figure1.2: Overview of the different atmospheric layers in height, with scales and values for Earth. However, the general structure applies to all planets. Almost everything collo- quially referred to as weather takes place in the troposphere, the ozone layer is roughly located in the stratosphere, and meteorites typically burn up in the mesophere. The homopause marks the point below which atmospheres are considered well-mixed, whereas material begins to segregate more in higher layers. Satellites are located in the thermosphere and above, in the exosphere, collisions between particles become rarer and the atmosphere stops to behave like a fluid. The ionosphere is more fluid, because it is dominated by electrons and ionised particles from interactions with stellar irradiation. It typically intersects with the thermosphere and mesosphere. This graphic was adapted from NASA/Goddard/Holly Zell:https://www.nasa.gov/mission_pages/

sunearth/science/atmosphere-layers2.html. For the purpose of this thesis, the

‘lower atmosphere’ reaches to the homopause (at the 10⁻³bar level), the ‘upper atmosphere’ starts around the nanobar level, whereas the ‘intermediate atmosphere’ bridges

these two realms via the thermosphere.

For the daily life of humanity studying our atmosphere in its current state is of the utmost importance, however, in the grander scheme, the question is whether Earth’s configuration is an outlier or the norm. Why did our atmosphere evolve to its current form from its early stages with a younger sun and without greenhouse gases (Zahnle et al.,2007)? And why is it so different to Venus, a planet with roughly the same starting point (Lammer et al.,2008)?

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To answer these questions, it is important to see Earth as a mere data point in the parameter space of possible atmospheres.

1.2.2 Inner Solar System planets

The two other inner solar system planets and our closest planetary neighbours are Mars and Venus. Due to their proximity, knowledge of the existence of the Venusian atmosphere dates back to 1761, when Lomonosov observed its refraction during the second contact of the transit (Cruikshank,1983). Since then, the atmosphere of Venus has been studied by multiple probes, starting with the Mariner 2 flyby in 1962 (e.g. Fjeldbo, Kliore, and Eshleman,1971;

Barsukov et al.,1986; Bazilevskii et al.,1986; Zasova et al., 2007; Svedhem et al., 2007;

Nakamura et al.,2016). The inner Solar System planets are particularly interesting due to their heightened irradiation and thus temperature.

The thick sulfuric acid clouds completely covering the planet and CO2gas make probing the lower atmosphere of Venus extremely challenging without in-situ probes. It is the high CO2

concentration that drives the strong greenhouse effect of the planet and its divergence from Earth’s atmosphere (Adams and Dunham,1932). The thick cloud layer is located between 48 and 70 km in altitude and also contains an as of yet unidentified ultraviolet absorber in the upper clouds (Imamura et al.,2020). From cloud tracking, we know that super-rotation plays a major role above 40 km in height, with less knowledge in the lower layers (Lebonnois et al., 2010). Super-rotation, where the planetary rotation and the atmospheric circulation are aligned with excess angular momentum around the equator, is known for Venus, Titan, Jupiter and Saturn (Imamura et al.,2020) and is one of the major wind patterns discussed in this thesis. From follow up work for Venus, we also know that energy is transported from the equator to the pole via meridional, circulation flow, not dissimilar to Earth, with the most dominant flow located in the mid-latitude layers of the permanent cloud cover (Lebonnois, Sugimoto, and Gilli,2016). This strong wind shear decreases the zonal wind to∼ 60 m s⁻¹ at the cloud base for the mid-latitude and equatorial region, but observations show uniform zonal winds with altitude in the polar region (Imamura et al.,2020). The zonal circulation at the cloud base (∼ 47 km) is most likely driven by heating from the deep atmosphere closer to the surface, while the other half of the circulation cells stems from the uninhibited cooling of the upper cloud layers (∼ 55−60 km) into space (Lebonnois et al., 2010; Lebonnois, Sugimoto, and Gilli,2016).

The mesosphere of Venus (see Figure1.2) is thought to have super-rotational zonal winds in the lower part, in retrograde direction, and a day-to-night side wind pattern from the subsolar to the anti-solar point in the upper part (Bougher, Rafkin, and Drossart,2006; Gérard et al.,2017). Gérard et al. (2017), with airglow measurements, the intrinsic emissions of a planetary atmosphere, and Takami et al. (2020), with mid-infrared CO2 absorption line observations, established the switch from super-rotational to day-to-night side zonal flow at an altitude lower than 90 km in the atmosphere. While the day-to-night side wind is driven by irradiation on the dayside (Goldstein et al.,1991), the driver of the deeper-atmospheric super-rotation is not as clearly established (Lebonnois et al.,2010). Both wind patterns are parallel to the surface at the terminator and are called ‘zonal winds’ in the following.

The idea of a mixture of super-rotation and day-to-night side winds is not new and has been explored by global circulation models, (Brecht et al.,2011; Brecht and Bougher,2012, and Schubert et al.,2007), while observational evidence has existed for far longer. An overview of the different pieces of evidence gathered in the era of the space exploration boom was created in Goldstein (1989) and can be found in Figure1.3.

These results were later confirmed by the VIRTIS instrument on-board Venus Express which observed nearly constant zonal winds in latitude around the equator of Venus. The average wind speed of this flow was measured at 100 m s⁻¹and no wind shear in the vertical direction

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1.2. A review of atmospheric circulation patterns in the Solar System 5

Figure1.3: Overview of observational evidence for different circulation patterns taken from Goldstein (1989). The additional reference provided in the Figure are Brinton et al.

(1980), Niemann et al. (1980), Keating, Nicholson, and Lake (1980), Stewart and Barth (1979), Betz (1977), Betz (1982), Clancy and Muhleman (1985a), Clancy and Muhleman

(1985b), Limaye (1984), Goldstein et al. (1987), and Goldstein et al. (1988).

could be observed above the zonal flows (Sánchez-Lavega et al.,2008). However, this does not seem to be a global feature, because vertical wind shears were observed via descent probes in the mid and high layers of Venusian clouds (Schubert et al.,1980) and reproduced by global circulation models (Lebonnois, Sugimoto, and Gilli, 2016). The local absence of vertical sheer, which could lead to interesting zones of stable, vertical vortices, could stem from instabilities observed in the mid-cloud layers. These instabilities produce strong convection within the layer (Ando et al.,2020), which would inevitably weaken the vertical shear. Those zones are of special interest in the context of permanently suspended cloud regions and the current controversy regarding the detection or, based on current evidence, rather the non-detection of phosphine and its possible microbial origin (e.g. Greaves et al., 2020b; Villanueva et al., 2020; Encrenaz et al.,2020; Greaves et al.,2020c; Snellen et al., 2020; Greaves et al., 2020a; Thompson, 2021; Trompet et al., 2021; Akins et al., 2021;

Lincowski et al.,2021). These zones merit further in-situ studies, since the deep layers of the atmosphere are not accessible via ground-based observations. Currently, the easiest method to study mid-latitude zonal flows in Venus is the tracking of cloud layers via UV images (Bullock et al.,2020). Bullock et al. (2020) were able to measure mid-altitude zonal winds to within 4% and detect top wind speeds at the equator of 100− −120 m s⁻¹with a drop-off in the lower clouds to 55− −65 m s⁻¹. Additionally, the equatorial wind shows a decrease with latitude and a time variation on the order of few Earth days (Bullock et al.,2020). An overview of the wind flows in and above the top cloud layer is shown in Figure1.4, idealised in the top panel and more realistically depicted in the lower panel taking into account rotation and shear (from Mengel et al.,1989).

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Above these layers, in the homopause, lighter particles start to dominate the atmosphere of Venus (Fox and Bougher, 1991). To explore these layers, two UV photometers were brought to Venus in 1967 by the US flyby Mariner 5 and the Soviet Venera 4 mission (Fox and Bougher,1991), which found strongHαemission during both missions, confirming the assessment of lighter particles dominating the upper layers. Mariner 5 studied the Jeans escape of particles in the exosphere (see Figure1.2) and restricted the atmospheric escape of Venus to 6·10⁵cm⁻²s⁻¹on the night side, a negligible fraction of the atmospheric mass per year (McElroy and Hunten,1969). The Venera probe also studied the night side and found no escaping particles but instead encountered a well-defined border with interplanetary space with low temperatures of 350 K (Kurt, Dostovalov, and Sheffer, 1968; Barth et al., 1967).

However, on the day side, the measured mass loss rate of hydrogen was larger than 10⁷ cm⁻²s⁻¹(McElroy, Prather, and Rodriguez,1982). This difference between the day and night side stems from the difference in radiation and subsequent temperature difference (Paxton, Anderson, and Stewart,1988a; Paxton, Anderson, and Stewart,1988b).

Figure1.4: Overview of the wind flows in the atmospheric layers at the top and above the cloud layer from Mengel et al. (1989). The upper panel shows the idealised impact of the day-to-night side wind with vertical shear on the atmosphere, while the lower panel shows a more realistic depiction taking into account the rotation of the system. He

stands for helium.

While the Venusian atmosphere has a rich dynamical life, from the point of view of space colonisation, Venus holds little interest, given that it is inhospitable even to probes, as most instruments send to study its surface melt in a matter of minutes (22 minutes for the Venera 7 probe for example;

Avduevskij et al.1971). That is why compa- rably, much fewer missions were dedicated to study Venus in comparison with our other closest neighbour: Mars.

For Mars, decades of observational data are available from the Thermal Emission Spec- trometer aboard NASA Mars Global Sur- veyor Spacecraft (e.g. Montabone et al., 2014) and the Mars Climate Sounder aboard the Mars Reconnaissance Orbiter (e.g. Mc- Cleese et al., 2007; Kleinböhl et al.,2009) which provide temperature, dust and water vapour densities as well as ozone measurements from SPICAM (Spectrometer for the Investigation of the Characteristics of the Atmosphere of Mars) aboard the Mars Express (e.g. Forget et al., 2009). Re- cently, nearly two decades worth of these observations were catalogued in the Open- Mars database (Holmes, Lewis, and Pa- tel, 2020) providing tools to predict Mars weather with unprecedented precision. Al- ready, long term studies of optical dust depths and temperature profiles help track atmospheric circulation for Mars, for example, for six Martian years worth of data in Giuranna et al. (2021).

Given that Mars has no liquid surface oceans and can be qualified as a desert planet (and has been one for around 4 to 4.3 Gyrs; Cassata 2017), the main driver of the circulation of the Martian atmosphere is suspended dust controlling the atmospheric temperature profile (Gierasch and Goody,1972; Kahn et al.,1992; Montabone et al.,2015). Since the subsequent temperature profile, both parallel to the surface and in the vertical, drives the circulation in

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1.2. A review of atmospheric circulation patterns in the Solar System 7 the thin atmosphere of Mars, thermal emission observations can be employed to track winds on a global scale (e.g. Martin and Kieffer,1979; Wilson,2000).

In general, when the atmosphere is clear of dust, meaning the optical depth in the optical is far below 1, the constant heating of the daytime surface of Mars creates a convection layer stretching up to one scale height in altitude (10 km) (Leovy,2001). Once the surface is cooling (Martian night time), the convection layer collapses and produces a temperature inversion close to the surface. Above this layer, at mid-latitude, zonal eastward winds increase with altitude and become jet streams at about 30 km in height. The only exception to this tempo- rally stable wind pattern is the Martian mid-summer, when westward winds dominate low- and mid- latitudes (Leovy,2001). Additionally, Mars has the equivalent to Earth’s Hadley cells, although with much larger wind speeds in the vertical branches and spanning further in latitude (up to 60^◦) (Haberle et al.,1993; Conrath et al.,1999). High up in the atmosphere, above approximately 40 km, time-dependent oscillations of the temperature profile were observed (Heavens et al.,2020), most likely linked to vertically expanding waves (Schofield et al.,1997).

The Hadley cell-like circulation flow creates trade winds in the northern and southern hemisphere, picking up particles up to∼ 100µm in diameter and creating dust storms. Strong dust storms are the most curious feature on Mars, since these winds are not restricted to ap- prox±30^◦in latitude as on Earth, but cover up to±50^◦of the surface of Mars (Greeley et al., 1992; Joshi et al., 1994; Hinson et al., 1999). These dust storms are local phenomena but can build to impact the entire atmosphere. They can reach through all atmospheric layers due to the strong circulation of Mars’ atmosphere and low gravity and tend to last longer than similar phenomena on Earth (tens of Martian days) (Kahn et al.,1992; Cantor et al.,2001;

Montabone et al.,2015).

Figure1.5: Two pictures of Mars, taken in May and July of the same year with the Mars Color Imager (MARCI) camera onboard NASA’s Mars Reconnaissance Orbiter (MRO).

The left picture from May 2018 shows the Valles Marineris chasms to the left, a dust storm at the top and the early south polar cap at the bottom, and at the centre the Meridiani Planum, the landing cite of the Opportunity rover (Squyres et al.,2004). On the right, the same view is shown, but none of the features are visible due to a thick dust and haze cover over the entire planet. Image credit: NASA/JPL/Malin Space Science Systems One such extraordinary dust storm, which engulfed the planet for 150 Martian days was observed in 2018 by the Mars Reconnaissance Orbiter and subsequently analysed in Montabone et al. (2020), who argue that intertwined dust storms and strong circulation led to the remark- able dust coverage of Mars (see Figure1.5). In summary, our two closest neighbours have

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atmospheres roughly dominated by day-to-night side wind flow in the lower atmosphere stemming from the irradiation of the sun with vertical waves propagating into the upper layers.

1.2.3 Giant planets

Just like for Venus, humanity observed Jupiter and Saturn centuries ago and even knew about their atmospheres (Kaspi et al.,2020). More recently, due to the more challenging observing conditions, Uranus and Neptune joined the giant planets and also had their atmospheres confirmed. The banded structure of Jupiter, with its ‘zones’ (light regions) and ‘bands’ (dark regions), has been tracked since the dawn of telescopes in the 17th century (Kaspi et al., 2020). Similarly historical observations are available for the Giant Red Spot, a sustained anticyclonic vortex fed by strong atmospheric winds (Ingersoll,1990; Marcus,1993; Marcus and Lee,1994; Sanchez-Lavega et al.,2001). Although Jupiter and Saturn are conventionally referred to as the gas giants, while Uranus and Neptunes are called the ice giants (more con- troversially also known as ’failed gas giants’, Frelikh and Murray-Clay2017), they mainly differ in composition and not in atmospheric dynamics (Guillot, 2005; Liu and Schneider, 2010). While a proper model of an atmosphere requires additional knowledge of the composition and temperature profile (Fortney and Nettelmann,2010), in this work we will treat all four planets as giant planets without the distinction in two subclasses.

The atmospheric dynamics of all giant planets are mainly known for the cloud deck and above, where the atmospheres are dominated by molecular H2and helium with a high metal- licity composition (Saumon and Guillot,2004; Soubiran and Militzer,2016). For this reason the atmospheric composition is not a pressing concern for this introduction (see Guillot,2005, especially Figures 6 and 9) as this thesis focusses on atmospheric layers above possible cloud decks for giant exoplanets.

Compared to the inner planets, the giants planets have received much fewer visits from spacecrafts. The Voyager spacecrafts passed by them on their way out of the solar system (Smith et al.,1979; Smith et al.,1981; Smith et al.,1986; Smith et al.,1989) and provided important information on their dynamical structure (Campbell and Synnott,1985; Campbell and An- derson,1989) and decades later in 1995 the Galileo probe dropped into Jupiter’s atmosphere during its mission finale (Atkinson, Pollack, and Seiff,1996).

A real observational revolution of our understanding of the giant planets below their cloud deck came recently with the Juno mission to Jupiter and the Grand Finale of the Cassini mission to Saturn. The Juno mission contains the Juno gravity experiment, which measures the gravity harmonics of Jupiter (Hubbard,1999; Kaspi et al., 2010). Mapping the gravity spectra of Jupiter at high accuracy is one of the main missions of Juno to update the last measurements dating back to the Galileo probe. Fortuitously, the Cassini mission operated during the same time frame, and was put on a polar orbital configuration, just like Juno, for its Grand Finale (its final orbits before being crashed into Saturn) and obtained gravitational measurements of similar quality for Saturn (Edgington and Spilker,2016).

The gravity harmonics are translated back to the wind field that created them, giving us detailed information of the zonal flows below the cloud cover (however, caveats regarding degeneracies have to be accounted for; Kaspi et al.2020). Before these missions, the gravity harmonics of Jupiter and Saturn dated back mainly to Voyager data and were updated by as much as two orders of magnitude with the described recent mission (Iess et al.,2018; Iess et al.,2019, see also supplemental Figure 1 in Kaspi et al.2020). Even without the tracking of gravity harmonics, the jet structure of giant planets’ atmospheres is revealed by tracking the top cloud layers (García-Melendo et al., 2011; Tollefson et al., 2017). These studies found six jets in each of Jupiter’s hemispheres, with the main jet located at the equator and super-rotating eastward, while the jets at higher latitudes appear narrower. The jets are not

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Figure1.6: Figure 1 from Kaspi et al. (2020) showing the zonal wind profiles of Jupiter and Saturn. The wind patterns for Jupiter are from Tollefson et al. (2017), scaled on a Hubble Wide Field camera image, and for Saturn from García-Melendo et al. (2011) overlaid on the combined image of Cassini and Voyager data (by Björn Jónsson). The grid is spread by 20^◦in latitude and 45^◦in longitude. The zonal flows are scaled by one for Jupiter on the longitudinal grid and for Saturn by three. The lower panels are divided into the north-south symmetric contributions in black and antisymmetric ones in orange.

Figure1.7: Figure 1 from Liu and Schneider (2010) showing zonal wind profiles with the respective simulation (blue line). Jupiter: Cassini observations (Porco et al.,2003, orange) and model at 0.75 bar. Saturn: Voyager (orange line), Hubble Space Telescope (HST) (Sánchez-Lavega et al.,2003, green crosses), and Cassini observations (Sánchez- Lavega, Hueso, and Pérez-Hoyos,2007, magenta circles:∼0.06 bar, turquoise squares:

∼0.7 bar) and model at 0.1 bar. Uranus: Voyager (circles), HST (Hammel et al.,2001, crosses), and Keck telescope (Hammel et al.,2005, squares) observations and model at 25.0 mbar. Neptune: Voyager (circles) and HST (Sromovsky et al.,2001, crosses) and

model at 25.0 mbar.

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symmetric in both hemisphere, e.g. the fastest of the observed jets (140 m s⁻¹), located in the northern hemisphere, has no equivalent in the south (Tollefson et al.,2017). Saturn shows overall stronger wind speeds than Jupiter, creating a wider equatorial jet (reaching up to 30^◦ in latitude) with wind speeds reaching 400 m s⁻¹. Due to the larger equatorial jet, only three to four jets can be observed polewards for each hemisphere (García-Melendo et al.,2011).

How zonal flows translate to the banded structure of the clouds is not entirely understood yet (Fletcher et al.,2019), but empirically eastward jets seem to be paired with a ‘zone’ in the south and a ‘belt’ in the north (and vice versa for westward jets).

From Cassini’s Grand Finale, we are even able to deduce local wind patterns for deep atmospheric layers, which indicate that wind speeds increase for winds close to the equator at about 2-3 bar (with the cloud level at 0.5 bar), while more poleward wind patterns remain constant or even weaken with depth (Choi, Showman, and Brown, 2009; Studwell et al., 2018). Within the cloud deck zonal winds are now tracked with great detail, as shown in Figure1.6depicting the zonal wind profiles for both Saturn and Jupiter with images of both planets as latitude indicators (from Kaspi et al., 2020). The same technique can in theory also observe zonal winds for Uranus and Neptune, these planets are the only ones without a dedicated space mission (Fletcher et al.,2019). The only available gravitational spectral data stem from the Voyager flybys (Smith et al.,1986; Smith et al., 1989), making zonal wind profiles significantly less precise. Nonetheless, upper bounds for the winds and depth of the circulation were set from Voyager’s data (Kaspi et al.,2013), showing a strong prograde flow for the cloud top with wind speeds of up to 200 m s⁻¹for Uranus and∼ 400 m s⁻¹for Neptune at the equator with retrograde jets at mid-latitude (Kaspi et al.,2020).

Reproducing observations of zonal winds in giant planets has been a hot topic in the modelling community since the early days of Voyager data and attempts to reproduce the jet structure at the cloud deck have mainly separated in two approaches: the ‘shallow’ model, which assumes that the zonal jets are surface features, and the ‘deep’ model, which assumes the zonal jets are the result of deep interior convection. In the shallow scenario, the jets form quite similar to Earth zonal winds and some promising results in modelling Uranus and Neptune but also Jupiter and Saturn were obtained using geostrophic turbulence theory, re- lating the horizontal pressure forces to the horizontal Coriolis force (Rhines,1975; Held and Larichev,1996; Chemke and Kaspi,2015). Shallow models can successfully reproduce jet widths and also the total number of jets (Panetta,1993; Cho and Polvani,1996; Smith,2004;

Showman,2007; Kaspi and Flierl,2007) and even super-rotation to some degree (Scott and Polvani,2008; Lian and Showman,2008; Young, Read, and Wang,2019; Spiga et al.,2020).

However, the shallow model cannot distinguish between super-rotating and sub-rotating atmospheres (e.g. Scott and Polvani,2008). On the other hand, in the deep scenario, the visible zonal jets are just a phenomenon of deep internal convection columns. These models nat- urally produce super-rotation, but do not automatically produce multi-jet structures (Busse, 1970; Sun and Lindzen, 1993; Christensen et al., 2001; Wicht, Jones, and Zhang, 2002;

Heimpel, Aurnou, and Wicht,2005; Kaspi, Flierl, and Showman, 2009; Heimpel, Gastine, and Wicht,2016) and have to involve large internal heat fluxes, an order of magnitude above what is observed (Heimpel and Aurnou,2007). The lack of observational evidence has inhib- ited a convergence between the two approaches (Vasavada and Showman,2005; Showman, Tan, and Zhang,2018), but with the recent observations of Cassini and Juno (Iess et al.,2018;

Iess et al.,2019) and their analysis regarding zonal winds (Kaspi et al.,2020, see Figure1.6) a combination of both approaches has yielded promising results (Imamura et al.,2020). The 2D meridional-vertical convergence of the deep model and the meridional convergence of the shallow model are most likely driven by eddy momentum flux convergence at the equator, even if this might not be the only mechanism driving super-rotation for giant planets (Galanti, Cao, and Kaspi,2017; Connerney et al.,2018; Duer, Galanti, and Kaspi,2019; Moore et al., 2019; Imamura et al.,2020).

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Figure 1.8: Figure 3 from Liu and Schneider (2010) showing zonal winds (left) and relative vorticity (right) in the steady state of the simulations for all giant planets. The flow field is shown at the same pressure levels indicated in Figure1.7.

The mentioned Rossby waves which generate the equatorial super-rotation are visible for the Jupiter and Saturn simulation as large wave packets. For Jupiter and Uranus, coherent vortice patterns are

visible.

So far, one of the models that best reproduce available data is published in Liu and Schneider (2010). It operates on the hypoth- esis from Schneider and Liu (2009), that giant planets have prograde equatorial zonal jets when the transport of angular momentum to the equator via convectively created Rossby waves is strong enough. Because the generation of Rossby waves is driven by the intrinsic heat flux coming from the planet interior, prograde jets are effectively dependent on the heat flux. Concurrently, a disruption of this process by differential radiative heating in the higher atmospheric layers and the subsequent instabilities lead to multiple poleward jets. Therefore, ac- cording to the model presented in Schnei- der and Liu (2009) and Liu and Schneider (2010), the jet-like structure is dominated by the ratio between intrinsic heat flux from the interior and differential radiative heating of the upper atmosphere from space.

The main result of Liu and Schneider (2010), the zonal velocity profiles in latitude for all four giant planets, can be found in Figure1.7, with the state of the art observational constraints on the same profile from Kaspi et al. (2020) for Jupiter and Saturn in Figure1.6. In Figure 1.8, the same simulation result is shown as a surface map, reproducing the jet structure and vortices for all four giant planets. They find an equatorial jet for Jupiter at ∼ 150 m s⁻¹ with a similar width than the observations (see Figure 1.6 for comparison), while Saturn’s simulated jet at∼ 230 m s⁻¹ is weaker than the corresponding observation. For Uranus and Neptune, the overall simulated structure is quite similar to observations, but the wind speeds for Neptune are significantly lower than what the Voyager constraints suggest (Liu and Schneider,2010). Remarkably, the model of Liu and Schneider (2010) is even able to simulate the vorticity of Jupiter, which might have given rise to the Giant Red Spot (Ingersoll et al.,1981; Read et al.,2006) which is observed directly in images taken with Juno (Adriani et al.,2018). For Saturn, the simulation shows a much more stable vortex structure with high wavenumber undulations which could ultimately explain the "polar hexagon", a stable vortex structure in Saturn’s polar region (Godfrey,1988;

Allison, Godfrey, and Beebe,1990; Fletcher et al.,2008).

Our understanding of the gas giants almost exclusively relies on tracking of the cloud layers in different wavelengths. And just as our observational knowledge of the deep convective layers is incomplete at best, the current understanding of the atmospheric layers above the zonal jets is equally patchy (Fletcher et al.,2020a). Above the visible cloud level, the simulation of

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Liu and Schneider (2010) suggests vertical shear for the atmospheres of Jupiter and Saturn, comparable with observations in Atkinson, Pollack, and Seiff(1998) and Sánchez-Lavega, Hueso, and Pérez-Hoyos (2007). Observationally, tracking winds above the cloud layer is even more complicated than for the deep layers, since shear winds above the clouds can only be inferred indirectly from temperature measurements (Miller et al.,2006; Fletcher et al., 2007), with large uncertainties. Indirect measurements of winds through temperature profiles imply that high-entropy, aerosol depleted air parcels descend vertically from higher atmospheric layers to the cyclonic belts of Jupiter (Conrath and Pirraglia,1983). For Uranus and Neptune, the jets are strongest below the stratosphere (see Figure1.2), compatible with the limited data available from Voyager (Hubbard et al.,1991). Models predict a thermally- driven Hadley cell-like structure for the stratosphere (Conrath, Gierasch, and Leroy,1990), with mid-latitude vertical winds rising in the atmosphere and equatorial down-welling for Uranus. This process, if observable, is generated by wave-driven circulations. Observational evidence for wave propagation stems from the high temperatures which were observed in the upper atmospheres of the ice giants, which cannot be produced from the stellar irradiation received this far out in the Solar System. Instead, it could be achieved by wave propagation and breaking as a form of energy transport to the thermosphere (Herbert et al.,1987; Stevens, Strobel, and Herbert, 1993; Melin et al., 2020; Fletcher et al., 2020b). Another piece of observational evidence for mid-latitude vertical wind structure in the gas giants is a curious local maximum of hydrocarbons on Saturn located at 25 ^◦N, which is interpreted as the downwards arm of a cell-like circulation reaching beyond the stratosphere (Guerlet et al., 2009; Fletcher et al.,2020b). Summarising, the wind structure in the upper atmosphere of the gas giants can only be described tentatively and dedicated missions to map temperatures and abundances of atmospheric tracers are needed in the future to shed a clearer light on these more elusive layers (Fletcher et al.,2020a). As we will see in this work, things could be much different for strongly irradiated gas giants in other planetary systems. A first hint is shown in the tentative comparison between the here discussed solar system planets showing atmospheric circulation patterns and two strongly irradiated gas giants in different systems in Table1.1, where the equatorial wind speed is orders of magnitude larger for the highly irradiated planets at comparable sizes.

Table1.1: Basic comparison on super-rotation of solar system planets and two highly irradiated exoplanets (adapted from Read and Lebonnois,2018; Imamura et al.,2020).

Planet Radius (km) Rot. period (days) Equatorial rotation (m s⁻¹) Eq. wind (m s⁻¹)

Venus 6 052 243 1.81 100-120

Jupiter 69 911 0.41 12 300 60-140

Saturn 58 232 0.44 9 540 350-430

HD189733b 79 500 2.2 2 600 2 400

HD209458b 94 380 3.5 1 960 1 940

1.3 Exoplanet atmospheres

While many missions have explored most of the solar system planets in-situ, distance be- comes soon of the essence. Decades after their launches, the Voyager probes have barely left the solar system, highlighting why probes are not a feasible strategy to characterise planets outside the solar system, so called exoplanets. However, thanks to technical advances for telescopes and instruments, remote observation methods from Earth are plenty.

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1.3. Exoplanet atmospheres 13 1.3.1 Planet and atmosphere detection techniques

To detect planets themselves and subsequently their atmospheres and dynamical structure each of the following techniques provide their own set of information. Current observational techniques to study exoplanets are radial velocity (RV) measurements, astrometric measurements, measurement of orbit timing residuals, microlensing, photometry and spectroscopy during transits, and direct imaging. For the sake of brevity, only transit spectroscopy is discussed in depth as the main technique used for this thesis, while others are summarised here.

Direct imaging: This technique is designed to detect exoplanets via their intrinsic thermal emission. That logically requires the removal of the light of the star, making the technique most effective for systems that show us their orbital plane face on, especially massive, young planets with high thermal emissions (however, see also Bonnefoy et al.,2011 for a counter example). The first detections of exoplanets date back to 2005 with Chauvin et al.

(2005a), Chauvin et al. (2005b), Itoh et al. (2005), Neuhäuser et al. (2005), Luhman et al.

(2006), Marois et al. (2008), Lagrange et al. (2009), and Lagrange et al. (2010). To date, the NASA exoplanet archive lists 323 exoplanets detected via direct imaging¹. A state-of-the-art review on direct imaging can be found in Rickman (2020).

Microlensing: Gravitational microlensing occurs when a background star and a foreground object (another star or stellar remnant for example) are both located directly along the same line of sight from the observer. Due to the mass of the foreground lens object, the light of the background star is bent around the lens object and creates two lensed images. If the foreground object has a companion that sits at the right distance it will disturb one of the two lensed images. The microlensing method is particularly suited to detect exoplanets at large distances, and it can even detect planets far from their hosts (Beaulieu et al.,2006) and rogue planets without a host star that would not be otherwise identified (Wright and Gaudi, 2013). Since the first detection of a rogue planet (Bennett et al., 2006), the technique has matured enough to detect rogue planets down to Earth-mass (Mróz et al.,2018) and provides important information on planet formation. However, in terms of physical parameters of the detected planets, microlensing can only measure the planet’s mass within loose constraints.

Orbit timing residuals: This technique makes use of the reflex motion of the star due to the planet in its orbit by detecting changes in the periodic signature of the star, requiring some form of pulsating signal from the host star (Wolszczan and Frail,1992). It is therefore mainly used for pulsars and the more common planet host: binary star systems (Bednarek and Sitarek,2013). The technique can constrain the orbit and mass of the found objects.

Astrometric measurements:In general, astrometry refers to the displacement of objects with respect to other reference objects in space. This can mean solar system bodies within the system, stars within the galaxy or even galaxies themselves. In the context of detecting exoplanets, astrometry aims to measure the displacement of the host star due to its gravitational interaction with the planet with respect to the ‘plane of the sky’ (Wright and Gaudi, 2013). So far, astrometric measurements have been mainly used to confirm already detected exoplanets and determine their orbits and masses (Bean et al.,2007; Bean and Seifahrt,2009;

McArthur et al.,2010).

RV measurements:RV measurements look at the Doppler-shift of the light coming from the host star due to the movement of the star with respect to the observer. The movement of

1https://exoplanetarchive.ipac.caltech.edu/cgi-bin/TblView/nph-tblView?app=

ExoTbls&config=directimaging&constraint=immodeldef=1, retrieved 15.12.2020

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the star is due to the gravitational pull of its planet(s) and, therefore, allows to measure the minimum mass of the planet. The change of the Doppler-shift with time is therefore directly proportional to the mass of the planet(s). This makes RV measurements one of the most important techniques to characterise exoplanets. It was used to detect the first exoplanet around a sun-like star (Mayor and Queloz,1995) and the majority of exoplanets found in the first decade of exoplanet science (Butler et al.,2006; Udry and Santos,2007; Wright et al.,2011).

Transmission spectroscopy:

Figure1.9: Figure 2 from Winn (2010) showing the schematic of a transit. The upper part shows the disk of the host star with the coordinate system set at the centre. The orbiting planet is shown in black at the four contact points with the disk, with the impact parameterb. The lower part shows the light curve of the transit, meaning the flux as a function of time during the transit. The transit depthδ, transit durationT, and ingress

durationτare also indicated.

For this thesis, the crucial technique for exoplanet detection and atmospheric characterisation are transit observations. As the name implies, it requires a system to face the observer edge- on, so that the planets occult part of the star during parts of their orbits. Observing the flux from the star before and while the planet is transiting with a photometer allows us to track it across the stellar disk (see Figure1.9). The transit depth is proportionate to the ratio of the stellar disk surface to the planet disk surface, orR²_planet/R²_star, allowing to infer the planet radius (Charbonneau et al.,2002). By combining transit observations with RV measurements the exoplanet density can be inferred and subsequently used to deduce its bulk composition.

Transits can also be observed with a spectrometer, where we are not primarily interested in the flux change of the host star, but in the light’s interaction with the planet atmosphere as it passes through. At each point in time, the light crossing the atmosphere is split in wavelength, allowing us to analyse the spectral lines of the elements in the planet’s atmosphere (see Figure 1.10for a schematic, as well as Seager and Sasselov2000). Since this is the main technique used in Chapter2, I will elaborate in detail how to build such a transmission spectrum of an exoplanet atmosphere in the following.

The transmission spectrum is built by observing the flux of the star while the planet transits (‘in-transit’) F_in(λ), but also when the star is not eclipsed by the planet (‘out-of-transit’) F_out(λ).

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1.3. Exoplanet atmospheres 15

Figure1.10: Schematic of a transmission spectrum in the visible. The spectra taken during the transit are corrected for the stellar lines and combined to show the absorption height (the planetary radius) as a function of wavelengths. Elements that absorb the passing light at higher altitude, therefore, make the planet appear bigger during its transit at their

specific absorption wavelength.

Basically, a transmission spectrum R is a ratio between the out-of-transit spectra and the in-transit spectra to identify which parts of the spectra do not come directly from the host star, but were changed by the planet atmosphere (Brown, 2001). The in- and out-of-transit spectra are each respec- tively summed together to form a master-in (sum of the in-transit)M_in(λ) = ^P_iF_in(λ)i

and master-out (sum of the out-of-transit) M_out(λ) =^P_iF_out(λ)i(Charbonneau et al., 2002; Redfield et al., 2008). To find out which lines stem solely from the planet one divides the master-in by the master-out and gets a spectrum ratio, which is the transmission spectrum:

R_basic= ^Mⁱⁿ(λ)

M_out(λ) ^(1.1) The adaptation of transmission spectroscopy

to the application to exoplanets was introduced in Seager and Sasselov (2000), Brown (2001), Hubbard et al. (2001), Charbonneau et al. (2002), and Redfield et al. (2008), where more de- tails on the theoretical musings can be found. In these works, low and mid-resolution data (Rsim10²−10⁴) was analysed, meaning that absorption features can be detected, but the line shapes are not resolved. In this thesis, the focus lies on the characterisation of resolved line to study their line shape. The high resolution (R∼ 100 000) requires a careful account of the movements of both the source of the signal and the detection instrument, since both introduce shifts in wavelength. In the following, we will focus on the practical considerations when observing exoplanet atmospheres in transit with a high-resolution instrument.

During the observations, from one exposure to the next, the planet-star system moves in relation to the observer, as well as the planet with respect to the host star. These movements introduce Doppler-shifts as a function of the velocity difference to the observed light. To build the master spectra these shifts have to be taken into account and all exposures shifted into the planetary rest frame (PRF) which properly aligns the spectral lines stemming from the exoplanet atmosphere.

To arrive in the PRF from the observer rest frame in which the exposures are taken, the complex movement between observer and observed planet has to be taken into account. Firstly, to separate the stellar spectrum from the planetary contribution, all spectra have to be aligned in the stellar rest frame (SRF). For the shift to the SRF we need to take into account the motion of the system, host star, and Earth itself. The different steps are illustrated in Fig. 1.11. The observer moves from one exposure to the next on its trajectory around the barycentre of the solar system (~vBERV, see shiftain Fig. 1.11). Additionally, the motion of the barycentre of the observed system with respect to the barycentre of the Solar System has to be taken into account (b in Fig. 1.11, called the systemic velocity~vsys), and lastly, the trajectory of the host star around the barycentre of the observed system (cin Fig. 1.11), parametrised by the relative velocity of the starRV~ star.

The wavelength shift for each exposureican be described by:

λ_shifted(i) =λ(i)_·(1−|~vBERV(i)_|

c )_·(1+^|^~^v^sys^|

c )_·(1+^|^RV^~ ^star(i)_|

c ) (1.2)

Exoplanet winds: Modelling atmospheric dynamics via resolved spectral lines

Thesis

Reference