Martian Upper Atmospheric Thermal Structure, Composition, and Water and Their Significance for Atmospheric Escape and Evolution

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Martian Upper Atmospheric Thermal Structure, Composition, and Water and their Significance for Atmospheric Escape and Evolution

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Authors Stone, Shane Wesley

Citation Stone, Shane Wesley. (2021). Martian Upper Atmospheric Thermal Structure, Composition, and Water and their Significance for Atmospheric Escape and Evolution (Doctoral dissertation, University of Arizona, Tucson, USA).

Publisher The University of Arizona.

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Link to Item http://hdl.handle.net/10150/660769 MARTIAN UPPER ATMOSPHERIC THERMAL STRUCTURE, COMPOSITION, AND WATER AND THEIR SIGNIFICANCE FOR ATMOSPHERIC ESCAPE AND EVOLUTION

Shane Wesley Stone

A Dissertation Submitted to the Faculty of the

DEPARTMENT OF PLANETARY SCIENCES

in Partial Fulﬁllment of the Requirements for the Degree of

DOCTOR OF PHILOSOPHY

in the Graduate College

THE UNIVERSITY OF ARIZONA

2021 2

4 5

ACKNOWLEDGEMENTS

I must principally acknowledge my advisor, Professor Roger Yelle: thank you for catalyzing my transformation from a polymer chemist into a planetary one. Thank you for pushing me to perform well beyond what I believed were my limits. Thank you for your guidance through the research projects that made it into this dissertation, those that did not, and through those corridors of academic science other than research. Thank you for, in one of our first few conversations, convincing me that chemists have an important role to play in planetary science when I had been disabused of such a notion. I have markedly improved as a scientist as a direct result of your advising. I will forever be grateful. I began to contemplate the transition from polymer chemistry to planetary science as a third-year graduate student in organic chemistry at the University of California, Los Angeles (UCLA). Bench chemists have an abundance of time to contemplate wild ideas while their reaction stirs in a flask or while cleaning said flask for the hundredth time. I was, and certainly still am, fascinated by planetary atmospheres (and still polymers too). I had been fascinated by atmospheres for most of my life, but had not realized in a practical sense that I could devote my academic career to the topic or, perhaps, I lacked the confidence in my abilities to pursue such a dream. In either case, I began to search for a Professor in the Department of Earth, Planetary, and Space Sciences at UCLA who would either be willing to accept into their research group a chemist with no background at all in the study of planetary science or, much more likely, at least provide useful advice while escorting me back out of their office. So, I walked from Young Hall (which houses a portion of the Department of Chemistry and Biochemistry), through a short hallway that bridges the two buildings, to Geology, where one would find those who study rocks, of course, but perhaps too those who study the tiny envelopes of gas that cling to big rocks in space. One Professor across that bridge had little to say on my transition from chemistry to planetary science, he knew of no openings for such a student. One told me that there was little left to accomplish in the study of planetary atmospheres for a person with my set of skills. I was crushed. But one suggested I get in touch with a Professor Yelle at the Lunar and Planetary Laboratory (LPL). So to UCLA Professor Jonathan Mitchell, who set me out in the right direction down this path, I must say thank you. Your excitement for planetary atmospheres and your kindness for this student who wandered into your office were motivational and heartening. I will always remember that conversation. I will always remember also the next conversation we had. By then I was a first-year graduate student at LPL attending my first scientific conference. I proclaimed then, and do so again here, “I made it!” I wish to thank all of the Professors who taught the many courses I took in my first years at LPL. Each of you has also played a critical role in my transition to 6 planetary science and my development as a scientist: Professors Isamu Matsuyama, Joe Giacalone, Adam Showman, Tom Zega, Caitlin Griffith, Lucy Ziurys, Shane Byrne, and Dante Lauretta. Shane, I suppose you can have your identity back now. Perhaps you enjoyed receiving my emails as much as I enjoyed receiving yours. Thank you also to Professor Travis Barman for agreeing to be my academic advisor and for the insightful conversations and advice throughout the years. We should have had more of those conversations. Thank you, Professor Tommi Koskinen, for your always intelligent and insightful advice regarding various research projects. Thank you to those Professors that served on the committees for my oral examination and final dissertation defense: Tim Swindle, Isamu Matsuyama, Caitlin Griffith, and Tom Zega. Our meetings were always encouraging and I am honored to have your signatures on this dissertation. Thank you to all of the LPL staff, especially Mary Guerrieri, Bert Orosco, Amy Brenton, Vicki Robles de Serino, Maria Schuchardt, Eneida Guerra de Lima, John Pursch, and Pam Streett. I knew on the first day of my visit as a prospective student that the administrative staff at LPL were spectacular. All of you shepherd us graduate students through our degrees in different ways and we could not do it without you. Mary and Amy, you both ensure we never miss a deadline or forget to jump through some bureaucratic hoop. Bert, I will always hear your laugh and see your smile when I think of you. Thank you for all of your help. Maria, thank you for your support during countless outreach events. Vicki, thank you for helping me with all of the paperwork. Eneida and John, thank you for the tech support. Thank you to all of the graduate students and postdocs at LPL, most of all for your comradery. Joshua Lothringer, Daniel Lo, Hamish Hay, and many others, thank you for the hours and hours we spent together poring over coursework. Molly Simon and Sarah Peacock, our friendship has been especially valuable, so thank you for the endless laughs and helpful advice. This experience would not have been as fun without you. Thank you, Molly, for our fast friendship, your support in my first years at LPL, and for being a wonderful officemate. Sarah, thank you for lunches and long conversations, often about the Senate. Ali Bramson, thank you for housing me during my prospective visit, for being our Graduate Representative to the Faculty, and for your guidance as I stepped into that position behind you. Thank you to Sarah Morrison for encouraging me to participate in outreach at LPL, coordinating those outreach events, and ensuring I had an easy transition into the role of Graduate Outreach Coordinator. These outreach experiences dramatically improved my abilities as a public speaker and science communicator. Thank you, Justin Erwin, for your friendship which has been particularly enjoyable and for your academic support which has been particularly useful. You were always willing to stop what you were doing to explain in detail some concept which eluded me. Thank you, Jon Bapst, for all of the long conversations about planetary science and hockey out by the Mars garden or after Space Drafts. Thank you to the Neutral Gas and Ion Mass Spectrometer (NGIMS) team at 7

NASA Goddard Space Flight Center, past and present, especially Mehdi Benna and Paul Mahaﬀy. The entire NGIMS team inﬂuenced the trajectory of my career with the launch of NGIMS onboard the NASA Mars Atmosphere and Volatile Evolution mission. Mehdi and Paul, your expertise in the acquisition and interpretation of mass spectrometer data was critical to the success of this dissertation. Thank you to the entire MAVEN team, including everyone who has participated in construction, launch, operations, and science. Without you this dissertation would not have been possible. Finally, I must thank the Professors, teachers, and other mentors who con- tributed to my education before I arrived at LPL. From the University of Texas at Dallas (UTD), where my research career began: Professor John Ferraris, thank you for accepting me into your research group. I remember waiting outside your group meeting to ask to join your lab and managing to brag about my rank in Pro- fessor Biewer’s organic chemistry class. Thank you to Drs. Doyun Lee and Grace Kalaw and the entire Ferraris lab: your mentorship was invaluable. Thank you also to Professors Mihaela Stefan, Kenneth Balkus, Gregg Dieckmann, John Sib- ert, Michael Biewer, Paul Pantano, Jie Zheng, Warren Goux, Steven Nielsen, and Mieczys law Dabkowski. Thank you all for your dedication to my learning. From the faculty of UCLA, I would like to thank Professors Timothy Deming, Yves Rubin, Heather Maynard, Paula Diaconescu, Neil Garg, and Kendall Houk. I learned an incredible amount of chemistry from you all in just a short period of time. Thank you to Dr. Steven Hardinger for your mentorship in teaching UCLA undergraduates over many quarters. Your dedication to teaching is inspiring. I must also acknowledge the work of so many wonderful teaching assistants at UTD and UCLA. To my chemistry teachers at the School of Science and Engineering Magnet, Dr. Wilson and Dr. Charles Tuttle, thank you for sparking my interest in science. 8 9

DEDICATION

To Gabe Never stop being you, you’re pretty cool. 10 11

TABLE OF CONTENTS

LIST OF FIGURES ...... 15

LIST OF TABLES ...... 19

ABSTRACT ...... 21

CHAPTER 1 Introduction ...... 23 1.1 The Volatile History of Mars ...... 23 1.1.1 Warm and Wet or Cold and Icy ...... 25 1.2 Atmospheric Escape to Space ...... 29 1.2.1 Jeans Escape ...... 30 1.2.2 Photochemical Escape ...... 31 1.2.3 Sputtering Escape ...... 33 1.2.4 Ion Escape ...... 34 1.3 The NASA Mars Atmosphere and Volatile Evolution Mission . . . . . 35 1.4 The MAVEN Neutral Gas and Ion Mass Spectrometer ...... 42 1.5 Outline ...... 47

CHAPTER 2 Thermal Structure of the Martian Upper Atmosphere 49 2.1 Introduction ...... 49 2.2 Methods ...... 53 2.2.1 Treatment of Data ...... 53 2.2.2 Random Uncertainty ...... 61 2.2.3 Temperature Derivation ...... 62 2.2.4 Horizontal Correction ...... 67 2.3 Results and Discussion ...... 72 2.3.1 Deep Dip Temperatures ...... 73 2.3.2 Exospheric Temperature Variations ...... 78 2.3.3 Comparisons with Previous NGIMS Temperatures ...... 80 2.3.4 Comparisons with Other Observations ...... 82 2.3.4.1 Entry Probes ...... 84 2.3.4.2 Orbiter Accelerometer Measurements ...... 85 2.3.4.3 Stellar Occultations ...... 89 2.3.4.4 Dayglow Measurements ...... 91 2.3.4.5 MENCA Measurements ...... 92 2.3.5 Model Comparisons ...... 93 2.4 Conclusions ...... 101 12

TABLE OF CONTENTS — Continued

CHAPTER 3 Composition of the Martian Upper Atmosphere ... 105 3.1 Introduction ...... 105 3.2 Methods ...... 109 3.2.1 Treatment of Data ...... 109 3.3 Results and Discussion ...... 114 3.3.1 Compositional Trends with Latitude ...... 120 3.3.2 Compositional Trends with Local Time ...... 125 3.3.3 Seasonal Variations ...... 131 3.3.4 Comparisons with Previous Work ...... 136 3.3.4.1 Viking Entry Probes ...... 136 3.3.4.2 Imaging Ultraviolet Spectrograph (IUVS) ...... 137 3.3.4.3 Mars Global Ionosphere-Thermosphere Model (M- GITM) ...... 140 3.4 Conclusion ...... 141

CHAPTER 4 Hydrogen Escape from Mars is Driven by Seasonal and Dust Storm Transport of Water ...... 143 4.1 Introduction ...... 143 4.2 Methods ...... 147 4.2.1 MAVEN NGIMS Ion and Neutral Abundances ...... 147 4.2.2 Calculation of Water Abundances ...... 148 4.2.3 Uncertainties in NGIMS Densities and Derived Quantities . . 150 4.2.4 Validity of the Photochemical Equilibrium Assumption . . . . 152 4.2.5 On the Assumption Tn = Ti = Te ...... 155 4.2.6 Photochemical Model ...... 155 4.3 Results and Discussion ...... 156 4.3.1 Water in the Upper Atmosphere ...... 160 4.3.2 Previous and Coincident Measurements of Water ...... 162 4.3.3 Molecular Hydrogen in the Upper Atmosphere ...... 164 4.3.4 Water as a Source of Escaping Hydrogen ...... 165 4.4 Conclusions ...... 168

CHAPTER 5 Conclusion ...... 173 5.1 Summary ...... 173 5.2 Future Lines of Inquiry ...... 175 5.2.1 The Carbon Monoxide Abundance in the Martian Upper At- mosphere ...... 176 5.2.2 The Climate Evolution of Mars ...... 176 5.2.2.1 Extrapolation of Escape Rates ...... 177 13

TABLE OF CONTENTS — Continued

5.2.2.2 Water in the Upper Atmosphere ...... 177 5.2.3 The Climate Evolution of Venus ...... 178 5.2.4 Beyond the Solar System ...... 179 5.2.5 The Beneﬁts of Laboratory Measurements ...... 179

REFERENCES ...... 181

LIST OF FIGURES

1.1 Early Mars timeline...... 24 1.2 Dendritic valley networks on the surface of Mars...... 25 1.3 A schematic of early Mars...... 27 1.4 The MAVEN spacecraft...... 39 1.5 The MAVEN orbit...... 42 1.6 The NGIMS instrument...... 46

2.1 Coverage of Mars by MAVEN NGIMS from September 2014 to Oc- tober 2017...... 52 2.2 Instrumental background subtraction and the use of proxy channels. . 56 2.3 An NGIMS mass spectrum for DD2 orbit 1060...... 57 2.4 Density correction factors...... 60 2.5 Random uncertainty in NGIMS measurements...... 62 2.6 The temperature derived for a single orbit...... 64 2.7 The eﬀect of averaging temperature proﬁles to remove wave activity. . 65

2.8 Comparison of average DD2 Ar, CO2, and N2 temperatures with no horizontal correction...... 67 2.9 Ar densities near periapsis for a single bin of orbits (bin 16) and the fit to the color crosses which determines the horizontal density gradient, dN/ds...... 69 2.10 The horizontal density gradient normalized by the fitted density at closest approach, 1/N◦ × dN/ds, as a function of each MAVEN orbit. 70 2.11 The effect of the horizontal correction on a bin of inbound Ar densities. 72 2.12 The effect of the horizontal correction on a bin of Ar temperatures. . 73 2.13 The horizontal density gradient normalized by the fitted density at periapsis, 1/N◦ × dN/ds, plotted as a function of the derivative of solar zenith angle with horizontal distance covered, d(SZA)/ds. . . . 74 2.14 Mean temperature for the first 8 DDs...... 75

2.15 Ar temperature binned as a function of CO2 density and local time. . 79 2.16 Ar temperature as a function of Martian local time at two constant 6 −3 9 −3 CO2 density levels: 10 cm and 10 cm ...... 80

2.17 Ar temperature as a function of latitude at two constant CO2 density levels: 106 cm−3 and 109 cm−3...... 81

2.18 The [O]/[CO2] ratio measured by NGIMS for each of the 8 DDs. . . . 94 2.19 Comparison of modeled temperature proﬁles with NGIMS data. . . . 95 2.20 The temperature at equatorial latitudes versus local time in the 1D model...... 96 16

LIST OF FIGURES — Continued

2.21 Comparison of the observed diurnal variation of the temperature at 6 −3 9 −3 CO2 densities of 10 cm and 10 cm with the diurnal variation of 7 −3 the temperature in the 1D model at a CO2 density of 10 cm . . . . 97 2.22 Energy balance terms for noon and midnight conditions from our 1D model...... 99

3.1 Coverage of Mars by MAVEN NGIMS between September 2014 and August 2020...... 108 3.2 A mass spectrum from aerobraking orbit 8625...... 112 3.3 Count rate proﬁles from aerobraking orbit 8617 as a function of time since closest approach and altitude...... 113

3.4 Vertical proﬁles of CO1, Ar, N2, O, He, and H2 densities measured by NGIMS on aerobraking orbit 8625...... 114 3.5 Mean densities measured by NGIMS over the orbit range 8716–8742. 116 3.6 Mean densities measured by NGIMS during DD5 and DD8...... 117 7 −3 3.7 Ar, N2, O, He, and H2 to CO2 ratios at a CO2 density of 10 cm measured by NGIMS over the course of the MAVEN mission...... 119

3.8 NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and latitude and constrained between 12 a.m. and 8 a.m...... 121

3.9 NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and latitude and constrained between 8 a.m. and 4 p.m...... 122

3.10 NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and latitude and constrained between 4 p.m. and 12 a.m...... 123

3.11 Latitudinal trends in the Ar, N2, O, He, and H2 to CO2 ratios and temperature measured by NGIMS at two CO2 densities and from three local time periods...... 124

3.12 NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and local time and constrained to latitudes between 90°N and 30°N. . 126 3.13 NGIMS Ar, N2, O, He, and H2to CO2 ratios binned on CO2 density and local time and constrained to latitudes between 30°N and 30°S. . 127 3.14 NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and local time and constrained to latitudes between 30°S and 90°S. . 128 3.15 Diurnal trends in the Ar, N2, O, He, and H2 to CO2 ratios and temperature measured by NGIMS at two CO2 densities and from three latitude bins...... 130

3.16 NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and LS and constrained to local times between 8 a.m. and 5 p.m. . . 132 3.17 NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and LS and constrained to local times between 8 p.m. and 4 a.m. . . 133 17

LIST OF FIGURES — Continued

3.18 Seasonal trends in the Ar, N2, O, He, and H2 to CO2 ratios and temperature measured by NGIMS at two CO2 densities and during two local time periods...... 134 3.19 The seasonal variation of Ar in the upper atmosphere as measured by NGIMS...... 135 3.20 Comparison of NGIMS data with Viking Lander and MAVEN IUVS data...... 138

4.1 Density at which τC = τD...... 154 4.2 MAVEN Location and Atmospheric Conditions During Martian Dust Storms...... 158 4.3 Variation of H2O Ions Measured Using NGIMS...... 159 4.4 Variation of H2O and H2...... 161 4.5 Seasonal Variation of Upper Atmospheric H2O...... 163 4.6 Calculated 1D Model Abundances and Reaction Rates...... 166

LIST OF TABLES

2.1 MAVEN Deep Dip Ephemeris...... 76 2.2 Temperature Comparison with Bougher et al. (2017b)...... 83

3.1 Ephemeris for MAVEN Deep Dips and aerobraking...... 109

4.1 Column-integrated Rates for Excluded Reactions...... 150 4.2 H2O Budget and H Production...... 168 20 21

ABSTRACT

Mars has lost the majority of its atmosphere to space over the last 4 billion years, leaving the planet cold, dry, and oxidized. The NASA Mars Atmosphere and Volatile Evolution (MAVEN) spacecraft arrived at Mars in 2014 to investigate the Mars-near space environment and the processes leading to atmospheric escape today, with the goal of understanding the evolution of Mars’ atmosphere and climate through time. The Neutral Gas and Ion Mass Spectrometer (NGIMS) is a quadrupole mass spectrometer onboard MAVEN which directly measures the neutral and ionic composition of the Martian upper atmosphere as MAVEN ﬂies through it. Using data obtained from NGIMS between 2014 and 2020, we investigate the thermal structure and neutral composition of this region. In addition, we report on the discovery of water in the upper atmosphere. Each of these three research eﬀorts provides insight into the escape of the Martian atmosphere to space.

The thermal structure of the Martian upper atmosphere is important for the determination of atmospheric escape rates because temperature is a measure of the distribution of velocities of the atoms that can escape to space and it determines the rate of many chemical reactions which alter the composition of the upper atmosphere. Using NGIMS measurements of Ar, N2, and CO2 densities, we calculate vertical profiles of temperature by assuming hydrostatic equilibrium and using the ideal gas law. We find the thermal structure of the upper atmosphere is highly variable, with large diurnal variations, and is consistent with a 1D energy balance model which includes solar ultraviolet and near infrared heating, thermal conduction, and radiative cooling by the CO2 ν2 15 µm band. Determination of the composition of the upper atmosphere of Mars is necessary to understand the chemistry and energy balance in this region and ultimately what species escape to space. NGIMS measures the abundances of CO2, Ar, N2, O, He, and H2. These data are the first vertical profiles of H2, an important source of escaping H, in the Martian upper atmosphere. We investigate variations in the composition of the upper atmosphere with latitude, local time, and season. Transport-driven 22

polar and nightside enhancements are identiﬁed in the ratios to CO2 of N2, O, He, and H2. We also observe seasonal variations in the Ar mixing ratio associated with the seasonal deposition and sublimation of CO2 at the polar ice caps. The discovery of water in the upper atmosphere of Mars has a direct impact on the desiccation of the Martian atmosphere and surface, because H2O transported high into the upper atmosphere is rapidly destroyed by ions to ultimately produce H and O atoms which escape to space. We use NGIMS measurements of water- + + related ions, namely H2O and H3O , to determine the water abundance in the upper atmosphere. The H2O abundance varies with season, peaking in southern summer when Mars is closest to the Sun. Regional and global dust storms lead to a sudden splash of additional water into the upper atmosphere. We demonstrate that the proportion of escaping H atoms produced from H2O is comparable to that from H2, the classical source of escaping H, during most of the Martian year. H2O becomes the dominant source of escaping H during global dust storms. 23

CHAPTER 1

Introduction

As our most hospitable and nearest planetary neighbor, Mars is the next planet on which humans will step foot. Ambitious organizations now aim to put humans on Mars in the mid 2020s. Regardless of how quickly these plans actually come to fruition, Mars is the only realistic planetary target for human exploration because of its relatively high habitability: Venus’ caustic and toxic atmosphere, Mercury’s lack of an atmosphere and proximity to the Sun, and the other planets’ lack of inhabitable surfaces shall naturally focus humanity’s colonization eﬀorts on Mars.

But the Mars that humans will venture onto is a difficult place with a thin, O2- poor atmosphere. While Mars was once more Earth-like, with a warmer and wetter surface and thicker atmosphere, today Mars is cold and dry. This is because Mars lost the vast majority of its atmosphere to space over the last 4 billion years. After the planet’s core cooled and solidified, its atmosphere was effectively stripped away by the solar wind (the plasma emitted by the Sun), because its atmosphere was unprotected by a global magnetic field as we have on Earth. The escape of Mars’ atmosphere to space played a major role in the transformation of Mars into the red planet we know today.

1.1 The Volatile History of Mars

The atmosphere of Mars today is too thin to support liquid water on the planet’s surface, but billions of years ago liquid water carved familiar features into the planet’s now red rock, features which remain today (Wordsworth et al., 2015; Ramirez and Craddock, 2018; Haberle et al., 2017a). Shortly after the accretion of Mars 4.5 billion years ago, convection within its molten core generated a global magnetic ﬁeld which protected its atmosphere from the solar wind. Because Mars is relatively small, its interior cooled relatively rapidly and, as a result, Mars lost its magnetic 24

field around 4 billion years ago (Figure 1.1, see Mittelholz et al. (2020) for detailed discussion). In the Noachian Period (4.1–3.7 Ga), the atmosphere was thick enough to keep the surface warm and support a hydrological cycle, if only for transient periods. Episodic events such as volcanic eruptions and asteroid impacts could have also produced periods of warmth and flowing liquid water. The geological record indicates that at the end of the Noachian and into the Hesperian Period (3.7–3.0 Ga), the climate conditions allowing liquid water to flow on the surface of Mars rapidly deteriorated (Carr and Head, 2010).

Figure 1.1: Early Mars timeline. The timeline of major events early in Mars history. This ﬁgure appears in Haberle et al. (2017a) and is reproduced with permission. Credit Christina Olivas.

There is extensive geological evidence for the presence of liquid water on the surface of a warmer and wetter early Mars. Dendritic valley networks and other ﬂuvial features such as deltas, alluvial fans, and channels have been preserved in Noachian and Hesperian terrains (Carr and Head, 2010; Haberle et al., 2017a). These features are similar to ﬂuvial features on Earth. The valley networks (Figure 1.2), in particular, are compelling evidence of precipitation during the Noachian, rather than, e.g., groundwater processes alone. Many of these valleys terminate in impact 25

Figure 1.2: Dendritic valley networks on the surface of Mars. Im- age ESP 033682 2235 taken by the High Resolution Imaging Science Experiment (HiRISE) on the NASA Mars Reconnaissance Orbiter. Credit NASA / JPL / UArizona. craters, having formed ancient lakes in these depressions. The presence of certain types of minerals on the surface of Mars is additional evidence of significant liquid water on the surface of early Mars, especially when combined with geological evidence which can provide context for the formation of these minerals (Haberle et al., 2017a; Bibring et al., 2006). The surface of Mars is primarily basaltic. Sulfates, carbonates, phyllosilicates, chlorides, and perchlorates, in addition to other minerals, have been identified remotely from orbit and through direct measurement on the ground. The formation of phyllosilicates and sulfates required substantial quantities of water and, in most scenarios, significant amounts of water on the surface rather than the subsurface (Bibring et al., 2006). Phyllosilicates are associated with Noachian surfaces, while the sulfates are found in later Noachian and Hesperian surfaces, indicating the existence of at least two distinct epochs of mineral formation in the presence of liquid water.

1.1.1 Warm and Wet or Cold and Icy

While it is clear there was once enough ﬂowing water on the surface of Mars for the formation of the geological and mineralogical features discussed above, many questions remain regarding the planet’s early climate (Figure 1.3), especially with respect to warming mechanisms for the atmosphere, the history of atmospheric es- 26 cape to space, and the role of this escape in the evolution of the climate through time (Jakosky et al., 2015; Wordsworth et al., 2015; Wordsworth, 2016; Haberle et al., 2017a; Ramirez and Craddock, 2018). The community of Mars scientists remains split along the boundary between two scenarios: (1) a warm and wet early Mars and (2) a cold and icy early Mars with only transient warmer and wetter periods (e.g. Wordsworth et al., 2015; Ramirez, 2017; Ramirez and Craddock, 2018; Wordsworth et al., 2021). A 2018 editorial declared, “Mars at war” (Nature Geo- science, 2018), though this assertion was quickly rejected by some scientists involved, who instead framed the debate as healthy and productive (Wordsworth et al., 2018). A number of authors have observed that Martian oceans remain the planet’s single most controversial topic (Carr and Head, 2010; Wordsworth, 2016; Haberle et al., 2017a), but the fundamental disagreement between groups supporting these “warm and wet” and “cold and icy” scenarios arises from the failure of many climate models to reproduce a perennially warm ancient Mars with surface temperatures in excess of the freezing point of water (e.g. Forget et al., 2013; Wordsworth et al., 2015), though recent progress has been made with CO2-H2 atmospheres (Ramirez et al., 2013; Wordsworth et al., 2017; Ramirez, 2017; Turbet et al., 2019; Ramirez et al., 2020; Turbet et al., 2020; Godin et al., 2020).

Warming a dense CO2-dominated early Martian atmosphere has proved difficult for models of the planet’s early climate, which must contend with a faint young Sun whose luminosity was perhaps just 75 % of its current value, and Mars’ larger distance from the Sun relative to that of Earth, meaning Mars receives just 43 % of the solar energy Earth does (Wordsworth, 2016). These hurdles thus require the early Martian atmosphere to produce a greenhouse effect in excess of ∼65 K (Wordsworth, 2016). Increasing the density of the early Mars atmosphere would lead in a straightforward manner to an increase in the magnitude of the greenhouse effect, but escape calculations integrated over the planet’s history provide limits on the total density of the early atmosphere. The most thorough calculations thus far indicate &0.8 bar

CO2 has been lost to space (Jakosky et al., 2018). CO2 can also be sequestered on the surface in the form of carbonates, which are produced when water reacts 27

Figure 1.3: A schematic of early Mars. The timing and importance of many of the processes presented in this ﬁgure are highly uncertain. This ﬁgure appears in Haberle et al. (2017a) and is reproduced with permission. Credit Christina Olivas.

with Mars’ basaltic crust under its CO2-rich atmosphere, but carbonates are rare on the surface of Mars and their total inventory in the subsurface is largely uncertain (Haberle et al., 2017a; Wordsworth, 2016). Thus, there is no strong evidence for an early atmosphere with a surface pressure in excess of one to perhaps two bar.

Even scenarios including extraordinarily dense and wet CO2 atmospheres cannot produce the needed greenhouse eﬀect (Forget et al., 2013). CO2 clouds become plentiful in such models, but provide relatively little warming, and can even cool the planet in some cases. At pressures higher than 3 bar, the atmosphere eventually collapses into permanent CO2 ice caps (Forget et al., 2013). More recently, models including 5–10 % H2 in the atmosphere have demonstrated that such mixtures can lead to surface temperatures above the freezing point of water (Ramirez et al., 2013; 28

Ramirez, 2017; Wordsworth et al., 2017; Ramirez et al., 2020; Turbet et al., 2020; Godin et al., 2020). Collision-induced absorption, the result of inelastic collisions

between CO2 and H2 in this case, is responsible for the spectral features that produce the necessary greenhouse eﬀect in these models. This is not necessarily a new idea, Sagan (1977) proposed a primary Martian atmosphere which was warmed by

H2 and NH3, though it is implausible Mars would have been able to retain such an atmosphere for the required length of time. However, the strength of these absorption features has only been measured in the laboratory quite recently (Turbet et al.,

2020; Godin et al., 2020). It has been posited that the H2 required by these models could be produced volcanically (Ramirez et al., 2013; Ramirez, 2017; Ramirez et al., 2020; Liggins et al., 2020) or through aqueous alteration of the crust (Wordsworth et al., 2017), with either case producing relatively steady warming over long periods of time; or through impacts, which would lead to transient warm periods (Haberle et al., 2019). CO2-H2 models may even be more consistent with a warm, semiarid climate than a warm and wet one (Ramirez et al., 2020). As the debate has raged, countries around the world have dispatched spacecraft to Mars at a rapid pace with hopes of addressing some of these questions. The NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) mission entered Mars orbit in late 2014 (Jakosky et al., 2015), the Indian Space Research Organization Mars Orbiter Mission (also known as Mangalyaan) did so just two days later (Arunan and Satish, 2015), the European Space Agency Trace Gas Orbiter successfully entered orbit in February 2018 (L´opez-Valverde et al., 2018), the United Arab Emirates al- Amal (Hope) mission entered Mars orbit in February 2021 (Sharaf et al., 2020), as did the Chinese Tianwen-1 mission (Zou et al., 2021), and the NASA Perseverance rover landed successfully on the surface shortly thereafter (Farley et al., 2020). The upper atmosphere is the reservoir of gas which can escape to space, so characterization of this reservoir in terms of its composition, variability, and thermal structure is necessary to understand ongoing escape processes in the present epoch and, by extension, escape that occurred deep in Mars’ past. Thus, an in-depth study of this region of the atmosphere has long been a goal of the community of 29

Mars scientists. Out of this ambition has emerged the MAVEN mission, designed to investigate atmospheric escape in the current epoch and its role as a force for climate change throughout the history of Mars.

1.2 Atmospheric Escape to Space

Around 66 % of Mars’ atmosphere has been lost to space (Jakosky et al., 2017) and the indelible mark of that escape remains in the atmosphere that is left: the isotopic ratios of many elements in the Martian atmosphere differ significantly from nominal Solar System values (Jakosky et al., 2015; Haberle et al., 2017a). That is, the Martian atmosphere is enriched in heavier isotopes of a number of elements. On Mars, the D/H ratio is about 5 times the value measured on Earth, 13C/12C is 1.05 times the terrestrial value, 14N/15N is 1.7 times terrestrial, 18O/16O is 1.05 times terrestrial, and 38Ar/36Ar is 1.3 times terrestrial (see Jakosky et al., 2015, Table 3). Enrichment in the heavier isotopes occurs because escape processes preferentially remove lighter species from the atmosphere and because these processes operate on the top of the atmosphere, a region enriched in lighter species due to diffusive separation. Above the homopause (∼100 km), the atmosphere is in diffusive equilibrium (the steady state established by diffusion in the absence of turbulent mixing, also called gravitational equilibrium), therefore the abundance of each molecular or atomic species declines with height according to its own scale height, or vertical distance over which the abundance of the species decreases by a factor e. The scale height is defined as H = kT/mg, where k is the Boltzmann constant, T the temperature, m the mass of the species, and g the acceleration due to gravity. Thus, lighter species have larger scale heights and their abundance decreases with height less rapidly than that of heavier species. There are a number of escape processes operating on the top of the Martian atmosphere (Jakosky et al., 2015; Lillis et al., 2015; Lammer et al., 2008; Johnson et al., 2008; Brain et al., 2017; Gronoff et al., 2020). These processes include Jeans escape, photochemical escape, sputtering, and multiple ion escape mechanisms. To- 30

gether, these processes are responsible for the loss of the majority of Mars’ secondary atmosphere over the last ∼4 billion years.

1.2.1 Jeans Escape

Light species at the top of the atmosphere with kinetic energies in the high- energy tail of the Maxwell-Boltzmann distribution which describes them can attain outward velocities in excess of the escape velocity of Mars (∼5 km s−1). This is referred to as Jeans escape (Jeans, 1925; Johnson et al., 2008; Gronoff et al., 2020). Jeans escape occurs at or near the exobase, the region of the atmosphere where it transitions from being collisionally dominated to collisionless. The collisionless region above the exobase is called the exosphere. The exobase is often referred to as a discrete altitude at which the Knudsen number, Kn = `/H, is equal to 1. Here ` is the mean free path, the mean distance a species travels between collisions. However, the transition from collisional to collisionless is gradual, escaping species may arise from well below the exobase defined by Kn ∼ 1, and the processes responsible for the energization of these atoms or molecules arise from and are strongest below the exobase (Johnson et al., 2008). The Jeans parameter is a measure of the tendency of an atmosphere to escape in the manner described above. It is defined as,

2 vesc 2GM/rexo GMm λJ = 2 = = , (1.1) vmp 2kT/m kT rexo

where vesc is the escape velocity, vmp the most probably velocity, rexo the exobase radius, G the gravitational constant, and M the mass of the planet. Equation 1.1 can be conveniently rewritten as λJ = rexo/H, with the scale height calculated at the exobase. It is instructive to understand that λJ is the gravitational potential energy of an atom or molecule divided by its kinetic energy: in the limit as λJ approaches inﬁnity, the atmosphere is entirely bound to the planet and no Jeans escape occurs and, in the limit as λJ approaches 0, large kinetic energies lead to rapid loss of the atmosphere. 31

The ﬂux of atoms or molecules escaping via the Jeans mechanism, φJ, is written as,

1 φ = √ N v (1 + λ )e−λJ , (1.2) J 2 π exo mp J

where Nexo is the number density of the species at the exobase. Estimates of the Jeans flux can be readily calculated with measurements of the abundance of the escaping species at the exobase and the exobase temperature. The Jeans mechanism is only significant for the lightest species present. That is, the heavier species do not have enough kinetic energy to reach the escape velocity of Mars. In more exact terms, this means that Jeans escape is the main mechanism for escape of the lightest atom, H (Bhattacharyya et al., 2017b; Chaffin et al., 2018), and is only significant for

H, D, H2, and He. This mass dependence has important implications for studying atmospheric escape that occurred in the distant past. Because D is twice the mass of H, H will escape via the Jeans mechanism much more rapidly than D, leading to an increase in the D/H ratio in the Martian atmosphere. This isotope ratio is a measurable result allowing for the quantiﬁcation of integrated escape through time.

1.2.2 Photochemical Escape

Exothermic chemical reactions occurring in the upper atmosphere can produce atoms with outward velocities in excess of the Martian escape velocity. This is called photochemical escape. On Mars, this process produces escaping O, N, and C atoms (Johnson et al., 2008). Photochemical escape is the main process responsible in the current epoch for the loss of O, N, and C from the Martian atmosphere, and has likely played a major role in the evolution of the Martian climate through time (Brain et al., 2017; Lillis et al., 2017; Cui et al., 2018; Lo et al., 2020). 32

The most signiﬁcant reactions responsible for photochemical escape at Mars are,

+ − 3 3 O2 + e −−→ O( P) + O( P) + 6.99 eV, (1.3) −−→ O(1D) + O(3P) + 5.02 eV, (1.4)

CO2 + hν −−→ C + O2, (1.5) CO + hν −−→ C + O, and (1.6)

N2 + hν −−→ 2 N. (1.7)

The main reaction responsible for the production of “hot” O atoms with energies in + excess of the escape energy is dissociative recombination with an electron of O2 , the main ion in the Martian ionosphere (or charged portion of the atmosphere) (Lillis et al., 2017; Fox and Ha´c,2018). Two channels of this reaction are capable of producing hot O atoms, as shown in Equations 1.3 and 1.4. Escaping C atoms are produced mainly by the photodissociation (or splitting of a molecule by a photon) of

CO2 and CO (Equations 1.5 and 1.6, respectively) (Cui et al., 2018; Lo et al., 2020). Because these are photodissociation reactions, relatively large amounts of energy can be transmitted to the escaping atom by the energetic photon, resulting in escape. Similar to the case for C, escaping N atoms are produced by photodissociation of

N2 (Equation 1.7, see Cui et al. (2018)). The calculation of photochemical escape rates can be complicated by the lack of laboratory measurements of photoabsorption and collisional cross-sections and the + probabilities of each reaction channel (as for the dissociative recombination of O2 ).

Since the photodissociation of CO and N2 proceed by excitation into discrete states that lead to dissociation (a process called predissociation), high resolution is needed in the laboratory measurements of these cross-sections. Measurements of the ﬂux of extreme ultraviolet (EUV) photons from the Sun and densities and temperatures of neutral species, ions, and electrons in the Martian upper atmosphere are also needed to compute these escape rates. This can complicate extrapolation backward in time, since all of these quantities become much more uncertain in the distant past. 33

1.2.3 Sputtering Escape

Atmospheric sputtering is the process by which high-energy incident atoms, accelerated by the solar wind in the anti-sunward direction, impact the atmosphere and eject atoms or molecules into space (Luhmann et al., 1992; Jakosky et al., 2015). This process likely occurs at a relatively slow rate today, but was more important in the early Solar System when the Sun was more active in terms of coronal mass ejections. H and O atoms escaping from the sunward hemisphere of Mars, such as those produced by the escape processes discussed above, are often ionized and “picked-up” by the solar wind (Rahmati et al., 2017). Then, these H+ and O+ pickup ions are accelerated back toward Mars, eventually impacting the atmosphere and ejecting other atoms or molecules from near the exobase. Specifically, the solar wind, moving at velocity v with magnetic field B, accelerates pickup ions through the v × B electric field it generates. The ions can be accelerated to velocities up to twice the velocity of the solar wind, 250–750 km s−1, and lead to multiple collisions and escape events. Since pickup ions energize the upper atmosphere and lead to additional escape beyond the initial H or O atom, the sputtering process can lead to a positive feedback loop of escape. Solar Energetic Particles (SEPs) can also lead to sputtering escape. SEPs are high-energy solar wind particles (mostly protons and electrons) generated by solar flares and the coronal mass ejections (CMEs) that sometimes accompany them, but not every every CME event leads to the generation of SEPs.

The rate of sputtering escape, like that of Jeans and photochemical escape, must be calculated. Necessary measurements of the solar wind velocity and composition can complicate such calculations since these are not always available at Mars. Ex- trapolating these parameters backward in time over billions of years is even more challenging. The frequency of CMEs is also a problematic parameter in such calculation for the same reasons. Upper atmospheric densities are also required since the atoms and molecules in the exosphere and upper thermosphere (the region just below the exobase) are the targets for sputtering. Thermospheric and exospheric 34 densities and temperatures must be known to understand the population of escaping atoms which can be converted into pickup ions.

1.2.4 Ion Escape

Ions may escape the Martian atmosphere through multiple mechanisms which can be grouped into at least three categories: ion pickup, ion bulk escape, and ion outflow (Jakosky et al., 2015; Brain et al., 2017; Gronoff et al., 2020). First, escape via ion pickup occurs when pickup ions, as described in the previous section, do not impact the Martian atmosphere and are instead accelerated past the planet in the anti-sunward direction. This process is responsible for a “polar plume” of escaping O+ ions at Mars (Dong et al., 2015). Second, ion bulk escape occurs when any process removes coherent clouds of the ionosphere and accelerates these clouds away from the planet. These processes are thought to occur mainly by way of momentum transfer from the solar wind to the ionosphere (Halekas et al., 2016). Third, ion outflow is the name given to the group of processes which lead to the escape of relatively low-energy (or “cold”) ions along “open” planetary magnetic field lines, those that are connected with interplanetary magnetic field (IMF) lines. These cold ions are accelerated outward by the electric fields generated on these field lines and/or plasma heating. A number of such outflow processes have been observed on Earth and there should be analogues to these processes which occur at Mars: though Mars lacks a global magnetic field, there are remnant crustal magnetic fields in its southern hemisphere (e.g Connerney et al., 2001). The magnetic field lines emanating from the crustal magnetic fields can reconnect with the IMF like the global magnetic field on Earth does. Ion pickup, ion bulk escape, and ion outflow are processes that lead to popula- tions of ions that are often directly measurable, in contrast to previously discussed escape process which require calculations to determine escape fluxes (Brain et al., 2017; Gronoff et al., 2020). However, while the population of escaping ions is measurable, it is difficult to obtain the context which allows one to determine the process, or combination of processes, which led to the liberation of the ion from the atmosphere. 35

This is especially true since such measurements of the population of escaping ions are made in situ at the site of a spacecraft, which can only investigate one location and set of conditions at one time. This underscores the need to measure not just the population of escaping atoms themselves, but the drivers for the processes that lead to escape, e.g. the solar EUV flux, solar wind pressure and density, IMF direction and strength, SEP flux, and even dust activity on the surface, which alters the structure and composition of the atmosphere above. With these quantities and coincident measurements of the escaping atom population, one can begin to piece together mechanisms responsible for variations in the escape flux over time.

1.3 The NASA Mars Atmosphere and Volatile Evolution Mission

The NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) mission is a Mars orbiter designed to study the Martian upper atmosphere, the Mars-solar wind interaction, and the escape of the atmosphere to space. The concept of a mission like MAVEN has a long history. This concept was built on the successes of missions with similar scopes and objectives which studied the upper atmospheres of Earth and Venus: at Earth, the Atmosphere Explorer missions in the 1960s and 1970s (Dalgarno et al., 1973; Spencer et al., 1973; Nier et al., 1973; Pelz et al., 1973) and Dynamics Explorer satellites in 1980 (Hoffman, 1980) and, at Venus, the Pio- neer Venus Orbiter, which operated from 1978 to 1992 (Colin and Hall, 1977; Colin, 1980). Starting in the 1980s, the Mars Aeronomy Observer (MAO) was a candidate mission in the NASA Planetary Observer Program intended to “address the last major aspects of [the] Martian environment which have yet to be investigated: the upper atmosphere, the ionosphere, and the solar wind interaction region” (Hunten et al., 1986). Another similar mission named Earth/Mars Aeronomy Observer (EMAO) was proposed for further study around this time (Brace, 1989, 1992). MAO and EMAO were designed in response to a report from the Solar System Exploration Committee of the NASA Advisory Council, which described an aeronomy orbiter mission that would determine “the character of the Martian magnetic field, the na- 36 ture of the planet’s interaction with the solar wind, and the structure and dynamics of the upper atmosphere” (Solar System Exploration Committee of the NASA Ad- visory Council, 1983). Their proposed instrument compliments were quite similar to the suite of instruments eventually carried to Mars by MAVEN. Later, the Mars Upper Atmosphere Dynamics, Energetics, and Evolution (MUADEE) concept was formulated as a Discovery-class mission and selected by NASA for further study in 1994, though it did not fly (Killeen and Brace, 1995). The main goal of the MUADEE mission would have been to “gain an understanding of the physics and chemistry of the Martian upper atmosphere, and then to use that understanding to make informed inferences about the evolution of the atmosphere” (Killeen and Brace, 1995). MUADEE would have used an orbit much like that of MAVEN and carried a similar suite of instruments. In the 1990s, the Japanese Aerospace Explo- ration Agency PLANET-B (or Nozomi) orbiter employed an instrument suite and orbit similar to those now employed by MAVEN (Tsuruda et al., 1996; Yamamoto and Tsuruda, 1998). It was launched in 1998, but failed to enter Mars orbit. In the 2000s, the MAVEN proposal, and a similar proposed mission which was called “The Great Escape” (TGE) responded directly to the decadal survey of the Na- tional Research Council of the National Academies, which was published in 2003 and highlighted the need for a “Mars Upper Atmosphere Orbiter” which would study “the dynamics of the upper atmosphere; hot atom abundances and escape fluxes; ion escape; minimagnetospheres and magnetic reconnections; and energetics of the ionosphere” (National Research Council, 2003). Formulation of the MAVEN concept and team began in 2003 in anticipation of the 2006 Mars Scout Announcement of Opportunity (Jakosky et al., 2015). It was selected for Phase A study in 2007 and selected for flight in 2008 over TGE. MAVEN is the second and final mission of the NASA Mars Scout Program (the first being the Phoenix Lander, see Shotwell (2005)). The Scout program, a part of the NASA Mars Exploration program, was designed to send smaller, lower-cost missions to Mars: MAVEN had a total cost less than $600 million for its construction, launch, and operation through its primary mission. Prior to selection, launch of the second Scout mission was delayed 37 from 2011 to 2013 due to an organizational conflict of interest (Hautaluoma, 2007). Years later, as the launch date for MAVEN neared, a budget impasse in the United States Congress led to a shutdown of the United States Federal Government, which suspended government operations, including most operations at NASA. However, MAVEN was given an emergency exemption and launched successfully aboard an ATLAS V-401 rocket on 18 November 2013 and entered Mars orbit on 21 September 2014 (Jakosky, 2013; Jakosky et al., 2015). The MAVEN science objectives are to (Jakosky et al., 2015):

• Measure the composition and structure of the upper atmosphere and ionosphere today, and determine the processes responsible for controlling them.

• Measure the rate of loss of gas from the top of the atmosphere to space, and determine the processes responsible for controlling them.

• Determine properties and characteristics that will allow us to extrapolate back- wards in time to determine the integrated loss to space over the four-billion- year history recorded in the geological record.

MAVEN is designed to reach these objectives by studying energy inputs from the Sun (solar EUV flux, the properties of the solar wind, the SEP flux, and the IMF direction and intensity) and the response of the Martian upper atmosphere to this energy (its thermal structure and its neutral and ionic composition) (Jakosky et al., 2015; Lillis et al., 2015). These energy inputs drive escape from the planet in various ways. The EUV flux heats and ionizes the upper atmosphere. This heating determines the thermospheric temperature, thus also determining the location of the exobase from which species may escape. The ionization caused by EUV photons gives rise to the entire ionosphere, thus driving the photochemical escape rate, and contributing to the sputtering and ion escape rates. The SEP flux similarly impacts escape rates through heating and ionization. The density and pressure of the solar wind determine the rate at which exospheric neutrals are ionized by the solar wind (so called charge exchange) and picked up to be lost behind the planet (relative to 38 the Sun) or accelerated into the planet to cause sputtering escape; the solar wind pressure determines the location of the boundary between the near-Mars environment and the solar, which determines what fraction of the exosphere is exposed to the solar wind; and the pressure of the solar wind compresses Mars’ remnant crustal magnetic fields, affecting escape processes such as ion outflow which occur from these regions. The IMF direction and intensity affects ion escape since it is the IMF which determines the Lorentz force driving the motion of pickup ions as they escape or impact the top of the atmosphere. Further, the IMF, along with the crustal magnetic fields, determine the arrangement of open and closed field lines along which escaping ions and solar wind charged particles will travel away from or toward the planet, respectively. Finally, dust storms on the planet can also impact atmospheric escape by altering the thermal structure and composition of the entire atmosphere. The MAVEN spacecraft design is based on the designs of the NASA Mars Recon- naissance Orbiter (MRO) (Graf et al., 2005), Juno (Matousek, 2007), and Gravity Recovery and Interior Laboratory (GRAIL) (Zuber et al., 2013), each built by Lock- heed Martin. MAVEN carries with it a suite of 8 instruments, with some mounted on the cubic central body of the spacecraft, one on the tips of the gull-wing solar panels, and three on an Articulated Payload Platform (APP), which is a rotating platform held below the main body of the spacecraft that allows for pointing of these instruments independent of the rotation of the rest of the spacecraft (Figure 1.4). The 8 science instruments onboard MAVEN are (Jakosky et al., 2015):

• Solar Wind Electron Analyzer (SWEA) measures the energy and angular distributions of both solar wind electrons and ionospheric photoelectrons. Solar wind electrons deposit energy in the upper atmosphere, while both pop- ulations of electrons are responsible for many chemical reactions in the upper atmosphere.

• Solar Wind Ion Analyzer (SWIA) measures the energy and angular distributions of solar wind ions (mainly H+ and He2+). These measurements provide 39

Figure 1.4: The MAVEN spacecraft. (top) The MAVEN spacecraft in a clean- room after assembly. Copyright Jon Brack and reproduced with permission. (bottom) A schematic of the MAVEN spacecraft and its instruments. Credit NASA / LASP / GSFC / JPL. 40

information about the solar wind pressure and the acceleration of pickup ions. SWIA has no mass resolution, but can diﬀerentiate between H+ and He2+ by their mass to charge ratio.

• Solar Energetic Particle (SEP) instrument measures the energy spectrum and angular distribution of solar energetic electrons and ions, providing information on atmospheric heating, ionization, and sputtering. The diﬀer- ence between the species measured by SEP and those measured by SWEA and SWIA is their energy: SEP measures electrons in the 30 keV–1 MeV range and ions in the 30 keV–12 MeV range, while SWEA measures electrons in the 5 eV–6 keV range and SWIA measures ions in the 13 eV–5 keV range.

• Suprathermal and Thermal Ion Composition (STATIC) instrument measures velocity distributions and mass of suprathermal and thermal ions, providing information on the composition of the solar wind, pickup ion population, and the ionosphere.

• Langmuir Probe and Waves (LPW) contains both a Langmuir probe and an EUV monitor. The Langmuir probe measures photoelectron density and temperature along with waves in the electric ﬁeld, which are crucial for understanding upper atmospheric chemistry, photochemical scape, and the structure of the ionosphere. The EUV monitor measures the EUV ﬂux from the Sun, which is the primary source of energy for the upper atmosphere.

• Magnetometer (MAG) measures the intensity and direction of the magnetic field at the spacecraft. Depending on the location of the spacecraft, MAG measures the IMF, the ionospheric magnetic field, or the crustal magnetic fields. This is important in particular for ion escape mechanisms.

• Imaging Ultraviolet Spectrograph (IUVS) remotely measures UV photons in at least 4 modes, which include limb scans, planet-wide mapping, mapping of the Martian corona, and stellar occultations. From these measure-

ments, densities are obtained of CO2,N2, and O. Measurements of Lyman-α 41

brightness enables the modeling of H and D abundances and their Jeans escape rates.

• Neutral Gas and Ion Mass Spectrometer (NGIMS) measures the neutral and ionic composition of the upper atmosphere, with a 1 u mass per charge (m/z) resolution (which enables the measurement of isotopic ratios) and high spatial and temporal resolution (each measurement takes just ∼27 ms).

In addition to these 8 science instruments, the MAVEN accelerometer (ACC) collects measurements of the drag of the atmosphere on the spacecraft, which allows for calculations of the total density of the atmosphere at the location of the spacecraft, but with no information on composition Tolson et al. (2017). These data are useful from an operational standpoint to aid in guidance of the spacecraft through the Martian atmosphere, and from a scientiﬁc standpoint, as the measurement of the total density provides useful information on the structure and variability of the upper atmosphere. The MAVEN orbit is designed to precess around Mars to sample a wide range of latitudes and local times (Figure 1.5). This ensures that its instruments sample a wide range of conditions on Mars. The orbit has a nominal periapsis altitude of 150 km, apoapsis altitude of 6220 km, and period of 4.5 h. NGIMS and other in situ instruments which measure the Martian atmosphere operate during the periapsis segment of the orbit, between 150 to 500 km. MAVEN executed nine roughly week- long Deep Dip (DD) maneuvers over the course of its primary and extended science missions, wherein the periapsis altitude was lowered to ∼125 km. These maneuvers allowed the spacecraft to obtain a nearly complete picture of the upper atmosphere from above the exobase to the mesopause. For much of its science mission, MAVEN also carried out relay operations in addition to its science operations, sending data received from ground assets such as the Curiosity rover and InSight lander to Earth. In Spring 2019, MAVEN commenced an aerobraking operation to lower its apoapsis altitude, during which MAVEN reached periapsis altitudes as low as those achieved during DDs for a period of about 2 months. This aerobraking period, and a sub- 42 sequent periapsis raise in mid-2020, served the purpose of nearly circularizing the MAVEN orbit. The circularization of the orbit will extend the mission’s fuel lifetime to 2030 or beyond and enable more frequent relay operations.

Figure 1.5: The MAVEN orbit. An illustration of the MAVEN orbit around Mars. Note that the MAVEN orbit precesses around Mars, such that periapsis does not always occur in the same location. This ﬁgure appears in Jakosky et al. (2015) and is reproduced with permission.

1.4 The MAVEN Neutral Gas and Ion Mass Spectrometer

The MAVEN Neutral Gas and Ion Mass Spectrometer (NGIMS) is a quadrupole mass spectrometer which measures the neutral and ionic composition of the upper atmosphere as MAVEN passes through it (Mahaffy et al., 2015b). Mass spec- 43 trometers were invented around the turn of the 20th century and have flown on sounding rockets since at least 1949, starting with the German V-2 rockets cap- tured by the United States and Soviet Union after World War II (Townsend et al., 1954; Meadows and Townsend Jr., 1958; Meadows and Townsend, 1960; Johnson, 1961; Taylor and Brinton, 1961; Pokhunkov, 1962; Istomin and Pokhunkov, 1963; Pokhunkov, 1963c,a,b; Meadows-Reed and Smith, 1964; Nier et al., 1964; Schaefer and Nichols, 1964b,a); on satellites since Sputnik 3 in 1958 (NASA, 2021), and on satellites launched from the United States since the NASA Atmospheric Explorer-A (Explorer XVII) mission in 1963 (Spencer and Reber, 1963; Spencer et al., 1965); and, since the 1970s, mass spectrometers have been sent beyond Earth to the Moon, various comets, Mars, Venus, Jupiter, Saturn, and Titan (Arevalo et al., 2019). At Mars, mass spectrometers were onboard Viking Lander 1 and 2 as they descended through the upper atmosphere of Mars (Nier et al., 1972; Nier and McElroy, 1976; Nier et al., 1976a,b; Nier and McElroy, 1977), but those are the last and only direct measurements of the composition of the Martian upper atmosphere prior to the arrival of NGIMS. The Viking Landers obtained exactly two vertical profiles of composition. At the time of writing, NGIMS has measured vertical profiles of composition on nearly 9000 MAVEN orbits. NGIMS was developed in parallel with the Neutral Mass Spectrometer on the Lunar Atmosphere and Dust Explorer (LADEE) mission (Mahaffy et al., 2015c), and its components have a heritage in mass spectrometers developed for Venus (Niemann et al., 1980b), Jupiter (Niemann et al., 1992), the PLANET-B mission to Mars (Niemann et al., 1998), and both Saturn and Titan (Niemann, 2002; Waite et al., 2004). The Ion and Neutral Mass Spectrometer (INMS) on Cassini and the NGIMS instrument on the Comet Nucleus Tour (CONTOUR) mission (Veverka et al., 1995) are the immediate antecedents of MAVEN NGIMS. Both of these instruments were based on the NGIMS instrument on the Comet Rendezvous Flyby Mission (CRAF), which was developed before the instrument was recommended to be descoped and the mission eventually can- celed (Mahaffy et al., 2015b; National Research Council, 1990). NGIMS either ingests and ionizes atmospheric neutrals or ingests atmospheric 44 ions, then separates the resultant ion beam by the mass per charge ratio (m/z) of each species (Figure 1.6). NGIMS can operate in three modes (Mahaffy et al., 2015b):

• Closed source neutral mode, wherein atmospheric neutrals are forced by the ∼4 km s−1 velocity of the spacecraft through a small aperture into an antechamber. Once in the antechamber, the gas thermalizes through collisions with the walls of the chamber. Any highly reactive species, such as O, N, and

C, have a chance to recombine to form, e.g., O2,N2, CO, and NO. The advantage of this mode is a mass-dependent density enhancement, leading to a higher instrument sensitivity. After exiting the antechamber, the neutrals are ionized by the impact of electrons emitted by a hot ﬁlament.

• Open source neutral mode, in which atmospheric neutrals are collimated and passed immediately into an ionization region without ﬁrst thermalizing in an antechamber. In this mode, reactive species do not have the opportunity to recombine as they do in the closed source neutral mode, which allows for the measurement of their atmospheric abundance.

• Open source ion mode, which is identical to the open source neutral mode except for the ionization step, which is unnecessary because the atmospheric ions are already charged.

In each case, the resultant ion beam is then passed through the quadrupole mass analyzer (QMS, also called a quadrupole mass ﬁlter), which selects the ions that shall reach the detectors using a combination of radio frequency and static DC voltages. The detectors are Channeltron electron multipliers. NGIMS carried with it a calibration gas consisting of N2, CO2, Ar, Kr, and Xe, which can be used inﬂight to assess the health of the instrument. NGIMS covers an m/z range of 1 to 150 u, which means that, in the Martian upper atmosphere, NGIMS can measure the abundances of H2, He, O, N2, Ar, and

CO2. The unit mass resolution of the instrument provides the ability to resolve 45 elemental isotopes, such as 12C and 13C; 16O, 17O, and 18O; 14N and 15N; and 36Ar, 38Ar, and 40Ar. In the open source ion mode, NGIMS can measure the abundances + + + 2+ + + + + + + + + + + of H2 ,H3 , He ,O ,C , CH ,N , NH ,O , OH ,H2O ,H3O ,N2 + CO , + + + + + + + + + HCO +HOC +N2H , HNO ,O2 , HO2 , Ar , CO2 , and HCO2 (Benna et al., 2015a). Each NGIMS measurement is taken in just 27 ms and each m/z channel is measured every 1 to 3.5 s depending on its scientiﬁc utility. Rapid integration time and measurement cadence produces unprecedented spatial and temporal resolution in the measurement by NGIMS of the abundances of these species. 46

Figure 1.6: The NGIMS instrument. (top) The NGIMS instrument before integration with MAVEN. Credit NASA / LASP / GSFC. (bottom) A schematic of the operation of the NGIMS instrument spacecraft and its instruments. This image appears in Mahaﬀy et al. (2015b) and is licensed under the terms of Creative Commons CC-BY. 47

1.5 Outline

The research presented in this dissertation is motivated by the characterization of the upper atmosphere of Mars and the determination of the escape rate of the neutral atmosphere to space using data from NGIMS, guided by the science goals of the MAVEN mission (Section 1.3). First, in Chapter 2, is an investigation of the thermal structure of the upper atmosphere. Temperature proﬁles are derived from

NGIMS measurement of the Ar, N2, and CO2 abundances. The thermal structure of the upper atmosphere must be studied to understand the energy balance of this region. The measurement of the thermal structure of the upper atmosphere and the investigation of the processes controlling this structure (that is, the energy balance of this region) are fundamental to atmospheric escape (see Section 1.2). Second, Chapter 3 is an investigation of the neutral composition of the upper atmosphere according to NGIMS: abundances of H2, He, O, N2, Ar, and CO2 are reported. Atmospheric escape rates also depend on the composition of the upper atmosphere as they do the thermal structure. It is also of note that these are the ﬁrst in situ measurements of H2 reported for Mars. Third, in Chapter 4, is the discovery of water in the upper atmosphere (where it is quickly destroyed and escapes to space in the form of H and O), the seasonal variation of the upper atmospheric water abundance, and the exact ion chemistry mechanisms for its destruction. Thus, Chapter 4 contributes to the determination of the current escape rate of the atmosphere. 48 49

CHAPTER 2

Thermal Structure of the Martian Upper Atmosphere

The contents of this chapter were published in Stone et al. (2018).

2.1 Introduction

The role atmospheric escape has played in the transformation of the Martian climate through time must be understood to determine the history of water and potential habitability on the surface of Mars (Jakosky and Phillips, 2001). The main science objective of the NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) mission is to study the composition and structure of the upper atmosphere of Mars to better determine the current and historical atmospheric escape rates (Jakosky et al., 2015; Lillis et al., 2015; Bougher et al., 2015a). Escape from Mars occurs through numerous processes (Lillis et al., 2015), all of which depend closely on the atmospheric thermal structure. Indeed, proper characterization and understanding of the thermal structure of the upper atmosphere is an integral part of any investigation into the present day or historical escape rates. Here, we use data from the Neutral Gas and Ion Mass Spectrometer (NGIMS, see Mahaffy et al. (2015b)) onboard MAVEN to characterize and investigate the thermal structure of the upper atmosphere of Mars. NGIMS is the first mass spectrometer to directly sample the upper atmosphere of Mars since the descents of Viking Lander 1 and 2 in 1976 (Nier et al., 1972; Nier and McElroy, 1976; Nier et al., 1976a; Nier and McElroy, 1977; McElroy et al., 1976) and the first mass spectrometer on a Mars orbiter. Other in situ measurements of upper atmospheric neutral densities and temperatures were made prior to the arrival of MAVEN by the accelerometers on Viking Lander 1 and 2 (Seiff, 1976; Seiff and Kirk, 1976, 1977; Withers et al., 2002); the Mars Pathfinder Atmo- spheric Structure Instrument (ASI) and accelerometers during descent (Seiff et al., 50

1997; Schoﬁeld, 1997; Magalhaes et al., 1999; Spencer et al., 1999; Withers et al., 2003b); and the Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) accelerometers during the aerobraking phases of their missions (Keating et al., 1998; Bougher et al., 1999b; Withers et al., 2003a; Withers, 2006; Tolson et al., 1999a,b, 2005, 2008). The Phoenix lander, Mars Ex- ploration Rovers Spirit and Opportunity, Beagle 2, and Mars Science Laboratory also collected atmospheric density and temperature data during their descents to the surface, but these measurements either do not extend above 120 km or are uncertain above this altitude (Withers and Smith, 2006; Withers and Catling, 2010; Montabone et al., 2006; Blanchard and Desai, 2011; Karlgaard et al., 2014; Chen et al., 2014; Holstein-Rathlou et al., 2016). The ISRO Mars Orbiter Mission (MOM, see Arunan and Satish (2015)) arrived at Mars subsequent to MAVEN and the Mars Exospheric Neutral Composition Analyzer (MENCA, see Bhardwaj et al. (2015)) quadrupole mass spectrometer onboard MOM has collected in situ measurements of the Martian exosphere. Bhardwaj et al. (2016) derived exospheric temperatures from MENCA measurements. NGIMS measurements analyzed here, obtained over 4231 MAVEN orbits and covering more than a Mars year, signiﬁcantly extend the coverage of the Martian upper atmosphere in terms of local time, latitude, season, and altitude.

Remote sensing observations have also produced information on the thermal structure of the upper atmosphere of Mars. Stellar occultation investigations carried out in the UV by the Spectroscopy for Investigation of Characteristics of the Atmosphere of Mars (SPICAM, see Bertaux et al. (2006)) spectrograph on Mars Ex- press (MEX) (Quémeraiset al., 2006; Forget et al., 2009; Montmessin et al., 2017) and the Imaging Ultraviolet Spectrograph (IUVS, see McClintock et al. (2015)) on MAVEN (Grölleret al., 2015, 2018) have produced atmospheric temperature profiles that extend up to ∼130 km, near the base of the thermosphere. Solar occultation observations made during two solar flares by the RF-15 X-ray radiometer onboard Phobos 2 also produced temperature profiles that extend to the base of the thermosphere (Krasnopolsky et al., 1991). Dayglow observations from the Mariner 6, 7, 51 and 9 UV spectrometers (Anderson and Hord, 1971, 1972; Stewart, 1972; Stewart et al., 1972; Anderson, 1974; Krasnopolsky, 1975), SPICAM (Leblanc et al., 2006, 2007; Huestis et al., 2010; Stiepen et al., 2015), and IUVS provide information on upper atmosphere temperatures (Evans et al., 2015; Jain et al., 2015), but with less altitude resolution than the occultations. Upper atmospheric neutral temperatures have also been derived from topside ionosphere scale heights obtained from radio occultation measurements made by the Mariner 4, 6, 7, and 9, Mars 2, 3, 4, and 6, and Viking 1 and 2 satellites (Fjeldbo et al., 1970; Kliore et al., 1973; Lindal et al., 1979; Bauer and Hantsch, 1989; Kliore, 2013), and from calculation of the neutral scale height using Chapman theory and measurements of total electron content and maximum electron density made by the MGS radio occultation experiment, Mars Express Orbiter Radio Science Experiment (MaRS), and Mars Advanced Radar for Subsurface and Ionospheric Studies (MARSIS) instrument aboard MEX (Safaeinili et al., 2007; Mendillo et al., 2015; Sánchez-Cano et al., 2015, 2016). NGIMS gathers in situ measurements of the Martian atmosphere on every MAVEN orbit. The spacecraft’s elliptical ∼4.5 h orbit precesses slowly to cover the planet in local time every ∼6 months and latitude every ∼7 months (Figure 2.1). The combination of the MAVEN orbit and the high temporal and mass resolution of NGIMS has produced a data set of high quality atmospheric density measurements with coverage from the poles to the equator, from the dawn terminator to the dusk terminator, from the subsolar point to the antisolar point, and across the seasons in the northern and southern hemispheres. A nominal periapse pass for MAVEN begins around 500 km altitude, continues through periapsis around 150 km, and ends again around 500 km altitude. Roughly week-long low altitude excursions called Deep Dips (DDs) allow NGIMS to sample down to altitudes as low as 125 km. Eight DDs have been executed to date. The MAVEN orbit does not precess significantly in latitude or local time over the course of each DD, but many longitudes are sampled as a result of planetary rotation. In Figure 2.1, panel D illustrates an example of a DD2 periapse pass. Demcak et al. (2016) discuss the navigation of the MAVEN spacecraft and the implementation of 52

Date

Sep '14 Apr '15 Oct '15 Apr '16 Oct '16 Apr '17 Oct '17 190 3000 A D 170

150 2000 130 Altitude (km)

110

24 B 1000 18

12 0 Mars 6 Local Time (h) 0 Distance (km)

90°N C -1000 45°N

0°

Latitude 45°S -2000

90°S 125 km 0 1000 2000 3000 4000 5000 6000 250 km MAVEN Orbit -3000 240 300 0 60 120 180 240 300 0 60 2500 3000 3500 4000 L (degrees) Distance (km) S Figure 2.1: Coverage of Mars by MAVEN NGIMS from September 2014 to October 2017. (A) Altitude, (B) local time, and (C) latitude at periapsis for each MAVEN orbit. (D) Illustration of a periapse pass on DD2 orbit 1060 (black) shown relative to Mars (orange) with lines representing 125 km altitude (blue dash- dot) and 250 km altitude (green dash-dot). The axes for panel D refer to distance from the center of the planet. 53 these DD maneuvers in greater detail. Mass spectrometer measurements of the vertical variation of the densities of atmospheric species enable the determination of neutral temperatures from hydrostatic equilibrium and the ideal gas law. We use NGIMS upper atmospheric Ar,

CO2, and N2 density measurements from 4231 MAVEN orbits to derive upper atmospheric temperatures, investigate the diurnal and latitudinal variation of these temperatures and the thermospheric gradient during the DDs, and compare our results with a 1D model and previous measurements.

2.2 Methods

To calculate Ar, CO2, and N2 densities from NGIMS measurements we first correct for detector nonlinearity (dead time), background signal levels, molecular scattering within the instrument, and ram effects related to the interaction of the spacecraft with the ambient atmosphere. We also separate horizontal and vertical variations in the atmosphere as manifest in measurements along the spacecraft trajectory. High resolution vertical temperature profiles from the upper atmosphere of Mars are then reconstructed from measured densities assuming hydrostatic equilibrium and using the ideal gas law. We have selected Ar, CO2, and N2 densities for this analysis because the measurement of these species by NGIMS, described below, is well understood, and their vertical distributions in the atmosphere are not appreciably affected by photochemical processes: the temperatures derived from these three species are the bulk neutral temperature.

2.2.1 Treatment of Data

We utilize MAVEN NGIMS Level 1 (L1) export, versions 9 and 10, revision 1 data files to carry out our analysis. The same data is available publicly in the MAVEN NGIMS Level 1b (L1b) files. Version 10 of the L1 export corrected typographical errors that affected a subset of orbits. The files with the most up to date version and revision at the time of writing were used. These data files contain counts registered 54

by the detector per 27 ms integration period for each measured mass per charge (m/z) value. NGIMS operates at unit m/z resolution and each m/z channel is measured at a cadence of 1–3.5 s, depending on the channel. Only the closed source neutral data contained in these files are used in our analysis. Data collected during part of December 2014 and all of January 2015 are excluded due to fluctuations in the instrument sensitivity. For further discussion of this problem, see the Supporting Information of Mahaffy et al. (2015a). The instrument was turned off and thus did not collect data due to spacecraft safing events from April 3 to 14, 2015 (orbits 987 to 1049) and August 11 to 21, 2015 (orbits 1690 to 1743), and during periods of Mars solar conjunction from May 27 to July 1, 2015 (orbits 1272 to 1468) and July 18 to August 7, 2017 (orbits 5424 to 5540). Therefore the data span the time periods from October 18 to December 28, 2014 (orbits 108 to 481); February 11 to April 3, 2015 (orbits 714 to 986); April 15 to May 26, 2015 (orbits 1050 to 1271); July 2 to August 11, 2015 (orbits 1469 to 1689); August 21, 2015 to July 18, 2017 (orbits 1744 to 5423); and August 8 to October 23, 2017 (orbits 5541 to 5950); with only short data gaps due to, for example, passes dedicated to communication with Earth. We calculate the spacecraft position, velocity, and NGIMS pointing vectors using version N0066 of the MATLAB implementation of the SPICE observation geometry system provided by the NASA Navigation and Ancillary Information Facility (NAIF) (Acton, 1996). The MAVEN mission utilizes a planetographic coordinate system in contrast to the MGS, ODY, MEX, and MRO missions, which use a plane- tocentric coordinate system (Withers and Jakosky, 2017). The planetographic coordinate system is preferred because vertical is more nearly aligned with the direction of gravity. While longitudes between the two systems are essentially equivalent, latitudes differ by up to 0.34° and altitudes differ by up to 2 km. For our calculations we set the equatorial and polar radii of Mars to 3396.19 to 3376.20 km, respectively (Archinal et al., 2011). This yields a flattening coefficient f = 5.886 × 10−3. Before densities can be calculated, count rates must be corrected for detector dead time and background signal must be removed. From Benna and Elrod (2018), 55 the dead time correction takes the form,

m = n exp (−nτ) , (2.1) where m is the measured count rate in units of s−1, n the true event rate in units of s−1, and τ the dead time given by,

τ = max{A log m + B, 0}. (2.2)

The coefficients A and B are determined from the data by comparing signals between molecular fragments at different counting regimes (Benna and Elrod, 2018). We use dead time coefficients A = 9.49 × 10−9 s and B = −1.39 × 10−7 s. Correcting for the detector dead time allows us to use count rates up to 2 × 107 s−1. The NGIMS data contain signal due to atmospheric species, background signal due to desorption of gases from the inner surfaces of the instrument, and background signal due to collisions in the quadrupole mass filter. The background signal is typically 3 to 4 orders of magnitude less than the atmospheric signal at periapsis, but accurate subtraction of the background extends the useful altitude range of the atmospheric signal. For the background signal due to desorption of gases from the inner surfaces of the instrument, we employ a simple approach and remove the mean of the first 50 s of the dead time corrected count rate at each relevant m/z value. The count rates and calculated background signals for relevant channels on a DD2 periapse pass can be found in Figure 2.2. We limit our analysis to measurements from the inbound leg of each periapse pass due to variation in instrument background levels. This variation is due to an increase in the rate of desorption of gases from the inner surfaces of the spectrometer, which becomes significant during the outbound portion of each periapse pass. This is illustrated in Figure 2.2. At high atmospheric densities (i.e., near periapsis, especially during DDs) gas densities inside the spectrometer can increase to the point that collisional scattering of ions in the mass filter leads to an increase of instrument background levels across all channels. The mass spectrum in Figure 2.3 shows the scattering background signal at m/z = 35 and m/z ≥ 49 during a DD2 periapse pass. The scattering 56

1011

1010

109

108

) 107 -1

106

105

Count Rate (s 10

103

102

101

100 -800 -600 -400 -200 0 200 400 600 800 TCA (s)

Figure 2.2: Instrumental background subtraction and the use of proxy channels. The count rates used to calculate densities of Ar (greens), CO2 (reds), and N2 (blue) on DD2 orbit 1060 are shown prior to background subtraction plotted against time since closest approach (TCA). The Ar profile is constructed from signal at m/z = 40. The dark green points are measurements with nominal instrument tuning. In order to avoid detector saturation, measurements are also taken with the instrument slightly detuned, and these are shown as the light green points. The CO2 profile is constructed from signal at m/z = 44 (dark red), m/z = 45 (red), and m/z = 13 (pink). The N2 profile is constructed from signal at m/z = 14. The calculated background signal for the Ar (dashed line), CO2 (solid line), and N2 (dotted line) profiles is also shown.

background can be removed by observing signal ﬂuctuations in certain m/z channels that do not correspond to any atmospheric species or fragments of atmospheric species and otherwise have low intrinsic background levels. In this work, we use m/z = 35 for this purpose. Using the signal in the m/z = 35 channel and empir- 57

108

) 7

-1 10

106

105

Mean Count Rate (s 10

103 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 40* z m ⁄ Figure 2.3: An NGIMS mass spectrum for DD2 orbit 1060. The mean count rate for each channel is taken over a time period of 10 minutes centered about periapsis. The m/z = 35 channel (blue) is used to calculate the scattering background. The signal in channels colored purple is also due to the scattering background. The channels colored green are used to calculate Ar, CO2, and N2 densities as discussed in Section 2.2.1. The m/z channel denoted 40* is detuned m/z = 40 as discussed in Section 2.2.1. ically derived formulas, the scattering background can be calculated for each m/z value (Benna and Elrod, 2018). The contribution from this scattering background is then removed from the dead time corrected count rates. It is also necessary to correct detector count rates for attenuation of the electron beam used to ionize incoming atmospheric neutrals (Benna and Elrod, 2018). The electron beam is attenuated by the electric field produced by ions traveling through the spectrometer. This leads to an effective decrease in the sensitivity of the instrument. The electron beam attenuation becomes significant at high atmospheric densities, as ion densities in the spectrometer become large. Densities are constructed from NGIMS measurements of count rates in channels corresponding to molecular ions or ion fragments of the parent neutral molecule. High in the atmosphere we use the channel corresponding to the primary ion, 58

12 16 + 40 + m/z = 44 for CO2 and m/z = 40 for Ar, which correspond to C O2 and Ar , 14 + respectively. For N2, the primary ion is N2 at m/z = 28, but this channel 12 16 12 16 also contains contributions from C O2 fragmentation and from C O (both as 12 16 + 14 + C O ); therefore, we use m/z = 14 ( N ) to determine the N2 density. A different approach is needed deeper in the atmosphere because the detector reaches saturation in the channels corresponding to the primary ions at count rates above 7 −1 2 × 10 s . For CO2, when the detector reaches saturation in m/z = 44, channels 45 and 13 are scaled to m/z = 44 to extend it beyond a count rate of 2 × 107 s−1. 13 16 + 13 + The m/z = 45 and 13 channels are dominated by C O2 and C (a fragment 13 of CO2), respectively. These two proxy channels track the atmospheric CO2 density as m/z = 44 does but, due to the relatively low abundance of 13C, measured count rates in channels 45 and 13 are significantly lower than that of m/z = 44. The m/z = 13 channel is only required when the detector reaches saturation in m/z = 45, which typically only occurs during DDs. The m/z = 45 and 13 channels, 12 16 once scaled to m/z = 44, may differ from the real number of C O2 ions that reach 12 13 the detector because of the small difference in the scale heights of CO2 and CO2 above the homopause. In principle, using m/z = 12 in place of m/z = 45 or 13 would eliminate this error, but the detector quickly reaches saturation in m/z = 12 12 12 + due to fragmentation of CO2 into C , so it is not used. The error introduced in this step is much smaller than systematic uncertainties in temperatures derived from CO2 densities discussed below. To scale a proxy channel to a saturated channel, ratios of the two channels are calculated by fitting a line to the count rate of the proxy channel as a function of the saturated channel for the inbound and outbound portions of the pass. A linear fit is then made to these two ratios to produce a scaling factor for the proxy channel as a function of time. Figure 2.2 depicts the result of this stitching procedure for m/z = 44, 45, and 13 for CO2 and 40 for Ar on DD2 orbit 1060. An m/z = 28 to m/z = 14 fragmentation pattern of 3.47 ± 0.42% enables the calculation of N2 densities from m/z = 14 and was obtained from six in-flight measurements of a calibration gas having known composition, which al- 14 14 + low us to investigate the fragmentation of N2 into N without interference from 59 other species like 12C16O+. The detector does not reach saturation in m/z = 14 for the observations discussed here and the N2 density is determined solely from this channel. For Ar, when the detector reaches saturation in m/z = 40 at optimal instrument tuning, measurements are also taken with the instrument slightly detuned by adjusting ion focusing lens voltages in the spectrometer (Mahaffy et al., 2015b). Lastly, we calculate atomic oxygen densities using m/z = 32, which corresponds 16 + to O2 . When m/z = 32 reaches saturation during DDs, measurements are also taken with the instrument slightly detuned, as with m/z = 40 for Ar. O densities + are calculated from the signal in an m/z channel which measures O2 ions because atmospheric O recombines rapidly on the walls of the spectrometer to form O2 and atmospheric O2 abundances are negligible in comparison to that produced by this recombination. It is assumed here that the O abundance is exactly twice the measured O2 abundance, implying complete recombination of atmospheric O into O2 inside the spectrometer and negligible contribution from atmospheric O2. Spectrometer sensitivities used to calculate densities from detector count rates are reported in Table 1 of the Supporting Information of Mahaffy et al. (2015a). All densities are corrected for the closed source enhancement using the method of Horowitz and LaGow (1957) as discussed by Mahaffy et al. (2015a). Densities calculated for orbits beyond 748 are divided by a factor of 1.5331 to account for an observed change in the sensitivity of the instrument following DD1 due to detector gain stabilization after exposure to high atmospheric densities encountered during the DD (Benna and Elrod, 2018). This sensitivity change was discovered during a comparison of NGIMS densities with atmospheric densities derived from data obtained by the MAVEN Accelerometer Experiment (ACC, see Zurek et al. (2015)). The change in sensitivity does not affect derived temperatures since it only alters the magnitude of a density profile, not the slope. Atmospheric densities are corrected for velocity ram effects that arise from the interaction of the spacecraft body with the atmosphere while traveling at 4 km s−1. This interaction increases atmospheric density in front of the spacecraft, artificially increasing measured densities, and decreases molecular velocity in front of the space- 60 craft, which also artificially increases measured densities by curtailing the closed source enhancement factor discussed in the preceding paragraph. Thus, the corrections for these effects decrease the measured density. These spacecraft ram effects become significant at high atmospheric densities, but correction factors have been developed that remove the effects from measured densities (Benna and Elrod, 2018). Figure 2.4 depicts the magnitude and density dependence of these correction factors and the electron beam attenuation correction factor discussed earlier in this section.

Correction Factor 0.75 0.8 0.85 0.9 0.95 1 1.05 1.1 1.15 1.2 260 CO Density 250 2 SC Ram Correction 240 SC Velocity Correction Attenuation Correction 230

220

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Altitude (km) 180

170

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130 106 107 108 109 1010 1011 Density (cm -3)

Figure 2.4: Density correction factors. (bottom axis) CO2 density (red) for DD2 orbit 1060 after correction for ram eﬀects. (top axis) The spacecraft ram (green), spacecraft velocity (blue), and electron beam attenuation (orange) correction factors for the CO2 density proﬁle. 61

These corrections are important for the analysis presented here because they correct the slope of measured density proﬁles and thus aﬀect the temperatures we derive from them.

2.2.2 Random Uncertainty

NGIMS measurements are also subject to uncertainties due to counting statistics. To determine these errors, we adopt an empirical approach and analyze count rates from 69 apoapse passes during which MAVEN is far from the Martian atmosphere and NGIMS background levels are relatively stable. For each pass, a linear fit was made to each of the count rates measured for m/z channels 12, 14, 16, 20, 22, 28, 30, 32, 44, 45, and 46. The standard deviation of the data about this fit was taken as the random uncertainty in the measurements. Using data from many different channels allows us to measure the uncertainty over a wide range of count rates. The standard deviations from each channel during each apoapse pass were fit in aggregate to obtain a formula for the random uncertainty at a given count rate,

σ = 6.54 · S0.51 s−1 (2.3)

where σ is the uncertainty and S the count rate, both in units of s−1. The power of 0.51 is close to the 0.5 expected from counting statistics. Figure 2.5 shows the random uncertainty in each channel for each of the apoapse passes versus count rate for that channel and the resultant fit to that data. At the smallest count rates, which correspond to 1, 2, or 3 measured counts per 27 ms integration period, the residuals between the data and the fit are biased positive. We exclude such small count rates prior to calculating densities and temperatures. The random uncertainty at all count rates is so small that it plays little role in the analysis that follows. The intrinsic variability of the atmosphere and systematic errors in the determination of densities are both more significant. 62

105

104

103 ) -1 (s

102

101

100 100 101 102 103 104 105 106 107 108 Count Rate (s -1)

Figure 2.5: Random uncertainty in NGIMS measurements. The uncertainty calculated from 11 channels over 69 apoapse passes (red +) and the resultant ﬁt (black line).

2.2.3 Temperature Derivation

The 3 species investigated here, Ar, CO2, and N2, are chemically inert with vertical distributions determined by hydrostatic equilibrium. We expect diffusive equilibrium in the thermosphere, with the altitude profile of each species determined by its mass. Although it is possible that vertical mixing via eddy diffusion could alter this distribution near the base of the thermosphere, we show below that this is not the case for the measurements discussed here. Assuming hydrostatic and diffusive equilibrium, we use the method of Snowden et al. (2013) to derive temperatures from 63

1 the vertical Ar, CO2, and N2 density proﬁles. First, the local partial pressure is calculated from the Ar, CO2, or N2 density by integrating the equation of hydrostatic equilibrium downward from the upper boundary, Z r GMmi 0 Pi = Pu,i + Ni 02 dr , (2.4) ru r where Pi, Pu,i, Ni, and mi are the partial pressure, partial pressure at the upper boundary, number density, and mass of the ith species, respectively, r is the distance from the center of the planet, ru the distance from the center of the planet to the upper boundary, G the gravitational constant, and M the mass of Mars. Then, temperature is calculated from the partial pressure using the ideal gas law,

Pi Ti = , (2.5) Nik

where Ti is the temperature of the ith species and k the Boltzmann constant. The temperature and pressure at the upper boundary are established by ﬁtting the density at high altitudes, assuming isothermality, to an equation of the form, GMmi 1 1 Ni = N◦,i · exp − , (2.6) kTi r r◦

where N◦,i is the density of the ith species at the lower boundary of the ﬁtted

region and r◦ the distance from the center of the planet to the lower boundary of the ﬁtted region. We use measurements between densities of 104 to 4 × 105 cm−3,

7 8 −3 5 6 −3 10 to 10 cm , and 8 × 10 to 8 × 10 cm for Ar, CO2, and N2, respectively, to perform the fitting procedure that determines the upper boundary. Thermal conduction dominates high in the thermosphere, ensuring that the atmosphere is isothermal. Only waves, discussed in more detail below, can disturb this isothermal state. This fitting procedure results in isothermal temperatures that can be seen at the top of temperature profiles throughout the analysis below. Using this approach, we calculate temperatures from vertical variations in the Ar, CO2, and N2 densities for each MAVEN orbit. Figure 2.6 shows an example of a temperature profile for a single orbit. 1Methods similar to that outlined here have been used since at least the 1950s to determine atmospheric temperature from density or pressure (Newell, 1953; Elterman, 1953; Minzner et al., 1964, 1965; Minzner, 1965; Theon and Nordberg, 1965; Minzner and Sauermann, 1966). 64

Temperature (K) 150 175 200 225 250 275 300 260

250

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Figure 2.6: The temperature derived for a single orbit. (bottom axis) Ar density (red) for DD2 orbit 1060. (top axis) The temperature (blue) derived from the Ar density profile. The noise level in the density and temperature is apparent only above ∼210 km as ∼5 K fluctuations in the temperature that gradually increase in magnitude with increasing altitude. The isothermal temperature at the top of the profile is a result of the fitting process described by Equation 2.6 and the accompanying text.

Pervasive wave activity is apparent in the temperature profile shown in Figure 2.6 and is present on the majority of orbits with what appear to be random phases and varying amplitudes. This pervasive wave activity prevents the analysis of single profiles in terms of energy sources and sinks in the atmosphere, which is our goal here. Averaging a number of sequential passes together removes most of the wave- 65 like signatures and results in smoother, classical thermospheric profiles. An example of this is shown in Figure 2.7.

106 277

107 240 ) -3

108 204 Density (cm 2 CO 109 170 Mean Approximate Altitude (km)

1010 130 150 200 250 300 350 400 Temperature (K)

Figure 2.7: The eﬀect of averaging temperature proﬁles to remove wave activity. A bin (bin 16) of Ar temperatures (color +) and the mean temperature (black line) for the bin are shown. Average approximate altitudes for the mean temperature are given on the right axis.

To produce average temperatures, a group of temperatures derived from individual orbits are binned on CO2 density rather than altitude, as density is more physically meaningful. Changes in the thermal structure of the atmosphere, either local or nonlocal (e.g., in the region below that sampled by NGIMS), can move density levels up or down in altitude. Further, atmospheric density governs the optical thickness of the atmosphere to solar radiation which drives heating and photochemical processes. Therefore, more direct comparisons can be made between temperature 66

proﬁles by using density as the vertical coordinate. Additionally, the CO2 density is a convenient variable since it is directly measured by NGIMS and is the most abundant species in the Martian atmosphere, though atomic oxygen does become

more abundant than CO2 high in the thermosphere. Density bins that contained just one measurement were discarded. Mean approximate altitudes were calculated for these average temperature proﬁles by ﬁrst calculating a mean periapsis altitude

at the mean periapsis CO2 density using measurements from each orbit in the bin, then integrating upward using the mean temperature profile and assuming hydrostatic equilibrium to give the mean approximate altitude profile. Thermospheric gradients are derived from the mean temperature profiles by fitting the data below the roughly isothermal region with an equation of the form,

dT T (z) = T + (z − z ) , (2.7) ◦ dz ◦ where z is altitude, T◦ and z◦ are the temperature and altitude at periapsis, respectively, and dT /dz is the thermospheric gradient. In the atmospheric regions studied here, the thermosphere and lower exosphere, we expect Ar, CO2, and N2 to have equal temperatures. The high collision rates and the rapid interchange of molecules between upper and lower regions ensure equipartition of energy. The only exceptions to this are species that are subject to strong chemistry that provides them with additional energy (e.g., atomic oxygen on Mars (Deighan et al., 2015)) or are subject to strong loss of energy through rapid escape (e.g., H2 on Titan (Cui et al., 2008)). These exceptions do not apply to

Ar, CO2, or N2 on Mars, so we assume that they have the same temperature. The

Ar, CO2, and N2 profiles in Figure 2.8 are in excellent agreement at low altitude and have similar shapes, but differ by tens of kelvins at the highest altitudes. The agreement at low altitude confirms that the atmosphere is diffusively separated at these levels. The disagreement between Ar and CO2 temperatures at high altitude

is likely related to adsorption of CO2 on the inner surfaces of the spectrometer.

This process causes a decrease in measured CO2 density on inbound trajectories at high altitudes when the inner surfaces of the spectrometer are relatively clean, but 67

106 Ar CO 2 N 2 107 ) -3 108

Density (cm 9

2 10 CO

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1011 120 140 160 180 200 220 240 260 280 Temperature (K)

Figure 2.8: Comparison of average DD2 Ar (red), CO2 (blue), and N2 (green) temperatures with no horizontal correction.

disappears as the surfaces become saturated with CO2 as the spacecraft moves to lower altitudes. The ∼5 K diﬀerence between the Ar and N2 temperature at high altitude is not understood. Given that it is chemically inert and has the lowest background signal (Figure 2.2), we adopt the Ar temperatures as representative of the atmosphere and rely exclusively on those in the analysis that follows.

2.2.4 Horizontal Correction

Temperatures are derived from vertical variations in the density according to the equations of hydrostatic equilibrium, but MAVEN also moves horizontally with respect to Mars as it descends through the upper atmosphere, as shown in panel D of Figure 2.1. NGIMS measurements are thus a combination of both vertical and 68

horizontal variations in the density. Horizontal motion is most significant near periapsis and horizontal density variations may be important throughout each periapse pass. Horizontal density gradients are apparent in the data as asymmetries about periapsis, as seen in Figure 2.9. Individual orbits have too much wave activity to permit identification of horizontal density gradients on a pass-by-pass basis. This variability in the density, both within an orbit and from one orbit to the next, can be seen in Figure 2.9. It is necessary to bin sequential orbits to meaningfully fit observed horizontal variations. Orbits were binned for this purpose according to the similarity of their local times, latitudes, solar zenith angles, and altitudes at periapsis. Tolerances for this binning procedure are set such that within each bin periapsis altitudes differ by less than 5 km, periapsis local times differ by less than 1 hour, the cosines of periapsis latitudes differ by less than 0.1, and the cosines of periapsis solar zenith angles differ by less than 0.1. Orbits which would have been in bins by themselves according to the binning tolerances were merged into the preceding bin. Using this procedure a total of 183 bins were constructed from 4231 orbits. It was necessary to manually arrange DDs 1, 4, 5, 6, and 7 into their own bins for a separate analysis due to orbital corrections which were made during each of the DDs and which significantly changed periapsis altitude. An example of the smoothing that results from binning six individual profiles is shown in Figure 2.9. The large perturbations disappear and a clear inbound/outbound gradient is apparent. The small residual perturbations resulting, we assume, from imperfect cancellation of the waves define the noise level of these mean profiles. The goal of this work is to analyze vertical density gradients, not the horizontal gradients; thus, we have developed a technique to correct for the latter to uncover the former. The densities in each bin were first fit in aggregate with an equation of the form, dN z N(s, z) = N + s exp − , (2.8) ◦ ds H where N is the number density, N◦ the number density at periapsis, s the change in horizontal distance measured from periapsis, dN/ds the density derivative with 69

respect to s, z is altitude, and H the density scale height. The free parameters in the

ﬁt are H, N◦, and dN/ds. We considered data within a horizontal range of 1000 km centered about periapsis. An example of this ﬁtting procedure for a bin of orbits is shown in Figure 2.9. The horizontal density gradients are shown in Figure 2.10.

Once dN/ds is obtained, a horizontal correction factor r is calculated,

1 dN r(s) = 1 + s, (2.9) N◦ ds

107 9

7 )

-3 6

4 Ar Density (cm

1 -500 -400 -300 -200 -100 0 100 200 300 400 500 Horizontal Distance (km)

Figure 2.9: Ar densities (color +) near periapsis for a single bin of orbits (bin 16) and the ﬁt to the color crosses (black line) which determines the horizontal density gradient, dN/ds. The mean Ar density taken over horizontal distance is also shown (black circles). Periapsis is set to s = 0 km. 70

and the corrected density Nc is given by

N(s, z) N (z) = . (2.10) c r(s)

Pressures and temperatures are then derived from the corrected density by the method discussed in Section 2.2.3. Orbits for which the horizontal correction factor exceeded a maximum of a factor of two are not included in the analysis below. A total of 305 orbits in 23 bins were excluded in this manner.2

2The original publication, Stone et al. (2018), reported 794 orbits in 30 bins were excluded in this manner. This was an accounting error.

10-3 1

0.8

0.6

0.4

) 0.2 -1

(km 0 s N d d ∘ 1

N -0.2

-0.4

-0.6

-0.8

-1 0 1000 2000 3000 4000 5000 6000 Orbit

Figure 2.10: The horizontal density gradient normalized by the ﬁtted density at closest approach, 1/N◦ × dN/ds, as a function of each MAVEN orbit. The procedure used to obtain these values is described in Section 2.2.4. 71

Figure 2.11 shows Ar densities for bin 16 before and after the horizontal correction has been applied. The effect of the horizontal correction is evident as a change in slope, which produces a modest change in the derived temperatures shown in Figure 2.12. Compared to the uncorrected temperature profiles in Figure 2.7, the corrected temperature profiles in Figure 2.12 are systematically cooler. In Fig- ure 2.9, the horizontal gradient present in the data, which is corrected for in Fig- ure 2.11, can be observed as a shift in the peak density from s = 0 km (periapsis) to s = −50 km and as an overall slope in the average density profile: the average density is ∼2 × 107 cm−3 at −500 km and ∼107 cm−3 at 500 km. Since the density peaks on the inbound side of periapsis (negative horizontal distances), dN/ds is negative. If the spacecraft encounters a horizontal density gradient in the opposite sense relative to the direction the spacecraft is traveling, i.e. the peak in average density is shifted to the outbound side of periapsis, then that positive value of dN/ds will lead to artificially cooler temperatures if not corrected for. We have found that the horizontal density gradient derived for each bin of orbits correlates with the direction the spacecraft is moving relative to the terminator or, in other words, the horizontal density gradient is proportional to the derivative of SZA with s, as can be seen in Figure 2.13. This indicates that the horizontal density gradients arise generally from the day-night temperature gradient. As mentioned above, the noise level of mean profiles is defined by small residual perturbations of ∼10 K, which remain in the mean profiles due to imperfect cancellation of the nearly random wave activity. This systematic uncertainty and the intrinsic variability of the atmosphere are much larger than the random uncertainty from counting statistics (see Section 2.2.2), which amounts to a few percent at the highest densities. One consequence of this is that it is not possible to assign uncertainties to individual data points, though 1-σ variabilities can provide useful information when discussing mean temperature profiles. Thus, we write T ± δT , where T is the mean temperature and δT is the standard deviation of the variability. This distinction is important because the mean can be precisely defined, given a large enough sample size, even if there is large variability within the group of ob- 72

106

107 ) -3

108 Density (cm 2 CO

109

1010 104 105 106 107 108 Ar Density (cm -3)

Figure 2.11: The eﬀect of the horizontal correction on a bin of inbound Ar densities. A bin (bin 16) of Ar densities prior to the application of the horizontal correction (reds) and after the application of the horizontal correction (blues).

servations used to calculate the mean. These variabilities are added in quadrature where necessary for their propagation. The uncertainties reported for thermospheric gradients are 95% conﬁdence intervals for the ﬁt parameter dT /dz (Equation 2.7).

2.3 Results and Discussion

We have produced high resolution Ar, CO2, and N2 temperature profiles of the Martian upper atmosphere for 4231 MAVEN orbits using data from NGIMS. Mean DD temperature profiles allow us to characterize the thermospheric gradient and provide estimates of the diurnal variation in the exosphere. Temperature profiles 73

106 270

107 234 ) -3

108 200 Density (cm 2 CO 109 168 Mean Approximate Altitude (km)

1010 133 150 200 250 300 350 400 Temperature (K)

Figure 2.12: The eﬀect of the horizontal correction on a bin of Ar temperatures. A bin (bin 16) of Ar temperatures (color +) subsequent to the application of the horizontal correction and the mean temperature (black line) for the bin are shown. The mean uncorrected (black dash-dot) temperature from Figure 2.7 is provided for comparison. Average approximate altitudes for the mean corrected temperature are given on the right axis. from nominal MAVEN orbits are used to probe the diurnal and latitudinal variation

6 9 −3 of the exospheric temperature between CO2 densities of 10 and 10 cm . We then compare NGIMS temperatures to previous in situ and remote sensing measurements and predictions of a 1D model.

2.3.1 Deep Dip Temperatures

DDs probe to ∼125 km, much deeper into the Martian atmosphere than nominal orbits, which only penetrate to about 150 km. The Martian thermosphere is isothermal above 150 km, so DDs are an opportunity for NGIMS to measure the charac- 74

10-3 1

0.8

0.6

0.4

) 0.2 -1

(km 0 s N d d ∘ 1

N -0.2

-0.4

-0.6

-0.8

-1 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 d(SZA) (degrees km-1) ds Figure 2.13: The horizontal density gradient normalized by the ﬁtted density at periapsis, 1/N◦ × dN/ds, plotted as a function of the derivative of solar zenith angle with horizontal distance covered, d(SZA)/ds. teristic thermospheric temperature rise that occurs below 150 km. As mentioned in the Introduction, latitude and local time at periapsis are roughly constant during each DD, but the rotation of Mars below MAVEN means that many longitudes are sampled over the duration of these low-altitude excursions. Therefore, DD averages of the temperature are most appropriately considered longitudinal averages.

Figure 2.14 shows average temperature proﬁles for each of the 8 DDs. In MAVEN planning, the DDs were chosen to sample a variety of latitudes and local times, targeting the subsolar point, antisolar point, and dawn and dusk terminators, as can be seen in Table 2.1. Mean daily spectral irradiances for wavelengths ≤ 90 nm 75

106 DD6

7 DD3 ) 10

-3 DD5 DD7 8 10 DD8 DD4 109 DD1

Density (cm Density DD2 2

CO 1010

1011 50 100 150 200 250 300 Temperature (K)

Figure 2.14: Mean temperatures for ﬁrst the 8 DDs. The shaded regions represent 1-σ variabilities. from the Flare Irradiance Spectral Model-Mars (FISM-M) (Thiemann et al., 2017)

7 9 −3 and the mean isothermal temperatures between CO2 densities of 10 to 10 cm for each DD are also shown in Table 2.1. The FISM-M spectral irradiances were obtained from the MAVEN Extreme Ultraviolet Monitor (EUVM) Level 3 daily version 10, revision 1 data files (Eparvier et al., 2015). DD2 occurred near the subsolar point and is the warmest DD, while DD6 occurred near the antisolar point and is the coldest. The comparison of mean temperature profiles from these two DDs provides an estimate of the magnitude of the 7 diurnal variation of the temperature at the equator. At CO2 densities between 10 to 109 cm−3, in the isothermal region of the atmosphere, the DD2 temperature is 260 ± 7 K and the DD6 temperature is 127 ± 8 K. This establishes a diurnal variation between the subsolar and antisolar point of 132 ± 11 K, or about a factor of two, though it must be noted that the EUV irradiance short of 90 nm measured at Mars during DD6 is 30% smaller than that measured during DD2. Model studies have indicated that the Martian exospheric temperature depends linearly on the solar EUV flux (Bougher et al., 2009; González-Galindo et al., 2009b). 76 8 5 7 8 7 7 7 10 (K) ± ± ± ± ± ± ± ± d iso 194 173 127 135 220 129 260 232 T c ) 1 − 4 4 3 3 3 3 3 3 densities − − − − − − − − 2 nm 10 10 10 10 10 10 10 10 2 × × × × × × × × − 8.60 8.93 1.18 1.23 1.21 1.31 1.67 1.95 (W m EUV irradiance ° ° ° ° ° ° ° ° S L (h) b 3.5 11.4 0.7 194.1 5.2 166.9 13.7 76.3 20.3 49.4 16.0 37.5 11.9 328.6 18.3 291.1 LTM ° ° ° a ° ° ° ° ° Values are means at periapsis over each DD unless otherwise noted. variability. σ Mean daily spectral irradiance at Mars for wavelengths c S 91.1 S 110.4 N 25.0 N 87.0 N 96.5 N 109.1 S 166.4 S 9.3 ° ° ° ° ° ° ° ° Mean temperature in the isothermal region between CO d Local time. b with associated 1- 3 − 714 – 747 42.6 5909 – 5950 18.9 5574 – 5620 63.6 3551 – 3586 2.9 3285 – 3327 33.2 1802 – 1838 63.9 1501 – 1538 62.6 1059 – 1086 3.8 cm 9 to 10 7 4 3 2 1 8 7 6 5 90 nm from FISM-M. Solar zenith angle. a ≤ Deep Dip Orbits Latitude SZA of 10 Table 2.1: MAVEN Deep Dip Ephemeris. 77

Comparison of DDs 3 and 4 provides a measure of the diurnal variation of the temperature in the upper atmosphere at higher latitudes, as both DDs occurred at roughly 60°S, but nearly twelve hours apart, at 4 a.m. and 4 p.m., respectively. During DD4, temperatures in the isothermal region reach 220 ± 6 K on the dayside, while during DD3 temperatures only reach 129 ± 7 K in this region on the nightside. Thus, we observe a temperature diﬀerence between 4 a.m. and 4 p.m. at 60°S of 91 ± 10 K. The solar EUV irradiance short of 90 nm is similar for DDs 3 and 4 since they were executed just 2 months apart. DDs 3, 5, and 6 occurred on the nightside of the planet around 4 a.m., 5 a.m., and 12 a.m. local time, respectively. Little variation in the temperature between these nightside DDs is observed, despite the fact that they span latitudes from 33°N to 64°S and roughly 180° in LS. The nightside DD temperature proﬁles are nearly isothermal over the entire vertical region sampled by NGIMS. For example, during DD6, the temperature increases from 92 ± 16 K at periapsis to just 122 ± 34 K near

7 −3 a CO2 density of 10 cm . There is wide variation among and within the 4 dayside DDs 1, 2, 4, and 8, which were executed around 6 p.m., 12 p.m., 4 p.m., and 2 p.m. local time, respectively. DDs 8, 4, and 1, in that order, show a gradual increase in temperature of about 38 ± 12 K from 2 p.m. to 6 p.m. in the midlatitudes, though the relatively high solar EUV irradiance during DD1 must be taken into account. The two warmest

DDs, 1 and 2, occurred shortly after perihelion (LS = 251°), which helps to explain why DD1, executed at 43°N in northern Winter, is warmer than DD4, which was executed at 64°S in southern Autumn. The mean daily EUV irradiance short of 90 nm for DD4 is just 63% of that for DD1 (Table 2.1). DD7, executed around 8 p.m. local time, is the only DD to occur in the late evening hours. Further, mean daily EUV irradiance during DD7 is 46% of that of DD1, which was executed around 6 p.m. local time. As a result, the DD7 temperature profile is intermediate between those of the warmer dayside DDs and the cooler nightside DDs. The characteristic thermospheric temperature gradient is well characterized in the warmer DD temperature profiles. The thermospheric gradient can only be fully 78 observed in NGIMS DD profiles since MAVEN does not descend low enough into the thermosphere on nominal orbits to completely traverse this critical region. The observed rise in temperature with altitude in the lower thermosphere (at CO2 densities greater than ∼109 cm−3) is a result of the fact that this region is optically thick to most solar EUV radiation, which is thus absorbed leading to a rise in temperature.

9 −3 Between periapsis and a CO2 density of 10 cm , the thermospheric gradients for the warmer DDs (in order of increasing isothermal temperature) 7, 8, 4, 1, and 2 are 1.33 ± 0.16, 2.18 ± 0.21, 2.49 ± 0.19, 1.72 ± 0.10, and 2.69 ± 0.33 K km−1, respec-

11 11 −3 tively. Near the mesopause, at CO2 densities of 4 × 10 to 5 × 10 cm , the mean temperatures of all 8 DDs are constrained between 92 ± 16 K (DD6) and 137 ± 23 K (DD2).

2.3.2 Exospheric Temperature Variations

Figure 2.15 shows the diurnal variation of the temperature in the upper at-

6 10 −3 mosphere of Mars between CO2 densities of 10 to 10 cm . The temperatures represent the average in a given local time and altitude bin over measurements for any longitude, LS, and latitude between 60°N and 60°S. From this data, it can be seen that the thermosphere begins to warm at 5 a.m. and quickly reaches temperatures over 200 K. A peak temperature of 249 ± 11 K is reached around 3 p.m. at

7 −3 a CO2 density of 10 cm . The atmosphere then rapidly cools to 159 ± 43 K by 11 p.m. at the same density level, dropping below 100 K close to the mesopause.

Figure 2.16 shows this diurnal variation of the temperature at two constant CO2 density levels, 106 and 109 cm−3. It is clear that the thermosphere is systematically

6 −3 9 −3 warmer at a CO2 density of 10 cm than it is at 10 cm . At a CO2 density of 106 cm−3, the temperature rises rapidly from 132 ± 39 K at midnight to 249 ± 11 K

9 −3 around 3 p.m. Similarly, at a CO2 density of 10 cm , the temperature rises rapidly from 132 ± 24 K at midnight to 215 ± 12 K around 3 p.m. Thus the magnitude of

6 −3 this diurnal variation is 117 ± 40 K at a CO2 density of 10 cm and 81 ± 27 K at 109 cm−3.

The latitudinal variation of the temperature on the dayside of Mars at two CO2 79

106 300

250 107 ) -3 200

108

Density (cm 150 2 Temperature (K) CO

109 100

1010 50 0 4 8 12 16 20 24 Local Time (h)

Figure 2.15: Ar temperature (in color) binned as a function of CO2 density (vertical axis) and local time (horizontal axis). White bins signify no data. Measurements are constrained to latitudes between 60°N and 60°S. density levels is shown in Figure 2.17. Measurements used to construct these latitudinal proﬁles were constrained to local times between 9 a.m. and 5 p.m. MAVEN does not dip low enough into the Martian upper atmosphere at the poles for NGIMS to collect density measurements there. Therefore, our analysis is constrained to latitudes between 80°N and 80°S. As can be seen in Figure 2.16, the thermosphere 6 −3 9 −3 is systematically warmer at a CO2 density of 10 cm than at 10 cm in Fig- ure 2.17. Higher in the thermosphere, the diﬀerence in the temperature between the equator and the poles is 39 ± 17 K, from 210 ± 14 K near the poles to a mean of 248 ± 9 K on average between 10°N and 10°S. Though there is more noise in the data at 109 cm−3, similar variation is observed lower in the thermosphere, as temperature increases from 173 ± 12 K near the southern pole to 204 ± 8 K on average between 80

10°N and 10°S, a diﬀerence of 31 ± 14 K. However, with the level of noise present in the NGIMS data with current sampling in latitude (see panel C in Figure 2.1), it is diﬃcult to ascertain the variation of the temperature with latitude.

2.3.3 Comparisons with Previous NGIMS Temperatures

Initial mean DD1 and DD2 temperature proﬁles and exospheric scale height temperatures from NGIMS were reported by Mahaﬀy et al. (2015a) and used to investigate the variation of the temperature with SZA. Initial mean DD2 temperature

280 106 cm-3 260 109 cm-3

240

220

200

180

Temperature (K) Temperature 160

140

120

100 0 4 8 12 16 20 24 Local Time (h)

Figure 2.16: Ar temperature as a function of Martian local time at two 6 −3 9 −3 constant CO2 density levels: 10 cm (red) and 10 cm (blue). Mea- surements are constrained to latitudes between 60°N and 60°S. The shaded regions represent 1-σ variabilities. 81

profiles have also been compared with simulated temperatures from the Mars Global Ionosphere-Thermosphere Model (M-GITM) (Bougher et al., 2015b,c). The densities and temperatures initially reported did not include the scattering background subtraction described in Section 2.2.1, the spacecraft ram and electron beam attenuation corrections shown in Figure 2.4 and discussed in Section 2.2.1, or the horizontal correction discussed in Section 2.2.4. These corrections have substantially refined the reduction of NGIMS data and the derivation of temperatures from NGIMS densities since the initial reports by Mahaffy et al. (2015a) and Bougher et al. (2015b). Further, two additional years of NGIMS data have enabled a more

300 106 cm-3 109 cm-3 280

260

240

220

Temperature (K) Temperature 200

180

160

140 80°S 60°S 40°S 20°S 0° 20°N 40°N 60°N 80°N Latitude

Figure 2.17: Ar temperature as a function of latitude at two constant 6 −3 9 −3 CO2 density levels: 10 cm (red) and 10 cm (blue). Measurements are constrained to local times between 9 a.m. and 5 p.m. The shaded regions represent 1-σ variabilities. 82 thorough investigation of the variation of the temperature with important geophysical variables such as local time and latitude that has been presented in the previous sections. An extensive comparison of IUVS dayglow and NGIMS temperatures over 7 periods from 2015 to 2016 was carried out by Bougher et al. (2017b). The authors found good agreement between NGIMS and IUVS temperatures in the 150 to 180 km altitude range over the 7 sampling periods selected for SZAs less than 75° within that altitude range. Table 2.2 compares the mean NGIMS Ar temperatures calculated by Bougher et al. (2017b) and from this work. The emission and spacecraft ram correction factors had not been implemented in the NGIMS Level 2 data products used by Bougher et al. (2017b), therefore some differences should be expected between the temperatures derived in that work and those derived here. Further, the temperatures calculated by Bougher et al. (2017b) are not corrected for the horizontal motion of the spacecraft. Despite these discrepancies, the NGIMS temperatures derived by Bougher et al. (2017b) generally agree well with the temperatures we have derived here. The biggest difference between our temperatures and those of Bougher et al. (2017b) occurs in the bin of orbits 3165 to 3192, where our mean temperature is 32.1 ± 40.1 K warmer than the mean temperature of Bougher et al. (2017b). Since the same data is used to produce the temperatures reported in this work and in Bougher et al. (2017b), the difference in the mean values must be due to a difference in processing. We observe large horizontal density gradients during this period, which have a relatively large effect on derived temperatures. Using temperatures derived from densities that have not been corrected for the observed horizontal gradients, we calculate a temperature of 180.0 ± 29.5 K for this bin, which is closer to the 173.6 ± 21.6 K calculated by Bougher et al. (2017b).

2.3.4 Comparisons with Other Observations

Comparisons between MAVEN NGIMS observations and past in situ and remote sensing observations are complicated by variations in solar activity and the helio- centric distance of Mars, changing seasons, and diﬀerences in spatial and temporal 83

Table 2.2: Temperature Comparison with Bougher et al. (2017b). Temper- atures are means between 150 and 180 km altitude and σ is the standard deviation of the variability.

a b a b Orbits T Ar (K) T Ar (K) σ (K) σ (K) 865 – 885 245.1 241.6 15.6 29.2 1059 – 1086 228.1 251.5 23.2 41.2 1900 – 2000 205.6 214.8 27.7 46.0 2023 – 2150 194.3 203.2 31.6 52.2 2194 – 2274 182.4 188.6 24.1 36.9 2873 – 2974 199.9 205.1 21.5 29.3 3165 – 3192 173.6 205.7 21.6 33.8 aBougher et al. (2017b). bThis work.

resolution of the measurements. Pervasive wave activity also leads to large variations in observed densities and temperatures. Entry probes and orbiters can also conflate horizontal variations in the density with vertical variations in the density, as discussed in Section 2.2.4. Despite these difficulties, comparisons can be made between NGIMS temperature profiles and those derived from atmospheric measurements obtained by entry probe mass spectrometers and accelerometers, orbiter accelerometers, and UV spectrographs. The vertical domain sampled by NGIMS overlaps well with that sampled by the Viking and Pathfinder Landers. NGIMS DD measurements probe deeply enough into the atmosphere to overlap with the domain sampled by the MGS, ODY, and MRO accelerometers during the aerobraking phases of those missions, and the presence of ACC on MAVEN provides a unique opportunity to compare temperatures obtained by two different types of in situ instruments on the same spacecraft. Dayglow measurements from SPICAM and IUVS overlap with NGIMS temperature profiles obtained on nominal orbits, while stellar occultation measurements from SPICAM and IUVS overlap with NGIMS DD temperature profiles. 84

2.3.4.1 Entry Probes

Entry probes have gathered in situ measurements of the Martian upper atmosphere as they descended to the surface. Nier and McElroy (1977) present temperatures derived from data collected by the Viking Lander 1 and 2 neutral mass spectrometers (above 120 to 130 km altitude) and entry accelerometers (down to ∼6 km, see Seiﬀ and Kirk (1977) and Withers et al. (2002)). Deriving tempera-

ture from CO2 density with a method similar to that used here, Nier and McElroy (1977) noted an “interesting and complex thermal structure” with unexpected “vertical variety” attributed to wave activity in the lower atmosphere. Viking Lander 1

touched down at 22.5°N at around 4 p.m. local time and an LS of 83°, entering the atmosphere equatorward of the landing site and covering a signiﬁcant horizontal distance during its descent. This is similar to the MAVEN orbit geometry during DD8 (Table 2.1). MAVEN moved from latitudes south of the equator toward

∼20 °N at periapsis around 2 p.m. local time at an LS of 76°. The presence of wave activity in the Viking Lander 1 temperature profile complicates the comparison, though similarities to the average NGIMS profile are observed. The Viking Lander 1 temperature profile exhibits a thermospheric gradient of approximately 2 K km−1 over the 130 km to 170 km altitude range and a temperature maximum of approximately 200 K. Significant wave activity is observed above 170 km. In comparison, a thermospheric gradient of 2.18 ± 0.21 K km−1 is observed for DD8, with maximum temperatures reaching approximately 205 ± 45 K (Figure 2.14). Viking Lander 2 had a similar trajectory to Viking Lander 1, but landed at 48°N around 10 p.m. local time at an LS of 117°. The most similar DD is number 7, which occurred at

64°N around 8 p.m. local time at an LS of 76°. There is pervasive wave activity in the Viking Lander 2 temperature proﬁle and there are no measurements from m/z = 44 above 170 km. This prevents any meaningful characterization of the thermospheric gradient during the Viking Lander 2 descent. A maximum temperature of about 160 K is reached in the Viking Lander 2 proﬁle, while DD7 reaches a maximum of about 183 ± 24 K. Agreement between NGIMS temperatures and single 85

temperature profiles from the Viking Landers is good overall, despite the difficulty that arises from the variability of the Martian upper atmosphere observed in both data sets. The temperature profile derived from the Mars Pathfinder lander accelerometer measurements also overlaps significantly with NGIMS DD temperature profiles (Ma- galhaes et al., 1999; Withers et al., 2003b). Pathfinder entered the atmosphere poleward of 24°N and landed at about 19°N, near Viking Lander 1. However, Pathfinder descended at around 3 a.m. local time. Although uncertainties are large in the Pathfinder temperature profile above 120 km, the mean temperature profile reaches a minimum of ∼110 K near that height and a maximum of ∼150 K at 135 km. DD3 was executed around 3:30 a.m. local time, though at a much different latitude than the Pathfinder entry, and exhibits a similar temperature minimum of about 116 ± 10 K at an average altitude of 122 km and a maximum of around 135 ± 35 K at

6 −3 an average altitude of 189 km, which corresponds to a CO2 density of 5.6 × 10 cm . The other nightside Deep Dips, 5 and 6, reach 91 ± 22 and 92 ± 16 K, respectively, at periapsis. Within the stated uncertainties of the two data sets and despite the fact that the data were collected in relatively distinct locations on the planet, NGIMS nightside DD temperatures are similar to the Pathﬁnder entry accelerometer temperature proﬁle.

2.3.4.2 Orbiter Accelerometer Measurements

Withers (2006) derives temperatures from accelerometer measurements taken during the aerobraking phases of MGS and ODY. These temperatures are derived from density scale heights at 120 km for ODY and 120, 130, 140, 150, and 160 km for MGS between 80°N to 80°S with some sampling of both the dayside and the nightside. At 120 km, MGS and ODY temperatures can be compared to NGIMS DD temperatures near periapsis. MGS Phase 2 dayside scale height temperatures are relatively constant across all latitudes with scatter between 110 to 150 K. The relatively small amount of variation at this altitude is consistent with what is observed by NGIMS. Periapsis temperatures for the dayside DDs also fall within this 86

temperature range, while spanning a latitude range of 63°N to 63°S. MGS Phase 2 nightside temperatures of 90 to 110 K are obtained south of the equator from 40°S to 80°S and ODY nightside temperatures of 90 to 140 K (with one extreme measurement reaching nearly 200 K) are obtained across all northern latitudes. The nightside DDs 3, 5, and 6 reach 116 ± 11, 91 ± 22, and 92 ± 16 K at periapsis, respectively, in good agreement with the accelerometer measurements. The latitudinal variation of the temperature as seen by NGIMS can be compared to that in panel f of Figure 2 in the work of Withers (2006). From NGIMS measurements, a density of 109 cm−3 roughly corresponds to an altitude between 165 and 183 km, depending on the temperature, and the latitudinal variation observed at that density level is 31 ± 14 K, from 173 ± 12 K at the pole to 204 ± 8 K near the equator, as seen in Figure 2.17. The latitudinal variation is about 25 K at an altitude of 160 km as seen by MGS, from 200 K near the pole to 225 K near the equator, or about 30 K at an altitude of 150 km from 180 K near the pole to 210 K near the equator. The

MGS measurements were all collected near aphelion, between 30 and 100° LS, in the late afternoon/evening hours after 2 p.m., while NGIMS measurements span

all LS values across the local time window of 9 a.m. to 5 p.m. Thus, the solar insolation at Mars was significantly different during the periods sampled by the MGS accelerometer and NGIMS measurements. This difference in solar insolation is consistent with the magnitude of the difference of the latitudinal variations of the temperatures derived from the two data sets. The NGIMS temperature data set is otherwise in good agreement with temperatures derived from MGS and ODY accelerometer measurements.

Tolson et al. (2008) derive atmospheric scale heights from MRO accelerometer measurements taken during that mission’s aerobraking phase which was executed over the southern hemisphere at local times from about 8 p.m. to about 4 a.m. (see Figure 3 of Tolson et al. (2008)). For orbit 352, which was executed in the southern midlatitudes around 4 a.m., Tolson et al. (2008) derive temperatures of 98 and 164 K, respectively, from inbound and outbound scale heights at 130 km. DD3 was executed at 63°S around 4 a.m. local time and we observe a temperature of 87

117 ± 19 K at an average approximate altitude of 130 km, in reasonable agreement with the temperatures derived by Tolson et al. (2008).

Accelerometer measurements from MAVEN ACC provide a unique opportunity for comparison with NGIMS measurements since these two in situ instruments measure the same region of the atmosphere at the same time. Zurek et al. (2017) use ACC measurements to derive scale heights at periapsis and 150 km for 6 individual passes, as well as average scale heights at 150 km for 77 bins containing 30 to 70 sequential orbits. Six of these bins correspond to the first 6 DDs. The DDs are especially important since there is greater signal-to-noise in ACC measurements at the high densities achieved during these maneuvers. In order to compare the scale heights obtained by Zurek et al. (2017) with our results, we convert the scale heights to temperatures using T = µgH/k, where µ is the average molecular weight of the atmosphere and g is gravity. Values of µ = 43.49 Da and g = 347 cm s−2 are chosen here to be consistent with previous accelerometer investigations (Withers, 2006). For DD2 orbit 1060, Zurek et al. (2017) derive, at 150 km, inbound and outbound scale heights of 17.3 and 9.13 km, respectively, and 8.25 km at periapsis (∼135 km). These scale heights correspond to temperatures of 314, 166, and 150 K, respectively. For comparison, the NGIMS temperature profile for the inbound portion of orbit 1060 is shown in Figure 2.6. A temperature of roughly 240 K is observed by NGIMS at 150 km, but extreme variability makes the comparison difficult. Mean DD2 temperatures from NGIMS, which do not exhibit the strong variability seen in individual orbit profiles, are 137 ± 23 K at periapsis and 212 ± 26 K at a CO2 density of 1010 cm−3, which corresponds to an approximate altitude of 151 km. The variability likely explains the difference between the two scale heights derived from ACC measurements at 150 km as well as the differences between NGIMS and ACC temperatures. At the periapsis of orbit 3552 from DD6, Zurek et al. (2017) obtain a scale height of 3.56 km which corresponds to a temperature of just 65 K. While the average DD6 temperature is 92 ± 16 K at periapsis as seen in Figure 2.14, NGIMS also observes temperatures near 60 K at periapsis on multiple orbits during DD6. Zurek et al. (2017) find binned scale heights at periapsis for the first 6 88

DDs of roughly 7.5, 8.5, 6.5, 6.5, 6, and 6 km, which correspond to temperatures of 136, 154, 118, 118, 108, and 108 K, respectively. For comparison, mean periapsis temperatures from NGIMS for the ﬁrst 6 DDs are 126 ± 21, 137 ± 23, 116 ± 11, 129 ± 18, 91 ± 22, and 92 ± 16 K. The ACC temperatures are slightly warmer than the NGIMS temperatures, but otherwise the two instruments are in good agreement. The warmer temperatures from ACC are likely due to the fact that the ACC scale heights are produced by ﬁtting the lowest 10 km of data around periapsis and temperature increases with height in the thermosphere. While overall good agreement is found between temperatures derived from ACC scale heights and NGIMS density measurements, there remains some discrepancy between total atmospheric mass densities measured by the two instruments during the 8 DDs. The ratio of mass densities, ρNGIMS/ρACC, generally increases with 9 −3 increasing density from ∼1 around a CO2 density of 10 cm to a maximum of 11 −3 ∼1.2 around a CO2 density of 10 cm (periapsis). The source of the discrepancy between the two instruments is still unknown at the time of writing. If the source of the discrepancy is a systematic problem with NGIMS, then only NGIMS

CO2 densities would likely require correction, as CO2 constitutes the vast majority of the mass density in the region of overlap between the two instruments, while

species like Ar, and especially the lighter species N2, CO, O, N, He, H2, and H,

are much less important. Such a correction would alter the CO2 densities used as a vertical coordinate above and, since this correction would be density dependent,

any temperatures derived from NGIMS CO2 abundances, but would not affect the temperatures derived from NGIMS N2 or Ar abundances, the latter of which are utilized in the current analysis. The maximum difference in temperatures derived from NGIMS CO2 abundances before and after such a correction would be ∼10 K at periapsis. Overall good agreement is found between NGIMS temperatures and accelerometer scale height measurements from MGS, ODY, MRO, and MAVEN ACC. Discrep- ancies, where they exist, are of order tens of kelvins: given the extreme variability of the atmosphere, we view this as good agreement. DD temperatures, which reach 89 high enough densities to overcome the signal-to-noise limitations of the accelerometers, agree with accelerometer measurements from all four missions over a range of local times on the dayside and nightside. Measurements taken simultaneously by NGIMS and ACC during the DDs agree well at periapsis, and both instruments see surprisingly cold temperatures of 60 K near periapsis on individual orbits deep on the nightside during DD6. We observe about a factor of two greater latitudinal variation with NGIMS than was observed by MGS at an altitude of 160 km, though this can be explained by differences in solar insolation during the two periods sampled.

2.3.4.3 Stellar Occultations

Stellar occultations observed with the SPICAM UV spectrometer on the MEX mission produce atmospheric densities from 50 to 130 km altitude (Quémeraiset al., 2006; Forget et al., 2009; Montmessin et al., 2017). This altitude range overlaps with NGIMS DD measurements, offering an opportunity for comparison between the remote observations from SPICAM and the in situ measurements of NGIMS. Because SPICAM altitudes are referenced to the MOLA areoid and MAVEN uses the planetographic coordinate system, it is most straightforward to compare between the two missions on a pressure scale. The temperatures at the top of the SPICAM profiles are poorly constrained, which limits the accuracy of the profiles to pressures greater than ∼10−4 Pa (120 to 130 km). The DDs reach pressures of about 10−4 Pa at periapsis, so there is only a small region of overlap. In their Fig- ure 9, Forget et al. (2009) derive an average dayside temperature profile for local times between 10 a.m. and 3 p.m. and latitudes between 40°N and 50°N. This profile reaches a minimum of ∼125 K at the mesopause (∼10−4 Pa). During DD1, at a latitude of 43°N and a local time of 6 p.m., NGIMS measured a temperature of 146 ± 27 K at 10−4 Pa during the same season as the SPICAM measurements. The DD4 average temperature, which was measured at an average latitude of 64°S and at a local time of 4 p.m., is 122 ± 21 K at the same pressure level. SPICAM nightside temperatures from local times between 10 p.m. and 3 a.m. at latitudes of 40°N to 50°N reach about 115 K at a pressure of 10−4 Pa. The temperature profile 90 derived from DD3 measurements at 63°S around 4 a.m. local time also reaches a temperature of 118 ± 15 K at 10−4 Pa. The other nightside DDs (5 and 6) are cooler than DD3, reaching 91 ± 22 K and 92 ± 16 K, respectively, at pressures lower than 10−4 Pa, which implies the mesopause was even colder during this period. Forget et al. (2009) obtain additional average temperature profiles from SPICAM, shown in Figure 16 of their work, which span an entire Martian year at different latitudes and indicate mesopause temperatures between 100 and 140 K around a pressure of 10−4 Pa, consistent with NGIMS DD temperatures between 92 ± 16 K (DD6) and 137 ± 23 K (DD2) at the same pressure. Overall agreement is good in the relatively small pressure range in which measurements from SPICAM stellar occultation measurements and NGIMS DD measurements overlap.

The IUVS instrument on MAVEN has executed 12 stellar occultation campaigns to date and Grölleret al. (2018) derive temperature profiles from density measurements using the same method employed here for NGIMS data. The nightside temperature profiles obtained from IUVS by Grölleret al. (2018) are shown in their Figure 17. The profiles correspond to local times between 1 and 3 a.m. and latitudes near 2°N, 30°N, and 56°S. Near 10−4 Pa, the IUVS temperatures are between 95 and 100 K, which is within the 90 to 115 K range of nightside temperatures observed by NGIMS around the same pressure. Dayside profiles in Figure 18 of Gröller et al. (2018) reach high enough in the atmosphere to show part of the thermospheric gradient. At 10−4 Pa, the IUVS temperatures are 130 K to 140 K, consistent with the warmer dayside DDs 1, 2, and 4 which reach 122 ± 21 K (DD4) to 164 ± 18 K (DD2) at 10−4 Pa. Grölleret al. (2018) also characterize the diurnal variation of the temperature in the midlatitudes using IUVS temperatures at pressure level of 3 × 10−5 Pa. In Figure 2.16, we show the diurnal variation of temperature in the midlatitudes as seen by NGIMS. The 109 cm−3 density level corresponds to pressures between 1.5 and 3 × 10−5 Pa. In the IUVS data set, temperatures rise from ∼100 K near midnight to a peak near 200 K at ∼3 p.m. Similarly, in the NGIMS data set temperatures rise from 132 ± 24 K near midnight to 215 ± 12 K at 3 p.m. The IUVS stellar occultations and NGIMS data sets agree well within the region in 91

which the data sets overlap, especially with respect to the diurnal variation of the temperature.

2.3.4.4 Dayglow Measurements

Stiepen et al. (2015) derive temperatures in the 150 to 180 km altitude range + and 20 to 55° SZA range from scale heights of the CO Cameron and CO2 UV doublet (UVD) emission profiles collected by SPICAM aboard MEX. The authors find large variability in the thermospheric temperature, similar to that observed in the NGIMS temperature profiles presented in the current work, although less altitu- dinal context for this variability can be inferred from dayglow measurements. Scale heights derived from the CO Cameron band varied from 10.9 to 22 km, which correspond to temperatures of 182 and 400 K, respectively, with a mean temperature of 275 ± 6 K (Stiepen et al., 2015). In the low SZA dayside DDs, 2 and 8, tempera-

tures from NGIMS vary between 190 ± 26 K (DD8) and 253 ± 30 K (DD2) at a CO2 density of 109 cm−3, which corresponds to altitudes of 170 and 184 km, respectively, as compared to the 150 to 180 km altitude range of the dayglow measurements. The mean thermospheric temperature derived from the CO Cameron band scale heights are in agreement with the warmest temperatures observed by NGIMS in the same + altitude region, specifically during DD2. The temperatures derived from the CO2 UVD scale heights vary between 153 and 400 K, with a mean of 270 ± 5 K, which agrees well with those derived from the CO Cameron band. NGIMS has observed temperature extremes above 400 K, consistent with the warmest SPICAM dayglow results. + Using similar methodology, CO Cameron and CO2 UVD scale heights have been measured by IUVS aboard MAVEN. Jain et al. (2015) calculate scale heights in the 150 to 180 km region of the atmosphere for two periods in 2014 and 2015, encompassing MAVEN orbits 109 to 128 and 1160 to 1305 (with a gap from orbit 1221 to orbit 1276), respectively. For these two bins, Jain et al. (2015) find the mean + CO2 UVD scale heights to be 16.2 ± 0.1 km and 14.0 ± 0.1 km, corresponding to temperatures of 300 ± 2 K and 250.6 ± 1.7 K, respectively, with standard deviations 92 of 29 K for both bins, which represents variability rather than measurement error. NGIMS and IUVS do not measure the same region of the atmosphere during these time periods since IUVS probes the atmosphere some distance away from the spacecraft. Further, NGIMS does not sample all the way down to 150 km early in the MAVEN mission (see Figure 2.1). However, the measurements from NGIMS and IUVS do sample the same solar and seasonal conditions. Over 17 orbits between 109 and 128 (the first period analyzed by Jain et al. (2015)), we obtain an average temperature below 180 km of 288.1 K with a standard deviation of 45.2 K, indica- tive of large variability. Over 53 orbits between 1160 to 1220 and 1277 to 1305 (the second period analyzed by Jain et al. (2015)), we obtain an average temperature below 180 km of 253.6 K with a standard deviation of 47 K. Thus the temperatures + we derive from NGIMS measurements are in good agreement with IUVS CO2 and CO Cameron band scale height temperatures from the same time period.

2.3.4.5 MENCA Measurements

The MENCA quadrupole mass spectrometer onboard MOM directly sampled the Martian upper atmosphere over the course of 4 orbits in December 2014. During this time period, the spacecraft reached altitudes down to about 260 km at periapsis. Bhardwaj et al. (2016) estimate atmospheric scale heights of MENCA measurements in the m/z = 44, 28, and 16 channels to derive exospheric temperatures at local times between 5 p.m. and 6:30 p.m. and LS between 255 and 262° (near perihelion). Bhardwaj et al. (2016) observe a temperature range of 243–287 K, with a mean of 271 ± 5 K, over the 3 channels and all 4 orbits. This mean temperature is warmer than the Tiso of 232 ± 10 K we calculate for DD1, which was executed at a local time of 6 p.m. at LS = 291°. DD1 was executed during a period which was further from perihelion than the MENCA measurements, which could explain why the exospheric temperatures from MENCA are warmer. Bhardwaj et al. (2017) identiﬁed and analyzed some anomalous thermal proﬁles high in the thermosphere using a combination of MENCA and NGIMS data. We have not carried out a thorough investigation of this structure and so do not address it here. 93

2.3.5 Model Comparisons

The temperature distributions described in the previous sections are broadly in accord with expectations based on solar UV and near IR heating, thermal conduction, and radiative cooling, the primary drivers of the thermal structure of the Martian upper atmosphere that have been thoroughly described in the liter- ature (Bougher et al., 1994, 1999a, 2000, 2006, 2009, 2015a). To demonstrate this we have constructed time-dependent 1D models for the thermal structure of the upper atmosphere. Although these models neglect dynamical redistribution of heat, they compare surprisingly well with the data. This comparison can be used to investigate some characteristics of the redistribution of heat by dynamics.

This 1D model was ﬁrst described in Yelle et al. (2014), but has been modiﬁed for present purposes. We include solar energy deposition and associated heating

from CO2 and O by using a heating eﬃciency parameter of 20%, within the range of predicted values (Fox et al., 1996). We also include a parameterization of the heating

associated with absorption of sunlight in the CO2 near IR overtone bands. This is done primarily so that model temperatures agree with temperatures derived from observations at the lowest altitudes. This heating term is not important throughout

most of the thermosphere. Cooling occurs via radiative emissions from the CO2 ν2 band at 15 µm and to a lesser extent by the O ﬁne structure transition at 63 µm. The

CO2 ν2 band is excited primarily by collisions with O and we adopt a rate coeﬃcient −12 3 −1 for this process of 3 × 10 cm s . We include only CO2 and O in the models as

N2 and Ar are radiatively inactive and play no significant role in the thermal balance of the upper atmosphere. The heat deposited by solar radiation is transported to locations of radiative cooling by thermal conduction. This results in a second order differential equation that requires two boundary conditions for solution. Guided by the observations, we fix the temperature at the lower boundary to 100 K and specify a temperature derivative of zero at the upper boundary.

The most important difference in the model from Yelle et al. (2014) is that the O distribution is taken from NGIMS measurements rather than a chemical/diffusion 94 calculation. This is important because the O distribution exhibits significant diurnal variations that cannot be accurately predicted with a 1D model. We base our analysis on the O/CO2 mixing ratio profiles measured during the DDs, which are shown in Figure 2.18. As discussed earlier, the DDs occur at a range of local times and therefore provide good coverage of the diurnal variations of the O/CO2 ratio.

We use simple interpolation with a third degree polynomial to estimate the O/CO2 ratio at other local times.

106 DD6 DD3 DD5 DD7 107 DD8 DD4

) DD1 -3 DD2 108

Density (cm 9

2 10 CO

1010

1011 10-2 10-1 100 101 [O] / [CO ] 2

Figure 2.18: The [O]/[CO2] ratio measured by NGIMS for each of the 8 DDs.

Figure 2.19 compares the model temperature proﬁle for equatorial latitudes at 12 p.m. to that derived from DD2 data and at 12 a.m. to that derived from DD6 95

107

108

) -3 109

Density (cm Density 10

2 10 CO

1011

1012 50 100 150 200 250 300 Temperature (K)

Figure 2.19: Comparison of modeled temperature profiles with NGIMS data. The model temperature profiles for equatorial latitudes at 12 p.m. (red lines) and 12 a.m. (blue lines) compared to DD2 (red +) and DD6 (blue +) NGIMS temperature profiles. The solid lines are for models calculated with the nominal −12 3 −1 O-CO2 collisional de-excitation rate of k = 3 × 10 cm s , the dotted lines for k = 6 × 10−12 cm3 s−1, and the dashed lines for k = 1.5 × 10−12 cm3 s−1. The shaded regions represent 1-σ variabilities of the NGIMS temperatures. data. The model calculations are conducted for equatorial latitudes and, as mentioned earlier, the data is averaged over latitudes below 60°. The agreement is quite good, suggesting that our choice of 20% for the solar heating efficiency is reasonable, with the caveat that some of the energy deposited on the dayside may be transported to the nightside by the circulation of the upper atmosphere. We come back to the importance of this process below. Similarly, Figures 2.20 and 2.21 show that the diurnal variation of the exospheric temperature in the model reproduces the ob- 96

107 300

108 250 ) -3

109 200

Density (cm 10 150 2 Temperature (K) CO

1011 100

1012 50 0 4 8 12 16 20 24 Local Time (h) Figure 2.20: The temperature at equatorial latitudes versus local time in the 1D model. served diurnal variation. The model temperatures peak in the mid-afternoon near 3 p.m., as do the measured temperatures. This indicates that the model accurately captures the thermal time constants in the thermosphere. The nighttime temperatures in the model are cooler than the observations, which are shown in Figure 2.15. Figure 2.19 shows that the model temperature near midnight is close to isothermal, while the observed proﬁle displays a ∼20 K temperature rise. Figure 2.21 shows that the exospheric temperature in the model reaches 100 K, the lower boundary temperature, near midnight and stays at this level until 6 a.m., while the minimum observed exospheric temperature is ∼120 K. This diﬀerence is likely due to the neglect of dynamics in the 1D models. Our results indicate that the dynamical redistribution of heat in the thermosphere is modest. A temperature rise of 20 K in the nightside thermosphere requires that 10 to 15% of the solar energy deposited on the dayside 97

280

260

240

220

200

180

Temperature (K) Temperature 160

140 106 cm-3 120 109 cm-3 Model 10 7 cm-3 100 0 4 8 12 16 20 24 Local Time (h)

Figure 2.21: Comparison of the observed diurnal variation of the tem- 6 −3 9 −3 perature at CO2 densities of 10 cm (red) and 10 cm (blue) with the diurnal variation of the temperature in the 1D model at a CO2 density of 107 cm−3 (black). The shaded regions represent 1-σ variabilities.

is transported to the nightside. This would have only a minor effect on dayside temperature and is, for example, of the same order as the temperature difference due to the uncertainty in the solar heating efficiency (Fox et al., 1996). In contrast, the Mars Thermospheric Global Circulation Model (MTGCM) predicts ∼30% of energy deposited on the dayside is carried away by horizontal advection (Bougher et al., 2009). Figure 2.22 shows the terms in the full energy balance equation for noon and midnight conditions. Near noon, solar UV heating is balanced primarily by thermal

10 −3 conduction at high altitudes (CO2 densities less than 10 cm ) and CO2 radiative 98

10 −3 cooling at low altitudes (CO2 densities greater than 10 cm ). The peak in the

CO2 radiative cooling rate is produced by the combination of a decreasing collision rate with altitude and an increasing O mole fraction. The heating and cooling terms do not balance in this time-dependent calculation and, in fact, the time derivative of temperature term is comparable to, though somewhat smaller than, the solar heating rate. We can gain some insight into the phase shift between the peak solar insolation and peak temperature by employing some simplifying, but severe, approximations. The time-dependent energy balance equation can be written as

∂T ∂ ∂T ρc = Q − Q + κ , (2.11) p ∂t UV IR ∂z ∂z

where ρ is the mass density, cp the speciﬁc heat at constant pressure, QUV the

solar UV heating rate, QIR the radiative cooling rate, and κ the thermal conduction coeﬃcient. To estimate the thermal time constant we will assume that QIR ∼ 0 in the region of interest and that

QUV = Q◦ exp (iΩt) , (2.12)

where Ω is the planetary rotation frequency. We also deﬁne

T = T◦ + ∆T exp (iΩt) . (2.13)

Substitution of Equation 2.12 and Equation 2.13 into Equation 2.11 gives

∂ ∂ ∆T ρc iΩ ∆T = Q + κ . (2.14) p ◦ ∂z ∂z We now approximate ∂ ∂ ∆T ∆T κ ∼ κ 2 , (2.15) ∂z ∂z HT

where HT is the scale length for the temperature gradient. Solving for ∆T gives Q H2 1 + iΩH2 λ−1 ∆T = − ◦ T T , (2.16) ρc λ 2 −1 2 p 1 + (ΩHT λ )

where λ = κ/ρcp is the thermal diﬀusivity. 99

107

108 ) -3

109

1010 Density (cm 2 CO 1011

1012 -1000 -500 0 500 1000 1500 Heating Rate (K sol-1) 107 Solar UV Heating Thermal Conduction CO Radiative Cooling 8 2 10 O Radiative Cooling

) Solar Near IR Heating

-3 dT/dt 109

1010 Density (cm 2 CO 1011

1012 -250 -200 -150 -100 -50 0 50 100 150 200 250 Heating Rate (K sol-1) Figure 2.22: Energy balance terms for (top) noon and (bottom) midnight conditions from our 1D model. The legend in the bottom panel refers to both panels. 100

The phase shift between the maximum of solar heating, at local noon, and the maximum temperature gradient is determined by the imaginary part of Equa- tion 2.16. To estimate this phase shift for Mars, we apply Equation 2.16 to a density level of 1010 cm−3, where the temperature gradient is near its maximum value. The scale length for the gradient at this location is roughly 20 km and the temperature ∼200 K. At this temperature the thermal conduction coefficient is κ = 1.64 × 103 erg K−1 s−1 cm−1. Inserting these values we have for the phase shift 2 ΩHT /λ = 0.83 rad, which corresponds to a time shift of ∼3 h, consistent with that observed. This suggests that the 3 hour time shift is due primarily to the ratio of the thermal conduction time constant to a Mars day. The exospheric temperatures and thermospheric temperature rise derived from the MAVEN NGIMS observations are consistent with heating by solar UV radiation and cooling by a combination of thermal conduction and radiation in the CO2 15 µm band. The 1D time-dependent models presented here show that a heating efficiency of 20% provides a good match to the observed dayside temperature profiles. This result is insensitive to the choice of the O-CO2 collisional de-excitation coefficient, within the range of 1.5 × 10−12 to 6.0 × 10−12 cm3 s−1. These models also provide a good match to the diurnal variation of exospheric temperature, predicting a temperature maximum near 3 p.m. Redistribution of heat by global circulation appears to be relatively modest and can account for the 1D model predictions falling below observed nighttime temperatures by ∼20 K. Overall, the agreement between the observations and these 1D models is quite good. The match between the vertical temperature profiles and the diurnal variation suggests that we understand the energy sources and sinks in the present day upper atmosphere. The radiative cooling rate from CO2 has been a source of significant uncertainty in previous models of the Mars thermosphere because the atomic oxygen density was poorly constrained (Yelle et al., 2014; Bougher et al., 2015b). The NGIMS measurements of the O density significantly reduce this uncertainty and lead to a result in accord with observations using nominal values for heating efficiency and the O-CO2 collisional de-excitation rate. 101

Detailed comparisons of the temperature distributions described in previous sections and 3D global circulation models (GCMs) such as M-GITM (Bougher et al., 2015c) and the Mars GCM developed at Laboratoire de MètèorologieDynamique (LMD-MGCM, see González-Galindoet al. (2009b,a, 2010, 2015)) can further elucidate the role of dynamics in driving the thermal structure of the Martian upper atmosphere, especially on the nightside. Additionally, these models can investigate the role of gravity wave momentum deposition in the thermosphere. Pervasive wave activity observed in the NGIMS data motivates a thorough investigation using these sophisticated models.

2.4 Conclusions

Using NGIMS data from 1.75 Mars years, we have calculated upper atmospheric density profiles of Ar, CO2, and N2 with high temporal and spatial resolution, which we have used to derive upper atmospheric temperature profiles by assuming hydrostatic equilibrium. We have demonstrated the necessary corrections to the NGIMS data that have been developed to date, including corrections for the scattering of ions inside the spectrometer, the attenuation of the electron beam used by the spectrometer to ionize neutrals, the ram effects of the spacecraft body passing through the atmosphere, and the horizontal motion of the spacecraft. These corrections are critically important for the derivation of temperatures from NGIMS data, because they each affect the slope of the measured density profile.

The NGIMS data set densely samples all local times at CO2 densities between 106 and 1010 cm−3, with good coverage across latitudes from 80°N to 80°S. We observe extreme variability from pass to pass, but this variability is not present in mean proﬁles calculated from even a few sequential orbits. Thus, we believe that the short term variability is due primarily to waves. Average DD temperature pro- ﬁles characterize the thermospheric gradient across a wide range of local times and latitudes. Observed thermospheric gradients range between 1.33 ± 0.16 K km−1 and 2.69 ± 0.33 K km−1 on the dayside. The diurnal variation of the temperature is well 102 characterized and variations of about a factor of two from 127 ± 8 K to 260 ± 7 K are

6 −3 observed at a CO2 density of 10 cm . The latitudinal variation of the temperature is observed to be 39 ± 17 K at the same density level. NGIMS temperatures are broadly consistent with previous in situ and remote measurements of the Martian upper atmosphere. Viking Lander 1 and 2 observed the same complexity in the thermal structure as we do on nearly every MAVEN pass. Measurements of the thermospheric temperature gradient made by entry probes are consistent with the values we calculate. Atmospheric scale heights and the resultant latitudinal variation of the temperature as seen by the MGS, ODY, and MRO accelerometers during the aerobraking phases of those missions agree well with temperatures we derive in the 120 to 160 km altitude range. Measurements obtained by NGIMS and MAVEN ACC during DDs overlap in time and space, but densities and temperatures are derived from the two data sets using two distinct method- ologies. Despite this fact, the temperatures obtained from NGIMS and ACC show broad agreement. Both NGIMS and ACC observe surprisingly low temperatures near 60 K around 125 to 130 km on the nightside. Stellar occultation observations made by SPICAM aboard MEX and IUVS aboard MAVEN produce high quality temperature profiles that extend up to altitudes that are also sampled by NGIMS during the DDs and agree well with our observations. Atmospheric scale heights derived from dayglow measurements made by these instruments also agree well with NGIMS temperatures presented here and in a previous investigation carried out by Bougher et al. (2017b) prior to the development of the corrections to the NGIMS data described herein. Finally, comparisons of NGIMS temperatures and temperatures produced by 1D models show that our observations are consistent with heating by solar UV radiation and cooling through a combination of CO2 radiation at 15 µm and thermal conduction. We use nominal values for the UV heating efficiency and O-CO2 collisional de-excitation coefficient, and measured O/CO2 mixing ratios from the DDs in the 1D model, which reproduces the thermospheric gradient and exospheric temperature we observe in the NGIMS data. The diurnal variation of the temperature that 103 we observe also compares well with that produced by the model, with a maximum near 3 p.m. The redistribution of heat by circulation from the dayside to the nightside, not included in the 1D model, can explain the ∼20 K difference between the observed and modeled nightside temperatures. This modest difference suggests that the day-night transport of heat is weak. The MAVEN NGIMS data set will facilitate future inquiries into the past and present composition, structure, and variability of the Martian upper atmosphere. The data set can be improved by the development of a background correction procedure that enables analysis of outbound data. Such a procedure would effectively double the amount of usable NGIMS data, leading to more dense sampling of the upper atmosphere of Mars and improved averages of the density and temperature, which are important for removing pervasive wave activity. We have been able to identify trends in the thermospheric and exospheric temperatures with a subset of important geophysical variables, especially local time, but we have not been able to investigate the impacts of geophysical variables like solar irradiance in as thorough a manner. With more NGIMS data covering a wider range of solar irradiance levels, it would be possible to analyze trends in the structure and composition of the upper atmosphere with variations in solar activity. A thorough analysis of this type is critical for investigations into past epochs when the solar EUV flux was significantly larger than present day levels. For example, stronger solar EUV fluxes may have prevented a dense CO2 atmosphere from forming in the early Noachian period (Tian et al., 2009). This has significant ramifications for the history of liquid water on the surface of Mars. Comparisons of the NGIMS data set with 3D GCMs such as M-GITM and LMD-GCM must also be carried out. This will enable more thorough analyses of the energy balance of the upper atmosphere than are possible with a 1D model, especially with respect to the transport of heat from the dayside to the nightside and the role of tides and waves in the thermosphere. 104 105

CHAPTER 3

Composition of the Martian Upper Atmosphere

The contents of this chapter have been submitted for publication in Journal of Geophysical Research: Planets.

3.1 Introduction

The tenuous upper atmosphere of Mars, starting at the mesopause (∼90 km altitude) and including the thermosphere (∼100–200 km) and the exosphere (above ∼200 km), is the reservoir of gas that can escape to space and which absorbs and dis- tributes solar extreme ultraviolet (EUV) energy (Bougher et al., 2017a; Lillis et al., 2015; Jakosky et al., 2018). In this region of the atmosphere there is a transition in the dominant species from CO2 to O, a product of the destruction of CO2 by EUV photons, and a transition from the collisionally dominated thermosphere to the collisionless exosphere. Because escape processes operate directly on the upper atmosphere and because solar EUV is a signiﬁcant contributor to the atmospheric energy budget, characterization of the composition and variation of the molecular and atomic neutral species in this region is integral to any investigation of the loss of the atmosphere to space. Using in situ data from the Neutral Gas and Ion Mass Spectrometer (NGIMS; see Mahaﬀy et al. (2015b)) on the NASA Mars Atmosphere and Volatile EvolutioN (MAVEN; see Jakosky et al. (2015)) spacecraft, we investigate the neutral constituents of the upper atmosphere of Mars: CO2, Ar, N2, O,

He, and H2, with a focus on variations in composition with local time, latitude, and season. Such horizontal gradients in the composition of the upper atmosphere atmosphere can be used to constrain the dynamics of this region and are important for our understanding of the current state and evolution of the Martian atmosphere through time. The last direct measurements of the composition of the upper atmosphere of Mars were obtained by the Viking 1 and 2 landers as they descended to the surface, 106

providing two vertical proﬁles of the CO2, Ar, N2,O2, and NO abundances from roughly 120 to 200 km (McElroy et al., 1976; Nier et al., 1972; Nier and McElroy, 1976; Nier et al., 1976a). The Indian Space Research Organization Mars Orbiter Mission (MOM; see Arunan and Satish (2015)) arrived at Mars just after MAVEN and carries a quadrupole mass spectrometer like NGIMS named Mars Exospheric Neutral Composition Analyzer (MENCA; see Bhardwaj et al. (2015)). This instrument has obtained 10 proﬁles of CO2, Ar, and O abundances between 160 to 400 km altitude (Bhardwaj et al., 2016, 2017; Rao et al., 2020). Direct measurements of total upper atmospheric mass density have been obtained by a number of accelerometers on numerous spacecraft and entry probes, though these measurements do not include information on the composition of the atmosphere.

Compositional measurements have also been obtained using remote sensing techniques. Solar occultation measurements obtained by the Spectroscopy for Investi- gation of Characteristics of the Atmosphere of Mars (SPICAM; see Bertaux et al. (2006)) spectrograph on the ESA Mars Express spacecraft have produced vertical profiles of the CO2 and O2 abundances up to ∼140 km altitude (Quémeraiset al., 2006; Forget et al., 2009; Sandel et al., 2015; Montmessin et al., 2017) and similar solar occultation measurements obtained by the Imaging Ultraviolet Spectrograph (IUVS, see McClintock et al. (2015)) on MAVEN have produced vertical profiles of the CO2 and O2 abundances up to an altitude of ∼150 km (Grölleret al., 2015,

2018). IUVS observations of the N2 Vegard-Kaplan (VK) bands have produced vertical profiles of N2 and observations of the NO γ band resonance fluorescence have produced vertical profiles of NO (Stevens et al., 2019). Observations of the O 130.4 and 135.6 nm UV dayglow emissions provide constraints on the O abundance in the upper atmosphere and have been obtained by the UV instruments on the Mariner spacecrafts (Barth et al., 1971, 1972b,a; Barth, 1974; Strickland et al., 1972, 1973; Stewart et al., 1992), SPICAM (Leblanc et al., 2006; Chaufray et al., 2009), and IUVS (Chaufray et al., 2015a; Ritter et al., 2019). Lyman-α measurements obtained by the Mariner spacecrafts (Anderson and Hord, 1971, 1972; Anderson, 1974), Hubble Space Telescope (Clarke et al., 2014; Bhattacharyya et al., 2015, 2017a,b), 107

SPICAM (Chaufray et al., 2008; Chaffin et al., 2014), and IUVS (Chaffin et al., 2015; Clarke et al., 2017; Mayyasi et al., 2017; Chaffin et al., 2018; Mayyasi et al., + 2019) provide constraints on the H and D abundances in the exosphere. CO2 airglow emissions measured by Mariner 6 and 7 (Krasnopolsky, 1975) have been used to derive CO2 densities, as have SPICAM and IUVS measurements of Lyman-

α (Chaufray et al., 2011, 2019). The Martian H2 abundance has been measured only once using the Far Ultraviolet Spectroscopic Explorer (FUSE), which is situated in low Earth orbit (Krasnopolsky and Feldman, 2001). In contrast to in situ mass spectrometer measurements, measurements of airglow emissions are conﬁned to the dayside, solar occultations are conﬁned to the terminators, and all remote sensing measurements are made along the instrument’s line-of-sight. NGIMS obtains excellent vertical resolution and coverage in terms of local time, latitude, and season since the MAVEN orbit is highly elliptical and precesses around

Mars (Figure 3.1). NGIMS measurements of CO2,N2, Ar, O, and He have been reported previously (Mahaﬀy et al., 2015a; Elrod et al., 2017). The measurements presented here expand upon these reports in terms of local time, latitude, and sea-

sonal coverage, and the NGIMS H2 measurements are the ﬁrst vertical proﬁles of H2 measured on Mars. We report data obtained on 8617 MAVEN orbits from February 2015 to August 2020, including all 9 Deep Dip (DD) maneuvers (Figure 3.1, blue), which are week-long low-altitude excursions (Demcak et al., 2016), and the MAVEN aerobraking (AB) period (Figure 3.1, green), a 45 d period of low-altitude measurements (Demcak et al., 2020). Mean periapsis ephemeris data for these DD and AB periods are shown in Table 3.1. We use this data to characterize compositional variations in the upper atmosphere and compare our results to previous compositional measurements where possible. 108

Date

Apr '15 Oct '15 Apr '16 Oct '16 Apr '17 Nov '17 May '18 Nov '18 Apr '19 Sep '19 Feb '20 Jul '20 210 A 190 170 150 130 Altitude (km) 110

24 B 18

6 Local Time (h) 0

90°N C 60°N 30°N 0° 30°S Latitude 60°S 90°S 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 Orbit

240 300 0 60 120 180 240 300 0 60 120 180 240 300 0 60 120 180 240 300 L (degrees) S Figure 3.1: Coverage of Mars by MAVEN NGIMS from September 2014 to August 2020. (A) Altitude, (B) local time, and (C) latitude at periapsis for each MAVEN orbit. The blue points correspond to the nine Deep Dips (DDs) and the green points correspond to the aerobraking (AB) period. 109

Table 3.1: Ephemeris for MAVEN Deep Dips and aerobraking. Values are means at periapsis over each period.

a b Period Orbits Latitude SZA LTM (h) LS DD1 714 – 747 42.5°N 109.0° 18.3 291.1° DD2 1059 – 1086 3.8°S 9.3° 11.9 328.6° DD3 1501 – 1538 62.6°S 110.3° 3.5 11.3° DD4 1802 – 1838 63.9°S 91.1° 16.0 37.5° DD5 3285 – 3327 33.2°N 96.5° 5.2 166.9° DD6 3551 – 3586 3.0°S 166.4° 0.7 194.2° DD7 5574 – 5620 63.6°N 87.0° 20.3 49.4° DD8 5909 – 5950 18.9°N 25.0° 13.7 76.3° DD9 6936 – 6973 49.5°S 55.5° 12.1 166.2° AB 8535 – 8807 26.3°S 116.7° 20.0 294.1° aSolar zenith angle. bLocal time.

3.2 Methods

To calculate neutral densities from NGIMS measurements we correct for detector nonlinearity (dead time), background signal levels, scattering of ions within the instrument, and ram eﬀects related to the interaction of the spacecraft with the atmosphere. We also separate horizontal and vertical variations in the atmosphere as manifest in measurements along the spacecraft trajectory. In previous work, we have described this process for CO2, Ar, N2, and O densities (Stone et al., 2018).

Here we describe the process for He and H2.

3.2.1 Treatment of Data

We utilize MAVEN NGIMS Level 1 (L1) export version 12 data files. The same data are available publicly in the MAVEN NGIMS Level 1b (L1b) files. We use data collected by NGIMS in its closed source neutral mode (Mahaffy et al., 2015a) during the inbound portion of each periapse pass (Stone et al., 2018). In addition to the time periods described in Stone et al. (2018), we use data from 24 October 2017 to 23 August 2019 (orbits 5953 to 9771) and 14 September 2019 to 6 August 2020 (orbits 9912 to 12088). Except for the data gap spanning 23 August 2018 to 14 September 2019, a result of Mars-solar conjunction, there are only short gaps in these time 110

periods due to, e.g., relay operations. The MAVEN orbit has been circularized to facilitate these relay operations and, in August 2020, MAVEN periapsis altitude had risen to the point that periapsis densities are too low for the derivation of neutral temperatures as described in Stone et al. (2018), though neutral and ion density measurements continue (Figure 3.1A) and MAVEN is expected to return transiently to the density corridor in which neutral temperatures can be derived. The data set analyzed here thus includes 8617 orbits, from orbit 683 to 12088.

4 He and H2 densities are constructed from NGIMS measurements of count rates 4 + + in mass per charge (m/z) channels corresponding to He and H2 , namely m/z = 4 and 2, respectively (Figures 3.2 and 3.3). Potential contamination in these m/z channels, but is unlikely. At m/z = 2, atmospheric D ionized by NGIMS to D+, or D+ produced by molecular fragmentation in the spectrometer, could be counted as H2. However, the D abundance is at most a few percent of the H2 abundance near periapsis (Mayyasi et al., 2019), so any correction for D would be smaller than the uncertainty in any NGIMS measurement (Benna et al., 2015a; Stone et al., + 2018). Similarly, atmospheric D2 could be ionized to D2 and counted at m/z = 4, 4 but the D2 abundance is negligible relative to that of He. The detector does not reach saturation in these m/z channels, so no proxy channels are required for the calculation of He or H2 densities, unlike the cases of CO2, Ar, and O (as shown in Figure 3.3, see also Stone et al. (2018)). At high atmospheric densities, molecular backscattering in the instrument can become a signiﬁcant contributor to m/z = 2 and 4. This occurs when the gas density in the spectrometer reaches a level such that the quadrupole mass analyzer can no longer eﬃciently reject species of undesired m/z from reaching the detector (Figure 3.2, purple). As such, we only use data from 8 −3 m/z channels 2 and 4 when the CO2 density is <10 cm , which occurs close to 9 −3 periapsis on nominal orbits (Figure 3.1, red), where the CO2 density is ∼10 cm .

This background is observed in Figure 3.3 as the peak in the He (m/z = 4) and H2 (m/z = 2) count rates between approximately −200 and 150 s. Backscattering is not a signiﬁcant issue for CO2, Ar, N2, or O (or more accurately 4 < m/z < 49) because the quadrupole mass analyzer remains relatively eﬃcient at the relevant voltage 111

settings (Mahaﬀy et al., 2015b) and a simple correction has been developed (Stone et al., 2018). In addition to the retrieval method described in Stone et al. (2018) for

CO2 and O, the CO2 count rate is divided by a factor of 0.7692 and the O2 count rate (which is multiplied by 2 to obtain the O density) is divided by a factor of 0.83 to account for the fragmentation of these species, which lowers the count rate in the

channels used (m/z = 44, 45, and 13 for CO2 and m/z = 32 for O) (NIST Mass Spectrometry Data Center, William E. Wallace, Director, 2021).

Instrument background at m/z = 4 is corrected in the same manner as that for

CO2,N2, and Ar, as described in Stone et al. (2018) and no instrument background

is subtracted from the H2 signal at m/z = 2. For He, the mean of the ﬁrst 50 s of inbound data are taken as the instrumental background (Figure 3.3, from approximately −780 to −670 s). There is relatively little background in m/z = 4 since He is a noble gas, thus having essentially no gettering interaction with the inner walls of NGIMS, and since no other species produces fragments at this m/z value. The

relatively large abundance of H2 over the entire altitude range over which NGIMS collects data precludes the calculation of an instrumental background at m/z = 2 during the normal periapse portion of the MAVEN orbit as is done for other species. We can, however, investigate the background in m/z = 2 during the apoapse portion of the pass, when MAVEN is relatively far from Mars and NGIMS is pointing away from the ram direction (that is, away from the direction the spacecraft is moving).

These conditions preclude the measurement of atmospheric H2. During 107 such apoapse passes, the mean background at m/z = 2 is calculated to be 1182 ± 561 s−1 and the median is 1063 s−1. No fragments of other species are measured at m/z = 2. It is possible for H, produced by the fragmentation of other molecules or present in the atmosphere, could recombine to form H2, which would be measured as background signal in m/z = 2. However, no background signal other than backscattering discussed above is apparent in the m/z = 2 data, which would be seen as a ﬂat line in Figure 3.3. Analysis of the m/z = 2 data shows that it has a scale height expected for a 2 u species. Thus, it is evident that the instrumental background in the m/z = 4 and m/z = 2 channels is small relative to the measured signal over 112 the majority of the atmosphere measured by NGIMS, speciﬁcally the region where

8 −3 the CO2 density is less than 10 cm . The calculation of the CO abundance from 12 16 12 16 NGIMS data is complicated by the fragmentation of C O2 into C O, which produces a background in m/z = 28 that must be accurately subtracted from the signal due to atmospheric 12C16O. Therefore we do not include the derivation or analysis of the CO abundance here.

108

) 7 -1 10

106

105

104 Mean Count Rate (s

103 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 32* 40* z m ⁄ Figure 3.2: A mass spectrum from aerobraking orbit 8625. The mean count rate for each m/z channel is calculated over a period of 10 minutes centered about periapsis. The m/z = 35 channel (blue) is used to calculate the scattering background (Stone et al., 2018). The signal in channels colored purple is also due to the scattering background. The channels colored green are used to calculate CO2, Ar, N2, O, He, and H2 densities as discussed in Section 3.2. The m/z channels denoted 32* and 40* are detuned m/z = 32 and 40 (Stone et al., 2018).

Spectrometer sensitivities for CO2, Ar, N2, O, and He, which are used to calculate densities from detector count rates, are listed in Table S1 of Mahaﬀy et al. (2015a).

The sensitivity of NGIMS to H2 is relatively uncertain, as there exists no ground calibration of NGIMS at m/z = 2. Here we extrapolate the 4He sensitivity to m/z = 2 using electron impact ionization cross sections obtained from the National 113

Institute of Standards and Technology (NIST) for He and H2 (Kim et al., 1997). Speciﬁcally,

σEI,H2 4 SH2 = S He (3.1) σEI,He where σEI is the electron impact ionization cross section at 75 eV (the energy which

Altitude (km) 470 385 309 246 194 157 134 126 134 157 195 247 311 388 474 1011 CO 10 2 10 Ar N 109 2 O 108 He H 2 ) 107 -1

106

105

4 Count Rate (s 10

103

102

101

100 -800 -700 -600 -500 -400 -300 -200 -100 0 100 200 300 400 500 600 700 800 TCA (s)

Figure 3.3: Count rate profiles from aerobraking orbit 8617 as a function of time since closest approach (TCA, bottom axis) and altitude (top axis). The CO2 profile (reds) is constructed from m/z = 44 (dark red), m/z = 45 (red), and m/z = 13 (pink). The Ar profile (greens) is constructed from m/z = 40 with nominal instrument tuning (dark green) and with the instrument slightly detuned to avoid detector saturation (light green). The N2 (blue) profile is constructed from m/z = 14. The O profile (purples) is constructed from from signal in nominal and detuned m/z = 32, similar to Ar. The He profile (brown) is constructed from m/z = 4 and the H2 profile (orange) is constructed from m/z = 2. 114 electrons are accelerated to once emitted by the NGIMS filament) for each species 2 2 indicated by subscript, σEI,H2 = 1.017 A , and σEI,He = 0.340 70 A , to give SH2 = 1.06 × 10−2 s−1 cm−3.

3.3 Results and Discussion

NGIMS CO2, Ar, N2, O, He, and H2 densities for aerobraking orbit 8617 are shown in Figure 3.4. This orbit extends relatively deep into the atmosphere since MAVEN periapsis was lowered to increase drag on the spacecraft during this period with the intention of altering apoapsis altitude (Figure 3.1A, green). During aerobraking and the DDs, MAVEN approaches the mesopause, making vertical proﬁles

400 CO 2 Ar 350 N 2 O He H 300 2

250 Altitude (km) 200

150

100 103 104 105 106 107 108 109 1010 1011 Density (cm -3)

Figure 3.4: Vertical proﬁles of CO1, Ar, N2, O, He, and H2 densities measured by NGIMS on aerobraking orbit 8625. 115

obtained during these periods particularly valuable from a scientific perspective. H2 densities can be retrieved up to relatively high altitudes due to the light species’ large scale height, leading to relatively high abundances and good signal-to-noise even in the exosphere. As shown in the mean profiles in Figure 3.5, binning multiple sequential orbits removes the signature of gravity waves and point-to-point scatter observed in Figure 3.4. Mean density profiles such as those shown in Fig-

ure 3.5 are obtained by binning on CO2 density, rather than altitude, and mean approximate altitudes are derived from the CO2 density and the neutral temperature profile assuming hydrostatic equilibrium (Stone et al., 2018). CO2 density is the more physically meaningful vertical coordinate because changes in temperature can move density levels up or down in altitude. If the data are binned on altitude, then these variations in temperature could be misconstrued as variations in composition. The data in Figures 3.4 and 3.5 demonstrate the vertical variation typical of the atmosphere above the homopause. The homopause is the region in which the atmosphere transitions from the well-mixed homosphere below, where eddy diffusion dominates, to the heterosphere above, where molecular diffusion is faster than eddy diffusion. In the heterosphere, each species’ vertical variation is determined by its own scale height, H, or vertical distance over which the density of the species decreases by a factor e, where H = kT/mg. In this equation, k is the Boltzmann constant, T the temperature, m the species’ mass, and g gravitational acceleration. Thus, lighter species have large scale heights and their abundance decreases with height less rapidly than that of heavier species. As a result, the mean molecular mass of the atmosphere decreases with height and its composition is eventually dominated by light, atomic species produced by the destruction of molecules by solar photons or the ions or electrons these photons generate. The effect of temperature on the scale height, thus the vertical variation of the neutral atmosphere, can be seen in Figure 3.6. In this figure, the data represented with solid lines were collected during DD5, which was executed at the morning terminator (Table 3.1), where the atmosphere is relatively cool (Stone et al., 2018). The data represented with dotted lines were collected during DD8, which was exe- 116

320 CO 2 295 Ar N 2 O 270 He H 2 245

220

195

170 Mean Approximate Altitude (km)

145

120 103 104 105 106 107 108 109 1010 1011 Density (cm -3)

Figure 3.5: Mean densities measured by NGIMS over the orbit range 8716–8742. The altitudes given are mean approximate altitudes, derived assuming hydrostatic equilibrium (Stone et al., 2018).

cuted just after noon, a period of the day which is relatively warm. The difference in temperature between the two DDs leads to a number of observable effects on the composition of the upper atmosphere and its variation with height. First, the abundances of the lightest species (He and H2) are enhanced significantly at the morning terminator (DD5, solid) as compared to the afternoon atmosphere. This is due to solar-to-antisolar flow, following by downwelling on the nightside of the planet. This effect is investigated in greater detail in Section 3.3.2. This effect can

also be seen in the O and N2 proﬁles. Since these species are heavier than He and

H2, the eﬀect is smaller. Ar is eﬀected the least of the species shown in Figure 3.6 117

103 Ar 4 N 10 2 250 O 5 He 10 228

) H 2 -3 106 206

107 185

Density (cm 8 2 10 168 Altitude (km) CO

109 150

1010 135

1011 103 104 105 106 107 108 109 1010 Density (cm -3)

Figure 3.6: Mean densities measured by NGIMS during DD5 (solid) and DD8 (dotted). DD5 was executed near the morning terminator and DD8 was executed near the evening terminator (Table 3.1). The altitudes given are mean approximate altitudes, derived assuming hydrostatic equilibrium (Stone et al., 2018). since its mass is relatively similar to the mean mass of the atmosphere. Second, changes in temperature lead to changes in the scale height, H. If the temperature increases, H is larger, and thus the abundances of each species decrease more slowly with altitude.

Variations in the ratios to CO2 of Ar, N2, O, He, and H2 at a constant CO2 density are shown in Figure 3.7. The magnitude of these variations increases from the heaviest species (Ar, Figure 3.7, top) to the lightest, (H2, Figure 3.7, bottom). These variations are due to changes in local time, latitude, and season, as the MAVEN orbit precesses about Mars and Mars moves through its orbit around the sun. Herein we characterize the impact of each of these variables on the composition 118 of the upper atmosphere of Mars. 119

Date

Apr '15 Oct '15 Apr '16 Oct '16 Apr '17 Nov '17 May '18 Nov '18 Apr '19 Sep '19 Feb '20 Jul '20 ] 2 10-1

[Ar] / [CO 10-2

1 ]

2 10

100 ] / [CO 2

[N 10-1

] 1 2 10

100

[O] / [CO 10-1 ] 2 10-1

10-2

-3 [He] / [CO 10 ] 2 10-1

-2

] / [CO 10 2

[H 10-3 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 Orbit

240 300 0 60 120 180 240 300 0 60 120 180 240 300 0 60 120 180 240 300 L (degrees) S

Figure 3.7: Ar, N2, O, He, and H2 to CO2 ratios at a CO2 density of 107 cm−3 measured by NGIMS over the course of the MAVEN mission. 120

3.3.1 Compositional Trends with Latitude

MAVEN periapsis precesses across Mars in latitude roughly every 7 months (Figure 3.1), though periapsis is never poleward of 75° latitude. Binning the NGIMS

data on latitude, with CO2 density as the vertical coordinate, produces Figures 3.8– 3.10 for local times of 12 a.m. to 8 a.m., 8 a.m. to 4 p.m., and 4 p.m. to 12 a.m., respectively. It should be noted that NGIMS data are relatively scarce poleward of 70° latitude. Further, any seasonal trends and bin-to-bin noise may impact the interpretation of the latitudinally binned data in this section, since the observed latitudinal trends are relatively small in magnitude.

Latitudinal trends in the mixing ratios of the lighter species are due to transport, which leads to upward then horizontal ﬂow of gas enriched in lighter species from the top of thermosphere in the warmer regions of the atmosphere — so enriched due to the larger scale height of the lighter species — to the colder regions of the atmosphere, where this gas is then transported downward. The expected polar

enhancement in the ratios to CO2 of N2, O, He, and H2 is visible approaching the southern pole in all local time bins, as shown in Figure 3.11. This is most signiﬁcant

for He and H2 in the local time bin spanning 4 p.m. to 12 a.m. at a CO2 density 8 −3 of 10 cm (Figure 3.11C). At this level in the atmosphere the H2 to CO2 ratio −3 −3 increases from 2.4 × 10 at 52.5°S to 6.7 × 10 at 72.5°S and the He to CO2 ratio increases from 2.3 × 10−3 to 9.4 × 10−3 at the same latitudes.

Perhaps the most striking trend in Figure 3.11 is observed in the He and H2

to CO2 ratios shown in Figure 3.11A, the panel corresponding to local times of 12 a.m. to 8 a.m. There is a steady decrease in these ratios with increasing latitude, from 32.5°N to 77.5°N. This trend is especially prominent in the data obtained at 8 −3 −3 a CO2 density of 10 cm , where the H2 to CO2 ratio decreases from 7.6 × 10 at −3 −3 32.5°N to 2.0 × 10 at 77.5°N and the He to CO2 ratio decreases from 5.7 × 10 −3 to 1.0 × 10 at the same latitudes. Similarly, in Figure 3.11C, the O to CO2 ratio

decreases with increasing latitude toward the northern pole. At a CO2 density of 8 −3 10 cm , the O to CO2 ratio decreases from 6.5 at 42.5°N to 2.7 at 77.5°N. However, 121

106 106 ) -1 ) 0.5 -3 -3 ] ] 2 7 2 7 10 -1.2 10 0 ] / [CO

8 8 2 10 -1.4 10 [Ar] / [CO -0.5 [N 10 10

Density (cm 9 Density (cm 9

2 10 -1.6 2 10 log log

CO CO -1 1010 1010 90°S 60°S 30°S 0° 30°N 60°N 90°N 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude Latitude

106 1 ) -3 ] 107 2 0 108 [O] / [CO 10

Density (cm 9

2 10

-1 log CO 1010 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude

104 104 ) ) -3 -3 ] 1 1 ] 2 2 105 105 0 0 ] / [CO 106 106 2 -1 [H [He] / [CO -1 10 10

Density (cm 7 Density (cm 7

2 10 -2 2 10 log log -2 CO CO 108 108 90°S 60°S 30°S 0° 30°N 60°N 90°N 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude Latitude

Figure 3.8: NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and latitude and constrained to local times between 12 a.m. and 8 a.m. Each bin is 5° in width and logarithmically spaced in CO2 density. the other light species do not follow this trend. NGIMS Ar measurements correspond to 40Ar, which has a mass of 40 u, nearly 12 16 the same mass as C O2 (44 u), and thus at all times Ar has a scale height similar in magnitude to that of CO2. Therefore, the Ar to CO2 ratio is only scarcely aﬀected by transport, in contrast to the relative abundances of the lighter species. The Ar to

CO2 ratio remains essentially constant across all latitudes measured. Comparisons of this ratio with the those of the lighter species aids in the identiﬁcation in underlying trends in the CO2 abundance. For example, if the Ar mixing ratio increases or 122

decreases in the same manner as the lighter species, this could be an indication of a

corresponding decrease or increase in the CO2 abundance rather than a transport- induced variation of the lighter species. The latitudinal trends discussed in the

preceding paragraphs are not mimicked in the Ar to CO2 ratio, leading to the conclusion that these are transport-induced trends in the abundances of the lighter species.

106 106 ) ) -3 -3 ] ] 2 7 -1.2 2 7 10 10 0 ] / [CO

8 -1.4 8 2 10 10 -0.5 [Ar] / [CO [N 10 10

Density (cm 9 -1.6 Density (cm 9

2 10 2 10 log -1 log CO CO 1010 -1.8 1010 90°S 60°S 30°S 0° 30°N 60°N 90°N 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude Latitude

106 ) 0.5 -3 ] 107 2 0

8 10 -0.5 [O] / [CO 10

Density (cm 9 -1 2 10 log

CO -1.5 1010 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude

4 4 10 1 10 ) ) 1 -3 -3 ] ] 2 2 105 105 0 0 ] / [CO

6 6 2 10 -1 10 -1 [H [He] / [CO 10 10

Density (cm 7 Density (cm 7 2 10 -2 2 10 -2 log log CO CO 108 108 90°S 60°S 30°S 0° 30°N 60°N 90°N 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude Latitude

Figure 3.9: NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and latitude and constrained to local times between 8 a.m. and 4 p.m. Each bin is 5° in width and logarithmically spaced in CO2 density. 123

6 6 10 10 0.5 ) ) -3 -3 ] ] 2 2 107 -1.2 107 0 ] / [CO 108 -1.4 108 2

[Ar] / [CO -0.5 [N 10 10

Density (cm 9 Density (cm 9

2 10 -1.6 2 10 log -1 log CO CO 1010 1010 90°S 60°S 30°S 0° 30°N 60°N 90°N 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude Latitude

106 ) -3

0.5 ] 107 2 0 8 10 -0.5 [O] / [CO 10

Density (cm 9 -1

2 10 log

CO -1.5 1010 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude

104 104 ) 1 ) 1 -3 -3 ] ] 2 2 105 105 0 0 ] / [CO

6 6 2 10 -1 10 -1 [H [He] / [CO 10 10

Density (cm 7 Density (cm 7

2 10 -2 2 10 log log -2 CO CO 108 108 90°S 60°S 30°S 0° 30°N 60°N 90°N 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude Latitude

Figure 3.10: NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and latitude and constrained to local times between 4 p.m. and 12 a.m. Each bin is 5° in width and logarithmically spaced in CO2 density. 124

Ar N O He H 2 2 T 250 A 101 225

2 0 10 200

175 10-1 150 Ratio to CO -2 10 Temperature (K) 125

10-3 100 280 B 101 260

2 100 240

10-1 220 Ratio to CO -2 10 200 Temperature (K)

10-3 180 300 C 101 275

2 0 10 250

225 10-1 200 Ratio to CO -2 10 Temperature (K) 175

10-3 150 90°S 60°S 30°S 0° 30°N 60°N 90°N Latitude

Figure 3.11: Latitudinal trends in the Ar, N2, O, He, and H2 to CO2 ratios and temperature measured by NGIMS at two CO2 densities and from three local time periods. The data were obtained at CO2 densities of 106 cm−3 (solid) and 108 cm−3 (dotted), between (A) 12 a.m. and 8 a.m., (B) 8 a.m. and 4 p.m., and (C) 4 p.m. and 12 a.m. Temperature, T , is given on the right axis. 125

3.3.2 Compositional Trends with Local Time

The most dramatic compositional variations in the neutral atmosphere are diurnal. These variations are apparent in the lighter species toward the bottom of Figure 3.7, where the ∼6 month period of the precession of MAVEN from the dayside to the nightside can be readily deduced by eye. MAVEN periapsis always crosses the morning terminator onto the nightside, then the evening terminator onto the dayside (Figure 3.1B). The diurnal variation can be better visualized by directly

binning the data on local time, using CO2 density as the vertical coordinate, as shown in Figures 3.12–3.14, with the data in each of these ﬁgures constrained to latitude bins of 90°N to 30°N latitude (northern polar), 30°N to 30°S latitude (equatorial), and 30°S to 90°S latitude (southern polar), respectively. We have chosen these latitude bins based on analysis of latitudinal trends in the data, which were discussed in Section 3.3.1. There are clear latitudinal trends in the data which diﬀer around the northern pole, the tropics, and the southern pole.

As described in Section 3.3.1, transport leads to enhancements of the mixing ratios of the lighter species in the colder regions of the atmosphere. This means that subsolar-to-antisolar ﬂow creates a nightside “bulge” in the mixing ratios of the lighter species. This phenomenon has previously been reported in H and He on Earth (Brinton and Mayr, 1971; Reber and Hays, 1973; Brinton et al., 1975) and Venus (Brinton et al., 1980; Niemann et al., 1980b; Taylor et al., 1984), and in He on Mars using NGIMS data (Elrod et al., 2017). Here we report a larger set of data

of the He to CO2 ratio and new observations of this same phenomenon in N2, O, and H2. The nightside bulge can be seen in the ratios to CO2 of all of the species lighter than Ar in Figures 3.12–3.14.

There are latitudinal diﬀerences in the diurnal variation of the lightest species,

He and H2, which are shown quantitatively in Figure 3.15. In the northern polar data (90°N to 30°N, Figure 3.15A), the diurnal variation of the lightest species is diminished relative to the other latitude bins (Figure 3.15, B and C). In addition, the

peak in the He and H2 to CO2 ratios is shifted to later in the day in the northern 126 polar data. For example, in the 90°N to 30°N latitude bin (Figure 3.15A), at a 8 −3 −3 CO2 density of 10 cm , the H2 to CO2 ratio varies from 7.73 × 10 at 5:30 a.m. to 2.79 × 10−3 at 3 p.m. (a factor of 2.76), while in the equatorial data (30°S to

30°N, Figure 3.15B), at the same CO2 density, the H2 to CO2 ratio varies from 10−2 at 3:30 a.m. to 1.8 × 10−3 at 3 p.m. (a factor of 5.47). The same comparison

6 −3 between Figure 3.15, A and B, but made at a CO2 density of 10 cm , yields

6 6

) 10 ) 10 0.5 -3 -3 ] ] 2 2 7 -1.2 7 10 10 0 ] / [CO 108 -1.4 108 2 -0.5 [Ar] / [CO [N 10 9 9 10 Density (cm 10 -1.6 Density (cm 10 2 2 log -1 log CO CO 1010 1010 0 4 8 12 16 20 24 0 4 8 12 16 20 24 Local Time (h) Local Time (h)

) 10 -3

0.5 ] 2 107 0 8 10 -0.5 [O] / [CO

9 -1 10 Density (cm 10 2 log -1.5 CO 1010 0 4 8 12 16 20 24 Local Time (h)

4 4

) 10 1 ) 10 -3 -3 ] 1 ] 2 2 5 5 10 0 10 0 ] / [CO

6 6 2 10 -1 10 -1 [H [He] / [CO 10 7 10 7 Density (cm 10 -2 Density (cm 10 2 2 -2 log log CO CO 108 108 0 4 8 12 16 20 24 0 4 8 12 16 20 24 Local Time (h) Local Time (h)

Figure 3.12: NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and local time and constrained to latitudes between 90°N and 30°N. Each bin is 1 h in width and logarithmically spaced in CO2 density. 127

similar results. The variation of the He and H2 to CO2 ratios in the southern polar data (30°S to 90°S, Figure 3.15C) is similar to that at the equator (Figure 3.15B). Finally, the nightside bulge has a shorter local time duration in the northern polar data (Figure 3.15A) as compared to the equatorial and southern polar data. In the

northern hemisphere, the He and H2 bulges are clear from perhaps 2 or 3 a.m. until 11 a.m. In contrast, at the equator and in the southern hemisphere, the nightside bulge

6 6

) 10 -1 ) 10 0.5 -3 -3 ] ] 2 2 7 7 10 -1.2 10 0 ] / [CO

8 8 2 10 -1.4 10 -0.5 [Ar] / [CO [N 10 9 9 10 Density (cm 10 Density (cm 10 2 -1.6 2 log -1 log CO CO 1010 1010 0 4 8 12 16 20 24 0 4 8 12 16 20 24 Local Time (h) Local Time (h)

) 10 -3 ]

0.5 2 107 0 108 -0.5 [O] / [CO

9 10 Density (cm 10 -1 2 log CO 1010 -1.5 0 4 8 12 16 20 24 Local Time (h)

4 4

) 10 ) 10 1 -3 -3 ] ] 2 1 2 5 5 10 0 10 0 ] / [CO

6 6 2 10 -1 10 [H [He] / [CO -1 10 7 10 7 Density (cm 10 -2 Density (cm 10 2 2

-2 log log CO CO 108 108 0 4 8 12 16 20 24 0 4 8 12 16 20 24 Local Time (h) Local Time (h)

Figure 3.13: NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and local time and constrained to latitudes between 30°N and 30°S. Each bin is 1 h in width and logarithmically spaced in CO2 density. 128

in He and H2 is apparent starting at around 8 p.m. until 10 a.m. or later. All of the diﬀerences noted between the northern polar data and the equatorial and southern polar data appear to be correlated with the temperature. A signiﬁcant amount of warming is observed on the nightside in the northern latitudes (Figure 3.15A, red). This is not seen in the equatorial and southern polar temperatures (Figure 3.15, B and C, red).

6 6 ) 10 -1 ) 10 0.5 -3 -3 ] ] 2 2 7 7 10 -1.2 10 0 ] / [CO

8 8 2 10 -1.4 10 [Ar] / [CO -0.5 [N 10 9 9 10 Density (cm 10 Density (cm 10 2 -1.6 2 log log

CO CO -1 1010 1010 0 4 8 12 16 20 24 0 4 8 12 16 20 24 Local Time (h) Local Time (h)

) 10 -3 0.5 ] 2 107 0 8 10 -0.5 [O] / [CO

9 10 Density (cm 10 -1 2 log CO 1010 -1.5 0 4 8 12 16 20 24 Local Time (h)

4 4

) 10 ) 10 -3 -3 ] ]

1 2 1 2 105 105 0 0 ] / [CO 106 106 2 [H -1 [He] / [CO -1 10 7 10 7 Density (cm 10 Density (cm 10 2 2

-2 log log -2 CO CO 108 108 0 4 8 12 16 20 24 0 4 8 12 16 20 24 Local Time (h) Local Time (h)

Figure 3.14: NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and local time and constrained to latitudes between 30°S and 90°S. Each bin is 1 h in width and logarithmically spaced in CO2 density. 129

The somewhat heavier species, N2 and O, have similar, though smaller diurnal variations when compared to He and H2: there is a clear nightside bulge in both the

N2 and O to CO2 ratios. In the northern polar data, there are two peaks in these ratios. There is one peak at the dawn terminator, around 6 a.m., and one at the dusk terminator, around 6 p.m. (Figure 3.15A). The peaks are more pronounced in

the O to CO2 ratio and, for both species, the peaks are more pronounced higher in 6 −3 the atmosphere — that is, at a CO2 density of 10 cm (solid lines in Figure 3.15,

A through C). The magnitude of the dusk peak in the N2 and O to CO2 ratios

decreases moving toward the southern pole. In the equatorial data, the O to CO2 ratio increases rapidly starting around 7 p.m. (Figure 3.15B), but in the southern polar data, this rise is signiﬁcantly smaller and extended over a longer time.

As in the previous section, the Ar to CO2 ratio is only scarcely aﬀected by solar-

to-antisolar ﬂow. There is no diurnal variation in the Ar to CO2 ratio and thus a

nightside Ar bulge is not present in the data. The Ar to CO2 ratio remains roughly 6 −3 8 −3 constant near 0.1 at a CO2 density of 10 cm and 0.04 at a CO2 density of 10 cm at all local times and in all three latitude bins (Figure 3.15, green). This is again an indication that transport is responsible for the trends observed in the lighter species. Finally, in the southern polar data collected between 30°S and 90°S (Figure 3.15C),

the He to CO2 ratio is equivalent to or greater than the H2 to CO2 ratio. This is in 6 −3 contrast to the northern polar and equatorial data. At a CO2 density of 10 cm ,

the mean H2 to He ratio is 1.7 ± 0.3 in the 30°N to 30°S latitude bin (Figure 3.15B),

but just 1.1 ± 0.3 in the 30°S to 90°S latitude bin (Figure 3.15C). At a CO2 density 8 −3 of 10 cm , the mean H2 to He ratio is 1.5 ± 0.2 in the equatorial data, and just 1.0 ± 0.2 in the southern polar data. 130

Ar N O He H 2 2 T 260 A 101 240

2 0 10 220

200 10-1 180 Ratio to CO -2 10 Temperature (K) 160

10-3 140 260 B 101 240

2 0 10 220

200 10-1 180 Ratio to CO -2 10 Temperature (K) 160

10-3 140 260 C 101 240

2 0 10 220

200 10-1 180 Ratio to CO -2 10 Temperature (K) 160

10-3 140 0 4 8 12 16 20 24 Local Time (h)

Figure 3.15: Diurnal trends in the Ar, N2, O, He, and H2 to CO2 ratios and temperature measured by NGIMS at two CO2 densities and from 6 −3 three latitude bins. The data were obtained at CO2 densities of 10 cm (solid) and 108 cm−3 (dotted), between (A) 90°N and 30°N latitude, (B) 30°N and 30°S latitude, (C) and 30°S and 90°S latitude. Temperature, T , is given on the right axis. 131

3.3.3 Seasonal Variations

The NGIMS data set considered here spans a small portion of MY 32, all of MYs 33 and 34, and the majority of MY 35 (Figure 3.1). While this means that NGIMS has obtained measurements spanning three MYs, providing good coverage in LS, local times and latitudes of these measurements of course vary throughout. These variations must be carefully accounted for in the search for seasonal variations in the upper atmospheric composition the NGIMS data. While the latitudinal variations are relatively small as shown in the previous section, the diurnal variations are much larger and could signiﬁcantly impact the observed seasonal variations.

The ratios of Ar, N2, O, He, and H2 are binned on LS with CO2 as the vertical coordinate in Figures 3.16 and 3.17, spanning local times between 8 a.m. to 5 p.m.

6 −3 and 8 p.m. to 4 a.m., respectively. Slices of this data at CO2 densities of 10 cm and 108 cm−3 are shown in Figure 3.18. In the dayside bin from 8 a.m. to 5 p.m. (Figure 3.18A), there is no discernible seasonal trend in the data. Large variations are seen over 10° to 20° of LS, which are likely due to the precession of MAVEN through local time. That is, these are likely diurnal trends. In the nightside bin, these species’ ratios to CO2 appear to decrease toward minima around LS = 90° and 270°. These time periods correspond to the summer solstices in the northern and southern hemispheres, respectively, which are important points in the seasonal

CO2 cycle on Mars. At these points in the Martian orbit, the CO2 mixing ratio is maximized as CO2 sublimates from the northern polar cap earlier in the Martian year, near aphelion, and the southern polar cap late in the Martian year, just after perihelion.

To better visualize the seasonal variation of the mixing ratio of the noncondens-

7 −3 able gases, the Ar to CO2 ratio at a CO2 density of 10 cm for the inbound portion of every MAVEN orbit is shown in Figure 3.19. The data in this ﬁgure are not ﬁl- tered by local time. Since there is essentially no diurnal variation in the Ar to CO2 ratio (Section 3.3.2), the seasonal variation in this ratio is not occluded by a diurnal trend. In this data, sublimation of CO2 from the northern polar cap near LS = 90° 132

and from the southern polar cap near LS = 290°, produces corresponding troughs in

Ar/CO2. This is the same trend observed in the lower atmosphere near the equator by the Sample Analysis at Mars instrument suite on the Curiosity rover (Trainer et al., 2019). Global circulation models predict the observation of only one trough in the Ar to CO2 ratio in the lower atmosphere in the southern hemisphere near the pole (the trough near LS = 90°) and, similarly, only one trough in the Ar to

CO2 ratio in the lower atmosphere in the northern hemisphere near the pole (the trough near LS = 270°) (Lian et al., 2012). In comparison, NGIMS measurements

) 6 ) 6 -3 -3 10 10 ] -1 ] 0.5 2 2 7 7 10 -1.2 10 0 ] / [CO

8 8 2 10 -1.4 10 -0.5 [Ar] / [CO [N

9 10 9 10

Density (cm 10 -1.6 Density (cm 10

2 2 -1 log 10 10 log

CO 10 CO 10 0 60 120 180 240 300 360 0 60 120 180 240 300 360 L (degrees) L (degrees) S S

) 6

-3 10 ]

0.5 2 107 0 8 10 -0.5 [O] / [CO

9 -1 10

Density (cm 10 2 log 10 -1.5

CO 10 0 60 120 180 240 300 360 L (degrees) S

) 4 ) 4 -3 -3 ] 10 10 ]

1 2 1 2 5 5 10 0 10 0 ] / [CO

6 6 2 10 -1 10 -1 [H [He] / [CO 7 7 10 -2 10 Density (cm 10 Density (cm 10 -2 2 2 log 8 -3 log 8

CO 10 CO 10 0 60 120 180 240 300 360 0 60 120 180 240 300 360 L (degrees) L (degrees) S S

Figure 3.16: NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and LS and constrained to local times between 8 a.m. and 5 p.m. Each bin is 10° in width and logarithmically spaced in CO2 density. 133

in the upper atmosphere are similar in both hemispheres, which indicates such a hemispherical dichotomy is eliminated by horizontal transport before reaching the

NGIMS sampling range. The mean Ar to CO2 ratio peaks at a value of 0.063 at

LS = 185° and the troughs correspond to values of 0.051 at LS = 85° and 0.039 at

LS = 285°.

) 6 ) 6

-3 10 -3 10 ] -1 ] 2

2 0.5 7 7 10 -1.2 10 0

8 8 ] / [CO 10 -1.4 10 2 -0.5 [Ar] / [CO 9 9 [N

-1.6 10 10

Density (cm 10 Density (cm 10 2 2 -1 log 10 -1.8 10 log

CO 10 CO 10 0 60 120 180 240 300 360 0 60 120 180 240 300 360 L (degrees) L (degrees) S S

) 6

-3 10

1 ] 2 107 0 108 [O] / [CO

9 10

Density (cm 10 -1 2 10 log

CO 10 0 60 120 180 240 300 360 L (degrees) S

) 4 ) 4 -3 -3

10 ] 10 ] 2 1 2 1 105 105 0 0 6 6 ] / [CO 10 -1 10 2

-1 [H 7 [He] / [CO 7 10 10

Density (cm 10 -2 Density (cm 10

2 2 -2 log 8 log 8

CO 10 CO 10 0 60 120 180 240 300 360 0 60 120 180 240 300 360 L (degrees) L (degrees) S S

Figure 3.17: NGIMS Ar, N2, O, He, and H2 to CO2 ratios binned on CO2 density and LS and constrained to local times between 8 p.m. and 4 a.m. Each bin is 10° in width and logarithmically spaced in CO2 density. 134

Ar N O He H 2 2 T 300 A 101 280

260 100 2 240

220 10-1 200 Ratio to CO Temperature (K) 10-2 180

160

-3 10 140 300 B 101 280

260 100 2 240

220 10-1 200 Ratio to CO Temperature (K) 10-2 180

160

-3 10 140 0 40 80 120 160 200 240 280 320 360 L (degrees) S

Figure 3.18: Seasonal trends in the Ar, N2, O, He, and H2 to CO2 ratios and temperature measured by NGIMS at two CO2 densities and during 6 −3 two local time periods. The data were obtained at CO2 densities of 10 cm (solid) and 108 cm−3 (dotted), between (A) 8 a.m. and 5 p.m. and (B) 8 p.m. and 4 a.m. Temperature, T , is given on the right axis. 135

0.1 0.09 Southern Northern 0.08

0.07

0.06 ] 2 0.05

0.04 [Ar] / [CO

0.03

0.02 0 30 60 90 120 150 180 210 240 270 300 330 360 L (degrees) S Figure 3.19: The seasonal variation of Ar in the upper atmosphere as 7 −3 measured by NGIMS. Inbound Ar to CO2 ratio at a CO2 density of 10 cm for each MAVEN orbit in the southern (red triangles) and northern (blue crosses) hemispheres. These data are not constrained by latitude or local time. The black line is the mean of all of the data shown. 136

3.3.4 Comparisons with Previous Work

Previous NGIMS measurements of multiple neutral species have been published (Ma- haﬀy et al., 2015a; Elrod et al., 2017, 2020). The He bulge has been previously reported (Elrod et al., 2017) and we extend those measurements here with an additional 4 years of observations. NGIMS observed the impact on the neutral atmosphere of the global dust storm which occurred in MY 34 (Elrod et al., 2020) and a day-by-day comparison with MENCA has been made for this period showing good agreement between the instruments (Rao et al., 2020). A previous investigation of the dawn/dusk asymmetry in the CO2, Ar, N2, and He abundances and Ar temperatures at constant altitude has been published (Gupta et al., 2019). Though we use here the CO2 density as a vertical coordinate rather than altitude, there appears to be broad agreement between the results of Gupta et al. (2019) and ours. Finally, we note that in Mahaﬀy et al. (2015a), the initial report of the NGIMS data after arrival at Mars, NO and O2 abundances were reported. Subsequent analysis of the entire NGIMS data set strongly suggests that the NO and O2 abundances previously reported were contaminated by recombination of N and O (for NO) or two O atoms

(for O2) on the inner walls of the spectrometer.

3.3.4.1 Viking Entry Probes

The landers deployed by Viking 1 and 2 used mass spectrometers to measure the abundances of neutral species as they descended through the upper atmosphere, including those of CO2, Ar, and N2 (McElroy et al., 1976; Nier and McElroy, 1976,

1977). Shown in Figure 3.20 are the Ar and N2 to CO2 ratios measured by the Viking landers alongside mean NGIMS DD and AB values. The Viking 1 Ar to

CO2 ratio (Figure 3.20, green circles) is significantly smaller than any measured by NGIMS during the 9 DDs and the AB period, though its slope agrees quite well with that of the NGIMS profiles, except for the lowest Viking 1 data point. Similarly, the Viking 2 N2 to CO2 ratio is significantly smaller than any measured by NGIMS 10 −3 at CO2 densities <3 × 10 cm . The Viking 2 Ar to CO2 ratio (Figure 3.20, green 137 triangles) agree well in slope and magnitude with the NGIMS measurements at 9 −3 CO2 densities >10 cm , though higher in the atmosphere the Viking 2 Ar to CO2 ratio does not increase as expected according to diffusive equilibrium as seen in the

NGIMS and Viking 1 data. The Viking 1 N2 to CO2 ratio agrees relatively well in slope and magnitude with the smallest of these ratios measured by NGIMS during the DD and AB periods. Since we compare here the Ar and N2 to CO2 ratios, there are two ways to interpret the observed disagreement: (1) the Ar and N2 abundances measured by the Viking landers are smaller than those measured by NGIMS or

(2) the CO2 abundance measured by the Viking landers is systematically larger than that measured by NGIMS. The CO2 abundance in the Martian atmosphere varies significantly due to its cyclical exchange between atmospheric and surface reservoirs (Haberle et al., 2017b), while Ar and N2 are noncondensable gases and so do not experience such a cycle. Additionally, it should be noted that we are comparing two single-orbit profiles obtained by the two Viking landers to mean profiles from the DD and AB periods of the NGIMS data and that there is significant orbit-to-orbit variability observed in the NGIMS data. This orbit-to-orbit variability could account for some disagreement between the three instruments.

3.3.4.2 Imaging Ultraviolet Spectrograph (IUVS)

Densities of N2 and CO2 are measured by the MAVEN IUVS instrument in an altitude range which overlaps with NGIMS measurements (Evans et al., 2015; Yoshida et al., 2020). Recently some limited O densities have also been reported using measurements from the OI 130.4 nm emission (Qin, 2020). Note that, though the instruments are mounted on the same spacecraft, they are measuring different locations in the atmosphere at any given time. This is because NGIMS measures the atmosphere at the location of the spacecraft, while IUVS measures the atmosphere at some distance from the spacecraft, where atmospheric conditions can be significantly different from those observed at MAVEN. In Figure 3.20, we compare the NGIMS

N2 to CO2 ratio from the DDs and AB period to the vertical proﬁle of the N2 to

CO2 ratio presented in Figure 1c of Evans et al. (2015). The IUVS proﬁle is an 138

108 ) -3

109 Density (cm 2 CO 10 10 Ar VL1 Ar VL2 N VL1 2 N VL2 2 N IUVS 2 1011 10-2 10-1 100 Ratio to CO 2 Figure 3.20: Comparison of NGIMS data with Viking Lander and MAVEN IUVS data. NGIMS DD and AB Ar and N2 to CO2 ratios (grey lines) are shown with Viking Lander 1 and 2 Ar to CO2 ratios (red circles and blue dia- monds, respectively), Viking Lander 1 and 2 N2 to CO2 ratios (green crosses and purple triangles, respectively), and the MAVEN IUVS N2 to CO2 ratio (orange squares). Viking data was digitized from Nier and McElroy (1977), Figures 3 (CO2 and Ar) and 4 (N2). The IUVS measurements are an ensemble average from Evans et al. (2015). ensemble average of 82 limb scans obtained on 18–22 September 2014 and 16–18 November 2014, at latitudes between −5 to 35°, and local times around 2 p.m. (for the September measurements) and 11 a.m. (for the November measurements). NGIMS measurements from the DDs and AB period were obtained over numerous orbits between 2014 and 2019 and over a wide range atmospheric conditions 3.1.

There is signiﬁcant disagreement between the magnitude of the mean of the 139

IUVS measurements of the N2 to CO2 ratio obtained from the VK bands (Evans et al., 2015) and the mean NGIMS DD and AB measurements of the N2 to CO2

ratio, as shown in Figure 3.20. The mean of the IUVS N2 to CO2 ratio is smaller

than all of the N2 to CO2 ratios for the 9 DDs and AB period, except for the lowest 10 −3 IUVS data point near a CO2 density of 6.5 × 10 cm . The uncertainty in the IUVS data becomes relatively large in this part of the atmosphere and, within the uncertainties of the two instruments, they agree.

While there is a signiﬁcant diﬀerence between the magnitudes of the IUVS and

NGIMS N2 to CO2 ratios, the diﬀerence in slopes of these ratios is more compelling.

The NGIMS N2 to CO2 ratios have a relatively constant slope over the entire density

range shown in Figure 3.20, which is expected in the heterosphere, where N2 and

CO2 follow scale heights proportional to their mass as described above. The temperature is the only variable producing signiﬁcant changes in the scale height and

N2 and CO2 are in thermal equilibrium in this region (Stone et al., 2018), meaning their scale heights are aﬀected identically by changes in temperature. Thus, only variations of the atmospheric composition with height can explain variations in the slopes of the proﬁles in Figure 3.20. In contrast to the relatively constant slopes of

the NGIMS data, the slope of the mean IUVS N2 to CO2 ratio varies significantly: 10 10 −3 deeper in the atmosphere, between CO2 densities of ∼6.5 × 10 to 2.5 × 10 cm , the slope of the IUVS profile is negative. The slope of the profile then becomes positive moving upward in the atmosphere. One physical mechanism that could lead to such variations in the composition of the atmosphere is the transition from the homosphere to the heterosphere; that is, the presence of the homopause could explain the variation in composition observed by IUVS. However, the homopause has not been detected in any NGIMS data and is not apparent in the Viking measurements, but was expected to occur at around 120 to 130 km according to their analysis (Nier and McElroy, 1977). 140

3.3.4.3 Mars Global Ionosphere-Thermosphere Model (M-GITM)

The Mars Global Ionosphere-Thermosphere Model (M-GITM, see Bougher et al. (2015c)) is a 3D global circulation model (GCM) of the Martian upper atmosphere. M-GITM makes predictions of the variation of neutral species with local time, latitude, season, and solar cycle. Earlier comparisons between the He bulge observed by NGIMS and that predicted by M-GITM have been discussed previously (Elrod et al., 2017) and predictions made by M-GITM of a nightside He bulge remain generally consistent with NGIMS observations. Qualitative comparisons can be made

between the O to CO2 ratio measured by NGIMS and that predicted by M-GITM in Bougher et al. (2015c). The diurnal variation of the O to CO2 ratio is dependent on season and is asymmetric with respect to latitude (Bougher et al., 2015c, Figures

5 and 6). In all cases, though, there are peaks in the predicted O to CO2 ratio at the dawn and dusk terminators, which are observed in the NGIMS data. The peak observed by NGIMS at the dusk terminator in the southern latitudes (30°S to 90°S, Figure 3.15C) is smaller than that observed in the other two latitude bins. During perihelion (southern summer) and solar maximum conditions, M-GITM predicts the largest diurnal variation of the O abundance, but relatively little diurnal variation

in the O to CO2 ratio in the southern hemisphere (Bougher et al., 2015c, Figure 6, c and d). This is because the southern hemisphere, poleward of ∼60°S, is relatively warm throughout the day during southern summer, so the transport-induced bulge in O is of smaller magnitude. Thus, the observed difference between the NGIMS observations in the southern latitudes (Figure 3.15C) and that of the northern and equatorial latitudes (Figure 3.15, A and B) could be due to the effect of season on the temperature and transport in the southern hemisphere. With relatively sparse coverage of season in the NGIMS data set (Section 3.3.3), such seasonal effects are difficult to constrain. To carry out more quantitative comparisons between M- GITM predictions and the NGIMS observations, it will be necessary to compare the modeled and measured mixing ratios of the lighter species at a constant density level. 141

3.4 Conclusion

We have calculated upper atmospheric abundances of CO2, Ar, N2, O, He, and

H2, and the ratios of the lighter species to CO2, with high vertical resolution and

excellent coverage in local time and latitude, and good coverage in LS. We observe large diurnal variations in the composition of the upper atmosphere and smaller variations with latitude. While the magnitude of these variations makes it diﬃcult to observe the eﬀect of changing Martian seasons, the seasonal CO2 cycle is clear in the upper atmospheric Ar to CO2 ratio, which increases and decreases as CO2 is deposited on to and sublimes from the polar caps.

This is the ﬁrst report of the vertical distribution of H2 in the upper atmosphere of Mars. The column abundance of H2 on Mars has been measured using

FUSE (Krasnopolsky and Feldman, 2001). H2 is an important carrier of hydrogen from the lower atmosphere to the upper atmosphere, where the H2 is dissociated to produce H atoms which can escape to space. H2 can also escape directly via the

Jeans mechanism. Thus, the abundance and variation of H2 with time is signiﬁcant for studies of atmospheric escape. Our observations indicate there is a substantial nightside bulge in the H2 abundance, with the H2 to CO2 ratio decreasing by a maximum of a factor of 6 from the morning terminator to the evening terminator. The implications of such transport-induced diurnal variations must be investigated further.

The O to CO2 ratio is another important quantity in the upper atmosphere since collisions between O and CO2 are particularly eﬃcient in exciting the CO2 ν2 vibrational state, which leads to cooling when this excitation is quenched by the emission of a photon at a wavelength of 15 µm. This is an important cooling mechanism in the lower thermosphere (Bougher et al., 2015c; Stone et al., 2018). Thermal energy deposited in the upper thermosphere is conducted downward where it is ra-

diated away by CO2 in this 15 µm band. O is also responsible for the absorption of EUV photons at relatively low densities high in the atmosphere (altitudes greater than ∼200 km). While O dayglow measurements provide important constraints on 142 the O abundance in the thermosphere (Chaufray et al., 2009, 2015a; Ritter et al., 2019), direct measurements made by NGIMS provide information on the vertical, horizontal, and temporal variation of the O abundance and O to CO2 ratio. Such measurements are critical for understanding and modeling of the energy balance in the upper atmosphere, and thus for important physical processes like thermal escape as well. Compositional measurements from NGIMS will continue to drive and facilitate investigations of the upper atmosphere of Mars, the escape of the atmosphere to space, and the impact this escape has had on the evolution of the Martian climate through time. Ongoing comparisons between the NGIMS data and 1D photochemical and energy balance models and 3D global circulation models will lead to an improved understanding of chemical processes in the upper atmosphere, enable a detailed accounting of heating and cooling rates in vastly diﬀerent atmospheric and solar conditions, and elucidate the importance of horizontal transport and waves in the upper atmosphere. The accuracy of such models will be improved in turn. Mars is the solar system’s best laboratory for atmospheric escape to space and NGIMS observes these escape processes in spectacular detail. The characterization of Mars’ past and present atmospheric loss will inform our studies of the billions of planets outside of our solar system, a population of planets in which there is an “evaporation valley” carved by atmospheric escape and a “cosmic shoreline” separating planets with atmospheres from those without (Owen and Wu, 2017; Zahnle and Catling, 2017). 143

CHAPTER 4

Hydrogen Escape from Mars is Driven by Seasonal and Dust Storm Transport of Water

The results presented in this chapter were published in Stone et al. (2020).

4.1 Introduction

Though Mars is currently cold and dry, it was warmer and wetter billions of years ago (Wordsworth, 2016; Haberle et al., 2017a; Ramirez and Craddock, 2018). Strong evidence for this comes from enrichment of D/H in the Martian atmosphere and surface minerals relative to that of Earth, indicating that the vast majority of

Mars’ H2O was lost to space over the last ∼4 billion years (Jakosky and Phillips,

2001; Jakosky et al., 2018). In the classical paradigm, H2O was thought to be conﬁned to low altitudes below a hygropause (a cold layer at 40–50 km altitude at

which H2O condenses), while H2, produced in the lower atmosphere by the photodissociation of H2O and the odd hydrogen (HOx ) cycle, diffuses into the upper atmosphere where it is dissociated, producing H which escapes to space (Hunten and McElroy, 1970; Parkinson and Hunten, 1972; McElroy and Donahue, 1972; Lefèvreand Krasnopolsky, 2017). Recent observations of rapid order-of-magnitude variations in the exospheric H abundance contradict this classical picture, which de- livers H to the exosphere in a slow-and-steady manner (Chaffin et al., 2014; Clarke et al., 2014; Bhattacharyya et al., 2015; Clarke et al., 2017; Mayyasi et al., 2017; Halekas, 2017; Bhattacharyya et al., 2017b; Chaffin et al., 2018; Mayyasi et al., 2019). Using measurements from the NASA Mars Atmosphere and Volatile Evolu- tioN (MAVEN, see Jakosky et al. (2015)) Neutral Gas and Ion Mass Spectrometer (NGIMS, see Mahaffy et al. (2015b)), which samples in situ the neutral and ionic species in the Martian upper atmosphere, we observe the effects of the delivery of

H2O, another source of H, directly to the upper atmosphere of Mars. From these 144

measurements we infer the abundances of H2O and H2 in the upper atmosphere to investigate the variation of these hydrogen sources seasonally, diurnally, and amid both a regional and global dust storm. We demonstrate that, during the MAVEN

era, there is always >1 ppm H2O in the upper atmosphere of Mars, the upper atmospheric H2O abundance varies seasonally and this H2O is a strong and possibly dominant source of H atoms escaping the atmosphere of Mars. We also show that

dust storms dramatically increase the upper atmospheric H2O abundance over the course of just a few sols.

Slow and steady delivery of H2 from the lower atmosphere cannot explain recent observations of rapid order-of-magnitude variations in the exospheric H abundance and escape flux (Chaffin et al., 2014; Clarke et al., 2014; Bhattacharyya et al., 2015; Clarke et al., 2017; Mayyasi et al., 2017; Halekas, 2017; Bhattacharyya et al., 2017b; Chaffin et al., 2018; Mayyasi et al., 2019). These variations have been observed by Mars Express (MEX) Spectroscopy for the Investigation of Characteristics of the Atmosphere of Mars (SPICAM) in the ultraviolet (Chaffin et al., 2014), the Hub- ble Space Telescope (HST) (Clarke et al., 2014; Bhattacharyya et al., 2015, 2017b), and MAVEN Imaging Ultraviolet Spectrograph (IUVS) (Clarke et al., 2017; Chaffin et al., 2018). IUVS has also observed rapid variations in the upper atmospheric D abundance (Mayyasi et al., 2017, 2019). Measurements made by the MAVEN Solar Wind Ion Analyzer (SWIA) of protons penetrating into the upper atmosphere provide an independent confirmation of the variation of the exospheric H abundance (Halekas, 2017). All of these variations correlate with Martian season and dust activity in the lower atmosphere, peaking in southern summer when Mars is closest to the Sun and dust activity is at its yearly maximum. The HST (Clarke et al., 2014) and SPICAM (Chaffin et al., 2014) observations reported in 2014 correspond to the decline of the global dust storm of Mars year (MY) 28, while later observations from HST and IUVS demonstrate a seasonal increase in the exospheric H abundance in the absence of a global dust storm (Bhattacharyya et al., 2015; Clarke et al., 2017; Bhattacharyya et al., 2017b; Chaffin et al., 2018). However, since dust activity also varies seasonally it is often difficult to separate seasonal 145

eﬀects from the inﬂuence of dust. The most likely cause for rapid variation in the exospheric H abundance is direct

transport of H2O — the most abundant hydrogen-bearing species in the Martian atmosphere — into the middle and upper atmosphere. This transport is possible due to a weakening of the hygropause, which is warmed and raised in altitude as a result of increased solar insolation around perihelion and heating caused by dust in the atmosphere. Once in the upper atmosphere, H2O is destroyed through reactions with ionic and neutral species and ionized and dissociated by photons and suprathermal electrons (Fox et al., 2015; Krasnopolsky, 2019).

The vertical distribution of H2O in the Martian middle atmosphere (∼15 to 90 km altitude) has recently been measured by a number of instruments. SPICAM solar occultations in the infrared (IR) have shown that the middle atmospheric

abundance of H2O is often far in excess of the value implied by the vapor pressure at the hygropause and that transient events substantially alter the vertical distri-

bution of H2O (Fedorova et al., 2009; Maltagliati et al., 2011a, 2013). The most recent analysis of SPICAM IR occultations demonstrated a southern summer peak

in the H2O abundance at 50–80 km and an order-of-magnitude increase in the H2O abundance during the MY 28 global dust storm (Fedorova et al., 2018), coincident with observed variations in exospheric H abundance (Clarke et al., 2014; Chaffin et al., 2014). Observations from the Mars Climate Sounder (MCS) onboard the Mars Reconnaissance Orbiter (MRO) and the Observatoire pour la Minéralogie, l’Eau, les Glaces, et l’Activité(OMEGA) spectrometer onboard MEX demonstrate that the hygropause height rises in southern summer and peaks around perihelion,

thus allowing H2O into the middle atmosphere (Maltagliati et al., 2011b; Heavens et al., 2018, 2019). According to MCS, the hygropause was lifted to ∼80 km altitude during the MY 28 and MY 34 global dust storms, higher than during any other period observed (Heavens et al., 2018, 2019). The Nadir and Occultation for MArs Discovery (NOMAD) and Atmospheric Chemistry Suite (ACS) instruments onboard the ESA ExoMars Trace Gas Orbiter (TGO) observed a rapid increase in

the H2O abundance in the middle atmosphere during the MY 34 global dust event, 146 with peak abundances reaching more than 250 ppm near 40 km (Vandaele et al.,

2019). This collection of observations indicates that the H2O abundance in the middle atmosphere increases seasonally, peaking in southern summer, and is enhanced further during global dust events.

Seasonal variations in the column-integrated H2O abundance have been obtained from orbit by the Mars Atmospheric Water Detector (MAWD) instruments onboard the Viking orbiters in MYs 12, 13, and 14 (Jakosky and Farmer, 1982; Fedorova et al., 2010), the Thermal Emission Spectrometer (TES) onboard Mars Global Surveyor (MGS) in MYs 24–26 (Smith, 2004), OMEGA in MYs 26–27 (Maltagliati et al., 2011b), the Planetary Fourier Spectrometer (PFS) onboard MEX in MYs and 26– 29 (Fouchet et al., 2007; Tschimmel et al., 2008; Sindoni et al., 2011; Wolkenberg et al., 2011), SPICAM in MYs 27–31 (Trokhimovskiy et al., 2015), and the Com- pact Reconnaissance Imaging Spectrometer for Mars (CRISM) onboard MRO in

MYs 28–33 (Smith et al., 2009, 2018). And though the middle atmospheric H2O abundance has been shown to peak during southern summer and to increase rapidly during global dust events, in contrast the column-integrated H2O abundance has been shown to decrease in the southern hemisphere during global dust events in MYs 12, 25, and 28 (Smith, 2004; Smith et al., 2009; Fedorova et al., 2010; Trokhi- movskiy et al., 2015; Smith et al., 2018). This decrease is attributed to adsorption of

H2O onto regolith which is cooled due to greater absorption of sunlight by dust well above the surface. Further, the largest peak in the lower atmospheric H2O abundance occurs during northern summer, not southern summer (Jakosky and Farmer, 1982; Smith, 2004; Smith et al., 2009; Fedorova et al., 2010; Maltagliati et al., 2011b; Fouchet et al., 2007; Tschimmel et al., 2008; Sindoni et al., 2011; Wolkenberg et al., 2011; Trokhimovskiy et al., 2015; Smith et al., 2018), and is due to sublimation of

H2O ice from the northern polar cap. Thus, the trends in lower and middle/upper atmosphere H2O abundances are not always directly correlated and are surprisingly antithetical during global dust storms. This implies that one or more processes operating most eﬃciently during southern summer near perihelion are responsible for the vertical transport of H2O to the middle and upper atmosphere. 147

There is strong circumstantial evidence connecting seasonal changes in the vertical distribution of H2O to observed rapid increases in the H escape rate at Mars, but until now there has been no direct evidence for the presence and eﬀects of this

H2O in the upper atmosphere. We test the hypothesis that upward transport of

H2O leads to rapid variations in the H escape rate using data obtained by NGIMS and a 1D photochemical model. We detect the chemical intermediates that lie between H2O delivered from the lower atmosphere and H escape from the top of the atmosphere. NGIMS measures the abundances of ions produced through ion- + ization and dissociation of H2O — for example, H2O — or through ion-neutral + reactions with a hydrogen-bearing species such as H2O or H2 — for example, H3O + and HCO (Benna et al., 2015a). Assuming photochemical equilibrium, H2O abun-

dances are calculated from these ion measurements, and the variation of H2 is measured directly by NGIMS, providing insight into the variation in the upper atmosphere of these hydrogen reservoirs and their impact on H escape to space. The

variation of H2O in the upper atmosphere with season, during a regional dust storm in MY 32, and during the global dust storm of MY 34 is investigated. The classical H escape paradigm stipulates that photolysis of neutral species in the lower atmosphere is a critical aspect of H escape from Mars. We use a 1D photochemical model

to determine that ion reactions with H2O in the upper atmosphere are a strong and possibly dominant production mechanism of escaping H atoms.

4.2 Methods

4.2.1 MAVEN NGIMS Ion and Neutral Abundances

Ion abundances were obtained from MAVEN NGIMS Level 2 version 8 revision 1 data ﬁles (Benna et al., 2015a,b). HCO+ abundances, calculated from data at mass + + per charge (m/z) 29, are not corrected for the presence of HOC and N2H in the atmosphere, which also have a mass of 29 u and combined represent ∼8 × 10−4 % of the signal at 150 km altitude (MAVEN’s periapsis) according to 1D photochemical models which include these species (Fox, 2015; Fox et al., 2015). The electron abundance 148 was assumed to be equivalent to the total ion abundance (that is, charge neutrality is assumed). Neutral CO2,N2, Ar, O, and H2 densities and neutral temperature and pressure were calculated from NGIMS Level 1 export version 12 revision 1 data

ﬁles as described previously (Stone et al., 2018). H2 measurements are presented in arbitrary units because the absolute calibration of the instrument is currently unknown at m/z = 2, which corresponds to H2. Otherwise the H2 measurements are derived in the same manner that the other neutral measurements are, including all of the same corrections. The count rate in the channel thus demonstrates the relative variation of the H2 density. D is also counted at m/z = 2, but because the

D abundance is ∼1 % of the expected H2 abundance in this region, the correction would be negligible (well within the uncertainty in any NGIMS measurement, see below) and would not impact our analysis. We use NGIMS measurements taken when spacecraft potential is greater than −3.5 V, as the quality of some NGIMS ion measurements can be degraded by large, negative spacecraft potentials. This precludes, for example, the observation of the regional dust events in MY 33.

4.2.2 Calculation of Water Abundances

H2O is not directly measured by NGIMS because the signal in the relevant m/z channel, m/z = 18, is dominated by H2O synthesized in the instrument by reactive oxygen species and H2O produced by instrument outgassing. H2O abundances were calculated assuming photochemical equilibrium in the region sampled by NGIMS + using the production and loss reactions of H3O shown below.

+ − α1 H3O + e −−→ OH + H + H (SR1)

α2 −−→ H2O + H (SR2)

α3 −−→ OH + H2 (SR3)

α4 −−→ O + H2 + H (SR4)

+ k1 + HCO + H2O −−→ H3O + CO (SR5)

+ k2 + H2O + H2O −−→ H3O + OH (SR6) 149

+ + Thus, by assuming the production rate of H3O is equal to the loss rate of H3O (photochemical equilibrium), we construct the equation,

+ − + + (α1 + α2 + α3 + α4)[H3O ][e ] = (k1[HCO ] + k2[H2O ])[H2O], (4.1)

and solve for the H2O abundance to obtain,

+ − [H3O ][e ] [H2O] = (α1 + α2 + α3 + α4) + + . (4.2) k1[HCO ] + k2[H2O ] where the rates were obtained from the University of Manchester Institute of Science and Technology (UMIST) Database for Astrochemistry (UDfA) (McElroy et al., 2013; Jensen et al., 2000; Adams et al., 1978; Huntress and Pinizzotto, 1973):

−7 0.5 3 −1 −8 0.5 3 −1 α1 = 3.05 × 10 (300/Te) cm s , α2 = 7.1 × 10 (300/Te) cm s , −8 0.5 3 −1 −9 0.5 3 −1 α3 = 5.4 × 10 (300/Te) cm s , α4 = 5.6 × 10 (300/Te) cm s , −9 0.5 3 −1 −9 0.5 3 −1 k1 = 2.5 × 10 (300/Ti) cm s , and k2 = 2.1 × 10 (300/Ti) cm s , where

Te is the electron temperature and Ti is the ion temperature. The electron and ion temperatures were assumed equal to the neutral temperature in the atmospheric region examined. + H3O is a terminal ion in the Martian ionosphere, so is only destroyed by dissociative recombination (reactions SR1–SR4), though there are other reactions which + produce H3O that are excluded from the above analysis because the rates of these + reactions are so slow that they do not appreciably impact the H3O abundance (Fox, 2015; Fox et al., 2015; Krasnopolsky, 2019),

+ + H2O + H2 −−→ H3O + H, (SR7)

+ + HO2 + H2O −−→ H3O + O2, (SR8)

+ + HCO2 + H2O −−→ H3O + CO2, (SR9)

+ + H2 + H2O −−→ H3O + H, (SR10)

+ + H3 + H2O −−→ H3O + H2, (SR11)

+ + OH + H2O −−→ H3O + O, and (SR12)

+ + NH + H2O −−→ H3O + N. (SR13) 150

Proton transfer reactions SR8–SR13 do not appear to be included in previously published 1D photochemical models (Fox et al., 2015; Krasnopolsky, 2019), but are included in our 1D photochemical model. The column-integrated rates of these reactions are presented in Table 4.1.

Reaction Column Rate (cm−2 s−1) + 8 All H3O Production 2.1 × 10 SR7 3.4 × 10−2 SR8 6.2 × 10−5 SR9 1.4 × 100 SR10 5.4 × 10−3 SR11 2.1 × 101 SR12 6.4 × 10−2

Table 4.1: Column-integrated Rates for Excluded Reactions. Rates calculated by our 1D photochemical model. See Section 4.2.6 for details regarding this model.

4.2.3 Uncertainties in NGIMS Densities and Derived Quantities

Atmospheric ion densities measured by NGIMS are aﬀected by both statistical uncertainty, which can be estimated using Poisson counting statistics, and systematic uncertainty in the absolute sensitivity of the instrument to the species measured. The statistical uncertainty associated with an NGIMS measurement is given √ by σ = n, where n is the number of counts measured by the detector in a 27 ms integration period. This statistical uncertainty is visible as the point-to-point scatter in the data and is substantially smaller than systematic uncertainties as discussed elsewhere (Benna et al., 2015a,b; Stone et al., 2018). The uncertainty in NGIMS ion abundances is about 25% (Benna et al., 2015a,b). According to UDfA, the uncertainties in α1, α2, α3, α4, and k2 are 25% and the uncertainty in k1 is 50%. The relative standard deviation in calculated H2O abundances is obtained by adding in 151 quadrature the uncertainties in the NGIMS ion abundances and relevant reaction rates (Bevington, 2003). Splitting Equation 4.2 into parts for propagation of error yields,

a = α1 + α2 + α3 + α4, (4.3)

+ b = k1[HCO ], (4.4)

+ c = k2[H2O ], and (4.5)

d = b + c, (4.6) and the uncertainties in each of these quantities, indicated with subscripts, is,

q 2 2 2 2 σa = σα1 + σα2 + σα3 + σα4 , (4.7) σ √ b = 0.502 + 0.252, (4.8) b σ √ c = 0.252 + 0.252, and (4.9) c q 2 2 σd = σb + σc . (4.10)

Because Equations 4.7 and 4.10 give absolute uncertainties, while Equations 4.8 and 4.9 give relative uncertainties, we convert equations 4.7 and 4.10 to relative uncertainties by dividing them by a and d, respectively. Similarly, to calculate σd, we convert σb/b and σc/c to absolute uncertainties by multiplying them by b and c, respectively. Finally, the standard deviation in the H2O abundance is given by,

s 2 2 2 2 + − σa σd σH3O σe σH2O = + + + + − , (4.11) a d [H3O ] [e ]

+ − + − where σH3O /[H3O ] and σe /[e ] are both 0.25. The result is a systematic uncer- 8 −3 9 −3 tainty between 50% and 69% between CO2 densities of 5 × 10 cm and 10 cm . The mean uncertainty in this region is 68% and the median is 69%. 152

4.2.4 Validity of the Photochemical Equilibrium Assumption

The assumption of photochemical equilibrium is a standard model technique to calculate the abundances of atmospheric species on several planets (Hunten and McElroy, 1970; Parkinson and Hunten, 1972; Brinton et al., 1980; Fox and Dalgarno, 1981) and has been validated extensively in the upper atmosphere of Mars using 1D photochemical models (Fox, 2015; Fox et al., 2015; Krasnopolsky, 2019). These 1D models demonstrate that most ions are in photochemical equilibrium in the lower

thermosphere, where we calculate H2O abundances. To determine the region of the atmosphere in which the assumption of photochemical equilibrium is valid, we

compare the chemical time constant, τC, and the time constant for transport by + diﬀusion, τD, of H3O , for the calculation of H2O abundances. The chemical time constant is the timescale required for complete destruction of the species in question,

N τ = i , (4.12) C L

where Ni is the number density of the ion and L is the rate of its destruction. The

time constant for diﬀusion, τD, is given by,

H2 τ = p , (4.13) D D

where D is the diﬀusion coeﬃcient of the ion and Hp is the plasma scale height,

2kTp Hp = . (4.14) mig

In Equation 4.14, Tp = (Te + Ti)/2 is the plasma temperature, k is the Boltzmann constant, and mi is the mass of the ion. The diffusion coefficient D in Equation 4.13 is calculated from the densities of the relevant species and diffusion coefficients of the ion through those gases,

N N N N + N − tot = CO2 + O + O2 + e , (4.15) + − D DiCO2 DiO DiO2 Die where Ntot is the sum of the densities appearing on the righthand side of the equation, with species indicated by subscripts. The individual diﬀusion coeﬃcients for 153

the ion diﬀusing through CO2 and O, which are the major neutral species in the + – Martian upper atmosphere, O2 , the major ion in the ionosphere, and e are given, respectively, by,

kTi DiCO2 = , (4.16) µiCO2 νin

kTi DiO = , (4.17) µiOνin

kTi + DiO2 = , and (4.18) + µiO2 νil kT Die− = , (4.19) µie− νie− where µ is the reduced mass and ν the collision frequency between the diﬀusing ion and the relevant species, indicated using subscripts (Schunk and Nagy, 2009). The + – collision frequencies of the ion and a neutral species, the major ion O2 , and e are calculated, respectively, by, s 2 mn γne νin = 2.21πNn , (4.20) mi + mn µ

Nl νil = Bil 3/2 , and (4.21) Tl

2 NiZi − νie = 54.5 3/2 . (4.22) Te−

In Equation 4.20, Nn is the neutral CO2 or O density, mn the mass of the neutral, e the elementary charge, and γn the neutral polarizability, which is taken as −24 3 −24 3 2.63 × 10 cm for CO2 and 0.77 × 10 cm for O. In Equation 4.21, Nl is the + density of the ion through which the ion in question is diﬀusing, i.e. that of O2 ,

Bil the collision frequency coeﬃcient of the ion pair, which is taken to be 0.24 for + + the H3O -O2 pair, and Tl the temperature of that ion. Finally, in Equation 4.22,

Zi is the integer charge number of the ion, namely 1.

For each MAVEN orbit, we compare τC to τD and ﬁnd, generally, that for + the calculation of H2O from H3O , on the dayside, τC ≤ τD to CO2 densities of 154

7 −3 + <4 × 10 cm . On the nightside, because H3O is destroyed only by dissociative recombination and the e– density substantially decreases there, the minimum density at which the photochemical equilibrium assumption will be valid can vary strongly from ∼107 cm−3 to ∼109 cm−3. Thus, in this region on the nightside, dif- + fusion could play a role in determining the abundance of H3O . The results of this analysis can be found in Figure 4.1.

Nov '14Feb '15Jun '15Oct '15Mar '16Jul '16Oct '16Jan '17May '17Sep '17Jan '18May '18Aug '18 180

109 165 150

135 )

-3 120 8 10 105

75 Density (cm 2 60 CO 107 45 Solar Zenith Angle (degrees)

106 0 240 300 0 60 120 180 240 300 0 60 120 180 240 L (degrees) S

Figure 4.1: Density at which τC = τD. Each point is the CO2 density at which τC = τD for a single MAVEN orbit, which we use as a metric for evaluating the assumption of photochemical equilibrium in the upper atmosphere. The transition from red to blue corresponds to the shift from day to night. At densities greater than that plotted (lower in the atmosphere), τC < τD, i.e. the chemistry time constant is shorter than the diﬀusion time constant, and at densities less than that plotted (higher in the atmosphere), τC > τD. 155

4.2.5 On the Assumption Tn = Ti = Te

+ The assumption that Te = Tn may aﬀect the rate of H3O dissociative recombina-

tion — thus impacting calculated H2O abundances — and the determination of the

plasma scale height, Hp, as described above. Similarly, the assumption that Ti = Tn

may aﬀect the rates of reactions SR5 and SR6, impacting the H2O abundance and

the calculation of Hp. Higher values for Te will have the eﬀect of reducing the rate + of H3O dissociative recombination, thus reducing the calculated H2O abundance and increasing Hp. For example, if Tn = 250 K and Te is 100 K larger, then the H2O abundance calculated using Tn, as we assume, would be artiﬁcially larger by 15%.

In the same case, Hp would be artiﬁcially smaller by 20% if calculated using Tn

instead of the larger Te. Thus, our photochemical equilibrium calculation would be

valid over a larger altitude range if Te > Tn as in this example. A larger value of Ti would have the same eﬀect on Hp according to Equation 4.14. In a similar example where Tn = 250 K and Ti is 100 K larger, then k1 and k2 would decrease, and the

H2O abundance calculated using Tn would be artiﬁcially smaller by 18% than the

H2O abundance calculated using Ti.

4.2.6 Photochemical Model

Our photochemical model for Mars is adapted from a Titan photochemical model described previously (Vuitton et al., 2019; Lo et al., 2020). The calculations are one-dimensional and the system is solved by integrating in time until the terms in the continuity equation for each species are balanced to within 0.1%. The model 1 treats CO2 as ﬁxed and calculates the distributions of Ar, He, H2O, CO, O, O( D), 2 O2,O3, H, H2, N, N( D), OH, HO2,H2O2, NO, NO2, NO3,N2O, HNO, HONO, + + + + + + + + NH, C, HOCO, HCO, CH, CN, HCN, H ,H2 ,H3 , He ,N ,N2 , NH , NH2 , + + + + + + + + + + + + NH3 ,N2H , NO ,N2O , NO2 , HN2O , HNO ,O ,O2 , CO , HO2 , CO2 , + + + + + + + + + + + + HCO , HOC , HCO2 , OH ,H2O ,H3O , Ar , ArH ,C , CH , CN , HCN , + + + + and HCNH . The reaction rate coeﬃcients of CO2 + O −−→ O + CO2 and O + + CO2 −−→ O2 + CO were discussed in the main text. Other reaction rates and rate 156

coefficients can be found in previous work (Vuitton et al., 2019; Lo et al., 2020). The model includes diffusion of neutral species, but ion species are assumed to be in local chemical equilibrium (net production rate equals net loss rate). We fix the mole

fractions of N2, Ar, CO, O, H2O, H, H2, and He at the lower boundary. Other species are assumed to be in chemical equilibrium at the lower boundary. Most species are

assumed to be in diffusive equilibrium at the upper boundary, but H, H2, and O have a specified effusion velocity of 10 m s−1. We use this boundary condition rather than the more typical Jeans velocity condition to account for day-to-night transport of these species. The flux due to day-to-night transport is much larger than the Jeans escape flux. The effusion velocity of 10 m s−1 is adopted because it provides a match to the measured O profile (see Section 4.3.4). Photolysis of CO2,N2, Ar,

CO, H2O, NO, H, and H2 is included. Sources for the branching ratios and cross sections can be found in previous work (Vuitton et al., 2019). We use a solar ﬂux from the time of DD2 (17–22 April 2015) and adopt a solar zenith angle of 9°, also appropriate for DD2 (Thiemann et al., 2017).

4.3 Results and Discussion

The position of MAVEN’s periapsis, or closest approach to Mars, over the course of the mission is shown in Figure 4.2. Regional dust storms occurred during Mars years (MYs) 32 and 33, and a global dust storm in MY 34, also shown in Figure 4.2. MAVEN instruments directly sample the atmosphere during the periapse segment of its 4.5 h orbit, in which periapsis occurs at roughly 150 km altitude (Jakosky et al., 2015; Stone et al., 2018). During the observations of the last regional dust storm of MY 32, MAVEN’s periapsis precessed from 18°N to 8°N latitude, with measurements at the onset of the dust storm obtained near 13°N. This regional storm arose in the southern hemisphere near Martian subsolar longitude (Mars-Sun angle, LS)

313°, well after perihelion (LS = 251°) and southern summer solstice (LS = 270°). Amid the global dust storm of MY 34, MAVEN’s periapsis precessed from 21°S to 17°S latitude, with measurements at the onset of the dust storm obtained at 157

about 18°S. This global dust storm occurred around LS = 189°, prior to perihelion and just after southern spring equinox (LS = 180°). Figure 4.2A shows the total column dust optical depth from a combination of instruments: the Thermal Emission Spectrometer on Mars Global Surveyor, the Thermal Emission Imaging System on Mars Odyssey, and the Mars Climate Sounder (MCS) on Mars Reconnaissance Orbiter (Montabone et al., 2015, 2020). Figure 4.2B shows the dayside temperature in the middle atmosphere at the 50 Pa pressure level measured by MCS (Kleinb¨ohl et al., 2009; Kass et al., 2019). These quantities indicate the onset, evolution, and distribution in latitude of the dust events and the atmospheric response.

Figure 4.3 shows the variation of the abundance in the ionosphere, or charged + + portion of the atmosphere, of H2O and H3O , normalized by the abundance of electrons, near MAVEN’s periapsis over the course of the mission. These two species + + are produced mainly by charge transfer between CO2 and H2O, producing H2O , + + and proton transfer from HCO to H2O, producing H3O (see below). Three forms of variations are visible in Figure 4.3A. Firstly, there is diurnal variation across 2 orders of magnitude. The solar zenith angle, or angle between the vertical and Sun, in Figures 4.3A-C corresponds to the time of day at which the measurement was made (0° is noon at the equator, 90° dawn or dusk, and 180° midnight). Secondly, + H2O varies with season (LS), with repeatable maxima near LS = 270°, the peak of + southern summer, and minima near LS 40°. The relative abundance of H2O in the dayside ionosphere varies by more than an order of magnitude over a Martian year, from tens of ppm to hundreds of ppm, peaking in southern summer near perihelion + and declining during northern summer. The peak in [H2O ]/[e-] in southern summer coincides with the peak in observed seasonal trends in middle atmospheric H2O abundance (Fedorova et al., 2018; Heavens et al., 2018), the exospheric H and D abundances (Clarke et al., 2017; Bhattacharyya et al., 2015; Mayyasi et al., 2019), and H escape rate (Halekas, 2017; Bhattacharyya et al., 2017b; Chaﬃn et al., 2018). + Thirdly, Figure 4.3A shows large and rapid increases in the H2O abundance coincident with dust storms near LS 315° in MY 32 and LS 190° in MY 34. More detailed views of these events are shown in Figures 4.3B and 4.3C. 158

Oct '14Nov '14Jan '15Apr '15Jun '15Sep '15Dec '15Mar '16May '16Aug '16Oct '16Dec '16Feb '17May '17Jul '17Oct '17Jan '18Apr '18Jun '18Aug '18Nov '18 90°N 1.6 75°N A 1.4 60°N 45°N 1.2 30°N 1 15°N 0° 0.8

Latitude 15°S 0.6 30°S 45°S 0.4 60°S

0.2 Total Column Dust Optical Depth 75°S 90°S 0

90°N 225 B 75°N 215 60°N 205 45°N 200 195 30°N 15°N 185 0° 175

Latitude 15°S 165 30°S 155 45°S 145 Temperature at 50 Pa (K) 60°S 75°S 135 90°S 125 200 240 280 320 0 40 80 120 160 200 240 280 320 0 40 80 120 160 200 240 280 L (degrees) S

33 34 Mars Year Figure 4.2: MAVEN Location and Atmospheric Conditions During Mar- tian Dust Storms. (A) Gridded total column dust optical depth (red to yellow) (Montabone et al., 2015, 2020) and (B) the mean dayside temperature (red to yellow with black contour at 200 K) at the 50 Pa pressure level from Mars Climate Sounder measurements (Kleinb¨ohlet al., 2009; Kass et al., 2019) between October 2014 and November 2018. MAVEN’s periapsis positions are indicated with blue crosses. Gaps in MAVEN’s periapsis location correspond to gaps in the NGIMS dataset (see Section 4.2.1). Ticks in the Mars year axis occur at the beginning of the year (LS = 0). Dust storms correspond with heating in the middle atmosphere.

The dust storms shown in Figures 4.3B and 4.3C are substantial perturbations to the observed seasonal trend. At the onset in the upper atmosphere of the global 159

Date

Oct '14Nov '14Jan '15Apr '15Jun '15Sep '15Dec '15Mar '16May '16Aug '16Oct '16Dec '16Feb '17May '17Jul '17 Oct '17Jan '18Apr '18Jun '18Aug '18Nov '18 105 180 A 165 150 104 135 120 103 ] (ppm) 105 - 90

] / [e 2 75 + 10

O 60 2

[H 45 1 10 30 Solar Zenith Angle (degrees) 15 100 0 200 240 280 320 0 40 80 120 160 200 240 280 320 0 40 80 120 160 200 240 280 L (degrees) S

14 Mar '1517 Mar '1521 Mar '1524 Mar '1528 Mar '1531 Mar '1504 Apr '15 26 May29 '18 May01 '18 Jun05 '18 Jun08 '18 Jun12 '18 Jun15 '18 Jun19 '18 Jun22 '18 Jun26 '18 Jun '18 102 65 104 85 B C H O+ 2 60 H O+ 80 3 103 55 O+ / 10 5 75 2 50

] (ppm) ] (ppm) 70 - 101 - 102 45 65

[ion] / [e 40 [ion] / [e 60 101 55 35 Solar Zenith Angle (degrees) Solar Zenith Angle (degrees)

100 100 50 308 310 312 314 316 318 320 182 184 186 188 190 192 194 196 198 200 L (degrees) L (degrees) S S

Figure 4.3: Variation of H2O Ions Measured Using NGIMS. Mean + – [H2O ]/[e ] for each MAVEN orbit (A) between October 2014 and November 2018, (B) during a regional dust storm in MY 32, and (C) during the MY 34 global dust storm. Dotted boxes in panel A indicate the regions shown in panels B and C. + – + – Each data point is the mean [H2O ]/[e ] (color bars), [H3O ]/[e ] (blue triangles + – in panels B and C), or [O2 ]/[e ] (green squares in panels B and C) between CO2 densities of 5 × 108 to 109 cm−3 (MAVEN’s nominal periapsis) for a single orbit. + – The transition from red to blue for [H2O ]/[e ] corresponds to the shift from day to night.

+ dust storm of June 2018 (MY 34, Figure 4.3C), the relative abundance of H2O in + – the ionosphere rises sharply in a short period of time: [H2O ]/[e ] increases from 106 to 327 ppm, a factor of 3.1, over about 2 days, from 8 June 2018 to 10 June 2018. + – Simultaneously, [H3O ]/[e ] increases from 11 to 28 ppm, a factor of 2.5. MAVEN’s periapsis precessed onto the nightside of Mars shortly after the onset of the global 160

dust storm and measurements in this period are affected by the diurnal variation of the ionosphere (see below). Nevertheless, there is an abrupt increase in the relative abundance of these ions which coincides with the first effects of the dust storm on the upper atmosphere on 8 June 2018, as measured using the Imaging Ultraviolet Spectrograph on MAVEN (Chaufray et al., 2019) and neutral atmosphere density measurements from NGIMS (Elrod et al., 2020). The regional dust storm observed in March 2015 (MY 32, Figure 4.3B) occurs during the declining seasonal trend, with + – an upward perturbation caused by the storm: over 2 days [H2O ]/[e ] increases from + – 32 to 73 ppm, a factor of 2.3, and [H3O ]/[e ] increases from 2.4 to 3.9 ppm, a factor of 1.6. + Large diurnal variations are also observed in the relative abundance of H2O as MAVEN’s periapsis repeatedly precessed from the dayside to the nightside, a process which occurs over several months, as seen in Figure 4.3A. The relative abundance + of H2O increases on the nightside because, relative to other species in the Martian

atmosphere, H2O has a low ionization potential (IP), 12.6 eV, and OH has a high proton affinity (PA), 6.14 eV. In general, atmospheric ionization flows by electron transfer from neutral species with lower IPs to positive ions whose parent neutrals have higher IPs, and by proton transfer from species whose nonprotonated forms have lower PAs to species that have higher PAs (Fox, 2015). On the nightside, away from a constant source of photoionization driving the production of short-lived ions + + (like O2 ), H2O becomes more abundant. Thus, we can only observe the effects of dust storms on the dayside, otherwise the diurnal variation overwhelms the signal due to the storm.

4.3.1 Water in the Upper Atmosphere

+ + Assuming that the increases in H2O and H3O are due to an inﬂux of H2O

into the upper atmosphere, we calculate H2O abundances from NGIMS density + + + – measurements H2O ,H3O , HCO , and e obtained over 4254 MAVEN orbits. + We assume photochemical equilibrium for H3O , i.e. its production rate is equal to its loss rate. This assumption is known to be valid in the thermosphere on the 161

+ dayside, but has not been substantiated on the nightside (see Section 4.2.4). H3O

is mainly produced by proton transfer to H2O and is only destroyed by dissociative recombination with e– (Fox, 2015; Fox et al., 2015; Krasnopolsky, 2019). The results

of these calculations are shown in Figure 4.4. The diurnal variation of H2O is much + smaller than that of H2O , as expected in the neutral atmosphere, which is more chemically stable than the ionosphere.

Date

Oct '14Nov '14Jan '15Apr '15Jun '15Sep '15Dec '15Mar '16May '16Aug '16Oct '16Dec '16Feb '17May '17Jul '17 Oct '17Jan '18Apr '18Jun '18Aug '18Nov '18 180 A 102 165 150 135 120 1 10 105 90 75 60 100 45 O Mixing Ratio (ppm) 2

H 30 Solar Zenith Angle (degrees) 15 10-1 0 200 240 280 320 0 40 80 120 160 200 240 280 320 0 40 80 120 160 200 240 280 L (degrees) S

14 Mar '1517 Mar '1521 Mar '1524 Mar '1528 Mar '1531 Mar '1504 Apr '15 26 May29 '18 May01 '18 Jun05 '18 Jun08 '18 Jun12 '18 Jun15 '18 Jun19 '18 Jun22 '18 Jun26 '18 Jun '18 101 65 102 85 B C H O 2 60 H 80 2 55 75

50 70 101 45 65

40 60 Mixing Ratio (ppm) Mixing Ratio (ppm) 55 35 Solar Zenith Angle (degrees) Solar Zenith Angle (degrees)

100 100 50 308 310 312 314 316 318 320 182 184 186 188 190 192 194 196 198 200 L (degrees) L (degrees) S S

Figure 4.4: Variation of H2O and H2. Same as in Figure 4.3, but for the H2O mixing ratio (color bars) and H2 mixing ratio (blue triangles in panels B and C).

A repeatable seasonal trend occurs in the H2O abundance in the upper atmosphere, which peaks in southern summer between LS = 250 to 270°, shown in Fig-

ure 4.4A and Figure 4.5. This trend in upper atmospheric H2O coincides with the 162

seasonal trends seen in previous observations of the H2O abundance in the middle atmosphere (Fedorova et al., 2018; Heavens et al., 2018), the exospheric H and D abundances (Clarke et al., 2017; Bhattacharyya et al., 2015; Mayyasi et al., 2019), and H escape ﬂux (Halekas, 2017; Bhattacharyya et al., 2017b; Chaﬃn et al., 2018).

The mean upper atmospheric H2O mixing ratio is >1 ppm at all times and can exceed 10 ppm in southern summer. A sinusoidal model ﬁtted to the dayside H2O abundances from all MYs, but excluding regional and global dust events, is shown in Figure 4.5. This model has a maximum H2O mixing ratio of 4.3 ppm at LS 259° and a minimum of 2.0 ppm at LS 86°, for a variation of more than a factor of 2. The

H2O mixing ratio is never negligible, contrary to the assumption of 0–4 ppb made in numerous modeling studies (Hunten and McElroy, 1970; Krasnopolsky, 2002; Fox et al., 2015).

During the global dust storm of June 2018, the mean H2O mixing ratio increased by a factor of 2.4, from a mean value of 3.0 ppm to 7.1 ppm over 2 days. The water abundance then continued to increase following the seasonal and dust storm trends, reaching values >60 ppm at LS = 204°. This event included the highest persistent

H2O abundances we observed, holding at tens-of-ppm for more than 5 months at the end of 2018. During the regional storm observed in MY 32, the H2O mixing ratio increases by 7%, from 4.6 to 4.9 ppm in 2 days. Thus, dust storms drive perturbations in upper atmospheric H2O that are far more rapid than the diurnal variations and even small dust storms have a measurable impact. The MY 32 dust storm occurred when MAVEN was near the subsolar point and is superimposed on a declining seasonal trend. We interpret these variations as due to enhanced transport of H2O into the upper atmosphere during the dust storms.

4.3.2 Previous and Coincident Measurements of Water

The eﬀects of both regional and global dust storms on the H2O in the lower and middle atmosphere have been observed before. In MY 32, Mars Express observed large seasonal increases in the H2O mixing ratio, including an increase around

LS = 315° (Fedorova et al., 2018), coinciding with the increase we observe in Fig- 163

102 MY 32 MY 33 MY 34 Fitted Model

101 O Mixing Ratio (ppm) 2 H

100

0 30 60 90 120 150 180 210 240 270 300 330 360 L (degrees) S

Figure 4.5: Seasonal Variation of Upper Atmospheric H2O. Each data point is the mean dayside (solar zenith angle <90°)H2O mixing ratio between CO2 densities of 5 × 108 to 109 cm−3 for a single MAVEN orbit over MYs 32 (red circles), 33 (blue triangles), and 34 (green squares). The solid line is a sinusoidal model ﬁtted to the data from all three Mars years to illustrate the seasonal variation. Dust storm data (dotted boxes) are included in the plot, but excluded from the ﬁtting.

ure 4.3 and Figure 4.4. These measurements indicate an increase in the hygropause altitude and an injection of water into the middle atmosphere, coinciding with our + + observed increases in the abundances of H2O, H2O , and H3O in the upper atmosphere. Similarly, MCS detected an increase in the hygropause altitude, up to 65–70 km, in this period (Heavens et al., 2018). During the global dust storm of

MY 34, Trace Gas Orbiter (TGO) measured a peak H2O abundance of roughly

100 ppm at 50 km altitude in the southern hemisphere (80 to 83°S) and a peak H2O 164 abundance of about 250 ppm just below 40 km altitude in the northern hemisphere (51 to 59°N), indicating an injection of water into the middle atmosphere coincident with our observations (Vandaele et al., 2019). Both of these measurements were obtained at LS = 196.64°. Further TGO measurements showed that H2O abundances of ∼5–10 ppm extended to altitudes up to 90 to 100 km (Aoki et al., 2019; Fedorova et al., 2020). The timescales of dust-storm-induced variations in the upper atmospheric H2O mixing ratio shown in Figure 4.4 are consistent with these simultaneous measurements of the middle atmospheric H2O mixing ratio during the

2018 global storm. MCS observed an H2O mixing ratio close to 300 ppm near 50 km altitude in the middle atmosphere (Heavens et al., 2019). At the same time, we measure a mean H2O mixing ratio of 7.5 ppm near MAVEN’s periapsis (∼150 km altitude) over an LS range of 191.05 to 193.21° and a latitude range of 13 to 18°S. These measurements in the middle atmosphere, below the NGIMS sampling range, provide context for the NGIMS measurements. Seasonally and during dust storms, the H2O abundance in the middle atmosphere increased substantially in the span of a few Martian days, coincident with NGIMS observations in the upper atmosphere.

4.3.3 Molecular Hydrogen in the Upper Atmosphere

Molecular hydrogen, H2, may contribute to variations in protonated ions and is a source of H in the upper atmosphere. Measured H2 variations obtained using NGIMS + are shown in Figure 4.4B-C. H2 reacts with numerous ions, mainly CO2 , to produce

H atoms that may escape the planet’s atmosphere. H2 itself can escape, although much more slowly than H because H2 is twice the mass of H and lighter species have lower escape energies. The absolute sensitivity of NGIMS to H2 is unknown, so we cannot derive an absolute H2 abundance. However, relative variations of H2 are measurable. No seasonal trend or impact of dust storms are apparent in the upper atmospheric H2 abundance (Figure 4.4B-C). H2 is therefore not the source of H responsible for seasonal and dust-storm-induced variations in the upper atmosphere. 165

4.3.4 Water as a Source of Escaping Hydrogen

We constructed a photochemical model to investigate the effects of the H2O abundances in the Mars ionosphere on the H escape rate. We constrain the model with data from a MAVEN Deep Dip (DD) campaign. During week-long DD campaigns, the MAVEN spacecraft penetrates to lower altitudes, roughly 125 km. The measured altitude profiles provide constraints on ionospheric composition. We use the second DD campaign (DD2) executed near LS 329° in MY 32 because MAVEN’s periapsis was close to the subsolar point. We average the measurements over the DD using a previously described technique to remove wave structure in the altitude profiles (Stone et al., 2018). The solar zenith angles and latitudes do not vary appreciably during a DD so the resulting profiles are effectively averages over longitude for a latitude of 4°S and local time of 12 p.m. The photochemical calculations are 1D and carried out for DD2 geometry. Neu- tral and ionic composition is calculated from 80 to 250 km, including photolysis, chemical reactions, and diffusion of neutrals (see Section 4.2.6). We include both molecular and eddy diffusion, adopting an eddy diffusion coefficient of 108 cm2 s−1. Ions are assumed to be in local photochemical equilibrium. Rate coefficients are discussed below.

The model is constructed to match the primary neutral constituents measured by

NGIMS, as shown in Figure 4.6A. We calculate H2O by assuming a mixing ratio of

2 ppm at 80 km, consistent with our measurements obtained near aphelion (LS = 71°)

in the absence of dust storms (Figure 4.5). Photolysis causes the H2O mixing ratio to decrease slightly with altitude until ∼160 km, where molecular diﬀusion begins to dominate and the mixing ratio starts to increase with height. For O, we assume a mixing ratio of 2% at 80 km, chosen to produce a vertical proﬁle consistent with NGIMS measurements at higher altitudes.

+ + Figure 4.6B shows the altitude proﬁles of H2O and H3O in the model are consistent the observations, validating our earlier inferences. The model also matches + + + measurements of CO2 ,O2 , and HCO , species involved in the chemical destruc- 166

Figure 4.6: Calculated 1D Model Abundances and Reaction Rates. (A) Neutral species abundances from our low H2O photochemical model (lines) compared to the NGIMS Deep Dip 2 (DD2) mean data (crosses). (B) The same as in A, but for ionic species. (C) Chemical reaction rates for selected reactions in the low and (D) high H2O model. The legend in panel D applies also to panel C.

+ tion of H2O. Our calculations also match the O observations. Models of the Mars + + + ionosphere have often assumed that O was produced by CO2 + O −−→ O + CO2 with a rate coefficient of 10−10 cm3 s−1 (Fehsenfeld et al., 1970); however, laboratory work has placed an upper limit of 6 × 10−13 cm3 s−1 on this rate coefficient (Fox et al., 2017; Tenewitz et al., 2018). Adopting this value, O+ is produced primar- + + + + ily by CO2 + hν −−→ CO + O and lost by O + CO2 −−→ CO2 + O and O + + CO2 −−→ O2 + CO. Previous models assumed a combined rate coefficient for these reactions of 10−9 cm3 s−1 (Anicich, 1993). However, state-specific measurements indicate a value of 4 × 10−10 cm3 s−1 (Alcaraz et al., 2004). Our model uses a value of 167

3 × 10−10 cm3 s−1, chosen to match DD2 observations. Between 140 to 150 km the predicted and observed protonated ion densities agree to within 25% (Fig 4.6B). There are larger discrepancies at higher altitudes and near MAVEN’s periapsis, but the observed densities near periapsis are uncertain because the spacecraft is moving primarily horizontally (Stone et al., 2018) and the model densities are uncertain at higher altitudes because ion diﬀusion has been neglected in the model.

We use the model to calculate the net destruction rate of H2O and the production rate of H in the ionosphere (Table 4.2). The NGIMS measurements are only available above the ionospheric peak, the location of the maximum total ion density (Figure 4.6B, 135 km), so we rely on model predictions to investigate chemical processes down to 80 km. In addition to the results for the DD2 model, we present rates for a similar model calculated for the same conditions and input data, but in which we adopt an H2O mixing ratio of 40 ppm at 80 km, consistent with our measurements obtained during the global dust storm of MY 34 (Figure 4.5). H production in the

7 −2 −1 ionosphere for the low H2O model is 5 × 10 cm s , at the low end of the range of H escape rates inferred by previous studies, 107 to 5 × 109 cm−2 s−1 (Halekas, 2017;

Bhattacharyya et al., 2017b; Chaﬃn et al., 2018). The column-integrated H2O 9 −2 −1 destruction in the ionosphere for the high H2O model is 1.4 × 10 cm s , corresponding to an H production rate of 2.8 × 109 cm−2 s−1, at the high end of the range determined in previous studies (Halekas, 2017; Bhattacharyya et al., 2017b; Chaﬃn

+ 7 −2 −1 et al., 2018). H production from destruction of H2 by CO2 is 9.6 × 10 cm s , less than a factor of 2 times larger than H production from ionospheric destruction of H2O in the low H2O models, and substantially less than that in the high H2O models.

It is possible that ionospheric destruction of H2O is equally or more important than neutral photolysis of H2O for H escape. We cannot compare the upper and lower atmosphere contributions to escape in a more quantitative way because escape rates in these models are closely dependent on the boundary conditions on the H and

H2 mixing ratios at 80 km, which are assumed values chosen to replicate observations at higher altitudes. Boundary conditions on mixing ratios can introduce spurious 168

Table 4.2: H2O Budget and H Production. Two models with low and high H2O are listed, representing periods between and during dust storms, respectively (see Section 4.2.6). The H2O mixing ratios at 80 km for the low and high H2O cases are 2 ppm and 40 ppm. Total H production from H2O is twice the diﬀerence between all H2O destruction and all H2O production. Total H production from H2 is twice + the rate of destruction of H2 by CO2 .

Column Rate (cm−2 s−1)

Low H2O High H2O

H2O Production + – 7 8 H3O + e −−→ H2O + H 0.1 × 10 1.99 × 10

H2O Destruction + + 7 8 CO2 + H2O −−→ H2O + CO2 1.6 × 10 6.35 × 10 + + 7 8 HCO + H2O −−→ H3O + CO 0.5 × 10 7.56 × 10 + + 7 8 CO2 + H2O −−→ HCO2 + OH 0.5 × 10 2.18 × 10 H Production 7 9 Total H Production from H2O 5.0 × 10 2.85 × 10 8 8 Total H Production from H2 1.9 × 10 1.9 × 10

ﬂuxes into photochemical models. Physical boundary conditions, such as deposition velocities at the surface, are required to accurately calculate ﬂuxes. Our calculations

and the high H2O densities in the thermosphere found in the MAVEN observations show that ionospheric chemistry is a source of H which can escape from the Mars atmosphere.

4.4 Conclusions

Initial studies of H production and escape neglected ionospheric destruction of

H2O because H2O was assumed to be conﬁned to low altitudes by a hygropause (Hunten and McElroy, 1970; Parkinson and Hunten, 1972; McElroy, 1972). Later, it was

found that the hygropause varies in altitude with season and speculated that H2O saturation may not occur at all during dust storms due to elevated temperatures (Jakosky, 1985). More recent 1D photochemical models (Nair et al., 1994; Krasnopolsky, 2002; 169

Fox and Ha´c,2009) and 3D global circulation models (Gonz´alez-Galindoet al., 2015; Chaufray et al., 2015b; Daerden et al., 2019) have likewise not included chemical

destruction of H2O in the ionosphere. Occultation and limb proﬁle measurements in the middle atmosphere demonstrated that the hygropause does not conﬁne H2O to low altitudes (Heavens et al., 2018; Vandaele et al., 2019; Aoki et al., 2019; Fedorova et al., 2020) and it has been postulated the elevated exospheric H densities during dust storms could be explained by these enhancements in the middle atmospheric

H2O abundance (Chaﬃn et al., 2017). However, this model neglected ionospheric chemistry, assuming the H was produced solely by neutral photolysis. We have

shown that H2O is present in the ionosphere with substantial abundance throughout the Martian year during the entire MAVEN mission and that H is produced

from this H2O by ion chemistry.

The timescales for destruction of H2O and production of H by ionospheric chem-

istry are short. Once in the ionosphere, H2O is destroyed primarily by reactions + −9 −3 −1 with CO2 with a rate coeﬃcient of 2.4 × 10 cm s (Anicich, 1993). Adopt- + 4 −3 ing a CO2 density of 3 × 10 cm (Figure 4.6B, 135 km) implies a lifetime for

H2O of 4 h. This is more than an order of magnitude shorter than the H2O photolysis time constant of 2 × 105 s (Daerden et al., 2019). Assuming an electron density of 105 cm−3 (Figure 4.6B, 135 km) and electron recombination rates of

−7 −3 −1 + + 4.4 × 10 cm s (Jensen et al., 2000) for H2O and H3O yields a time constant

of roughly 20 s for production of H from electron recombination. Thus, H2O transported to the ionosphere is quickly broken apart and converted to H. We expect the H produced at these high altitudes to have a high probability for escape. This im-

plies that the limiting factor is the supply rate of H2O to the ionosphere from lower altitudes. This has implications for our view of H escape from Mars. In previous

models, H escape was controlled by production of H2 in the lower atmosphere and its slow diﬀusion through the middle atmosphere. In our interpretation, H escape

depends on how H2O moves past the hygropause and the rate it is transported from the middle atmosphere to the ionosphere. The relative importances of neutral and ion chemistry in the production and 170 escape of thermal and nonthermal H remain unclear. Because we observe that the H2 abundance is constant during the dust storms while the H2O abundance increases strongly, ionospheric destruction drives the elevated H escape rate during dust events. The importance of ion chemistry to H production has been discussed previously (Krasnopolsky, 2019), although without direct information on the H2O abundance in the ionosphere. The H escape ﬂux can be expressed as,

F = 1.6 × 108 + 1.4 × 1013f cm−2 s−1, (4.23)

where f is the H2O mixing ratio at 80 km (Krasnopolsky, 2019). The constant term 8 −2 −1 of 1.6 × 10 cm s is the limiting flux for an H2 mixing ratio of 15 ppm, the value imposed at the lower boundary in those models (Krasnopolsky, 2019). Adopting an H2O mixing ratio of 2 ppm in Equation 4.23 gives a contribution to escape from ion chemistry of 2.8 × 107 cm−2 s−1, roughly half the column-integrated production rate in Table 4.2, suggesting an escape probability of 50% for the H produced in the ionosphere. This result is strongly dependent on the H mixing ratio at 80 km, which is an assumed value. Thus, in this model and ours, the relative contributions of neutral and ion chemistry to escape depend on the boundary conditions for H and H2 at 80 km. The abundance of, exact mechanism of production for, and contribution to escape of a nonthermal component of the H corona at Mars have not been determined due to degeneracies in the models used (Bhattacharyya et al., 2017b; Chaffin et al., 2018) and cannot be determined from our results. NGIMS data are confined to altitudes above 125 km, while occultation and limb sounding experiments have measured H2O up to ∼100 km, leaving a large gap in coverage between 100 km and 125 km. Figure 4.6A shows our predicted H2O mole fraction from the middle atmosphere through the ionosphere, but this is based on a 1D model and the real atmosphere is likely to be more complex. The mixing ratios inferred for the middle atmosphere are often far greater than the values we calculate for the ionosphere (Vandaele et al., 2019; Aoki et al., 2019; Fedorova et al., 2020).

This contrast between the inhomogeneous H2O distribution derived from the middle atmosphere measurements and the roughly constant altitude proﬁle predicted 171

by the 1D model (Figure 4.6) suggests that the middle atmosphere measurements

are sensing a local enhancement of H2O that is transported horizontally around the planet as it diﬀuses upward. Such horizontal transport is not included in our 1D

model. The largest peak in the lower atmospheric H2O mixing ratio occurs in northern summer (Haberle et al., 2017b), the period in which we observe a minimum in

the upper atmospheric H2O mixing ratio (Figure 4.5). The cause of this discrepancy

between the seasonal variations in lower and upper atmosphere H2O abundances is unknown and cannot be explained using a 1D model.

The seasonal and dust-storm-mediated delivery of water to the upper atmosphere could have played a substantial role in the evolution of the Martian climate from its warm and wet state billions of years ago to the cold and dry planet we observe today.

Mars has likely lost enough H2O to cover the planet’s surface with an ocean tens to hundreds of meters deep and loss rates must have been larger in the past (Jakosky

et al., 2018). In a Martian year with no dust storms, assuming the H2O mixing ratio at 80 km is constant at 2 ppm, we calculate that 3.0 × 1015 cm−2 H would be

16 −2 + produced from H2O and 1.1 × 10 cm H by destruction of H2 by CO2 , assuming + all H, including that in HCO2 , is eventually liberated. During a global dust storm

like the one observed in MY 34, in which the H2O mixing ratio at 80 km reaches 16 −2 40 ppm, 1.1 × 10 cm H would be produced from H2O in just 45 days. Thus, a single global dust storm can produce more than an entire Martian year’s worth of H production and escape. If we extrapolate these numbers into the past, we ﬁnd

that over a billion years a 44 cm deep global layer of H2O would be lost due to

destruction of H2O in the ionosphere and, assuming a rate of about 1 global dust

storm every 10 years (Shirley et al., 2019), an additional 17 cm H2O would be lost due to global dust storms. Larger loss estimates would be obtained if included in

this extrapolation were the seasonal ﬂuctuation of H2O in the upper atmosphere (Figure 4.5) and regional dust storms, which, relative to global dust storms, likely have a smaller but non-negligible impact on H escape. These eﬀects, though, are smaller than uncertainties related to our lack of knowledge of the Martian climate billions of years ago (Jakosky et al., 2018). H escape driven by direct transport of 172

H2O to the upper atmosphere would have accelerated the loss of water from Mars as the Martian hygropause weakened due to a decrease in atmospheric pressure, itself driven by atmospheric escape and the development of a dry, dusty surface. 173

CHAPTER 5

Conclusion

The objective of this dissertation has been an investigation of the upper atmosphere of Mars and its escape to space using in situ measurements obtained by NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) Neutral Gas and Ion Mass Spectrometer (NGIMS). Using this data, we have completed the most thorough mapping to date of the thermal structure and composition of the Martian upper atmosphere and reported on the discovery of water in this region. Each of these topics is important to our understanding of the mechanisms responsible for loss of the Martian atmosphere to space and the rate at which this loss occurs today. Using estimates of the current atmospheric escape rate, scientists can begin to extrapolate back through time to investigate the eﬀect atmospheric escape has had on the climate of Mars over the last 4 billion years. In turn, we shall develop a better understanding of the evolution and past habitability of our nearest planetary neighbor, and perhaps even a better understanding of the evolution and habitability of small terrestrial planets in general in a time of rapid discovery of ever more planetary systems around other stars.

5.1 Summary

In Chapter 2, we derived vertical profiles of temperature in the Martian upper atmosphere using NGIMS measurements of Ar, N2, and CO2 abundances and assuming hydrostatic equilibrium. These temperature profiles extend from close to the mesopause (down to ∼125 km during Deep Dips, DDs) to around the nominal exobase (∼250 km), where the atmosphere becomes roughly isothermal. Strong gravity wave structure was observed in every temperature profile. This gravity wave structure is effectively eliminated from the temperature profiles when data from a number of consecutive orbits is binned together, yielding classic thermospheric temperature profiles. The precession of the MAVEN orbit combined with 174 the excellent spatial and temporal resolution of NGIMS allowed us to construct maps of the thermal structure of the upper atmosphere with respect to local time and latitude. No latitudinal variations in the temperature are readily apparent. Large diurnal variations are observed, with subsolar temperatures reaching upwards of 275 K and nightside temperatures decreasing to ∼100 K. The mean nightside upper atmosphere observed by NGIMS is nearly isothermal over the entire vertical range measured. The measured diurnal variations provide useful constraints on the dynamics of the upper atmosphere — specifically, constraints on the transport of heat from the dayside to the nightside. Using a 1D thermal structure model and the temperatures we derived from the NGIMS data, we investigated the energy balance of the upper atmosphere, and demonstrated that the NGIMS temperatures broadly agree with what is expected given our previous knowledge of the drivers of the thermal structure in this region.

In Chapter 3, we described the composition of the upper atmosphere of Mars as measured by MAVEN NGIMS. NGIMS measures the abundances of H2, He, O,

N2, Ar, and CO2 over an altitude range of ∼150 to 300 km (or ∼125 to 300 km DDs). That is, NGIMS measures the abundances of these species from near the mesopause to above the nominal exobase. These are the ﬁrst vertical proﬁles of

H2 in the atmosphere of Mars — only a single remote measurement of H2 had been previously reported (Krasnopolsky and Feldman, 2001). Further, these are the first in situ measurements of upper atmospheric composition since two profiles of the CO2,O2,N2, CO, and NO abundances were obtained by the Viking Landers as they descended to the surface in 1976 (Nier and McElroy, 1976; Nier et al., 1976a,b; Nier and McElroy, 1977). Using NGIMS data collected over more than 5 years and from 8617 MAVEN orbits, we constructed maps of the composition of the upper atmosphere with local time, latitude, and Martian season. There are large diurnal variations in the composition of the upper atmosphere, as gas enriched in the lighter species is transported downward on the nightside. This results in a nightside “bulge” in the abundances of the species significantly lighter than the mean atmosphere, which is primarily CO2. This phenomenon is most pronounced 175

in the lightest species, H2 and He, and is the dominant feature observed in their variation. The seasonal variation in the composition of the upper atmosphere is apparent in the data as CO2 sublimates from and is deposited on the polar ice caps.

In Chapter 4, we reported on the discovery of H2O high in the Martian upper atmosphere. We found that water lofted to such heights is rapidly destroyed by reactive ions rather than photodissociation. It was previously thought that any

H2O lofted high into the atmosphere would be photolyzed before reaching the upper atmosphere. The products of this destruction, ultimately H and O, can readily escape to space since they are produced so close to the exobase. We also demonstrate that the upper atmospheric H2O abundance varies with Martian season, peaking during Summer in the southern hemisphere when Mars is closest to the Sun. In addition to this seasonal variation, the abundance of H2O in the upper atmosphere varies with dust activity on the surface. The global dust storm of 2018 instigated a sudden splash of H2O into the upper atmosphere. Small regional storms which occur repeatably every Mars year have a similar, though smaller, eﬀect. We calculate that this process has removed a substantial amount of H2O from the Martian atmosphere over the last billion years.

5.2 Future Lines of Inquiry

A number of questions arise from the work presented in this dissertation and many more relevant questions remain unanswered on the topics of atmospheric escape from terrestrial planets, both in and beyond our Solar System. There is yet work to do on the determination of the mechanisms and rates of atmospheric escape in Mars’ past. The past climate of Mars is still uncertain in many respects. Simi- larly, many questions remain about the early climate of Venus and the evolution of its atmosphere through time. The spacecraft missions we send to the Solar terrestrial planets, and the in situ data they return to Earth, will not only reveal clues to the planets’ ancient pasts, but also guide our interpretation of remote sensing data obtained from the plethora of recently discovered small, rocky exoplanets. 176

5.2.1 The Carbon Monoxide Abundance in the Martian Upper Atmo- sphere

CO is an important species in the Martian atmosphere because it is produced from the photodissociation of CO2, then recycled back into CO2 by odd hydrogen (HOx ) chemistry. This is the process responsible for the initially surprising long term stability of the Martian atmosphere (Lef`evreand Krasnopolsky, 2017; Lo et al., 2020). CO abundances cannot currently be accurately calculated from the NGIMS data (Chapter 3) and upper atmospheric abundances have only been measured by the Viking Landers (Nier and McElroy, 1976, 1977). Measurements from the ESA Trace Gas Orbiter have produced vertical proﬁles of the CO abundance up to ∼110 km in two locations (Olsen et al., 2021). Nadir observations from multiple spacecraft also provide useful information on the volume mixing ratio of CO in a column-integrated sense (Encrenaz et al., 2006; Billebaud et al., 2009; Smith et al., 2009; Sindoni et al., 2011; Smith et al., 2018; Bouche et al., 2019, 2021). However, there is no dataset of CO abundance in the upper atmosphere which can be used to investigate the variability of CO with, for example, local time, latitude, and season. High resolution CO measurements in the upper atmosphere would provide important constraints on the dynamics and chemistry of the middle and upper atmosphere, with implications for the atmospheric escape of C.

5.2.2 The Climate Evolution of Mars

While it is clear there was much more water on the surface of Mars in the past, the nature of those early warm climate periods is uncertain (Section 1.1.1). Recent work has highlighted the need for a better understanding of the relative importance of atmospheric escape and crustal hydration to the desiccation of the Martian surface and atmosphere (Scheller et al., 2021). It is likely that laboratory analysis of surface samples, while only feasible in the distant future, would provide constraints on the past climate. In particular, ice cores from the nonexchangeable portion of the polar ice caps would prove useful to the study of the evolution of the Mars climate over a 177

portion the planet’s history.

5.2.2.1 Extrapolation of Escape Rates

According to the most current and thorough accounting of atmospheric escape

over the last 4 billion years, 0.8 bar CO2 or a 23 m global equivalent layer of H2O has escaped to space, depending on the source of the oxygen (Jakosky et al., 2018). These numbers are much larger than what would be obtained by assuming the current escape rate has been constant through time, which would result in the loss of just 78 mbar CO2 or a global equivalent layer of H2O just a few meters deep (Jakosky et al., 2018). This is because the Sun, though more faint, was more active in the past: it emitted a larger flux of high energy photons and solar wind particles (e.g. Wood, 2006; Tu et al., 2015, and references therein). Thus, the backward extrapolation of escape rates is difficult due to large uncertainties in these properties of the Sun and the properties of the Martian atmosphere, such as its composition and thermal structure. As a result, the integrated escape rate estimates obtained are likely lower limits and could be too small by perhaps a factor of several (see Jakosky et al., 2018, Section 3). Extrapolations could be improved with observations of escape over an entire solar cycle or longer (MAVEN has not observed Mars at solar maximum, for example); better constraints on the ionizing flux emitted by the Sun and the properties of the solar wind over the history of the Solar System; and more accurate models of escape which can be adapted to past conditions in place of simple exponential scaling laws. Rock and ice samples from the surface of Mars could dramatically reduce the uncertainties in estimates of the integrated loss rate, for example by constraining the composition of the early atmosphere.

5.2.2.2 Water in the Upper Atmosphere

We now know that H2O is transported directly into the Martian upper atmosphere and destroyed by reactions with ions (Chapter 4), but we do not know how

long this has occurred at an appreciable rate. The transport of H2O into the upper 178

atmosphere is only possible because the hygropause, the region in which H2O condenses, is relatively weak in its ability to trap H2O close to the surface. This would not be the case in a dense atmosphere. Thus, it is likely that H2O could only be transported to the upper atmosphere after a signiﬁcant portion of the atmosphere was lost to space. As a result, one question on this topic which remains is, “When did this mechanism begin to operate?” Further, since dust storms are responsible for transporting a relatively large amount of H2O to the upper atmosphere, it is important to know when dust storms became commonplace on Mars. Presumably, this would have been after at least a portion of the planet’s surface was desiccated.

5.2.3 The Climate Evolution of Venus

Like Mars, Venus has undergone massive climatic change sometime in its past and this process likely involved escape to space of a significant portion of its atmosphere, including the vast majority of its water (Bullock, 2001; Taylor and Grinspoon, 2009; Chassefièreet al., 2012; Kane et al., 2019). While the Venusian atmospheric D/H ratio has been measured to be 150 times the Earth value, many isotopic ratios, such as those of the noble gases, have not yet been measured accurately or at all (Chas- sefièreet al., 2012). Some of the noble gas isotopic ratios, such as the 36Ar/38Ar ratio which has been used to determine escape history at Mars (Jakosky et al., 2017), can provide useful constraints on the evolution of the Venus atmosphere and, by extension, its climate. At the time of writing, a number of countries appear poised to send their next mission to Venus in the 2020s (Glaze et al., 2018). Mass spectrometers have been dispatched to Venus in the past (Colin and Hall, 1977; Colin, 1980; Niemann et al., 1980a; Hoffman et al., 1979, 1980; Istomin et al., 1980), though large uncertainties remain where precision of perhaps 1–10 % or better is required (Chassefièreet al., 2012). These two factors motivate the design and implementation of mass spectrometers or other instruments which can perform the necessary measurements in the Venus atmosphere (for example, in the presence of highly condensable and reactive gases like H2SO4). 179

5.2.4 Beyond the Solar System

There exists an “evaporation valley” carved by atmospheric escape in the radius distribution of close-in Kepler exoplanets, a “cosmic shoreline” which separates planets with atmospheres from those that have lost theirs (Owen and Wu, 2017; Fulton and Petigura, 2018; Zahnle and Catling, 2017). The study of atmospheric escape and climatic evolution within our Solar System is thus useful in a comparative (exo)planetological sense. Venus, Earth, and Mars formed in the same Solar System, yet have histories diﬀerent enough to produce the vastly diﬀerent atmospheres and climates we now observe. Understanding how and why this is the case will aid in the interpretation of data from the wealth of roughly Earth-sized, rocky exoplanets that have been discovered. When combined, our knowledge of Venus, Earth, and Mars, provides a picture of the evolution of planets distributed through the “habitable zone” of their star (the radial area in the system in which liquid water is stable on the surface of planets): Venus is apparently within the interior edge of the long-term habitable zone boundary in the Solar System; Earth is inside the habitable zone; and Mars is near the exterior edge of the habitable zone. Mars is small relative to Earth and Venus, which means it may provide additional information useful for analyzing the evolution of relatively small planets in general, though this is a sample size of just one. The atmospheres of the three Solar terrestrial planets are the only terrestrial atmospheres from which we will obtain in situ measurements, unless and until probes are sent to other stars at some point in the distant future. Thus, the study of Venus, Earth, and Mars is important not only for understanding how our own Solar System has evolved into its current form, but also for the study of the evolution of planets around other stars.

5.2.5 The Beneﬁts of Laboratory Measurements

Recent advances in early Mars climate models highlight the need for laboratory measurements of quantities relevant to planetary atmospheres (Turbet et al., 2019, 2020; Godin et al., 2020). Another example relevant to the Martian atmosphere and 180

the evolution of the Martian climate is the application of high resolution measure-

ments of CO and N2 photodissociation cross-sections for the determination of C and N escape rates (Cui et al., 2018; Lo et al., 2020). These are just two examples from contemporary Martian science where laboratory measurements have signiﬁcantly advanced our understanding and the modeling of atmospheric processes. Labo- ratory investigations into numerous other quantities will be vital to the modeling and interpretation of data obtained from planetary atmospheres (Fortney et al., 2016, 2019; Fayolle et al., 2020). As an example, reaction rate constants are often highly uncertain, especially at higher temperatures relevant to the upper atmosphere and ionosphere, and the situation is similar for photoabsorption cross-sections: UV cross-sections at relatively high temperatures are needed for a long list of molecules relevant to upper atmospheres in the Solar System and elsewhere. 181

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