Vinitha Gadiraju
email: vinitha.gadiraju@colorado.edu

Jérémie Garcia
email: jeremie.garcia@enac.fr

Shaun K Kane
email: shaun.kane@colorado.edu

Anke M Brock
email: anke.brock@enac.fr

"It is fascinating to make these beasts fly": Understanding Visually Impaired People's Motivations and Needs for Drone Piloting

Keywords: CCS CONCEPTS, Human-centered computing, Accessibility, Accessibility design and evaluation methods Drones, vision impairment, personas, interviews 1

Drones have become fixtures in commerce, safety efforts, and in homes as a leisure activity. Researchers have started to explore how drones can support people with disabilities in piloting and serve as assistive devices. Our work focuses on people with vision impairment and investigates what motivates them to fly drones. We administered a survey to visually impaired adults that gauged general interest in drone piloting and previous experience with drones. From the 59 survey responses, we interviewed 13 participants to elaborate on how they envision using drones and how different feedback and modes of piloting can make the flying experience more accessible. We found that our participants had overarching interests in aviation, trying new technology, environment exploration, and finding collaborative activities to do with their sighted family members, which extended to an interest in piloting drones. This research helps lay groundwork for design scenarios and accessible features for future drones.

Human Drone Interaction

Human-Drone Interaction is a rich field tackling challenges such as privacy, security, social companionship, and multimodal interaction [START_REF] Cauchard | Toward a roadmap for human-drone interaction[END_REF]. Research has explored how people perceive and would like to interact with drones in public spaces [START_REF] Wojciechowska | Designing Drones: Factors and Characteristics Influencing the Perception of Flying Robots[END_REF], either as main users or as bystanders [START_REF] Mehmet Aydin Baytas | The Design of Social Drones: A Review of Studies on Autonomous Flyers in Inhabited Environments[END_REF]. However, this research has seldom involved participants with disabilities.

Researchers have made efforts to support drone piloting tasks with a wide variety of input devices and interaction techniques [START_REF] Mirri | Human-Drone Interaction: state of the art, open issues and challenges[END_REF][START_REF] Tezza | The State-of-the-Art of Human-Drone Interaction: A Survey[END_REF]. Some work proposes using gestural interaction with hands [START_REF] Cauchard | Drone & me: an exploration into natural human-drone interaction[END_REF][START_REF] Cauchard | Drone.io : A Gestural and Visual Interface for Human-Drone Interaction[END_REF][START_REF] Nagi | Human Control of UAVs Using Face Pose Estimates and Hand Gestures[END_REF][START_REF] Naseer | FollowMe: Person following and gesture recognition with a quadrocopter[END_REF][START_REF] Seuter | Running with Drones: Desired Services and Control Gestures[END_REF],

the body [START_REF] Plaisant | A storytelling robot for pediatric rehabilitation[END_REF][START_REF] Saha | Closing the Gap: Designing for the Last-Few-Meters Wayfinding Problem for People with Visual Impairments[END_REF][START_REF] Sanna | A Kinect-based natural interface for quadrotor control[END_REF], and feet [START_REF] Cauchard | Drone.io : A Gestural and Visual Interface for Human-Drone Interaction[END_REF][START_REF] Matrosov | LightAir: A Novel System for Tangible Communication with Quadcopters Using Foot Gestures and Projected Image[END_REF]. Other interactions use Brain-Computer Interfaces to pilot drones without physical peripherals or by using eye-gaze in conjunction with keyboards [START_REF] Paulin Hansen | The use of gaze to control drones[END_REF][START_REF] Nourmohammadi | A survey on unmanned aerial vehicle remote control using brain-computer interface[END_REF]. Commercial systems mainly rely on graphical user interfaces which provide video streams from the drone to the user as guidance during flight, often through a smartphone. Specifically, systems using first-person view enable piloting using Virtual Reality, as if the pilot were seated inside the drone. Most of these approaches are not inclusive of people with vision impairments because they rely on visual stimuli, either on-screen or seeing the drone's motion in space.

Accessible Human-Drone or Human-Robot Interaction

Human interaction with drones and robots has been extensively studied, but there is still a gap in this field regarding accessibility for people with different disabilities.

In the field of Human-Robot Interaction, Plaisant et al. designed a rehabilitation robot for children. The robot can be controlled by various sensors on the user's body [START_REF] Plaisant | A storytelling robot for pediatric rehabilitation[END_REF]. Their study endorses integrating wireless interfaces into wearable objects such as bracelets. They also advocate decorating these wearable objects with elements that highlight their link to the robot, like attaching a hand icon to indicate which part of the interface controls the robot's hand. Krishnaswamy and Kuber have explored controlling robots through gestural interaction and Brain-Computer Interfaces for people with motor impairments [START_REF] Krishnaswamy | Toward the development of a BCI and gestural interface to support individuals with physical disabilities[END_REF]. While gestural interaction is now integrated with commercial devices, Brain-Computer Interfaces are not yet available outside of research contexts. Bonani et al. studied interaction between blind people and assistive robots [START_REF] Bonani | What My Eyes Can't See, A Robot Can Show Me: Exploring the Collaboration Between Blind People and Robots[END_REF]. Participants could envision integrating robots into their daily life and expressed significant interest in using this type of assistive technology.

Within Human-Drone Interaction, Garcia et al. studied how to make drone piloting accessible as a leisure activity to people with motor and cognitive impairments [START_REF] Garcia | CandyFly: Flying drones by pilots with disabilities[END_REF][START_REF] Garcia | HandiFly: Towards Interactions to Support Drone Pilots with Disabilities[END_REF]. They suggested adapting the activity on three axes: hardware adaptations (e.g. creating modified joysticks), software adaptations (e.g. personalizing and configuring the interface), and automation (e.g. stabilizing the drone using automatic flight maneuvers). Work about visually impaired people and human-drone interaction has mainly focused on navigation and mobility. Grewe and Stevenson designed a drone-based system that helps visually impaired people be aware of their environment through exploration and obstacle detection [START_REF] Grewe | Seeing eye drone: a deep learning, vision-based UAV for assisting the visually impaired with mobility[END_REF]. Avila et al. explored using drones for guidance and navigations tasks, but not with visually impaired people directly piloting the drones [START_REF] Avila | DroneNavigator: Using Drones for Navigating Visually Impaired Persons[END_REF]. Their prototype used audio feedback and a leash tethered to the drone to guide visually impaired people through indoor spaces. Avila Soto and Funk studied the social acceptability of using such drone guides and techniques [START_REF] Avila | Look, a guidance drone! Assessing the Social Acceptability of Companion Drones for Blind Travelers in Public Spaces[END_REF]. They explain that while participants had concerns about "looking weird" in public spaces with a drone, the benefits that drone guidance provided outweighed the negative public perception they anticipated.

Drones have also been used to support specific recreational activities for visually impaired people, like running. Zayer et al. conducted a Wizard-of-Oz-Study with blind runners that showed they were able to follow a running path through sound feedback from a drone [START_REF] Al Zayer | Exploring the Use of a Drone to Guide Blind Runners[END_REF]. Researchers have also looked at using drones to teach orientation and mobility. Similar to Zayer et al., Ding et al. found that with audio feedback from drones, participants were able to follow a path, walk straight, and identify the location of the drone in the room [START_REF] Ding | HeliCoach: A Drone-based System Supporting Orientation and Mobility Training for the Visually Impaired[END_REF]. Recently, Hupper et al. [START_REF] Kang | FlyCam: Multitouch Gesture Controlled Drone Gimbal Photography[END_REF] designed a drone-based interface for hand-object localization tasks in unknown surroundings. The interface used haptic feedback to physically guide visually impaired people. Participants had higher accuracy localizing when using this interface than when using an audio-based hand guiding system. They also found that the haptic system had less of a learning curve. While we are interested in both navigation and environment exploration, our work builds upon this research by further investigating leisure drone use and centering visually impaired people as pilots for the drone.

METHODS

Qualitative research with visually impaired participants has often employed surveys and interviews to develop an understanding of users before designing and implementing new technologies [START_REF] Abdolrahmani | Embracing Errors: Examining How Context of Use Impacts Blind Individuals' Acceptance of Navigation Aid Errors[END_REF][START_REF] Stacy | Collaborative Accessibility: How Blind and Sighted Companions Co-Create Accessible Home Spaces[END_REF][START_REF] Colley | Investigating drone motion as pedestrian guidance[END_REF][START_REF] Storer | All in the Same Boat": Tradeoffs of Voice Assistant Ownership for Mixed-Visual-Ability Families[END_REF][START_REF] Williams | Pray before you step out": describing personal and situational blind navigation behaviors[END_REF]. Our work draws inspiration from these methods by using online surveys, phone and zoom interviews, and visiting aviation organizations to study their artifacts and observe drone users in context.

Survey

To explore BVI people's perceptions and interest in drones, we first conducted a survey. We then interviewed a subset of BVI people from our survey participants to elicit more detailed information about various modalities for piloting drones, desired uses of drones, and how differing feedback can create an engaging and accessible experience for participants. The survey was conducted through Google Forms and sent to participants across the United States and

France (where the research team were located). Through posting on various Facebook groups for BVI people, accessibility, and technology, we also had respondents from Australia. We also recruited participants through snowball sampling and mailing lists at various organizations working with blind or visually impaired adults in different parts of the world. The survey was available in both English and French. The survey has 10 multiplechoice questions, one 5-point Likert scale question, and five short answer questions. We asked for participant consent at the beginning of the form. If the participant wanted to participate in future research, such as the follow-up interview, they could enter their contact information at the end.

The survey first collects demographic information, including the participant's age (Figure 1) and level of vision (Figure 2). We then asked participants about their experiences with technology. These questions included what devices they use daily and what the pros and cons of these tools are. We did this to understand participants' comfort level with technology, how they integrate technology into their day-to-day life, and how drones can address gaps with their current devices. We then asked participants to rank their interest in drones and describe any previous experience they have had piloting drones or being around other people interacting with drones.

The survey then asks participants to consider different piloting contexts that they might be interested in, including leisure, navigation assistance, environment exploration, education, collaboration, and sound exploration. We also asked participants to discuss different piloting methods they would be interested in trying, such as smartphones, controllers, voice commands, and physical gestures. Finally, we asked participants to select how they want to receive feedback while flying, primarily focusing on sound and haptic feedback. 10 participants completed the survey in English. 49 participants completed it in French. After participants completed the form, we selected responses that we were interested in for follow-up interviews. Specifically, we selected participants who had previous experiences with drones.

Follow-up Interviews

We conducted semi-structured follow-up interviews with 13 participants that completed the initial survey. Participants were emailed a consent form before the interview. The interview took place either over the videoconferencing tool Zoom or via phone call. We audio-recorded the participants' responses after they provided verbal confirmation that they consented to be recorded (in addition to consenting in the Google Form). Our interview participants are described below in Table 1. During the interview, we asked participants to elaborate on their answers from the survey. We focused on the following themes:

Participant

Observational Work

In parallel with the interviews, we worked with Mirauds Volants, an association for blind pilots of regular aircrafts, to observe how people with vision impairments use different drones and study artifacts that blind pilots use to fly planes. We were interested in the parallels between planes and drones, as they both fall under the broader umbrella of aviation. We asked the president pf Mirauds Volants (P10) to try piloting drones using a controller, tangible blocks (Figure 6), voice commands, and physical gestures. He tried three different drones: the Tello drone by Ryze Tech [START_REF] Tello | Ryze Robotics[END_REF], the Crazyflie 2.0 by Bitcraze [START_REF]BitCraze[END_REF], and the SP300 Mini Drone by SNAPTAIN [START_REF]SP300 Mini Drone[END_REF]. P10 gave us feedback on the different forms of piloting and the audio feedback the drones produce. He also showed us a variety of artifacts that blind or visually impaired people use when piloting planes. These artifacts included tactile maps with raised surfaces, icons, and Braille labels (Figure 3 and Figure 4). Pilots feel the tactile maps to explore physical/technical aspects of the plane (Figure 3) and study the terrain of the land that they are flying over (Figure 4). We collected audio data and video recordings and took pictures with P10's consent. This observational work helped us visualize our survey and interview questions in real-world use cases. Specifically, we learned the pros and cons of using alternative methods of piloting different drone models with varying sizes and sounds.

Data Analysis

In this study, we focused our analysis on qualitative, open-ended responses from the survey and interview. However, we used quantitative survey data for triangulation [START_REF]The use of triangulation in qualitative research[END_REF] and report it through percentages or raw numbers.

From our survey, we received 160 descriptive responses. We transcribed all audio and video data from our interviews and observational work. We coded the descriptive survey responses and the transcribed data using open coding techniques [START_REF] Corbin | Grounded theory research: Procedures, canons, and evaluative criteria[END_REF]. During coding, we focused on the themes outlined in 3.2.

FINDINGS

In this section, we present emerging themes from our survey and interviews relating to our research questions.

We then delve into specific contexts that participants envisioned piloting in, different piloting modalities, desired system feedback, and general perceptions about drones. The majority of our survey participants, 54.23%, expressed a high interest in drone piloting (Figure 5), despite having little experience with them (55.10% of participants had never piloted nor been around drones before). These statistics might be biased, since people who are not interested in drone piloting may not have replied to the survey. Many participants who had drone piloting experience had flown with their young, sighted children. During these experiences, we learned that they were afraid of crashing the drone or losing it due to not getting enough feedback from the drone or their child. P1 describes an attempt at flying a drone with his son for the first time.

Interest and Experiences

"When we were playing basketball, my friends were using drones to take pictures. That kind of piqued my interest. Then recently, my father got this drone for my son. We didn't realize it was a drone actually.

We finally figured it out and launched it, but we didn't know how to land it correctly. My kid landed it pretty hard and it broke within five minutes." -P1

Surprisingly, almost all participants were more afraid of damaging and losing the drone than they were about their own safety. Participants perceived drones to be delicate and were worried that the drone would malfunction without them knowing, and therefore they would not be able to repair it.

P4 and P5 had never tried directly piloting drones but developed an interest after observing sighted people around them use drones for their hobbies, like fishing and photography. P5 explained that while on vacation, she heard a drone flying overhead and asked the pilot how it was being used.

"It was on holiday at the Cook Islands. My partner and I were there, and we witnessed this person taking these great photos capturing when whales would breach. It was really quite spectacular. I can see why they had such an advantage over holding a video camera and phones. Because you can just move it around remotely and get a great position that you could never get to. It was a real conversation starter." -P5

A few participants, like P11 and P13, had more extensive experience and background knowledge with drones. However, a commonality between participants with background knowledge and participants new to piloting is that sighted people were integral to their experience. Sighted people were either a pilot, a piloting assistant to the visually impaired person, or the visually impaired person was assisting them (the latter primarily being when the sighted person is a child). However, in our survey, only 38.77% of respondents expressed that they would prefer to pilot drones with a sighted person. One respondent expanded, "the first time needs to be with a sighted person, but I want to go towards independent piloting. If there is a way where we can be autonomous right away, I want to." This sentiment of wanting to fly independently but not knowing how to pilot without assistance may explain the discrepancy between participant experiences with drones and their interest in piloting.

Main Motivation to Fly

In line with the experiences in section 4.1, many participants explained that their primary motivation to fly was to do group activities with their sighted family members. This desire extended past free flying into using drones as guides for other recreational activities, like hiking and traveling. Specifically, participants were interested in using drones to receive environmental information during these activities, which we will expand on in the following sections.

Participants had a general curiosity about drones, as they would with most new, popular technology. A few of them had been around drones and heard them flying but could not imagine how they feel and look. Participants who had worked professionally in the technology field (P1, P6, P7, P9, and P13) were fascinated by drones as part of their passion for technology. Many of these participants worked in the fields of accessibility and navigation and were particularly interested in how drones could operate in these areas. For example, P6

often works on personal projects to develop open-source navigational tools for blind people. Many of our participants, primarily living in France, were aviation enthusiasts and felt that drones fell in that category. P9 explained, "nowadays, humans think it's normal to take off and land, but it's still a miracle. It is fabulous. Physics and science explain it, but we are still amazed." P11 expanded, "it is fascinating to make these beasts fly." A few participants who were interested in aviation also did some car and train model-making when they were younger and felt that this interest in Do-It-Yourself projects might carry over to drones.

Interested Contexts

Along with piloting for leisure and free flying, participants described using drones to explore their surroundings and navigate their environment. This aligns with findings from the related work that addresses navigation drones for visually impaired people [START_REF] Avila | DroneNavigator: Using Drones for Navigating Visually Impaired Persons[END_REF][START_REF] Grewe | Seeing eye drone: a deep learning, vision-based UAV for assisting the visually impaired with mobility[END_REF][START_REF] Avila | Look, a guidance drone! Assessing the Social Acceptability of Companion Drones for Blind Travelers in Public Spaces[END_REF]. In this section, we delve into how participants envisioned using a drone within these broader contexts.

Environmental Information

Using drones to explore the environment was the most popular context among respondents in the survey (97.96%). This preference is reflected in the interviews, as participants elaborated on how drones can help them explore new travel locations and track family members for safety.

Learning about your surroundings

P1, P4, and P5 advocated for using drones as travel guides for tourism. Drones can act like a concierge combined with a navigation aid by leading users to popular attractions and restaurants in new cities. P5 described how drones could give travelers a look at sacred monuments and natural landscapes while keeping these areas pristine and clear of tourist traffic.

P4 explained how as a low vision person, drones could give her an enhanced view of landscapes, especially at certain angles and distances that she cannot see.

"What drones did spark with me is that it could possibly be a really good way for me to see things better. It's actually easier to get a concept of something when you are looking down on something as opposed to looking out. An example of that, I have been on many boats and somebody will say 'oh there is a whale out there.' Looking across the horizon, I can't see. Another time, I experienced seeing whales from a cliff where the whales were close to the shore but a long way down. Because I am looking down on them, I can see their definition as opposed to looking across the horizon. That would be similar to using a drone because you are looking down." -P4 P3, P6, P7, P9 were more curious about their home environment than exploring new places. Participants described using drones to see if people are "spying" on them, look at the structure of their home, and investigate construction around their apartment building. P1 also noted that environmental information could help him complete chores that he finds difficult to do as a blind person, like mowing the lawn. In all of these contexts, participants are particularly interested in the camera function and how the drone can transfer visual information to usable audio information.

Tracking people in the environment

Within the environment, participants suggested tracking specific objects and people for recreational and safety purposes. P1 described using the real-time feedback application Aira while his son played in a soccer game and how a drone could have enhanced this experience [START_REF] Aira | [END_REF]. Aira connects visually impaired people to agents that describe what they see through the visually impaired person's phone camera view.

"We were sitting in the field and I turned on Aira to get what was happening while my son was playing soccer. They were able to do a good job but sometimes the players were far and there were some things that they couldn't quite catch. Actually, because we were only interested in what our son was doing, the drone could just track him at all times. You can target somebody. Oh man, you could be a detective too. Put information in about where my wife is going and have it follow her. I'm just kidding…" -P1 P3 and P7 echoed this desire to track people, but for safety purposes. P3 explained, "it's a good activity for parents who are trying to monitor what their child and their friends are up to. If there are other people around your child, it might be an unsafe surrounding." P5 suggested that people-tracking could also apply to search and rescue efforts.

Environment exploration focused on travel, learning about the home and the surrounding areas, and tracking people nearby. However, the desire to have more information about the surrounding environment overlapped into several other categories that participants were interested in, including navigation and recreational activities, which we discuss in the following sections.

Navigation

We asked participants to describe their current technology use and found that navigational assistive technology was common between all participants. Many of our participants used applications, including Google Maps, Microsoft Soundscape, and Aira, to travel for work and navigate through cities on public transportation [START_REF] Saha | Closing the Gap: Designing for the Last-Few-Meters Wayfinding Problem for People with Visual Impairments[END_REF].

However, these applications have pitfalls: users often cannot get enough information far enough ahead of them. Aira restricts users to directions and obstacles directly in their camera's view. When using navigation applications like Google Maps, they receive instructions on where to go but cannot anticipate roadblocks. P1

reflects on how a drone can fill this gap.

"In developing countries, the roads and sidewalks are not necessarily easy to navigate. Landscape changes so frequently, people park all kinds of junk on the road. They dig up holes in the street without any warning. I could send the drone 500 or 1000 feet ahead of me. Give me all the potential pitfalls that I should avoid. I don't want to get that information 10 ft ahead of me. Your cane can only go 5-6 feet ahead of you, so canes can only do so much." -P1

However, some participants were skeptical about using drones in the crowded, public setting that P1 describes, similar to the findings from Avila and Funk [START_REF] Avila | Look, a guidance drone! Assessing the Social Acceptability of Companion Drones for Blind Travelers in Public Spaces[END_REF]. "The streets and unknown terrain are already frightening for the handicapped, and it would be worse with a drone. For a hike or stroll in corn fields, why not? But it will never replace a cane or guide dog for the blind," P9 explains.

Participants felt more certain about using drones in remote areas that they go to for recreational activities. For example, P7 kayaks on the lake by his family's cottage. He does not venture out on the lake alone because he would not know how to return home. "If I could use the drone to go in front of me and make noise so I could follow it, perhaps? Essentially, acting like a beacon, kind of like my guide dog would do, but in places I can't take my guide dog," he explains.

P6, who sails on a small boat, has already started developing his own accessible navigation system for sailing and imagines how a drone could integrate with it.

"I would love to navigate alone on my small sailing boat. That is why we try to use raspberry pi with the GPS and develop an open-source solution. That is very important for me, for it to be shared on the web. We can imagine adding some cameras with software to identify points on the boat. I never imagined a drone can be used to help the sailor, but why not? I am sure that I will never go around the world by sailing. That is not for me in this life, perhaps the next one, I don't know. But if one day I would be able to navigate alone in small areas, a few kilometers, it would be wonderful for me." -P6

As with sailing, our participants envisioned using drones to help them navigate during other popular recreational activities like skiing, hiking, and bicycle riding. Drones can give users feedback on the terrain and obstacles in the vicinity relative to the user's position, enabling them to complete activities independently.

Whether they wanted to navigate through cities on public transportation or do recreational activities in the countryside, participants were concerned about the battery life of drones. Visually impaired people need a reliable device that will support their journey from start to finish. Our participants feared that the current state of drone battery life was not realistic for their envisioned scenarios. This fear is shared with sighted people, as found in prior research [START_REF] Anke | FlyMap: Interacting with Maps Projected from a Drone[END_REF][START_REF] Chang | Spiders in the Sky: User Perceptions of Drones, Privacy, and Security[END_REF].

Input Interaction

Participants reflected on various drone piloting methods, including voice commands, gestures, tangible objects, and standard controllers and joysticks. While participants could picture how each of these methods were accessible and inaccessible, the consensus was that they would need to test these methods in person to understand their feasibility.

Voice Commands

71.18% of survey respondents marked that they would be interested in piloting a drone with voice commands, making it the most popular input interaction method. Participants wanted to send directional commands to the drone, such as "go up 10 meters", combined with environmental information commands like "I want you to go 10 feet away and tell me what you see." During the interview, however, participants were more skeptical. P1 explained that while voice commands can provide an accessible option for people that cannot use their hands, it may be unrealistic to use them in public settings.

"Voice commands are good for people who don't have the ability to use their hands effectively. It covers a broader range of people. But if you want to be discrete, let's say you are sitting in a stadium and trying to understand what is happening on the field better, you don't necessarily want to be using voice assistants too much. You also don't want to seem crazy as you are walking and navigating." -P1 This concern of drones drawing too much attention to the user aligns with previous work looking at public perception of assistive technology [START_REF] Shinohara | Self-Conscious or Self-Confident? A Diary Study Conceptualizing the Social Accessibility of Assistive Technology[END_REF][START_REF] Avila | Look, a guidance drone! Assessing the Social Acceptability of Companion Drones for Blind Travelers in Public Spaces[END_REF].

P6 also wondered if drones would struggle to recognize voice commands in noisy cities or in the countryside where it is windy. He expands, "imagine that you are using a drone in the countryside with the wind and the trees. It will generate some noise. If there is wind or a car goes by, you can lose control of the drone."

However, even with these limitations, P2 prefers to use voice commands over traditional forms of piloting with a joystick or a controller.

"That would keep my hands free. I understand the limitations of voice commands if it's loud and crowded. Then we would have to do the joystick. But the limitations of the joystick are that you are using your hands for one more thing. If I am doing something and doing the drone at the same time, that is difficult to get feedback and control the drone via tactile. You can't ski and have your poles and still have your hands free to control the drone." -P2 Like skiing, as P2 mentions, users may also need to keep their hands free when using a drone while also using other devices like a cane. We described a system where participants could arrange or press blocks to create a flight plan that sends directional commands to a drone (Figure 6). We based the idea of tangible blocks on previous work for BVI users that have explored tangibles for programming [START_REF] Koushik | StoryBlocks: A Tangible Programming Game To Create Accessible Audio Stories[END_REF][START_REF] Morrison | Torino: A tangible programming language inclusive of children with visual disabilities[END_REF] and literacy [START_REF] Gadiraju | BrailleBlocks: Computational Braille Toys for Collaborative Learning[END_REF][START_REF] Jafri | Electronic Braille Blocks: A Tangible Interface-based Application for Teaching Braille Letter Recognition to Very Young Blind Children[END_REF] and were interested in its application for drones. We tested an early concept of our idea in our observational work, during which a participant flew a drone using arrow-shaped blocks. Due to COVID-19, we could not test this system with all of our participants. However, participants were familiar with tangible block interaction and believed that these alternative methods were fun ways to teach visually impaired children about drones and spatial awareness, but not necessarily appropriate for adults.

Tangible Blocks and Maps

"If they are going to be using remotes ultimately, isn't that defeating the purpose? My preference is to start with what you are going to be dealing with, even though it's harder. Then people only have to learn it once. The challenges that have to be worked out, that's part of the learning. You're going to think, 'oh well I was referencing these blocks, but this is nothing like the blocks, the buttons are different shapes.' They both have merit, but one would take longer." -P5 P9 explained that while blocks were fun and playful for people who have little experience with technology, we "do not want to give a false idea of what a drone is. First we should approach drone piloting in a playful workshop and then move on to real piloting." He also explained that blocks would not make sense for children who were already using mainstream technology comfortably, such as video games.

We also discussed users indicating where they want the drone to go by tracing a tactile map. Most participants thought this was interesting because it shared parallels with piloting planes and is used in the education of visually impaired people. However, P9 asserted that this idea should be "banned." "Tactile maps are something that sighted people want to give to blind people. It is very useful to explain and understand, but it is impracticable to live. The mental load is extremely high when using these maps. The blind person is constantly rebuilding what they feel." -P9 Overall, participants preferred standard forms of piloting with either a controller, smartphone, or voice commands over tangible objects. This may be because all our participants were adults (over the age of 18) who were comfortable using technology. As participants explained, tangibles may be of interest to younger participants and adults who are less familiar with drones and technology in general.

Controllers and Smartphones

Smartphones seemed to be the most obvious answer for piloting. Specifically, participants suggested tracing their phone screen to indicate the direction for the drone while receiving haptic feedback. P5 explains that using a phone to control a drone would allow for quick feedback that confirms (1) the drone is doing what you instructed it to do and ( 2) what obstacles are in the environment. Participants also always carry their phones with them, which reduces the need to bring additional devices to pilot their drone. However, the convenience of a phone comes with a downfall. P12 explains that as a visually impaired person, he becomes a target for thieves when they see he has a phone in his hand. "If we lose the phone, we lose the drone," he says.

Participants were not opposed to using a standard controller or joystick without an accompanying smartphone application but explained that accessible adaptations were needed. P1 suggested making buttons on the controller distinct shapes so that users could distinguish between the controls. P13 elaborated, "Joysticks are often not suitable for the visually impaired. We can do better than standard controllers.

We can look at video games, specifically pistol-type joysticks. They are very popular because they allow you to use your middle finger, index finger, and thumb in differentiated ways." -P13 P6 reflected on his experience using a joystick to pilot a drone. He explained that while it was easy to use the joystick itself, he received no feedback from the joystick or drone about the drone's position. His main issue was that he could not gauge how sensitive the drone was to the joystick's movements. P7 also explained if systems were to incorporate tactile feedback for visually impaired pilots, it would be difficult to use both a controller and receive feedback. He offered the solution of using one hand to receive tactile feedback while the other controls the drone through physical gestures. However, even when using physical gestures while piloting drones, P10 struggled with drone sensitivity and latency issues like P6. During our observational work, P10 attempted to fly using accelerometers on his wrist using the interface provided with the SP300 Mini Drone [START_REF]SP300 Mini Drone[END_REF].

There was a delay between moving his wrist and the corresponding movement of the drone. This latency was so significant that P10 was unable to pilot without crashing into the safety nets.

Feedback

Representing the three-dimensional (3D) space of flight is particularly difficult for people who are visually impaired. Therefore, the types of feedback participants want are complex and often require several modalities.

Participants require specific information on the position and movement of the drone. This includes altitude, velocity, and the general direction that the drone is going. However, P6 reminds us that feedback can also be overwhelming, and providing the appropriate amount of feedback is a delicate balance. "I have only one brain and only two ears, so I need to get efficient information with only one brain," he says. In this section, we examine when different feedback mechanisms, like audio and haptics, are appropriate.

Audio

Audio feedback from the drone allows pilots to receive information without depending on descriptions from sighted people. We split audio into two categories: (1) spoken information and (2) sounds. Participants felt that spoken information, similar to VoiceOver, should be reserved for safety threats to the drone, such as crash warnings, and crucial environmental information, like obstacle detection. P8 explains that spoken text "gives you a rough idea of what is happening but is not precise enough for a 3D space. We really need to have perceptual cues." Supplemental beeps, tones, and ambient sounds could better describe where the drone moves, characterize the 3D space and give perceptual cues about the user's environment. P1 expands on this concept.

"The closer you get to something, beeping could increase. Moving further, then it slows to a more regular rhythm. Different objects, we could assign different tones for different types of situations. For a pothole, like a boiling, bubbling, nasty sound. You should be able to have the ability to control the amount of feedback, so it doesn't get too annoying." -P1

However, this audio feedback should not come from the drone. Participants who had been around drones quickly informed us that they find the drone's noise unpleasant and that any audio feedback should come from an external source. P5 likened the sound to a "giant fly," while P7 described it as a "whiney sound that sounded like a bunch of bees ready to attack." Prior work with drones [START_REF] Chang | Spiders in the Sky: User Perceptions of Drones, Privacy, and Security[END_REF] shows that sighted people also dislike the sound that drones emit. While some participants, like P8 and P13, were open to receiving feedback from the drone when it was close to them, all participants agreed that headphones or smartphones were the most appropriate way to receive audio. P9 specified that bone conduction headphones would be the best option. This way, users could receive audio without being stuck in a "bubble" and still receive environmental sound.

During our observational work and piloting practice with P10, we noticed how the room's acoustics was a natural form of audio feedback and impacted the participant's ability to localize the drone. While flying in a large flight arena, the sound reverberation was strong. The noise interference made it difficult to hear where the drone was in the arena, particularly for drone models that emitted higher pitch sounds (lower pitch sounds were easier to distinguish).

Touch and Haptics

While audio feedback is ideal for free flying and environmental information, participants explained that tactile feedback is helpful for (1) object detection and proximity, (2) spatial awareness and distance perception, and (3) directional information. However, participants had a wide range of ideas on how they wanted to receive this haptic feedback. The most popular idea was receiving haptic feedback on their wrists and hands through bracelets, armbands, watches, and gloves. P13 explains that hands are sensitive to tactile feedback, making them an ideal location to place sensors. Some participants also imagined receiving haptic feedback over their clothes on different parts of their bodies. P1 offered, "maybe a buzz clip that you wear on your shirt." P6 exclaimed, "we can imagine something also in the pocket, something in the shoes, I don't know a lot of solutions! On the hat!" P6 also described an elaborate haptic feedback system worn on the shoulders that he tested for his job. P13 supports the "clock-like framing mode" that P6 describes, calling it "very powerful because it is egocentric."

P8 explained that he would prefer vibration on his phone over these alternative methods since he already carries his phone with him at all times. P7 brainstorms how a user could use a touchscreen to receive feedback from the drone while controlling it. "Imagine you have this vibro-tactile blip moving around the screen that tells you where it is. The drone is hovering, and I drag the blip towards me and that actually has an effect on the control mechanism of the drone and brings it towards me," he suggests.

When considering the many options for haptic sensors and tactile feedback for visually impaired people, P13 implores designers to consider vibration patterns. He emphasizes that for haptic sensors to provide detailed enough feedback for drones, designers must build "a lexicon and vibratory grammar in relation to specific situations."

DISCUSSION

From our interviews, we learned that visually impaired people are motivated to fly drones based on diverse personal interests, including aviation, technology, and family recreational activities. In this section, we present five personas designed around these unique motivations to better characterize types of visually impaired drone users. We then theorize how future user studies can build on these personas to test specific tasks our participants wanted drones to support. In our findings, we saw that participants had concerns about safety and drone crashes, particularly when first learning to pilot. Here, we further discuss training and safety protocols for visually impaired drone pilots.

Personas

From our participant interviews, distinct motivations to fly drones emerged, including who participants want to fly with, where they envision flying, and which tasks they want drones to assist and integrate with. We created the following five personas to understand the different types of fliers we observed: (1) The Family Flyer, (2) the Environment Explorer, (3) the Navigator, (4) the Aviation Enthusiast, and (5) the Technology Fan.

We note that while all of our participants fall into at least one of these five categories, some participants belong to more than one persona. These profiles are not all-encompassing, but these personas demonstrate how a user's hobbies and environment can lead to specific design scenarios for future user studies and accessible features for drones. For example, a Navigator may be more interested in a drone that pairs with existing navigation apps, provides information about nearby public transportation, and alerts users about obstacles on the sidewalk. Additionally, they may require interaction methods that are compatible with noisy cities and a drone that is smaller and does not draw too much attention in public. However, a Family Flyer may be more interested in a drone that offers collaborative piloting features and provides feedback about the terrain of the user's environment during recreational activities such as hiking.

We refrained from formally analyzing and including cultural differences in our personas due to our moderate sample size of 13 participants. However, we did reflect on some similarities in motivation between countries.

We found participants were interested in using drones for similar applications but tended to share specific interests based on where they lived. Our participants from Australia were interested in water-based activities, like whale-watching. American participants were similarly interested in outdoor activities, but in the mountains or within their neighborhoods. Many participants from France were passionate about aviation, perhaps due to France's national aviation schools, institutes and well-established organizations for Blind pilots. However, even with these specific interests, we found that the overarching motivations to use drones overlapped. This overlap could be because the US, France, and Australia are well-developed countries with similar resources and infrastructure for BVI users.

Training and Safety

Throughout our interviews, participants split between wanting to fly collaboratively and independently. However, for initially learning how to pilot drones, most participants advocated for hands-on instruction led by a sighted person. Participants who were alone during their first time flying feared crashing. This apprehension prevented them from exploring the full capability of the drone.

In-person instruction looks different for users based on what motivates them to fly. People interested in social and leisure drone piloting (the Family Flyer persona) may be open to informal instruction from friends. However, users interested in drones as a more serious hobby (the Technology Fan and Aviation Enthusiast personas) may prefer structured classes. P10 (the Aviation Enthusiast persona) explained it would be necessary to have a weekly training course or workshop by a club specializing in drone piloting. However, P4 (the Environment Explorer persona) had a more laissez-faire approach. "Personally, I am a 'hands-on and show me how to use this thing' person. I don't read instructions. I would rather get in there, play, and work it out."

As we saw in our study, participants were more concerned about damaging or losing the drone than their own safety. This concern indicates that along with instruction, drones for visually impaired people should contain extra features to protect the drone, such as obstacle detection and a "self-preservation mode", as P2 described.

Finally, while visually impaired people may receive extensive pilot and safety training, they cannot control the environment when other people fly drones around them. "I guess it's the same as cars, you have good and bad drivers. I think my concern at the moment is that it's not treated as seriously as driving. It's more of a really expensive toy or another mobile thing that doesn't have an impact. I can be as responsible and have all the technology to know what things are where, but if other people are careless then that's all undone. It has to be a shared space." -P5 Future work that investigates drone piloting for visually impaired people should consider how to design accessible training so that users feel supported in the different facets of drone interaction. As P5 summarized, "it's the entire solution that needs to be accessible."

FUTURE WORK AND LIMITATIONS

Our interviews allowed us to understand what motivates visually impaired people to fly drones, learn what interaction and feedback features can support accessible drone piloting, and create personas to inform user testing and design in future work. In this section, we expand on building user studies and address some limitations of our work.

The personas we created present different contexts that visually impaired people want to fly in. In future work, we are interested in designing user studies around each of these personas. We will create tasks that represent the diverse needs of users. We will also test different input configurations (voice commands, controllers, and smartphones) with feedback combinations (vibrotactile and audio). As we mentioned in the Discussion, future work can also investigate safety and training protocols for visually impaired drone pilots. Additionally, we can look at collaborative piloting directly between visually impaired and sighted people, or independent piloting in shared spaces populated by several drones.

A limitation of our work is that by recruiting online, we are inherently looking for participants who have baseline comfort with using technology. This familiarity with technology can indicate a certain level of socioeconomic privilege in our participants. Additionally, by working with organizations centered around BVI users, our participants may already have previous experience with research, surveys, and interviews. We conducted our interviews with participants across three different countries: The United States, France, and Australia. While socio-cultural factors undoubtedly contributed to our participants' interests and motivations, we felt that generalizing was inappropriate for this early stage in work around visually impaired people and drones. This limitation of our work may present a rich opportunity for future research that looks at how drone piloting and motivation among visually impaired people vary across cultures, as has been done for sighted people [START_REF] Landay | Drone & Wo: Cultural Influences on Human-Drone Interaction Techniques[END_REF].

CONCLUSION

This work established motivations and new application ideas that Blind and Visually Impaired (BVI) users have for using drones, both in navigation and other leisure hobbies. Our work presents domains that are not currently being addressed by prior/ongoing work for BVI users and elicit a new set of desires from participants. These motivations include navigation assistance, environment exploration, recreational activity support, and leisure, as displayed by the personas we designed. Our contribution also shows that several configurations of piloting methods and feedback are necessary, depending on the pilot's environment and preferences, to represent drones in a 3D space. Moreover, we discuss the need for training and safety features. We hope that this work enables other researchers and practitioners to further consider and improve the accessibility of future drones.

Figure 1 (

 1 Figure 1 (left). Age of participants who responded to our survey. Figure 2 (right). Vision level of participants who responded to our survey.

Figure 3 (

 3 Figure 3 (left). Tactile maps with Braille notation and raised-line icons to convey aviation information to visually impaired pilots. Figure 4 (right). A tactile map of France with raised regions and varying color to convey the altitude of the land.

Figure 5 .

 5 Figure 5. In the survey, participants ranked their interest in piloting drones on a scale from one (not at all interested) to five (extremely interested). The majority of respondents (54.23%) ranked their interest at five on the Likert scale.

Figure 6 .

 6 Figure 6. P10 exploring tangible blocks shaped like arrows to pilot a drone.

"

  Imagine you have four vibration systems on the shoulders. You have vibrations in front and at the back of the shoulders, two on left, two on right. If you have to ride only at two o'clock or ten o'clock [referring to direction], you will have vibration only at one shoulder on the front. If you have to ride directly at nine o'clock or three o'clock, so a rotation of 90 degrees, you will have a vibration on the same shoulder with both vibrations at the front and back. If there is an obstacle in front of you, four vibrations will be generated at the same time. I think it could be interesting to get something like that on your shoulders to interface with the drone and to have some vibration giving the direction of the motion of the drone." -P6

Table 1 .

 1 A breakdown of the interview participants by location, age range, gender, and level of vision impairment. We used the World Health Organization categories of vision impairment for our participants.

		Country	Age Range	Gender	Vision Impairment
	P1	United States	Between 35-44	Male	Near total blindness (less than
					20/1000)
	P2	United States	Between 45-54	Female	Total blindness
	P3	United States	Between 35-44	Female	Near total blindness
	P4	Australia	Between 45-54	Female	Moderate vision impairment (20/70
					to 20/160)
	P5	Australia	Between 45-54	Female	Total blindness
	P6	France	Between 45-54	Male	Profound vision impairment (20/500
					to 20/1000)
	P7	United States	Between 45-54	Male	Near total blindness
	P8	France	Between 18-24	Male	Near total blindness

ACKNOWLEDGMENTS

We thank our participants who completed our survey and interviews. We would also like to thank Mirauds Volants for collaborating with us on the observational work. This work was supported by the Chateaubriand Fellowship (through the French Embassy in the United States) and the National Science Foundation Graduate Research Fellowship under grant DGE 1650115. Any opinions, findings, conclusions, or recommendations expressed in this work are those of the authors and do not necessarily reflect those of the National Science Foundation or the French Embassy. Finally, we would like to thank our lab members at the Interactive 20 Informatics Team at ENAC Toulouse and the Superhuman Computing Lab at the University of Colorado Boulder for their support and feedback on this work.


Ekaterina D Starichenko
email: ekaterinastarichenko@phystech.edu

Denis A Belyaev

Alexander S Medvedev

Anna A Fedorova

Oleg I Korablev

Alexander Trokhimovskiy

Erdal Yiğit

Juan Alday

Franck Montmessin

Paul Hartogh

Erdal Yigit

Gravity wave activity in the Martian atmosphere at altitudes 20-160 km from ACS/TGO occultation measurements

établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The structure and circulation of planetary atmospheres are strongly affected by gravity waves (GWs), which are ubiquitous in any convectively stable atmosphere. They are primarily responsible for energy and momentum transfer from the lower to the upper atmosphere. Historically, GW-induced coupling was extensively studied in Earth's atmosphere (e.g., see reviews by [START_REF] Fritts | Gravity wave dynamics and effects in the middle atmosphere[END_REF]Yigit & Medvedev, 2015). With the progress in space exploration, the atmosphere of Mars has become the second beststudied example. Numerous space missions accompanied by numerical modeling have delivered ample evidence for the importance of GWs on Mars. Some of the Martian GW effects, their commonality and specifics with those on Earth, have been summarized in the recent review by [START_REF] Medvedev | Gravity Waves in Planetary Atmospheres: Their Effects and Parameterization in Global Circulation Models[END_REF]. Observational knowledge of GW activity on Mars is crucial but still insufficient for quantifying their effects and constraining Martian general circulation models (MGCMs). Our paper addresses this problem by utilizing high-resolution occultation data obtained from the Atmospheric Chemistry Suite (ACS) instrument on board the Trace Gas Orbiter (TGO).

Observations of the Martian GWs have been conducted from orbiters by different remote sensing techniques and in situ methods. In situ measurements of GW-induced density fluctuations in the thermosphere were performed with accelerometers during aerobraking operations by several spacecraft including Mars Global Surveyor (MGS), Mars manuscript submitted to JGR: Planets Odyssey (ODY), Mars Reconnaissance Orbiter (MRO), Mars Atmosphere and Volatile EvolutioN (MAVEN) and Trace Gas Orbiter (TGO) [START_REF] Keating | The Structure of the Upper Atmosphere of Mars: In Situ Accelerometer Measurements from Mars Global Surveyor[END_REF]Creasey et al., 2006a;[START_REF] Fritts | Mean and gravity wave structures and variability in the Mars upper atmosphere inferred from Mars Global Surveyor and Mars Odyssey aerobraking densities[END_REF][START_REF] Tolson | Application of Accelerometer Data to Mars Odyssey Aerobraking and Atmospheric Modeling[END_REF][START_REF] Tikhonov | Atmospheric modeling using accelerometer data during Mars Reconnaissance Orbiter aerobraking operations[END_REF][START_REF] Withers | Mars Global Surveyor and Mars odyssey accelerometer observations of the Martian upper atmosphere during aerobraking[END_REF][START_REF] Jesch | Density Fluctuations in the Lower Thermosphere of Mars Retrieved From the ExoMars Trace Gas Orbiter (TGO) aerobraking[END_REF][START_REF] Vals | Study of gravity waves distribution and propagation in the thermosphere of Mars based on MGS, ODY, MRO and MAVEN density measurements[END_REF][START_REF] Siddle | Density structures in the Martian lower thermosphere as inferred by Trace Gas Orbiter accelerometer measurements[END_REF]. GWs in the upper thermosphere were also measured by Neutral Gas and Ion Mass Spectrometer (NGIMS) on board MAVEN (Yigit et al., 2015;England et al., 2017;[START_REF] Terada | Global distribution and parameter dependences of gravity wave activity in the Martian upper thermosphere derived from MAVEN/NGIMS observations[END_REF]. Temperature and density disturbances associated with GWs have been remotely retrieved from stellar, solar and radio occultation data as well as from limb observations [START_REF] Hinson | Initial results from radio occultation measurements with Mars Global Surveyor[END_REF]Creasey et al., 2006b;[START_REF] Ando | Vertical wavenumber spectra of gravity waves in the Martian atmosphere obtained from Mars Global Surveyor radio occultation data[END_REF][START_REF] Wright | A one-year seasonal analysis of Martian gravity waves using MCS data[END_REF][START_REF] Heavens | A multiannual record of gravity wave activity in Mars's lower atmosphere from -17-ESSOAr[END_REF][START_REF] Nakagawa | Vertical Propagation of Wave Perturbations in the Middle Atmosphere on Mars by MAVEN/IUVS[END_REF].

The shortcoming of many previous GW observation techniques is their limited altitude coverage. For example, in situ measurements were confined to a relatively narrow vertical range in the thermosphere, while radio occultation and infrared limb sounding allowed for studying the lowermost (0-40 km) part of the atmosphere. Remote sensing in UV permitted the extension of the altitude coverage. The Spectroscopy for the Investigation of the Characteristics of the Atmosphere of Mars (SPICAM) instrument on board Mars Express (MEX) measured temperature and density profiles between 60 and 130 km [START_REF] Forget | Density and temperatures of the upper Martian atmosphere measured by stellar occultations with Mars Express SPICAM[END_REF]. The Imaging Ultraviolet Spectrograph (IUVS) on board MAVEN explored the thermospheric layers (100-150 km) (Medvedev et al., 2016;[START_REF] Gröller | MAVEN/IUVS stellar occultation measurements of Mars atmospheric structure and composition[END_REF]. Recently, [START_REF] Nakagawa | Vertical Propagation of Wave Perturbations in the Middle Atmosphere on Mars by MAVEN/IUVS[END_REF] obtained temperature profiles from IUVS data spanning the atmosphere from 20 to 140 km with a vertical sampling better than 6 km. ACS/TGO is the first IR instrument that allows for measuring in the solar occultation mode temperature and density distributions within an even broader range of altitudes (20-160 km). Since April 2018, the Middle InfraRed (MIR) spectrometer, one of the three spectrometers of ACS, delivered several hundreds of profiles, some of which having vertical resolution allowing for the study of GWs.

Smaller-scale GW-induced temperature perturbations have to be first separated from the background temperature field associated with the large-scale variations. Although this procedure has been frequently performed in the terrestrial and Martian context, there is no universal technique that can be applied to vertical profiles obtained from different instruments [START_REF] Ehard | JGR: Planets for gravity wave extraction from middle-atmospheric lidar temperature measurements[END_REF]. In this work, we explore the sensitivity of several methods for extracting GWs from the ACS MIR data and describe their applications for deriving various characteristics of the GW field (amplitudes, wave potential energy, momentum fluxes and wave drag) from the first available set of ACS/TGO data.

The paper is structured as follows. The ACS/TGO experiment and the instrument itself are outlined in Section 2. Section 3 describes the methods used in this study. In particular, retrievals of temperature profiles from measured spectra are presented in section 3.1, the techniques for extracting wave disturbances are given in section 3.2. Subsection 3.3 describes the derivation of wave activity (amplitude of wave packets) and potential energy, and 3.4 outlines the calculation of the absolute vertical flux of horizontal momentum and momentum forcing of the mean flow. The results are presented in section 4. They include a case study (4.1), the spatial distribution of wave characteristics (4.2), and the relationship between wave amplitudes and the Brunt-Väisälä frequency (4.3). Conclusions are given in section 5.

2 Atmospheric Chemistry Suite Instrument on Board Trace Gas Orbiter ACS is a set of three infrared spectrometers for ExoMars 2016 TGO mission. It has been operating in the Martian orbit since April 2018. ACS consists of the near-(NIR), middle-(MIR) and thermal-infrared (TIRVIM) channels, that altogether cover the broad spectral range of 0.7-17µm. [START_REF] Korablev | The Atmospheric Chemistry Suite (ACS) of three spectrometers for the ExoMars 2016 Trace Gas Orbiter[END_REF]. In this paper, we use the data retrieved from the cross-dispersion echelle MIR spectrometer working in the solar occul- manuscript submitted to JGR: Planets tation mode in the 2.3-4.2 µm range. This spectral coverage is achieved with a secondary dispersion grating, which can be rotated to one of 12 positions. During an occultation, the instrument is pointed to the Sun. Each measurement consists of an image at the 640× 512 pixels focal plane array (FPA), which accommodates up to 20 diffraction orders dispersed over FPA by the secondary grating. One occultation covers 0.15-0.3 µm range. The instrument's resolving power is λ/∆λ ∼25 000 and the signal-to-noise ratio varies between 1000 and 10000. The vertical resolution of MIR depends on the integration time (∼2 s per image) and ranges from 0.5 to 2.5 km. The transmission is obtained by division of the solar spectrum passed through the atmosphere to the reference one, which is measured above the altitude of 200 km, where the absorption by the atmosphere is negligible.

In this study, we use the 2.66-2.68 µm portion of the spectrum from the grating position #4, the echelle diffraction order #223, which includes a wing of the 2.7µm CO 2 absorption band (Figure 1a). Strong absorption lines of CO 2 allow for retrieving tem- perature and density in the Martian atmosphere with good sensitivity.

Methods

Retrieval of Temperature Profiles

The retrieval scheme consists of several iterations. On the first step, we retrieve temperature and pressure from the rotational structure of CO 2 absorption bands in spectral intervals without H 2 O lines (see Figure 1a). A priori altitude profiles of T (z) and p(z) as well as one of the CO 2 VMR, are taken from the Mars Climate Database (MCD) manuscript submitted to JGR: Planets for a specified occultation in MY34 (Millour et al., 2018). On the second step, we simultaneously retrieve temperature and CO 2 concentration, while the pressure profile is kept constant assuming the hydrostatic equilibrium p hyd (z) = p 0 (z 0 ) exp[-

z z0 g(z )M (z ) RT (z ) dz ],
where g is the acceleration of gravity, M is the atmospheric molar mass and R is the gas constant. The reference pressure p 0 is chosen at an altitude z 0 , usually around 30-50 km, where uncertainties of the fitting are smallest. We repeat the second step 5-7 times until the profiles reach convergence. In each iteration, we apply the Tikhonov regularization [START_REF] Tikhonov | Atmospheric modeling using accelerometer data during Mars Reconnaissance Orbiter aerobraking operations[END_REF] for the temperature and concentration altitude profiles with a smoothing coefficient less than 5 km. It defines the shortest wavelength to 5-6 km when analyzing vertical wavy structures. The third step focuses only on CO 2 and H 2 O concentration retrievals over the entire wavenumber range in order #223 (Figure 1a) using the p(z) and T (z) profiles already found. This step is not a subject of the present paper.

A similar fitting procedure, including the hydrostatic approximation, has been used in the work by [START_REF] Fedorova | Stormy water on Mars: The distribution and saturation of atmospheric water during the dusty season[END_REF] (proprietary code) and [START_REF] Alday | Oxygen isotopic ratios in Martian water vapour observed by ACS MIR on board the ExoMars Trace Gas Orbiter[END_REF] (the NEME-SIS code, [START_REF] Irwin | The NEMESIS planetary atmosphere radiative transfer and retrieval tool[END_REF]) in their retrievals of temperature and pressure from the ACS data. We validated our atmospheric temperature and number density profiles with simultaneous and collocated occultation measurements by ACS-NIR [START_REF] Fedorova | Stormy water on Mars: The distribution and saturation of atmospheric water during the dusty season[END_REF].

An example comparison is presented in Figure 1b. A weaker CO 2 absorption band at 1.58 µm measured by NIR allows for detection up to 110-120 km, or the density of ∼ 10 12 cm -3 , while the band at 2.7 µm observed by MIR is measurable up to 160-170 km, or ∼10 9 cm -3 . The lowermost altitude of the temperature profile retrieval is conditioned by the aerosol opacity and by the saturation of the CO 2 absorption lines.

Each temperature value in a vertical profile was retrieved by fitting a modeled transmission spectrum J mod to the measured one J mes at a specified altitude. We model the spectra by the Beer-Lambert law

J mod (ν, z) = exp -(σ CO2 (T, p)n CO2 (z ) + σ H2O (T, p)n H2O (z ) + τ a )dz , (1)
where n(z) are gaseous concentrations, σ(T, p) are absorption cross-sections of CO 2 and H 2 O correspondingly for specific temperature T (z) and pressure p(z) at an altitude z, and τ a is aerosol slant opacity. A transfer between the linear [cm -2 ] and the volume [cm -3 ] concentrations is performed using the well-known "onion-peeling" method with the numeric integration over all altitude layers z i above the i-th one. Molecular cross-sections are calculated line-by-line on a basis of the HITRAN2016 database (Gordon et al., 2017) considering pressure-broadening coefficients of the H 2 O lines suitable for a CO 2 -rich atmosphere [START_REF] Gamache | A spectral line list for water isotopologues in the 1100-4100 cm-1 region for application to CO2-rich planetary atmospheres[END_REF] and self-broadening in the case of CO 2 . Then we convolve the modeled spectrum by the previously determined instrument line shape (ILS) using wavenumber calibrations (see details in [START_REF] Alday | Oxygen isotopic ratios in Martian water vapour observed by ACS MIR on board the ExoMars Trace Gas Orbiter[END_REF]. The fitting procedure is conducted by minimizing the "chi-square" function

χ 2 = i A 2 (ν i ), A(ν i ) = [J mod (ν i )-J mes (ν i )]/δJ
, where δJ are transmittance uncertainties, and the sum is taken over all considered spectral points (pixels). Our optimization algorithm to search for the χ 2 minimum is based on partial derivatives of the Jacobian matrix ∂A/∂X [START_REF] Marquardt | An Algorithm for Least-Squares Estimation of Nonlinear Parameters[END_REF], where X is a vector of free parameters, i.e., temperature, CO 2 concentration, H 2 O mixing ratio, and aerosol slant opacity. Here, a significant contribution to the Jacobian comes from the rotational absorption lines, which are strongly sensitive to the temperature variability in the spectral range of interest.

Derivation of Wave Disturbances

Gravity wave-induced perturbations of temperature T are sought by separating the mean, or background profile T (z) from the measured one T (z): where the bar denotes an appropriate averaging. Generally, it implies averaging over wave phases, or spatial and temporal scales that are larger than the periods and wavelengths of contributing GW harmonics. In the case of almost instantaneous (with respect to the periods of GWs) occultation profiles, only separation in vertical scales is possible.

T = T -T , (2)
John and Kumar (2013) and [START_REF] Ehard | JGR: Planets for gravity wave extraction from middle-atmospheric lidar temperature measurements[END_REF] reviewed several common methods of the partition of measured temperature and/or density profiles into the "mean" and wave components. They work well if a clear separation in vertical wavelengths does exist between GWs and large-scale motions belonging to the background. This is not always the case in the Martian atmosphere, because vertical scales of disturbances associated with tides, planetary waves, and other motions may overlap with those due to GWs.

It is desirable to retain the former in the background, but one still has to set a vertical scale Λ z that separates GWs from the larger-scale features. In the following, we assumed Λ z = 30 km. This value may lead to an overestimation of the retrieved wave activity by including non-GW perturbations, but at least no large-scale GW components are missed.

Concerning the short-wavelength part of the spectrum, the limited vertical resolution favors detection of larger-scale waves, leaving out harmonics with smaller scales unobserved. [START_REF] Alexander | Interpretations of observed climatological patterns in stratospheric gravity wave variance[END_REF] has quantified this "observational filter" and pointed out that some large-scale harmonics refracted by the mean wind beyond the lowest resolution may be missing in observations as well.

We explore three methods: spectral filtering, sliding least-square polynomial fit and high-order polynomial fit. The former two have been discussed in relation to lidar and space-based measurements in the atmosphere of Earth [START_REF] John | A discussion on the methods of extracting gravity wave perturbations from space-based measurements[END_REF][START_REF] Ehard | JGR: Planets for gravity wave extraction from middle-atmospheric lidar temperature measurements[END_REF], and the references therein), while the latter was applied to profiles obtained in the terrestrial (e.g., [START_REF] Spiga | Identification of the sources of inertia-gravity waves in the Andes Cordillera region[END_REF] and Martian atmosphere (Yigit et al., 2015;[START_REF] Terada | Global distribution and parameter dependences of gravity wave activity in the Martian upper thermosphere derived from MAVEN/NGIMS observations[END_REF][START_REF] Jesch | Density Fluctuations in the Lower Thermosphere of Mars Retrieved From the ExoMars Trace Gas Orbiter (TGO) aerobraking[END_REF]. Since the ACS data are distributed irregularly over the altitude, they were first interpolated (oversampled) to an evenly spaced 500-m grid. We used only the temperature data with errors ≤10 K. Spectral filtering was per- This method yields smooth mean temperature profiles and, as a result, large deviations from the mean (Figure 2b andd). This is in particular obvious below 60 km and in the upper part of the domain (panels b and d).

For the sliding polynomial fit, we used a procedure described in the work of [START_REF] Whiteway | This content has not been peer reviewed. manuscript submitted to JGR: Planets in the upper stratosphere over Toronto[END_REF]. The background profiles are obtained by fitting cubic polynomials within the 60-km sliding intervals. Observational errors were used as weights, that assign a significance to the measurements at each altitude. At first, the intervals were shifted up from the bottom to top by a certain distance (shown in Figure 2a and c for 2 and 11 km), and then the procedure was repeated for the downward shifts starting from the top. The overlapping values of fits from each range were then averaged. Thus obtained profiles were then smoothed using a moving average. At the bottom of the profiles, we had to decrease the width of the sliding windows due to large spurious variations in fitted polynomials and in order to make most of the observational data. The upper and lower 4 km of thus obtained profiles have to be excluded anyway, because of the poor behavior of fitting polynomials, which cannot be averaged with counterparts from other sliding windows. This method occasionally produces disturbances oscillating not around zero. To correct for these numerical biases, we perform detrending by applying the Theil-Sen estimator [START_REF] Theil | A rank-invariant method of linear and polynomial regression analysis[END_REF][START_REF] Sen | Estimates of the Regression Coefficient Based on Kendall's Tau[END_REF] and fitting a linear function to the perturbation profile. The Theil-Sen estimator is a robust method, which is used for determining the linear regression taking the median of the slopes of all lines that can be drawn The results for the sliding polynomial fit are plotted in Figure 2 for the 2 and 11 km shift steps with green and yellow lines, correspondingly. It is seen that they are very close and, thus, the background and disturbances depend on the sliding step to a minor degree. The method shows some useful features in comparison with spectral filtering.

The fitted mean curves in the regions of large-scale disturbances (Case 1) follow the observed temperature profiles closer (Figure 2a) and are smoother where small-scale structure dominates (Case 2) (Figure 2c, between 70 and 130 km). This produces smaller wave amplitudes in Case 1, and reveals more wavy structures in Case 2. Especially plausible results are in the bottom of the profiles, where GWs are expected to have smaller amplitudes (due to larger density). manuscript submitted to JGR: Planets

We next explored the technique of fitting higher-order polynomials in the entire interval of heights. In particular, the seventh-order polynomial fit, which was previously used for extracting GWs on Mars (Yigit et al., 2015;[START_REF] Jesch | Density Fluctuations in the Lower Thermosphere of Mars Retrieved From the ExoMars Trace Gas Orbiter (TGO) aerobraking[END_REF], produces most plausible results. They are presented in Figure 2 with dashed and dotted blue lines. It is immediately seen that thus obtained wave disturbances are in a very good agreement with those derived by the sliding polynomial fit method, especially for profiles containing small-scale features (Figure 2d). For profiles dominated by large-scale perturbations, the agreement is also good in terms of the determined vertical structure of the wave, although the magnitudes are often exaggerated (Figure 2b). The weak point of the method is that it occasionally produces spurious disturbances near the edges of the vertical domain with vertical gradients of the mean temperature directed opposite to the measured profiles. After careful consideration of the three methods applied to the available measurements, we selected the sliding third-order polynomial fit as the most appropriate and robust.

Wave Activity and Potential Energy

The GW field is often characterized by the magnitude of fluctuations

|T | = (T 2 ) 1/2
and wave potential energy (per unit mass)

E p = 1 2 g N 2 T T 2 , ( 3
)
where N is the Brunt-Väisäla frequency

N = g T dT dz + g c p , (4)
g is the acceleration of gravity and c p is the specific heat capacity at constant pressure.

The amplitude of the wave packet at a given height |T (z)| (hereafter called "wave activity") represents an envelope of the measured profile T (z). We calculated it by performing Fourier decomposition in each sliding 60-km vertical interval and, based on Parceval's identity, summing up contributions of all harmonics. Examples of thus obtained envelopes and potential energy for the same selected profiles as in section 3.2 are presented in Figure 3. Blue and red dashed lines denote the quantities calculated from the entire spectrum and by accounting for contributions of only two largest harmonics. It is seen that the neglect of shorter-scale harmonics, as was occasionally done in analyses of satellite observations (e.g., [START_REF] Ern | Absolute values of gravity wave momentum flux derived from satellite data[END_REF], introduces little error to the estimated GW activity. However, the neglect of short-scale harmonics may lead to a noticeable underestimation of wave potential energy, (cf. Figures 3b andd).

Momentum Flux and Momentum Deposition

Another useful characteristic of the GW field is the vertical flux of horizontal momentum, or "momentum flux" for brevity, F = (F x , F y , 0) = ρ 0 (u w , v w , 0), where ρ 0 is the mean density and (u , v , w ) are the components of wave-induced perturbations of wind velocity u along with the two horizontal and the vertical axis, correspondingly.

Momentum flux is constant for conservatively propagating waves. Breaking/dissipating GWs deposit their momentum to the mean flow, thus inducing an acceleration or deceleration (depending on the sign) of the horizontal flow

(a x , a y ) = - 1 ρ 0 dF dz . ( 5
)
The direction of the flux cannot be determined from the occultation measurements, however total (or absolute) momentum fluxes for a harmonic be estimated (e.g., Ern et al., 2004, sect. 4):

F k,m = F 2 x,k,m + F 2 y,k,m can
F k,m = 1 2 ρ 0 k h m g N 2 |T k,m | T 2 , (6)
where k h and m are the horizontal and vertical wavenumbers, correspondingly, and |T k,m | is the amplitude. The latter two are found from the Fourier decomposition, whereas k h cannot be derived from our measurements.

The total flux F is the sum of contributions of individual harmonics F = m F k,m .

Since the horizontal wavenumber k h cannot be obtained from the measurements, it, therefore, serves as a scaling factor for the derived profiles of F and momentum forcing (5).

The densest atmospheric footprint at a target point in occultation geometry is 400-500 km horizontally, depending on the height. This constrains the upper limit for unresolved wavelengths. In our calculations, we assumed a representative horizontal wavelength λ h = 2π/k h = 300 km, the value typically used in numerical general circulation models (Yigit manuscript submitted to JGR: Planets disturbances. Near 110 km, N 2 drops almost to zero as the result of the temperature gradient (associated with a large amplitude of the disturbances) approaching the adiabatic lapse rate. Enhanced wave dissipation due to a combination of physical processes [START_REF] Yigit | Influence of gravity waves on the climatology of high-altitude Martian carbon dioxide ice clouds[END_REF] in the vicinity of the convective instability severely limits the GW amplitude, leading to the decrease of the momentum flux above this altitude and peaking of the mean flow acceleration (Figure 5d) at almost 2000 m s -1 sol -1 . In the analyzed data set, such large numbers are not common and occur only occasionally. Application of a smaller vertical shift of sliding intervals shows finer structure of the GW momentum flux and drag, but do not significantly modify the magnitudes.

Spatial Distribution of Gravity Wave Activity

In this section, we use the data obtained by the ACS instrument in MY34, at solar longitudes from L s = 164 • to 354 • . The data set contains altogether 144 occultation profiles: 84 in the northern hemisphere and 60 in the southern one. The latitudesolar longitude coverage is shown in Figure 6 with red and blue dots representing morning and evening occultation measurements, correspondingly. The longitudinal orbit coverage was fairly uniform, and is not discussed here. and Ion Mass Spectrometer (NGIMS) on board MAVEN revealed even larger GW magnitudes over the same time [START_REF] Leelavathi | Interannual Variability of Atmospheric Gravity Waves in the Martian thermosphere: Effects of the 2018 Planet-encircling Dust Event[END_REF]Yigit et al., 2021). The latitudinal structure of the GW activity in the mesosphere and lower thermosphere is not uniform.

For comparison, we overplotted the zonal wind simulated with the Max Planck Institute (MAOAM) MGCM https://mars.mipt.ru/ for MY34 and averaged over the same interval of L s as in the observations. The wind distribution varied during this time from the equinoctial to solstitial and back to the equinoctial types. The result reflects the largest contribution of the prograde and retrograde jets during the perihelion solstice. It is seen that the regions with large wave amplitudes encircle the upper edges of two midlatitude jets. This is the result of intensive filtering of individual harmonics by strong background winds. For the wave potential energy, which is a quadratic function of wave amplitudes, this pattern is even more obvious (Figure 7b). worthy that such distribution of the GW drag is very similar to that predicted by a Martian GCM (Medvedev et al., 2011, Figures 3 and 7) for the solstice and equinox, respectively, and represents the first (to the best of our knowledge) observational validation of the model predictions. The magnitudes of the GW drag, although defined up to the constant k h , agree with the simulations (using a similar k h ) as well.

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Frequency

In situ measurements with NGIMS on board MAVEN showed a clear anti-correlation between relative density fluctuations in the upper thermosphere and the ambient temperature (Yigit et al., 2015;England et al., 2017;[START_REF] Terada | Global distribution and parameter dependences of gravity wave activity in the Martian upper thermosphere derived from MAVEN/NGIMS observations[END_REF][START_REF] Vals | Study of gravity waves distribution and propagation in the thermosphere of Mars based on MGS, ODY, MRO and MAVEN density measurements[END_REF].

It was linked to convective instability as a dominant mechanism that limits growth of GW amplitudes with height (wave saturation). The arguments were based on the relation for a single harmonic (e.g., Fritts et al., 1988, Eq. 6) ear convective instability threshold demands a unit ratio, however observations suggested a ratio of 0.7 (Fritts et al., 1988, Eq. 2), and the theoretical consideration of the nonlinear diffusion mechanism yielded 1/ √ 2 ≈ 0.707 (Medvedev & Klaassen, 2000, Sect. 7). Regardless of the precise number, (7) establishes proportionality between the amplitude of relative temperature/density perturbations and squared mean Brunt-Väisälä frequency under the saturation condition. Near the exobase, where the majority of NGIMS/MAVEN observations were taken, the vertical gradient d T /dz is small and can be neglected in (4), thus giving the inverse proportionality of relative perturbation amplitudes and T .

|T | T = |u | |c -ū| N 2 mg , (7)
ACS/TGO occultation data cover altitudes below the exobase, where d T /dz can no longer be neglected. Therefore, we plotted in Figure 8a the amplitudes of relative temperature perturbations for all orbits as functions of N 2 . It is seen that red and blue dots corresponding to morning and evening measurements show no clear dependence on N 2 at all altitudes. To explore this further, we over-plotted the linear regression of the form |T |/ T = αN 2 +β and put the values of α and β in the legend. The coefficients α are far less than those expected from (7), i.e., several tens or hundreds, depending on the characteristic vertical wavenumber m. The distinction between morning and evening amplitudes is also insignificant, except above 100 km, where morning values are slightly larger.

Figure 8b presents the dependencies of amplitudes of relative temperature disturbances as functions of the mean temperature. They are nearly uniform. Although regression coefficients show a weak negative trends at all altitudes, their magnitudes are much smaller than to those observed previously (of the order of 0.5 to 1) near the exobase (Yigit et al., 2015;England et al., 2017;[START_REF] Terada | Global distribution and parameter dependences of gravity wave activity in the Martian upper thermosphere derived from MAVEN/NGIMS observations[END_REF][START_REF] Vals | Study of gravity waves distribution and propagation in the thermosphere of Mars based on MGS, ODY, MRO and MAVEN density measurements[END_REF]. A similar lack of correlation between GW amplitudes and atmospheric temperature was found from TGO aerobraking measurements at altitudes between 100 and 130 km [START_REF] Jesch | Density Fluctuations in the Lower Thermosphere of Mars Retrieved From the ExoMars Trace Gas Orbiter (TGO) aerobraking[END_REF], Figure 12). The atmospheric drag data were collected between L s = 332 • of MY33

and L s = 132 • of MY34. The ACS observations after the aerobraking cover the dusty second half of MY34. Thus, the absence of correlation between GW amplitudes and the background temperature in the lower thermosphere appear to be independent of the season and dust conditions. In the upper thermosphere, [START_REF] Leelavathi | Interannual Variability of Atmospheric Gravity Waves in the Martian thermosphere: Effects of the 2018 Planet-encircling Dust Event[END_REF], Figure 10d) This means that convective instability may not be the main mechanism responsible for damping GWs in the thermosphere, at least during dust storms.

Summary and Conclusions

We have presented the results of gravity wave (GW) retrievals obtained from the Atmospheric Chemistry Suite instrument on board the ExoMars Trace Gas Orbiter (ACS/TGO), which observed solar occultation spectra. GW disturbances are derived from the vertical temperature profiles retrieved from one of the three instrument channels -the midinfrared ACS/MIR. The uniqueness of the data is that they continuously cover a broad range of altitudes from the Martian troposphere to the thermosphere (20-160 km) and have a relatively high (0.5 to 2.5 km) vertical resolution.

Several techniques of separating GW components from the background temperature have been studied. The sliding-window least square polynomial fitting method have demonstrated to be the most robust and effective. The procedure was applied to 144 measurements collected over the second half of MY34 to derive vertical profiles of GW disturbances as well as further wave characteristics: amplitude, wave potential energy, absolute vertical flux of horizontal momentum and absolute momentum forcing produced by breaking/dissipating GWs ("GW drag"). The main results are listed below.

1. Amplitudes of GW-induced temperature fluctuations, generally, grow with height, while breaking/saturation processes often limit the wave amplitude growth at higher altitudes. Based on a half-year average, wave amplitudes are around 8-14 K near the mesopause, and often exceed these values in individual profiles. in the mesopause region has been demonstrated by MGCMs (e.g., [START_REF] Yigit | Influence of gravity waves on the climatology of high-altitude Martian carbon dioxide ice clouds[END_REF].

3. The spatial (altitude-latitude) distribution of the wave drag also agrees well with modeling results (e.g., [START_REF] Medvedev | The mars climate database (version 5.3)[END_REF]. This is the first direct observational validation of model predictions.

4. We did not find positive correlation between amplitudes of relative temperature perturbations and the Brunt-Väisälä frequency at all heights. This correlation is a more general formulation of the anti-correlation found near the exobase (Yigit et al., 2015;England et al., 2017;[START_REF] Terada | Global distribution and parameter dependences of gravity wave activity in the Martian upper thermosphere derived from MAVEN/NGIMS observations[END_REF][START_REF] Vals | Study of gravity waves distribution and propagation in the thermosphere of Mars based on MGS, ODY, MRO and MAVEN density measurements[END_REF] that accounts for vertically varying mean temperature.

The presented GW activity retrievals extending from the middle troposphere to the thermosphere, as derived from the ExoMars data, highlight the role of atmospheric gravity waves as a whole atmosphere phenomenon on Mars. Mars' thin and windy atmosphere favors strong gravity wave generation, thus an accurate characterization of gravity waves is absolutely essential for a better understanding of the Martian climate (Yigit & Medvedev, 2019).

ity waves on the Martian atmosphere: General circulation modeling. Journal of Geophysical Research, 116 (E10004). Retrieved from https://doi.org/10

.1029/2011JE003848 doi: 10.1029/2011JE003848

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 2 ESSOAr | https://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed.

  ://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed.

Figure 1 .

 1 Figure 1. Spectroscopy of CO2 and H2O absorption in the diffraction order #223 of ACS-MIR (panel A) and an example of retrieved atmospheric temperature and density vertical profiles (panel B). a) Transmission spectra measured at tangent altitudes of 150, 90 and 29 km (red dots) on a background of the best-fitted models (black solid lines); b) Vertical profiles of temperature (left) and atmospheric number density (right) derived from the MCD (black dashed line), from ACS-MIR (red dots), and from ACS-NIR (Fedorova et al., 2020) (green dots). Error bars for the temperature values express 1-σ uncertainties of the retrievals.

  ://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed.

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 5 ESSOAr | https://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed. manuscript submitted to JGR: Planets

  formed using Fourier decomposition within sliding 60-km intervals (±30 km around each point), and zero-order Fourier coefficients were used to calculate the background temperature. The examples are shown in Figure 2 for two characteristic profiles T(z). They visibly differ: the profile in Figure 2a (orbit 2892n1) contains large-scale disturbances, while the one in Figure 2c (orbit 3251n1) comprises mostly smaller-scale fluctuations.

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 6 ESSOAr | https://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed. manuscript submitted to JGR: Planets through the given dataset. The linear function is then subtracted from the profile to obtain the corrected temperature.

Figure 2 .

 2 Figure 2. Separation of the observed temperature into the mean and wave components for two characteristic profiles: dominated by large vertical-scale (orbit 2892n1, upper row) and smallscale disturbances (orbit 3251n1, lower row). Left column is for the mean temperature T (z), the right one is for the relative perturbations T (z)/ T (z) (in percent). The legend describes the applied methods. Red dashed lines correspond to the Fourier decomposition, green and yellow lines are for the sliding polynomial fit with 2-km and 11-km shift steps, correspondingly, and the blue lines are for the 7-th order polynomial fit. The observed temperature profiles are given with the solid black lines. Shaded area denotes the uncertainty of the measurements.

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 7 ESSOAr | https://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed.

Figure 3 .

 3 Figure 3. Wave activity |T | (left column) and potential energy (per unit mass, right column) for the same as in Figure 2 representative profiles. Dashed blue lines indicate quantities calculated for the entire spectrum, dashed red lines are for accounting two longest harmonics only. Shaded areas denote observational errors.

Figure 4 .Figure 5 .

 45 Figure 4. Absolute momentum flux (per unit mass) and the momentum forcing for two representative profiles (orbits 2892n1 and 3251n1, upper and lower rows, correspondingly). The legend describes the profiles calculated using the full spectrum and only two major harmonics along with sliding interval steps 2 and 7 km.

Figure 6 .

 6 Figure 6. Latitude-solar longitude (Ls) distribution of the ACS MIR occultation profiles used in this study. Morning and evening measurements are shown in red and blue, correspondingly.

  Figure 7. Latitude-altitude cross-sections of the retrieved GW a) amplitudes (in K), b) potential energy (per unit mass), c) vertical fluxes of absolute horizontal momentum (per unit mass) and d) associated momentum forcing (GW drag). The size of the employed latitudinal bins is 10 • . Contour lines present the zonal wind (in m s -1 ) simulated with the MAOAM MGCM for MY34 (https://mars.mipt.ru/data.php) and averaged over the same as in Figure 7 period of observations.

Figure

  Figure 7c shows that GW momentum fluxes reach local maxima near the mesopause (100-125 km) giving evidence of very intensive wave breakdown/dissipation in this region. The peaks of the associated momentum deposition approximately coincide (Figure 7d). They too wrap around the edges of the jets in the middle atmosphere. It is note-

  ESSOAr | https://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed. manuscript submitted to JGR: Planets 4.3 Amplitude Dependence on Mean Temperature and Brunt-Väisälä

  where |u | is the amplitude of fluctuations of horizontal velocity in the wave, c is its horizontal phase velocity and ū is the background wind. When |u | approaches |c-ū|, increasing dissipation limits |u | thus that the ratio |u |/|c-ū| becomes constant. The lin-

  found a positive correlation during the same second half of MY34, instead of a clear negative correlation over the first ("non-dusty") half of the year. Our results in the adjacent region (around 140 km) show no visible change, neither strong negative trend previously found in the MAVEN/NGIMS observations, nor indication of a positive trend.

Figure 8 .

 8 Figure 8. Amplitudes of relative temperature disturbances as functions of the squared Brunt-Väisälä frequency (a) and mean temperatue (b) at different heights. Red and blue dots are for the morning and evening measurements, correspondingly. Linear regressions of the form a) |T |/ T = αN 2 + β and b) |T |/ T = α T + β are shown with thin solid lines, and the values of the respective coefficients are given in the legends.

  ://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed.manuscript submitted to JGR: Planets 2. The mesopause (100-120 km) is the region of the strongest GW breaking/dissipation, which is evidenced by a local maximum of momentum fluxes and their vertical divergence, i.e., GW drag. Similarly, a large GW drag of hundreds of m s -1 sol -1

ESSOAr | https://doi.org/10.1002/essoar.10506561.2 | CC_BY_NC_4.0 | First posted online: Wed, 23 Jun 2021 01:51:34 | This content has not been peer reviewed. manuscript submitted to JGR: Planets

Acknowledgments

ExoMars is the space mission of ESA and Roscosmos. The ACS experiment is led by IKI Space Research Institute in Moscow. Science operations of ACS are funded by Roscosmos and ESA. The analyses of temperature profiles and wave structures at IKI are funded by the grant #20-42-09035 of the Russian Science Foundation. The ACS data are available from ESA's Planetary Science Archive at https://archives.esac.esa.int/psa/ #!Table\%20View/ACS=instrument. The data for latitude-altitude cross-sections of GW characteristics such as amplitudes, potential energy, fluxes, accelerations and zonal wind are available at the Mendeley database (Starichenko, 2021).