Wind and Turbulence Observations With the Mars Microphone on Perseverance
Stott, Alexander E.; Murdoch, Naomi; Gillier, Martin; Banfield, Don; Bertrand, Tanguy; Chide, Baptiste; De la Torre Juarez, Manuel; Hueso, Ricardo; Lorenz, Ralph; Martinez, German; Munguira, Asier; Mora Sotomayor, Luis; Navarro, Sara; Newman, Claire; Pilleri, Paolo; Pla-Garcia, Jorge; Rodriguez-Manfredi, Jose Antonio; Sanchez-Lavega, Agustin; Smith, Michael; Viudez Moreiras, Daniel; Williams, Nathan; Maurice, Sylvestre; Wiens, Roger C.; Mimoun, David
2023-05
Citation
Stott, Alexander E.; Murdoch, Naomi; Gillier, Martin; Banfield, Don; Bertrand, Tanguy; Chide, Baptiste; De la Torre Juarez, Manuel; Hueso, Ricardo; Lorenz, Ralph; Martinez, German; Munguira, Asier; Mora Sotomayor, Luis; Navarro, Sara; Newman, Claire; Pilleri, Paolo; Pla-Garcia, Jorge ; Rodriguez-Manfredi, Jose Antonio ; Sanchez-Lavega, Agustin ; Smith, Michael; Viudez Moreiras, Daniel; Williams, Nathan; Maurice, Sylvestre; Wiens, Roger C.; Mimoun, David (2023). "Wind and Turbulence Observations With the Mars Microphone on Perseverance." Journal of Geophysical Research: Planets 128(5): n/a-n/a.
Abstract
We utilize SuperCam’s Mars microphone to provide information on wind speed and turbulence at high frequencies on Mars. To do so, we first demonstrate the sensitivity of the microphone signal level to wind speed, yielding a power law dependence. We then show the relationship between the microphone signal level and pressure, air and ground temperatures. A calibration function is constructed using Gaussian process regression (a machine learning technique) taking the microphone signal and air temperature as inputs to produce an estimate of the wind speed. This provides a high rate wind speed estimate on Mars, with a sample every 0.01 s. As a result, we determine the fast fluctuations of the wind at Jezero crater which highlights the nature of wind gusts over the Martian day. To analyze the turbulent behavior of this wind speed estimate, we calculate its normalized standard deviation, known as gustiness. To characterize the behavior of this high frequency turbulent intensity at Jezero crater, correlations are shown between the evaluated gustiness statistic and pressure drop rates/sizes, temperature and energy fluxes. This has implications for future atmospheric models on Mars, taking into account turbulence at the finest scales.Plain Language SummaryThe NASA Perseverance mission sent microphones to the surface of Mars. This microphone has recorded signals due to the wind. We examine how these recorded signals vary with other sensor data from Perseverance, which shows a link between the microphone signal, the dedicated wind speed sensor and air temperature. Based on this finding, we develop a way to predict the wind speed from the microphone data using a machine learning technique. The microphone records data at a very high rate compared with sensors so far sent to Mars. This means that the wind speed predicted from the microphone data can be used to study the chaotic and variable wind behavior on Mars to a level never seen before. We show that this chaotic and variable behavior has links to temperature and the number of whirlwinds observed. This will lead us to better weather models for Mars.Key PointsWind-induced noise is observed by the SuperCam Mars microphone on PerseveranceMicrophone and air temperature data are used to estimate the wind speed at high frequencies, using a machine learning modelThe wind speed estimate is used to examine the relationships between turbulent intensity, pressure drops, temperature, and energy fluxPublisher
Wiley Periodicals, Inc. JGR: Planets
ISSN
2169-9097 2169-9100
Other DOIs
Types
Article
Metadata
Show full item recordCollections
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.