Measuring Mars Atmospheric Winds from Orbit

Guzewich, Scott D.; Abshire, James B.; Baker, Mariah; Battalio, J. Michael; Bertrand, Tanguy; Brown, Adrian; Colaprete, A.; Cook, Amanda; Cremons, Daniel R.; Crismani, Matteo; Dave, A.; Day, Mackenzie; Desjean, Marie-Christine; Elrod, M. K.; Fenton, L. K.; Fisher, Jenny A.; Gordley, L. L.; Hayne, P. O.; Heavens, N. G.; Hollingsworth, J. L.; Jha, Devanshu; Jha, Vandana; Kahre, M. A.; Khayat, Alain; Kling, A.; Lewis, S. R.; Marshall, B. T.; Martínez, G.; Montabone, L.; Mischna, M. A.; Newman, C. E.; Pankine, A.; Riris, Haris; Shirley, James H.; Smith, M. D.; Spiga, Aymeric; Sun, Xiaoli; Tamppari, L. K.; Young, Roland; Viúdez‐Moreiras, Daniel; Villaneuva, G. L.; Wolff, Michael; Wilson, R. J.

doi:10.3847/25c2cfeb.6576a506

Cited by 3 publications

(3 citation statements)

References 50 publications

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“…These latitudinal differences may have been caused by the different distributions of dust storms at different latitudes (Chen et al 2017). It is worth noting that the change observed in the electron density before and after the dust storm is also very intense, but no increase or decrease in global consistency [64,128,200,256,400,512] Training batch [8,16,32,64,128,256,512] Activate function search scope [Sigmoid, ReLu, Tanh] Hidden layers number [1,2,3,4,5,6,7] Epochs [100,200,300,400,500,600] Evaluating indicator R 2 is observed (Keating et al 1998;Jain et al 2020;Guzewich et al 2021).…”

Section: Results and Analysismentioning

confidence: 99%

Study of the Effect of Martian Dust Storms on Ionospheric Electron Density Based on Physical-grid Deep Neural Learning Technology

Zhong

Zhou

Deng

et al. 2023

ApJ

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The behavior of the Martian ionosphere during global dust storms has always been a popular topic. Based on many Mars Atmosphere and Volatile Evolution observations, a Martian ionospheric electron density model is constructed herein using a physical-grid deep neural network algorithm. The precision of the model is proved to be high, and the R 2 value of the test set is 0.979. On this basis, the effects of global dust storms on the electron density and peak height of the Martian ionosphere are explored. The results show that the MY34 global dust storm significantly raised the peak height of the Martian electron layer, and its effects mainly ranged from 20°N to 55°N. The periodicity of the global daily average peak electron layer height following this dust storm was more regular than that before the dust storm.

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Section: Results and Analysismentioning

confidence: 99%

Study of the Effect of Martian Dust Storms on Ionospheric Electron Density Based on Physical-grid Deep Neural Learning Technology

Zhong

Zhou

Deng

et al. 2023

ApJ

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“…particularly in our coverage of the diurnal cycle, and some quantities such as winds are not observed at all (Guzewich et al, 2020).…”

mentioning

confidence: 91%

“…This is balanced against the higher spatial resolution possible from such orbits. Large gaps remain, particularly in our coverage of the diurnal cycle, and some quantities such as winds are not observed at all (Guzewich et al., 2020).…”

Section: Introductionmentioning

confidence: 97%

First Assimilation of Atmospheric Temperatures From the Emirates Mars InfraRed Spectrometer

Young

Millour

Forget

et al. 2022

Geophysical Research Letters

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We assimilate atmospheric temperatures from the Emirates Mars Infrared Spectrometer on board the Emirates Mars Mission (EMM) into the Mars Planetary Climate Model at the start of EMM's early science phase (Mars Year 36 Ls = 57.34–92.90°). Mars data assimilation benefits significantly from EMM's unique near‐hemispheric observations, frequent repeated observations of the same location, and full diurnal cycle coverage. Our analysis verifies well against in‐sample temperature observations, and is 1–3 K warmer than Mars Climate Sounder observations. We identify a warm front in concurrent Emirates eXploration Imager observations by correlating an elongated water ice cloud with temperatures and winds in the analysis; the analysis winds are consistent with its observed motion. We also calculate the full horizontal wind diurnal cycle; the zonal flow is weaker and the meridional circulation is stronger than simulating the same time period using the model alone.

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The orbit schemes to monitor Martian dust storms: Benefits to China’s future Mars missions

Rong¹,

Wei²,

He³

et al. 2023

Chin. Sci. Bull.

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Measuring Mars Atmospheric Winds from Orbit

Cited by 3 publications

References 50 publications

Study of the Effect of Martian Dust Storms on Ionospheric Electron Density Based on Physical-grid Deep Neural Learning Technology

Study of the Effect of Martian Dust Storms on Ionospheric Electron Density Based on Physical-grid Deep Neural Learning Technology

First Assimilation of Atmospheric Temperatures From the Emirates Mars InfraRed Spectrometer

The orbit schemes to monitor Martian dust storms: Benefits to China’s future Mars missions

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Measuring Mars Atmospheric Winds from Orbit

Cited by 3 publications

References 50 publications

Study of the Effect of Martian Dust Storms on Ionospheric Electron Density Based on Physical-grid Deep Neural Learning Technology

Study of the Effect of Martian Dust Storms on Ionospheric Electron Density Based on Physical-grid Deep Neural Learning Technology

First Assimilation of Atmospheric Temperatures From the Emirates Mars InfraRed Spectrometer

The orbit schemes to monitor Martian dust storms: Benefits to China&rsquo;s future Mars missions

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The orbit schemes to monitor Martian dust storms: Benefits to China’s future Mars missions