Reanalysis Of Mars Orbiter Laser Altimeter Atmospheric
Features With Machine Learning Algorithms.
V. Caillé, Latmos, Sorbonne Université, Uvsq Paris-Saclay, Cnrs, Paris, France (Vincent.Caille@Latmos.Ipsl.Fr),
A. Määttänen, Latmos, Sorbonne Université, Uvsq Paris-Saclay, Cnrs, Paris, France, A. Spiga, Lmd/Ipsl, Sorbonne Université, Paris, France - Institut Universitaire De France, France, L. Falletti, Latmos, Sorbonne Université,
Uvsq Paris-Saclay, Cnrs, Paris, France, G. A. Neumann, Nasa Goddard Space Flight Center, Greenbelt, Maryland,
Usa.
Introduction
The Martian Atmosphere Is A Mix Of Diverse Kinds Of
Aerosols Structures And Clouds With Different Compositions Such As Dust, Water Or Co2 Ice. Processes Involved
In Their Formations Are Complex And Their Understanding Have Been Enhanced By Observations From The Last
Decades Mission. Between 1996 And 2006, Mars Global
Surveyor (Mgs) Carried Three Instruments, The Mars
Orbiter Camera (Moc), The Thermal Emission Spectrometer (Tes) And The Mars Orbiter Laser Altimeter
(Mola) That Have All Been Able To Observe Clouds During The Same Period With Different Methods. Gathering
And Comparing Results From These Three Datasets Could
Give An Appreciation Of What Has Happened In The Martian Atmosphere During 1,5 Martian Years. However,
Previous Studies Of Mola Observations Of Clouds [Neumann Et Al., 2003, Ivanov And Muhleman, 2001] Were
Numerically Restrained And We Suggest That Reanalysing
The Dataset With Recent Methods Could Give More Clouds
And Dust Observations. Since Then, Both Moc And Tes