Water-ice and Dust Retrieved from MAVEN/IUVS Data - INSU - Institut national des sciences de l'Univers Access content directly
Conference Poster Year : 2022

Water-ice and Dust Retrieved from MAVEN/IUVS Data


The Imaging Ultraviolet Spectrograph (IUVS) instrument on the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft takes mid-UV spectral images of the Martian surface and atmosphere. We can retrieve information about aerosols using this nadir imaging. Measuring local time variability of large-scale recurring features is made possible with MAVEN’s nearly-global imaging combined with its ~4.5-hour elliptical orbit, something not possible with sun-synchronous orbits. In this study we performed retrievals of water ice and dust from MAVEN/IUVS data to investigate their local time variability. To do this we employed the DIScrete Ordinates Radiative Transfer (DISORT) code as the core radiative transfer algorithm. We used dust radiative properties derived from the Mars year 34 global dust storm (see Connour et al, 2022) and water-ice radiative properties derived from droxtal-shaped particles. We selected the shortest wavelengths (205--220 nm) and the longest wavelengths (290--305 nm) for these retrievals as they provide the best opportunity to isolate the effect of dust and water ice while avoiding ozone in the spectrum. These retrievals allowed us to build a dust and water-ice climatology, and to understand these aerosols' diurnal evolution, spatial extent, and optical thickness. We also compared these retrievals to global circulation model (GCMs) simulations. These aerosols are important to the radiative balance in the models, yet there have been few datasets that can provide constraints to aerosols produced by the simulations---particularly at local times away from 3pm. We discuss the parameter adjustments needed to more accurately produce the aerosols seen in this dataset and the implications of these changes.
No file

Dates and versions

insu-03914775 , version 1 (28-12-2022)


  • HAL Id : insu-03914775 , version 1


Kyle Connour, Michael J. Wolff, Nicholas Mccord Schneider, Justin Deighan, Franck Lefèvre, et al.. Water-ice and Dust Retrieved from MAVEN/IUVS Data. AGU Fall Meeting 2022, Dec 2022, Chicago, United States. ⟨insu-03914775⟩
23 View
0 Download


Gmail Facebook X LinkedIn More