MAVEN/IUVS IN THE SKY WITH DUST AND WATER-ICE CLOUD PARTICLES.
K. Connour, Laboratory for Atmospheric and Space Physics, Boulder CO, USA (kyle.connour@colorado.edu),
M. J. Wolff, Space Science Institute, Boulder CO, USA, N. M. Schneider, J. Deighan, S. K. Jain, Laboratory for
Atmospheric and Space Physics, Boulder CO, USA, F. Lefevre, Laboratoire Atmospheres, Milieux, Observations
Spatiales (LATMOS), CNRS, Sorbonne Universite, UVSQ, Paris, France, E. Millour, F. Forget, Laboratorie de
Meteorologie Dynamique, Paris, France, M. A. Kahre, R. J. Wilson, NASA Ames Research Center, Moffett Field CA,
USA.
Introduction
Aerosols are an important aspect of the Martian climate
but their diurnal variability is largely unknown. Dust
is ubiquitous in the lower Martian atmosphere, absorbing and scattering incident solar radiation which warms
or cools the troposphere depending on local conditions.
Therefore, the thermal state of the atmosphere is quite
sensitive to the abundance and distribution of airborne
dust (Kahre, Murphy, Newman, Wilson, Cantor, Lemmon and Wolff, 2017). Water-ice clouds also play a role
in the climate, though often to a lesser extent than dust.
These clouds absorb in the infrared and consequently
they influence the global temperature structure and water
vapor transport (Clancy, Montmessin, Benson, Daerden,
Colaprete and Wolff, 2017). Unfortunately, many sunsynchronous spacecraft did not take observations that
allowed for local time monitoring of these aerosols, and
thus their diurnally variable properties (spatial extent,
optical depth, etc.) are unknown. Global circulation
models (GCMs) can predict properties of these aerosols,
but they would benefit from derivations of these properties from observations (Barnes, Haberle, Wilson, Lewis,
Murphey and Read, 2017).
The Imaging Ultraviolet Spectrograph (IUVS) instrument aboard the Mars Atmosphere and Volatile Evolution (MAVEN) spacecraft takes recurrent spectral images of the Martian atmosphere and surface. It takes data
between 205 and 306 nm in its mid-ultraviolet channel
and has a spatial resolution of about 7 km by 7 km
at apoapsis (McClintock, Schneider, Holsclaw, Clarke,
Hoskins, Stewart, Montmessin, Yelle and Deighan, 2015).
MAVEN has an elliptical orbit with a period of approximately 4.5 hours, and consequently IUVS is uniquely
suited to monitoring the diurnal evolution of both dust
and water ice in the ultraviolet. In practice, the elliptical
orbit allows it to image a location at several local times
spread across six hours of local time.
In this work, we will perform retrievals on a subset of IUVS data from Mars year (MY) 33 that shows
significant diurnal variability of water-ice clouds and
compare our retrieved values to GCM simulations. We
will investigate this data using radiative transfer techniques, which will provide both dust and water-ice optical depths over swaths of the planet. We ultimately

hope to compare these results to models in order to better constrain them and examine whether the water inventory of these models is consistent with our retrievals. To
do this, we obtained simulations from the LMD GCM
(Forget, Hourdin, Fournier, Hourdin, Talagrand, Collins,
Lewis, Read and Huot, 1999) and NASA Ames GCM
(Haberle, Kahre, Hollingsworth, Montmessin, Wilson,
Urata, Brecht, Wolff, Kling and Schaeffer, 2019; Kahre,
Wilson, Brecht, Haberle, Harman and Urata, 2022).
Having a better handle on Mars’ water inventory will
help improve models, which may be particularly significant when looking at the planet’s atmospheric evolution.

Radiative transfer
To study these aerosols in detail, one typically uses radiative transfer techniques. Performing these retrievals
is challenging as one needs to simultaneously specify
the single scattering albedo and single-scattering phase
function of each aerosol included in the model in a selfconsistent manner, and also specify the surface phase
function, Rayleigh scattering optical depth, etc. Fortunately, we recently determined the single-scattering
albedo of dust in IUVS’ spectral range (and the associated phase function) and can thus set the dust’s radiative properties (Connour et al 2021, under review). We
use the simulations to set the Rayleigh scattering optical depth. We are currently using spherically shaped
water-ice particles, but are investigating simulations of
radiative properties using a more realistic particle shape
(Wolff, Clancy, Kahre, Haberle, Forget, Cantor and Malin, 2019). With these values in hand, we can use radiative transfer techniques on IUVS data to uniquely
determine optical depths of dust and water-ice aerosols
(see figure 1).
We used the DISORT as the core radiative transfer
algorithm (Stamnes, Tsay, Wiscombe and Jayaweera,
1988). We used publicly available pyRT DISORT as
the pre-processing front end to make the required inputs
(Connour and Wolff, 2021).
We show preliminary results of our retrievals in figure 2. Our retrievals yield sensible values of dust optical
depths for this season. Our retrievals of water-ice optical depths show clouds that roughly match the clouds

Figure 1: Spectral variability seen in IUVS data over a range of physical conditions. In both images north is oriented upwards.
The top image (orbit 3459) shows clear conditions, localized dust storms, and thick water-ice clouds whereas the bottom image
(orbit 7414) shows thick dust present during the MY 34 GDS. Both images are enhanced-color projections representing what
IUVS observed at apoapsis. During clear conditions IUVS sees relatively featureless spectra, with an increase in brightnesses
at shorter wavelengths due to some Rayleigh scattering. Relatively small amounts of dust show similar reflectance values at
longer wavelengths but show lower reflectance values at shorter wavelengths as this dust obscures some of the Rayleigh scattering.
Optically thick dust continues this trend at shorter wavelengths but produces enough backscatter to increase reflectances at longer
wavelengths. Water-ice clouds backscatter much more efficiently than dust and thus are significantly brighter. We can leverage
these reflectance values along with the spectral shapes to determine the physical characteristics of aerosols present in IUVS data.

REFERENCES

seen in the false-color image of this location. The optical depths show higher values than values seen at this
season and local time in previous Mars years. We are
investigating the cause of this issue and once resolved
will continue with retrievals on many subsequent orbits.
References
Barnes, J.R., Haberle, R.M., Wilson, R.J., Lewis, S.R.,
Murphey, J.R., Read, P.L., 2017. The Global Circulation. Cambridge UK: Cambridge University Press.
volume 18 of Cambridge Planetary Science. pp. 229–
294. doi:10.1017/9781139060172.
Clancy, R.T., Montmessin, F., Benson, J., Daerden,
F., Colaprete, A., Wolff, M.J., 2017. Mars Clouds.
Cambridge UK: Cambridge University Press. volume 18 of Cambridge Planetary Science. pp. 76–105.
doi:10.1017/9781139060172.
Connour, K., Wolff, M.J., 2021. pyRT DISORT: A preprocessing front-end to help make DISORT simulations easier in Python. Github repository .
Forget, F., Hourdin, F., Fournier, R., Hourdin, C., Talagrand, O., Collins, M., Lewis, S.R., Read, P.L., Huot,
J.P., 1999. Improved general circulation models of the
Martian atmosphere from the surface to above 80 km.
Journal of Geophysical Research 104, 24155–24175.
doi:10.1029/1999JE001025.
Haberle, R.M., Kahre, M., Hollingsworth, J.,
Montmessin, F., Wilson, R., Urata, R., Brecht, A.,

Wolff, M., Kling, A., Schaeffer, J., 2019. Documentation of the nasa/ames legacy mars global climate
model: Simulations of the present seasonal water cycle. Icarus 333, 130–164.
Kahre, M.A., Murphy, J.R., Newman, C.E., Wilson,
R.J., Cantor, B.A., Lemmon, M.T., Wolff, M.J., 2017.
The Mars Dust Cycle. Cambridge UK: Cambridge
University Press. volume 18 of Cambridge Planetary
Science. pp. 295–337. doi:10.1017/9781139060172.
Kahre, M.A., Wilson, R.J., Brecht, A.S., Haberle, R.M.,
Harman, S., Urata, R.A.t., 2022. Update and Status
of the Mars Climate Modeling Center at NASA Ames
Research Center. MAMO.
McClintock, W.E., Schneider, N.M., Holsclaw, G.M.,
Clarke, J.T., Hoskins, A.C., Stewart, I., Montmessin,
F., Yelle, R.V., Deighan, J., 2015. The Imaging
Ultraviolet Spectrograph (IUVS) for the MAVEN
Mission. Space Science Reviews 195, 75–124.
doi:10.1007/s11214-014-0098-7.
Stamnes, K., Tsay, S.C., Wiscombe, W., Jayaweera,
K., 1988. Numerically stable algorithm for discreteordinate-method radiative transfer in multiple scattering and emitting layered media. Applied Optics 27,
2502–2509. doi:10.1364/AO.27.002502.
Wolff, M.J., Clancy, R.T., Kahre, M.A., Haberle, R.M.,
Forget, F., Cantor, B.A., Malin, M.C., 2019. Mapping
water ice clouds on Mars with MRO/MARCI. Icarus
332, 24–49. doi:10.1016/j.icarus.2019.05.041.

REFERENCES

Figure 2: Preliminary results of our updated retrievals. The top left panel shows a false-color image from a subset of an IUVS
image (orbit 3453; MY 33, Ls = 182.0◦ . The top right panel shows spectra of dust and ice in the image. The remaining left hand
panels show our retrievals of dust and water-ice optical depths. The dust values are consistent with seasonally averaged values. The
water-ice optical depths are higher than expected but show qualitative similarities with clouds seen in false-color image. The right
hand panels show retrieved values from the pipeline, which retrieves surface albedo, dust optical depth, and ozone. The addition
of clouds to the retrieval (unsurprisingly) has significant effects on the retrieved dust and albedo values.