| Summary: | How the dust cycle works on Mars is a key atmospheric issue, as the dust cycle is
arguably the dominant cycle in the current Martian climate. In addition, how much is
known about the Martian planetary boundary layer is mostly determined from models
with very little in-situ data from contemporaneous studies to validate such boundary
layer characteristic assumptions, and the model studies have not been able to define a
known height for a possible boundary layer on Mars using ground-based investigations
prior to this research. The Mars Exploration Rovers (MERs), however, show promise in
offering a unique chance to take surface-based measurements to offer support for dust
and boundary layer measurements made from remote sensors. There are three main
objectives of this study: to constrain the late-afternoon maximum height of the boundary
layer for both MER sites, to constrain the mean particle size and variance of the size
distribution in the atmosphere, and to use these results to demonstrate that sunset and
twilight imaging is a useful survey of otherwise difficult-to-determine parameters that
are needed in several tools for studying Mars’ atmosphere.
A modeling approach using twilight-based Sun imaging by the MERs (Sol 1959
for Spirit and Sol 695 for Opportunity) is used to constrain boundary layer and dust
particle size parameters. After determining which parameters control which observables,
resulting elevations and azimuths are matched up to specific observations from the
available MER datasets. A Monte Carlo code produces the model that is then compared
to Sol data with plotting of resulting error. Results include PBL height and structure
estimations and plots along with generalized particle size information for each MER site
on the given Sol. Figures show comparisons of this study’s particle size results with that
of previous studies as well as maps of fit qualities for boundary layer parameters
compared to a contemporaneous modeled scale height estimation. Results show promise
for planning future MER-based campaigns and models.
|
|---|
