PVL is headed to Houston! Today nine of our group (!!) arrive at the Lunar and Planetary Science Conference (LPSC) in The Woodlands, Texas. For many it will be their first international conference (and for others their first conference, period!). I remember my first LPSC ('04 - if you are counting) well and hope everyone has as much fun and learns as much as I did. To kick things off, here's undergraduate Brittney Cooper. She has provided a MARCI Composite Image of Mars, (Image: NASA JPL) reproduced above, to add some visual interest and context - enjoy, and come visit us in the poster sessions and in our talks!
By Brittney Cooper
This week will
be my first time attending the Lunar and Planetary Science Conference (LPSC) just
outside of Houston, Texas. I’m very excited to have the opportunity to not only
go to what is known as the largest planetary science conference in the world, but
to also be able to present a poster on my research.
For
about a year now, I’ve been working on project analyzing images taken by the
Mars Colour Imager (better known as MARCI). MARCI is a camera fixed to the Mars
Reconnaissance Orbiter (MRO) satellite, which as you may have probably
gathered, orbits Mars. MRO reached Mars in 2006, and began its Primary Science
Phase (PSP) in November of 2006, for about 2 Earth years.
The specific
images that I’m looking at were taken during this phase, when MARCI was locked
in a Sun-synchronous 3am-3pm orbit. This type of orbit is named as such because
it’s a polar orbit in which MARCI sees all of MARS at essentially the same
local solar time (LST), with MRO crossing Mars’ equator at an LST of 3 pm (or
in other words, when the Sun is at a 45 degree angle from what it would be at
noon). MRO also crosses Mars’ equator at 3am on what would be the dark side of
Mars at that time, but of course MARCI does not image that part of the orbit.
A figure I produced with an approximated orbital
path and imaging swath of MARCI over Mars, showing the range of emission angles
MARCI observes in each image.
As a result of
this orbit, MARCI takes 12-13 images a day, working as a push-broom imager. The
term push-broom refers to the rectangular area used on the charge coupled
device (CCD) that MARCI uses to capture images, with 5 different visual wavelength
filters physically adhered to it. As MARCI orbits Mars it takes an image every
few seconds, just as if you were pushing a broom along a glass-floor and
capturing what was below it every-few seconds. MARCI does this for each orbit
going from pole-to-pole, and assembling a long composite image that can then be
separated into 5 individual images for each filter. MARCI also has a separate part of its CCD
cordoned off for imaging in the ultraviolet wavelengths, set up in a similar
way as described for the visual wavelengths, but for only two UV filters.
(a)A small section of a raw MARCI image showing
a few frames each divided into 5 filter framelets, which eventually become
separated and consolidated into 5 images,
(b) is an example of a section of the image in (a)
compiled for the red filter.
Now that a
little bit of background on the MARCI instrument has been provided, I will go
on to discuss what it is that I hope to do with these images of Mars.
You may be aware
that like Earth, Mars also has clouds, and those clouds resemble what we know
to be cirrus clouds on Earth. They are typically optically thin, wispy clouds comprised
of ice-crystals as opposed to water droplets. Work is being done from both the surface
and orbit to try to understand a great deal more Martian ice-water clouds. We
want to be able to characterize their effect on the climate on Mars, as well as
answer smaller questions, such as whether or not rainbows can be observed on
Mars.
In my work specifically, I’m hoping to isolate the
dominant ice-crystal geometries of Martian water-ice clouds through the
analysis of these MARCI images taken during the PSP. I set out to do this by
using the known angular field of view of the MARCI imager to assign angles of
observation for each column of pixels in a MARCI image, and use that
information in combination with the knowledge of the angles at which each pixel
receives radiation from the sun (known by the LST) to determine a phase angle. The
phase angle tells us how the clouds in any image pixel receive and reflect
light, and that knowledge is key to understanding the geometries of its ice
crystals because each shape of crystal scatters incident light in different
ways for various scattering angles. The parameter used to describe the way
these crystals scatter light is known as the phase function. When the phase
function is plotted with respect to scattering angles, it can be observed that different
ice-crystal shapes have their own individual plot shape analogous to a unique fingerprint.
Chepfer et al made a number of laboratory measurements to demonstrate this, and
their resultant plot can be seen in Figure 2 (paper found here: http://onlinelibrary.wiley.com/doi/10.1029/2000JD000240/full).
Our goal is to
run through the thousands of images in the PSP and isolate the phase functions
of Martian clouds to ultimately perform a comparison, determining the dominant
ice-crystal geometries in Martian clouds.
In order to do
this, I set up a computational pipeline which reads in the MARCI images from
the Planetary Data System (PDS), calibrates them, separates each image into
individual filter-consistent images and extracts spectral radiance (or
radiometrically calibrated brightness values) from each of the image pixels. The
pipeline also calculates the observation and emission angles for each image
pixel, calculates reflectance values by dividing the spectral radiance by the
flux (of solar radiation that Mars was receiving at the time the image was
captured), and uses these values in combination with a few other parameters to
determine the scattering phase function for each pixel, in each filter.
In order to
ensure that we isolate only those pixels with clouds, we make the assumption
that the brightest pixels (which end up becoming the upper boundary of the
plots we produce) in each filter will be those corresponding to Martian clouds.
This is a safe assumption as we confine our computation range in the image to
equatorial regions to exclude the bright polar caps, and we know that ice water
clouds scatter equally in all wavelengths, which is why they appear white.
Once we have
these plots of scattering phase functions versus scattering angle, we can begin
the process of comparing the upper bounds in our plots to previous work done,
such as that by Chepfer, et al., in 2002. We can also look at how the
scattering phase function of the clouds varies over Mars’ orbit, along with
comparisons of the phase function in the red filter (which can largely be
attribute to Martian dust) and the blue filter (largely attributed to clouds)
to see where a majority of the atmospheric scattering phase function is coming
from at various points in a Martian year.
An additional data
set that provides values and inputs for calculations in the pipeline that were
originally being approximated has been recently discovered. Next steps on this
project involve re-vamping the pipeline to accommodate these new variable
inputs, and then running the approximately 9000 images within the PSP through
the pipeline to produce the desired plots mentioned above. From there we can
begin the data analysis to see what we can learn!
For more
information on this work, check out my LPSC abstract (http://www.lpi.usra.edu/meetings/lpsc2017/pdf/1360.pdf),
and if you’ll be attending the conference, please feel free to stop by my
poster on Tuesday March 21 at 6pm in the Atmospheres and Plasmas session!
Thank-you to Rachel
Modestino, Christina Smith, and John Moores for their contributions and
guidance on this project.
No comments:
Post a Comment