If we were to see the
world with polarization-sensitive eyes,
the sky would not be blue.
Grass would look gray.
There would be all sorts of strange things that would be happening.
What we reveal about
the environment with polarization
is really kind of another dimension of information.
The PACE mission holds the keys to unlock that dimension
with two toaster-sized instruments
called polarimeters,
and polarimeters like these measure the polarization of sunlight.
Generally, sunlight has a combination of different directions.
Polarization is some preference for an oscillation direction.
The ability to detect the specific direction
sunlight reflects back to PACE’s instruments
will give us more information
about clouds and tiny atmospheric particles called aerosols.
The aerosols are really important to human health,
so that's why we need to really quantify what is out there,
like what type of aerosols there are and where they come from.
Various interactions with light in the environment,
scattering events off of particles or surfaces can impose some preference
in the light that they reflect in terms of the polarization nature.
The two multi-angle
polarimeters were built by NASA's partners
both here and abroad.
The Hyper-Angular Rainbow Polarimeter #2,
or HARP2,
will measure atmospheric particles
in one of its spectral channels
in up to 60 viewing angles.
Why so many angles?
This is like a camera, like any other kind of camera.
But instead of taking a picture at
one particular geometry of what
we would understand as light,
it's looking at a scene from different angles.
We will move the different angles
to the one single location,
and in that way
we will collect the information at all the different angles.
And those different angles contain information about
what's present in the environment.
For instance, all these angles from HARP2 can analyze
the elusive cloud bow.
Cloud bows are slightly distinct from a rainbow.
Rainbow is light scattering off of rain droplets.
Cloud bows is light scattering off of cloud droplets, which
are a little bit smaller.
By being able to
observe cloud bows with polarization,
if we very accurately measure the geometry in which this happens,
the exact position of that cloud bow with respect to the Sun, in our observation,
it tells us a lot about the size distribution of the cloud droplets.
If we understand the size distribution of cloud droplets,
we can understand things about the formation of clouds and how long
they will persist if they're going to turn into precipitation or not.
Polarization can also reveal the shape of sunglint,
the pattern of sunlight reflecting directly off the ocean's surface.
Sunglint patterns can tell us how rough or smooth the ocean's surface is,
which can determine wind speed at the surface.
Clouds also have an impact on climate.
But the interaction between the two,
there's many pathways in which aerosols
can interact with clouds.
Cloud droplets can form around aerosol particles more easily
and other things that are going on in the local situation.
That complexity of the interaction between the two is one of the largest sources
of uncertainty in understanding our global climate,
and that's why we're making these measurements.
The data from PACE will allow researchers to tease out the species of aerosols,
which will help fine tune climate models so they make better predictions.
PACE’s other polarimeter, SPEXone, will tackle aerosol retrievals
and give us precise measurements of the angle, degree
and intensity of polarization.
But processing the sheer volume of data has been its own mission.
Each pixel of data the polarimeters measure covers about five kilometers square.
In that space are hundreds—even thousands— of observations at different angles,
wavelengths and state of polarization.
In the course of one full day of orbits
those pixels pile up.
If you put them together,
there will be more than ten million pixels.
That's a huge challenge on both storage and the computational power.
To meet that challenge,
the PACE team has turned to a kind of machine learning
called a neural network emulator.
Even before PACE gathers any data,
the emulator has been trained with
millions of simulations of the possible
atmospheric conditions in that one pixel.
With this emulator, what would take an hour for one
pixel is now a matter of milliseconds,
allowing PACE to process a seemingly
endless stream of data
for the mission
and atmospheric researchers all over.
They will require a lot of measurement,
especially if we can do that from a global scale with satellites
so we know where they're coming from so we can trace their source.
We probably can help to reduce its impact on human health.