- Welcome, everybody, to Wednesday Nite @ the Lab .
I'm Tom Zinnen.
I work here at the UW Madison Biotechnology Center.
I also work for UW Extension Cooperative Extension,
and on behalf of those folks and our other co-organizers,
Wisconsin Public Television, the Wisconsin Alumni Association,
and the UW Madison Science Alliance.
Thanks, again, for coming to Wednesday Nite @ the Lab.
We do this every Wednesday night, 50 times a year.
Tonight it's my pleasure to introduce to you Tim Schmit.
He's here on campus.
He works for the National Oceanic and Atmospheric Administration.
He's associated with the Cooperative Institute for
Meteorological Satellite Studies here in the tall building with
all the wonderful dishes on it.
My favorite joke is there's more dishes on that building
than in most restaurants.
[laughter]
And it's also one of the highest flow-through places of
meteorological data any place in the country,
possibly in the world, and the reason for that is what you see
up on what Tim has there.
UW Madison is one of the birth places of satellite meteorology.
So tonight's talk on the GOES-16 satellite is yet another
milestone in that long and proud tradition here of innovation,
meteorology, and meteorological satellites.
Tim was born in St. Louis Park, Minnesota,
went to high school in Hopkins, Minnesota,
went for two years at St. Johns University in Minnesota,
then came down here to UW Madison,
finished up his bachelor's degree in meteorology,
got his master's degree in meteorology,
30 years ago started working for SIMS,
20 years ago started working for NOAA.
He makes and builds and helps launch and drive satellites
that let us.
They are our eyes in the skies.
It's one of the great contributions of this university
to the well being of humanity around the world.
Please join me in welcoming Tim Schmit back
to Wednesday Nite @ the Lab .
[applause]
- Thanks, Tom. [applause]
So, thank you.
Yes, we're going to talk about satellites,
geostationary satellites.
We'll explain what they are,
basically past, present, and future.
And, yes, that is me under the mask there.
They don't actually let me build them, though.
That's the subtle distinction there.
So, of course, thanks to a lot of people.
You know, I get to tell you about this wonderful new
satellite that we just launched.
It's in its current check-out phase right now.
But it's literally a cast of, you know,
ten thousands for everybody to have their piece in it from the
hardware, software, building, transportation, check-out, etc.
So, we're going to start at the end with some conclusions,
a little bit of history
about especially satellites meteorology.
Then this new satellite, which is part of the GOES-R series.
We give them letters when they're on the ground,
and then when they get to geostationary,
they earn their numbers.
So, first of all, upper right there,
you can see that's where my office is on the second floor
there, or at least that's in 1967 when they were building.
They didn't quite get up there.
They were halfway done there.
So, anyway, the bottom line is these satellites,
geostationary weather satellites, critical continuity.
You know, save lives and property
for monitoring the environment.
We call them weather satellites because
that's originally what they were designed for,
but they have a lot more applications than that.
As you'll see, we've got instruments that look towards
the sun, monitor the space environment, you know,
aviation and environment, health, oceanography, etc.
And, as was mentioned, geostationary imagery,
it all started in Wisconsin with Professor Vern Suomi and
continues on to this day.
So, a little bit about history.
So, first of all, myself.
This is actually growing up.
It's a picture of my dad.
He worked to build these crystals.
He worked for Honeywell and as a research scientist.
And part of these crystals you could then measure the infrared
or the heat of an object.
So growing up I thought every kid's dad talked about detectors
and phase growth and carrier concentration.
I thought, I don't know, but maybe that's not the case.
Anyway, but of course with infrared you can see in the dark
and some of these same type crystals, mercury, [inaudible]
, are on the satellites that we'll show images from.
As mentioned, I try to keep it pretty simple for introductions.
Pretty much my entire professional career
is in the one building.
So, in 1985 I got my undergraduate degree
in what was then called meteorology,
now atmospheric and oceanographic sciences.
'87 my masters.
And then, as was mentioned, worked for Cooperative Institute
for Meteorological Satellite Studies as an academic staff for
UW and then as work for NOAA.
So there are a number of us
that work along with the state researchers.
So, there's a little bit of Venn diagram there of who's in at
least part of the building.
So we've got half a dozen NOAA researchers along with the
meteorology or Atmospheric and Oceanographic Sciences.
And then a large group in Space, Science and Engineering Center.
So, again, that's where the academic staff researchers,
etc, that we work with.
So, known as the father of weather satellites,
Vern Suomi's sitting there looking at some early GOES.
Probably maybe even pre-GOES, ATS-1 maybe, in 1966.. You know,
this was before the building on Dayton Street was built.
So his offices were over in Science Hall there.
And that's why, if you walk by today,
there's a plaque that says, amongst other things, that,
you know, the satellites that take the first images of the
Earth, you know, from space, you know, thought about,
designed in that building.
So geostationary, 1966, in December,
that's when ATS-1 was built.
So it was mid-'60s, mid-'64.
NASA was going to put up this applications technology
satellite at this special geostationary orbit.
Vern Suomi said, "Wait, you got to put an imager on there so we
can look at the clouds."
That was 1964.
By the end of 1966, there's the image from ATS-1,
the Spin-Scan Cloud Camera.
And as Vern proclaimed, now the weather moves,
not the satellite.
Again, it all started in Wisconsin.
So Vern Suomi and some other big names there.
So, again, a geostationary satellite is 36,
000 kilometers above the equator,
so it rotates at the same rate as the Earth.
So, ATS-1 had one sensor, one visible sensor,
or reflected sunlight, that it looks at.
So here it is.
And, again, this was utterly revolutionary when it came out.
Today I know you're thinking, I get a lot better than that
on my phone, come on. [laughter]
But still, you can see, first of all,
you can see the large expanse, in this case,
of the Pacific and North America in the corner there.
And, of course, you could also that this was a visible sensor
so you could see the white cloud during the day,
but as the sun goes and illuminates the other side of
the Earth, the images turn dark.
And, again, started in Wisconsin.
And, again, it wasn't that long.
So this was 1966, ATS-1.
You can see here's a hurricane.
May be hard to see there.
So, they didn't even know what to call these things, right?
A weather eye or a multipurpose moonlight,
which I'm glad they didn't call it because that's really hard to
say, if you say it quickly Continuous imaging from the
geostationary perspective, 1966.
Fast forward just a little bit.
Now 1967.
Now were onto ATS-3.
Vern Suomi and crew says, well, if we could put one visible
sensor on and get these black and white images,
let's put three visible sensors on in different parts of the
electromagnetic spectrum to see part of the blue, the green,
and the red spectrum, we can combine them together.
And here's a color image of the Earth.
So, again, just a little over one year later.
So, again, what do you do?
You make a movie.
So now the distinction is a multicolor Spin-Scan Camera.
So, again, these are on the equator This was at 47 west.
Now, first of all, I'll show you this first image.
This is not an actual image from the satellite.
That's coming up.
This is just showing you where it was.
This is actually a movie of a globe.
[laughter] Okay?
So, there's not really lines across the equator.
[laughter]
And, of course, it would have been clouds
if it was a real image, right?
So that just shows you where we're looking.
November 1967.
So here it is.
You know, now you can look at these beautiful color,
full-disc images.
So you see half of the globe.
Of course, when the sun sets the terminator line there goes there
and it goes dark because, again, it's just in the visible.
Of course, you can see a lot of things happening.
Here, we call it now days
"a low pressure system in the northeast" there.
Kind of get a couple glimpses of it as this color camera,
you know, is taking images.
The beauty of a geostationary image like this is you can look
anywhere in this full disk.
So you can look, for example, in this case,
south of South America.
You can see the spinning clouds there again.
So clouds are white.
And, again, it started in Wisconsin.
That's the theme.
So, I'll use it a number of times, GOES,
geostationary operational environmental satellite.
Geostationary tells you the orbit.
Operational says it's not a science experiment.
It's got to work 24 by 7, lives and property needs to be on.
Environmental because it's not just a weather satellite.
As I mentioned, we're monitoring, you know,
volcanic ash, the sea surface temperature,
the land temperature, the sun, the solar environment, etc.
And, of course, S stands for satellite.
The most important part of this picture
is that I used to not have gray hair.
[laughter]
So that's a half-scale model in the Air and Space Museum.
That's our current GOES.
So, geostationary orbit.
Again, this is this special spot where the satellite is rotating
at the same rate as the Earth.
So you might think it's geostationary above that spot on
the equator, but actually the satellite is moving
at something like three kilometers per second.
So that's how stationary geostationary is.
And this actually was first proposed in 1928.
There's a long history.
I just touched on the first ones, ATS.
Then, in 1975, then they realized that the weather
doesn't stop at night and put on an infrared sensor as well.
And then we'll fast forward to this GOES-R series.
There are four in the series.
The first one recently launched.
So, again, here's just a pictorial
of the different series, as we move through.
Again, GOES-1, 2, and 3 had one visible and one infrared sensor.
There's some pictures of the spacecraft.
So, when you build these detectors,
you have filters on it to just let in part of the
electromagnetic spectrum.
So, for example, these early ones, visible band, you know,
reflected light, infrared, the heat of the surface.
So, for example, if you're looking at a full-disk image,
this is actually from a recent satellite, full disk,
you can see the western part is illuminated,
the other is in night,
but if you looked at it in the infrared.
So, again, you know, data taken, calibrated,
put on a computer screen so you can see, for example,
the cloud patterns, etc, even though we don't have
the visible light because we have the infrared.
Another type of infrared is what's called a water vapor.
And so this is, again, a different part of
the electromagnetic spectrum, but this is where the frequency,
the radiation, is absorbed by the water vapor molecules so you
don't see this surface but then you can see jet streaks,
still see clouds, low pressure systems, etc.
So, again, those are a couple images from our current GOES.
So, again, this spectral band doesn't see the surface because
of the water vapor in the middle.
So I mentioned 1975.
So launched GOES-A, which became GOES-1.
So one visible, one infrared.
And then if you zoom in a little bit there on the hurricane
off the eastern seaboard there.
So, again, that was a great improvement
in the deal about GOES.
Again, it was operational.
It wasn't experimental
like the earlier ATS geostationary images.
So our current GOES constellation.
So we have a west satellite, so above the equator and 135 west,
which gives that great view of the Pacific.
And then another operational satellite on the east.
Again, the equator and 75 west.
So that gives you a view of South America,
the Atlantic for hurricanes, and of course North America.
We also have an on-orbit spare right now, GOES-14.
And so that's for a backup in case something would happen to
either the GOES east or GOES west or GOES-13 or GOES-15.
So we had that satellite, GOES-14, up there,
and we had this GOES-R, this new generation coming
where we're going to get one-minute imagery.
So somebody said, well, could we use that backup satellite to get
ready and take some special one-minute scans?
To my surprise, they said sure.
I found out later the person who made the decision
was retiring a month later.
So I don't know if that had anything to do with it.
[laughter]
But the bottom line, this was 2012 that we first got these
special one-minute scan.
So, again, this was to give a glimpse into what this new
generation was going to become.
But we got data then in 2012, 2013, 2014, 2015, and 2016,
and were able to flow the data in an experimental way to the
National Weather Service and other people so they could get
used to how they're going to use this rapid scan.
I like this loop because it shows convection
in over just 30 minutes.
So this might be the time between one image
or between two images with a current generation.
Obviously, a lot can happen.
You've seen the convection, the overshooting tops
or that bubbling.
So, again, there's one example from GOES-14,
and we looked at a lot of different phenomena.
This happens to be Hurricane Sandy.
We've gotten, actually, six days at it went up the coast.
I was in the position that I got to tell the satellite operators
where to look.
So I was always very worried that we were going to mess up
the coordinates and get like one-minute data of the southern
ocean trade winds or something instead of Hurricane Sandy.
But it all worked out.
But anyway, you can see that, you know,
center of the circulation there.
So on the left is the ABI, or advanced baseline imager,
what we have on the GOES-16 series.
And that time cadence, or the one minute,
versus the 15 or 30 minutes that we have on the current GOES on
the right.
So, again, this is just giving people a glimpse.
So a little closer to home in Wisconsin.
So, again, this is GOES-14 on the left.
Visible imagery every one minute.
So you see that bubbling, that convection,
overshooting top and the updrafts, very strong.
The feeder bands that go into this severe weather.
I think it was some hail in these storms.
So, again, we had a good run with this backup satellite
getting ready for the future.
When I started working on ABI it was 1999,
and there were these eight spectral bands proposed.
So eight different frequencies.
Some visible, some IR.
I said, you know, you got this long list of requirements.
You're never going to get there from here.
I said you need at least 12 bands.
So the powers that be said, okay, 12 bands.
12 bands?
You're embarrassing me.
We need 18 bands.
[laughter]
Well, they caught on and said, well, you can have 16 bands.
[laughter]
So that's what's on satellites.
There's also constellation
and other countries also have similar bands.
So here's a list of the bands.
And the bottom line is there a number in the visible
in the near infrared and infrared.
But each of these bands kind of had a champion that said, boy,
we really should put that band on.
And obviously some go back to Vern Suomi.
You know, you're the father of weather satellites,
you definitely get a couple bands.
Or other people, the bottom line here, the people,
those names in red have some associated,
direct association with UW Madison,
either went to school here or were employed at the time
that they suggested some of these bands.
One of these people was Dr. Steve Ackerman.
He wrote a memo.
This was back in the olden days when people actually wrote memos.
And said, you know, hey, NOAA, you should put one of these
spectral bands on your next generation GOES.
Nobody said it was a bad idea.
He wrote the memo in 1989, and we just launched in November
this advanced imager.
It's got one of these bands on it.
So that's helpful for volcanic ash and cirrus, etc.
So, GOES-R, again it's a series of four.
The first one was launched from Cape Canaveral November 19th.
There's a time, a lapsed picture there.
November 29th it earned its letter, or numbers if you will.
So GOES-R became GOES-16.
So if I call GOES-16 GOES-R
that's because I had been doing it for 17 years.
[laughter]
So bear with me.
I can still say, well, I meant the GOES-R series.
That's my out.
And, again, so we're in the middle of this check-out period.
For a new satellite like this, it's actually a year
before it goes operations, checking out the, you know,
on the engineering side, the processing side,
the science side, etc.
And so we've been real busy with
checking that out, including making the initial or first
light images that went out in January.
So there's me in the center, and to prove that I don't get to
build these, so the big solar array there.
And this is me explaining that this is really, really big.
[laughter] Okay?
So they also said do not get within a meter of anything.
So, again, very clear.
So by the red on the upper left there is where the instrument
is that would be pointing towards the Earth.
Luckily it's not my job to put the satellite into the plane.
And, of course, it gets flied to Cape Canaveral.
So you think, okay, great, now it's at Cape Canaveral.
It got there.
What could possibly go wrong with a launch date in October?
What could go wrong?
What could-- Oh, just went to the side, Hurricane Matthew.
There were some predictions, you know, maybe, you know,
getting it even closer to the Cape.
But it's, you know, the strongest winds on the
right-hand side stayed off so the instrument was safe.
So that was a big, big relief.
So that's when we went to the November launch date.
Of course, it gets put on top of the capsule
and put on the rocket.
And the rocket-- So here's a picture that I took.
Here's another one that I took, which are my favorites.
Then there's this one that professionals took.
[laughter] You know?
So you choose. You choose.
I'm showing them both.
So hopefully-- Here's another during, shall we say.
A colleague took this picture just after launch.
And you can see that was our view there.
You can see the plume there.
[inaudible]
I don't know if we have to do anything with the voice?
The sound?
Otherwise we'll just-- [inaudible]
Okay.
So, anyway, first of all, here's the, you know,
so that's time that lapsed.
It's not actually going that fast.
[laughter]
Okay, it took all afternoon.
You don't just wing it that fast.
You know?
So there's a launch pad.
You can see, you know, this is actually, I think,
more real motion there, how fast, how it's going.
So, of course, the satellite's on top of the rocket there.
And, of course, so this was near Thanksgiving.
So usually we get a two-hour window.
Say, well, you can launch it anytime then.
So boats and aircraft have to stay out of that space.
Well, it turns out that they say, well,
we're only going to give you one hour.
Well, no problem.
Well, a light came on, so, well, we can't quite, you know,
do it yet.
There's a boat in the area they have to get out.
There's a plane to get out.
So the whole launch window we're literally at the last minute.
The last part of the last minute in this launch window,
and then they give the countdown, and here it goes.
So we get five, four, three, two, one.
[makes rocket sound]
And this was the first launch I'd ever been at.
It really was spectacular, especially with
this night launch here.
So, again, there's, you know, I knew it was going to be loud.
I didn't understand how bright it was going to be.
So here you've got the different rocket boosters as they go up.
Then you'll see some of the rocket boosters fall off
at the different stages.
So then they also, so here's a view from the satellite.
You can see the edge of the Earth was there as it falls off.
So you see, again, the edge of the Earth as the nose cones
are falling back to space.
So, anyway, so that's how at least you get that rocket up to
space, but, again, also part of the fun weekend was they let me
go on a show called "The Weather Geek's,"
and it's on The Weather Channel.
As a meteorologist, I tell you, it doesn't get much better than that.
[laughter]
The point of the story, I was wearing my Bucky Badger there
with the lightning bolt on it there.
But the people around me had to listen to me on the TV and me
talking about what I could have or should have said
while I was showing them.
So, anyway, GOES-R.
As I said, we've got this imager,
advanced baseline imager.
But there's other things.
There's a brand new instrument called the lightning mappers,
the geostationary lightning mapper.
And then there's solar and space monitors too.
So, again, you can see, lower right,
how big this instrument is.
That's the telescope, the black part,
that looks down at the Earth.
So space weather instruments, so they measure,
you know thing that are happening right at the satellite
or they also look towards the sun in what's called the SUVI,
solar UV imager.
So this is one of the frequencies.
Again, this is real data from GOES-16.
You can't quite tell, but it is actually rotating
a little bit there.
So that's this imager, and they've got six different
frequencies there looking at different temperatures,
if you will, of the parts of the sun for things like coronal mass
ejections and coronal holes and lots of things like that.
But I have to admit I've got an Earth bias, I'll tell you that.
This geostationary lightning mapper looks towards the Earth.
It's an optical scanner, and it tells you the total lightning.
So if you think of all the cloud to ground lightning,
that's maybe only 15% of it.
So another way to say it, we're maybe missing 85% of the
lightning if you're only worried about the cloud to ground.
Why might we care?
So if you look at a time series along the bottom there in blue,
that's of the cloud to ground lightning.
Relatively constant before, in this case, a tornado.
But if you look at the red curve,
you see this quick ramp up, and then the decrease.
And often that can be a precursor to severe weather.
In this case more than 10 minutes before the tornado.
So, again, to increase the lead time for severe weather,
this geostationary lightning mapper will be a great,
great benefit.
What does that look like?
Again, this is real data.
GOES-16, geo LEM and those flashes are basically
when this optical center says, hey, it's brighter,
goes through a filter and says, ah-ha,
there must be lightning there.
So this whole loop of all these lightning flashes
I think is over two seconds.
So it's amazing.
You know, sometimes the lightning bolts are within
clouds or where you'd expect.
There's some other ones like, hmm, that was interesting.
So I think we're going to learn a lot with this geostationary
lightning mapper, especially when you combine it.
So I said GOES-R series.
It's got four satellites.
R became 16 and three upcoming launches, S, T, and U.
What I'm mostly going to talk about is the ABI.
So now I'll start my talk. [laughter]
So it's got more spectral bands.
I talked about this early days when we had two.
You know?
Currently we have five.
GOES-16 we have 16, and it just happened out that way.
And we also have finer spatial resolution
for what you can resolve.
And then more frequent imaging.
So there's another way to say that it's, on average,
five times faster coverage rate, four times spatial resolution.
So, for example, if you're looking at a fire or fog in a
river valley or whatever, you can see it that much finer and
approximately three times more the spectral.
And there's me in front of GOES-S to show you that one's
also been built, and now it's actually on the spacecraft
as well.
So there are couple different scan modes.
So this satellite looks at this full disk every 15 minutes,
plus the United States and that dash box every five minutes,
plus these two mesoscale locations.
Again, that's what we're getting ready for,
practicing for when we had the GOES-14.
And those areas are movable
based on where you might want to look at.
Here's a movie that shows just what I said.
So it's three of the spectral bands showing the full disk.
And that you're getting every 15 minutes.
This continental United States every five minutes.
And now we have these two mesoscale sectors right next
to each other, both doing every one minute imagery.
Obviously, if you put them at the same location,
you could get imagery as often as every 30 seconds.
So that's a huge improvement, you know,
when you're looking at rapidly changing phenomena,
such as convection.
So it's greatly improved temporal resolution
that we have with the ABI.
So and here's just an example of that.
So these full disk images, so on the left is the GOES-16,
and you can really just at the times.
We're getting data every 15 minutes.
That's to be compared we do a full disk today every three
hours.
So that's obviously a big, big improvement,
especially depending on where you are.
We have a number of what are called water vapor bands.
So, again, these are the ones that don't see the surface.
So, again, GOES-16 on the left, current on the right.
Now you put that in time motion, what do you see?
The GOES-16 you see images more frequently.
Five minutes versus this 15 or 30,
but you can also see finer spatial resolution.
On the right there, maybe you can see some artifacts,
some horizontal lines, but the data from the GOES-16
is much cleaner.
So, again, you're seeing some things that you haven't seen
before, like maybe some wave phenomena in the atmosphere that
you couldn't see with the coarse resolution of the current GOES.
I mentioned fires or hot spots.
So, same deal.
GOES-16 on the left.
Here we're actually running it in this 30-second mode.
And now it's color coded, so the hottest pixel's temperature are
color coded yellow and red.
So we're actually seeing the heat of these fires from this
geostationary perspective, about a tenth of the way to the moon
almost.
So current GOES updating every 15 or 30 minutes.
In this case, every 30 seconds for the ABI.
So, again, much improved spatial resolution.
I mentioned we've got these six spectral bands in the visible
near IR.
That's to be compared to one band that we have in the GOES
imager today.
So, obviously a big improvement.
So, again, we can make color movies,
we can look at surface vegetation, cirrus clouds, etc.
And if you think spectrally, this in the blue is the area
where the energy is absorbed by the detector.
So, on the top are the two visible bands.
It's why we call it the blue band and the red band.
And then, on the bottom, you can see the four near IR bands.
Similarly, on the infrared side, so, again,
these work day and night, we have four infrared bands on the
imager today, noted by the stars,
as opposed to the 10 that we have on the ABI.
So, for example, instead of looking at water vapor motion at
one layer, now we can see at three different layers in the
atmosphere.
Of course, that's important if you want to understand steering
currents of hurricanes or dynamics of severe weather.
And, again, we can see things that we now couldn't see before.
For example, you know, things associated
with volcanic eruptions and SO2.
Same deal.
Again, these are where we have these spectral bands,
where they measure, be it things that see the surface or things
that see clouds or higher in the atmosphere.
So, on to some data.
So here's some of these first images, GOES-16.
So the visible band, the blue band if you will.
The red band, now what we call the "veggie" band.
So if you flip back and forth you can see how much brighter
the land is.
So you can use that to determine where there may be burn scars or
fire happened or vegetation health.
Cirrus, upper level clouds.
Snow/ice determination,
important for aviation interests.
We go to the infrared.
There's a band that's very sensitive to temperature.
So, again, the hot spot that you might be able to see,
the land surface temperature, the sea surface temperature.
We, again, have three water vapor bands.
So upper level, middle, and the lower level water vapor, again,
to get three different levels of moisture flow
into the atmosphere.
Here's the band that Dr. Ackerman asked to put on
a geostationary satellite.
Boom, it was done, just like that.
And, again, this important band to look at
the phase of a cloud top, both day and night.
That's important for aircraft icing, etc.
Snow zone is its own sensitive band,
total ozone, and some windows, clean windows that you can see
the surface and a band is more sensitive to CO2
or the height of clouds.
So, if you put it together, this is what a 16 panel looks like
from GOES-16.
Two visible, four near IR, and 10 infrared.
And you compare that to what we have today.
That's fine.
We have five today.
Of course, it's not as good as the 16 that we have
with the ABI.
So, and of course from that you can do a lot more.
I mentioned these additional color channels.
So, today, at GOES-13, we usually show this black and
white image on the right versus a colorized where you can use
the multiple visible bands to look at this GOES-16 image.
This is actually how you're supposed to look at images,
on these big, huge hyper walls, not on these little phones,
because there's lots of pixels on a full disk image.
Even at the highest resolution, but the data
that we get down is, I guess the highest resolution is
22,000 lines by 22,000 elements.
So, again, even shown on this hyper wall,
it's not showing all the information.
Anyway, now we're getting to the title of the talk:
Why you should care about GOES-16 or some select applications.
So, as I mentioned, you know, severe weather, you know,
seeing the rapidly changing convection is key.
Transportation, be it surface transportation, fog,
or aviation, volcanic plumes.
Apparently pilots don't like to fly through ash plumes
because the engines stop.
[laughter]
So, obviously, from the satellite, if you can see these,
you can watch them very rapidly and see where the ash is moving.
So we'll see where you could fly.
You know, flash floods, air quality, energy, agricultural.
And then a lot of this information can then be put into
numerical models and do a better job of showing what the
forecast, the weather is going to be because you've got a
better job of understanding the current conditions.
So severe weather, here is just another case
of this 30-second data from GOES-16.
I should point out that this data is preliminary
and not operational.
But you almost get this idea that you're in a plane
flying over these clouds.
But here we are with a camera, 36,000 kilometers away.
So, again, the convective initiation,
that's something that a satellite's very good at.
You know, how fast is that cloud cooling?
Meaning, is it more likely or not, for example, to go severe.
And often you can get a signal sure of that on satellite
even before you get a big reflection on radar.
So that's just an example of convection.
Another one, a squall line.
Here now we've actually put two bands together.
One is the infrared band, and then there's also the visible
band as well and kind of a transparent.
So you're seeing, in this squall line rapidly moving, two things.
You're seeing the heat or the structure or the temperature
of the cloud top and some waves in the visible data.
Again, with 16 bands, there are a lot more ways to combine the
information together.
So that was visible and infrared together.
So a colleague looking at, you know, again,
this research was done with current GOES but to get ready
for this GOES-R.
So he looked at this rapidly cooling signature that you can
see on the satellite.
Also, did the cloud top glaciate or turn to ice?
And how much the anvil's spreading out, etc.
Combined it with other information as well,
radar and numerical model, and his research showed that the
lead time, medium lead time, was an improvement of 10 minutes.
And that's huge.
That's decades worth of improvement of severe weather.
And, of course, this research was done
before we had the GOES-16.
Of course, as I showed you and now you all know,
GOES-16 has got more spectral bands,
it's got finer resolution, the images come more frequently.
So we fully expect that to improve.
So, and even though it has radar with it,
the satellite has an important component.
So, in this case, showing at this time,
with using the satellite data too,
we showed a probability of 93% for this thing that we
subsequent had severe weather, versus without the satellite
only 40%.
So, again, the satellite's providing key information.
I mentioned transportation.
So here, again, was an algorithm developed for this GOES-R,
which is now GOES-16, but applied to our current GOES.
And, in this case, the time sequence of this low cloud and
fog moving towards, in this case, O'Hare Airport.
So they were able to see that satellite product,
know that they were going to lose their visibility,
and take different actions of having different planes not take
off to come there, other ones earlier.
I don't know exactly what they did, but they estimated
$600,000 of aircraft savings just in this one event,
and that's, again, with current GOES.
Obviously, the GOES-16 is better.
It might be a little bit dark.
Same trick, though.
GOES-16's on the left, current GOES is on the right.
So, here's fog in the Ohio River and some tributaries.
You can see some high cirrus there as well.
But you see, you know, the current generation visible
is brighter.
You can see more detail, again, because of the finer spatial
resolution.
To know whether visibility is going to be decreasing in these
lower lying valleys, we can, again,
see that from the geostationary perspective.
Let's see, another application has snow squall or lake effect
snow in the Chicago region.
Again, this is one of these visible images there.
As you can see, the northwest flow
in Madison in the upper left-hand corner.
So, again, it's not just all severe weather.
It's, you know, every day there's some different
application.
I mentioned volcanoes.
So, again, here's our 16 bands.
It happens to be night, so most of them are dark.
But you can see in one of those temperature-sensitive bands
a very hot spot there, color coded red.
And then the ash plume in some of the other bands.
Now, if we combine some of those bands together and animate it in
time, you can see that pink is the ash cloud from this volcano.
You can see it's going different levels because there's sheer in
the atmosphere.
Again, this is of interest to aviation if you're anywhere
in the area.
So you can see the pink there.
And then if you look at this just four hours later,
you can see how the expansive of the ash is.
So, again, you know, satellites are really king for monitoring
these volcanic ash events.
I won't go through all the details but, again,
I'd like to say the satellite data helps before, during,
and after with aviation.
And so in all phases, you know, before take-off, in flight,
or after.
I showed some of these cases earlier about
these wave structure.
Again, I mentioned we have three water vapor channels.
So you're looking at three different heights
in the atmosphere.
Again, these wave structures, now we can start doing the
research, see, you know, when are those associated
with clear air turbulence.
Again, another application for aviation safety.
So, again, there are a lot of different applications.
Here's another one for fires.
So now we're looking at one-minute data.
Again, we're taking, putting two spectral bands together.
The yellows denote the hot spots from one of the bands.
And then the gray is the smoke and emulating from the fires.
And there's some cirrus in the lower left there.
So, again, you can see there's a lot more information.
Again, then the next step is to not just have these images but
to put it into quantitative, you know,
information that you can look at.
So not just looking at the images.
Here is another case of fires and smoke.
I mentioned these burn scars.
So that's on the left, those dark regions would be areas
where they had fires previously.
So, again, you can use that.
You know, that's important.
Areas where you had fires might be more sensitive
to flash flooding.
So here's another view of the visible band.
So now you can see we're in the upper middle west area.
So cirrus coming over.
You see that nice swirl, a vortex in the Lake Michigan.
And then, of course, it gets to be dark.
Now here's the next day.
You can see the white snow on the ground.
Some of the swirls and the lake effect snow coming off Lake
Superior.
Of course, sunset comes again, doesn't illuminate,
and the following day again.
I think this is the day I showed earlier with some of the snow in
Chicago.
But, again, it's all connected, and you can see it with a
geostationary satellite type perspective.
So, again, we can combine these different spectral bands in
different ways to come in what's called this red-green-blue
composite, and there sure are a lot of ways to do it.
Here's another one of these kind of color images.
You can see the black shadow there.
This was the solar eclipse, the shadow falling on the Earth
earlier this year.
Of course, we're interested in that because we're looking
forward to the great eclipse in August 21st, where it comes,
the path of totality comes over the central part of the United
States, and GOES-16 will stand ready to take images like that.
So, as I said, there's all these images I'm showing you,
but the real benefit is when you do this quantitative work where
you don't just say, oh, I get it, there's clouds somewhere,
but determining where exactly are the clouds,
how high are the clouds, how fast are they moving,
how hot is the land, where's the fire,
and putting that data in numerical models.
So, for example, you know where the fire is,
you can then have where there's smoke going to be air quality
downstream.
So I've always said that there's two groups of users of
geostationary satellite data.
You've got your direct users of data.
So these are people putting it in numerical models, you know,
forecasters, broadcasters, people that know they're looking
at it because they're looking at their phone,
international users, etc.
But then, you have people who
are using products or services from those people.
So if you put those two groups together,
you'd basically have everyone. [laughter]
So I say you either know the data,
use the data and you know it,
or use the data and you don't know it.
So I'm still trying to find somebody that doesn't fall
into one of those two camps.
So, anyway, okay, summary and lengths.
I like to say this is my entire career in one slide.
GOES-1 to GOES-16 now.
So, first of all, the boxes represent if you have a spectral
band or not, and then the size of the box represent how small
of a feature you can represent.
So you can see on GOES-16, band two,
we now have something as fine as a half a kilometer of things
that we can resolve.
You know, it wasn't that long ago GOES-7 had a 14-kilometer
water vapor, then eight kilometers, four kilometers,
two kilometers now.
And, again, now you can start to resolve some of these features
that we couldn't before because we have that finer resolution.
So we do a lot of other things in the building there,
work with some colleagues on education apps.
So these are all on the web, and there are different ones where
you can learn about, for example,
the different spectral bands, what are their uses,
glue them together yourself, make your own favorite
red-green-blue composite image.
We've done some of the computer work,
and then various teachers have developed lesson plans that then
they put on these web pages too.
So it's not us telling the teachers how to do their job.
We're getting ideas from them, and then they can use satellites
to explain the whole, you know, business.
What is a satellite image, for example.
You know, the concept of pixels that make up the image, etc.
So, as I said, the GOES-R series is going to, you know,
do the critical continuity to keep this line going, you know,
that you saw from 1975 GOES-1.
That's number one.
You know, number two, it's greatly improved.
Three times spectral resolution, four times spatial resolution,
and five times the coverage rate.
Again, they're not just weather satellites.
You know, it's volcanic ash, it's aviation, it's fires,
it's smoke.
You know, cryosphere or ice, land, and,
maybe most importantly, it's part of this global
constellation.
A number of countries around the world have geostationary
satellites as well.
So I like to say this is really the Wisconsin Idea, you know,
gone global.
We won't go through all the details here, but, again,
if you look to the number of spectral bands,
look down to the bottom, we're at that GOES-13 and 15.
And now, when we go to the ABI, GOES-R,
that's the big improvement.
Going from, you know, five total to 16.
Spatial resolution.
Again, where we're at today, something like one or four
kilometers.
We got a factor of four, that big improvement in ABI.
Once there was a, when we first got the first light images,
there was a lot of press release on it.
The Capital Weather Gang talked about meteorologists are
drooling when they see this imagery.
Temporal resolution you already know the answer.
Finer spatial, finer temporal resolution as well.
So we had those 15 satellites, one through 15.
Now we can fill in this next one in the family, GOES-16,
with a color as well.
I'd like to thank a lot of people but most especially you.
As you know, you're also a part owner of this satellite.
Kind of like the Green Bay Packers there.
[laughter]
So, you know, I showed you the early images, full disk image,
you know, colorized 1967, we didn't have that capability.
Now it's back.
Just these beautiful images, you know,
on the large scale but also the small scale as well.
There's a number of, you know, websites with more information,
the GOES-R program office and how to get some data,
for example looking at satellite data on your phone.
So I'll leave you with this.
One satellite loop.
So, first of all, it's over the Midwest.
Again, this is this natural true color over time.
And you can see a lot of different features in it.
So you can see Madison there.
The clouds, periods, different levels of clouds.
So these are just a couple sequential days.
You can look at the fog there, you know,
pushing up against the land and then kind of bouncing back.
You can see, on the next day, you know,
the frozen lakes there up in Minnesota and Canada.
Again, some of the cirrus as it moves over.
So I'll just leave that image running,
but I thank you for your time and attention
to learn about NOAA's GOES-16.
[applause]