All right,
thanks very much!
It's a real privilege and
pleasure to be able to be here.
I don't have any charts;
I just got some notes for
myself that I am going to use.
Just to start out
I am thinking,
you know, gee, 50 years,
it has gotten to be a while.
And even if you
think about,
you know 15 years or so between
the first and the last launch
and then 15 years
that the last one worked
that meant that
these 30 years
that there's actual
real operations
and data acquisition going on,
which is an enormous time
and sort of what it meant
to have coactive discipline.
It's important I think
that we... that we recognize
that we've got both the
individual spacecraft
and the series aspect,
because this is one
of the things where,
you know, the fact that
there were multiple ones
succeeding themselves
is... is really big
and then really the series
didn't stop with numbers;
the series... or at least
for most of the things;
for a lot of the things the
series continued in the future.
So if I try to think about,
all right, so what did
it really do for us?
So I was... I was
trying to break this up
into a couple of
different categories.
So the first is I'll say,
well, everybody got
the planned results.
Now, there are things that
people set out to do
for specific reasons and
they worked, we got them.
We had a path to the future,
both little bit for research
and for... for operations.
So it becomes almost like
a biblical chronology
that you can think back for
a lot of instrument screens,
you know; LIMS we got CLAES,
which we got hurdles.
SAMS, we got ISAMS,
leading to hurdles;
you know, ERB to ERBS
to CIRRUS to RBI;
TOMS to... well, TOMS and
TOMS and NOMI and UNTS,
and there's a whole
bunch of these things.
There's so many
of the datasets
that we've all come to...
to know and... and love
really got their start
with the Nimbus series.
And when people are looking at
long-term system evolution,
in many cases and creating,
working with
the multi-instrument,
multiplatform datasets,
that that's the way that we have
to, address system evolution,
because we rarely
are in a position
of having any one
dataset long enough
to say, well, we'll just
look at evolution with one;
we've got to put
them together.
Well, for a lot
of those things
Nimbus is where it all
started, you know?
You look at a
lot of those...
the kind of quintessential,
trends diagrams that you'll see,
the left side of
that is Nimbus.
And there are some that
transition to operation
so that was always...
is good as well,
because transitioning things
from research into operations
continues to be a
challenge for the nation.
What are some other
things it did?
Well, you know, I was
calling it unplanned results;
maybe it's not unplanned,
but unanticipated results are
things where the smart folks,
many of them
actually worked here,
you know, looked
inside the data
and found things
in the data that,
you know, maybe not weren't
supposed to be there,
but weren't supposed
to be products,
but people were really
clever and figured out
how to do that.
And I think TOMS,
that you'll probably hear
more about from Paul
was a really good example.
I'll try to say a little
bit more about that.
Then you get some
combined products,
where people would say,
well, if I take this
from the Nimbus sensor
and this from
something else,
I can do something else.
That's the real
definition of synergy.
But, you know, two other
the things that...
that Nimbus really
did for us;
one is that, you know, we talk
about kind of a discipline
of earth system science,
but as a discipline
it's really pretty new.
Before Nimbus I think,
you know, you have
meteorology and oceanography
and a bunch of other things,
but people did
their own thing,
but I think it was really
when Nimbus came along
and you successively work
your way up to Nimbus-7,
which was probably
the... the...
the one that... that really
came furthest along,
in fact that's what
led people to really
look at different parts
of the earth system
at the same time and begin to
do the interdisciplinary work
and look at how the
different components
of the earth system
relate to each other.
And also to begin to sort
of integrate cause and effect
so that you have enough
comprehensiveness of measurement
that you could look at
different parameters
and how they would
vary in time and space
and test them
against models
and see whether the pictures
that one had held together
in the face of data
that essentially were
now comprehensive enough
that you couldn't
get the right answer
for the wrong reason
anymore, you know.
You had to... you know,
if you were getting it right
it had to be pretty much
because it was right.
And those were the
kinds of things
that... that...
that Nimbus let us do.
The other thing is it let
us do a lot of that in 3D.
You know, I think it's...
it's hard for many of us
to... to think back
before that time,
where for a lot of things,
especially like say for
3D atmospheric constituents,
you know, we'd have
some balloon profiles
and some aircraft
trajectories,
but we really didn't
have 3D climatologies,
let alone over a period long
enough that you could look at,
you know, what happens
from one season to the next,
what happens from
one year to the next.
And those are some of
the things that we got.
So I don't want to say
a lot about the details
of many of the things,
because the speakers
who are here after me
are way more knowledgeable about
those particular applications.
So you know, I'll just
maybe say a little bit
about those instruments that,
perhaps won't be represented
by some of the people
who are... who are here.
And, you know,
I mentioned LIMS;
seven months of data,
but going from,
I am thinking, what,
84 North to 64 South weather,
ozone, NO2, nitric acid,
with three-dimensional
distributions.
So there's a whole
bunch of things that...
it had temperature as well,
so things that
that led us do.
And when you combine that
with the SBUV profiles
and, you know, really
we had this three-dimensional
distribution of ozone
with good spatial
resolution working
its way down into the
lower stratosphere,
and then with the
NO2 and nitric acid
being able to look
at partitioning
and be able to
look at chemistry.
I'll say a little bit more
about some of the
things that that meant.
You had SAMS with the
methane and NO2 files
so that one was able to
get a sense of these
radioactively and chemically
active source gases
and the vertical
rates of decay,
which would provide some
information about photochemistry
and the balance between
chemistry and dynamics
in ways that
were very difficult
to have addressed before without
that kind of information.
You had SAMS-II
with the polar stratospheric
cloud measurements,
and say after the ozone
hole was discovered
and people were
trying to figure out
what was causing that,
having the distributions of
polar stratospheric cloud
from SAMS-II became
really important
to providing
information about
the... the climatology
of the particles
with services for the
heterogeneous chemistry.
And a lot of those I guess,
you know... I am not going to
say much about TOMS and SBUV;
I think Paul
will cover that.
Those were kind of
the planned products,
but then you also had the,
you know, unanticipated ones,
like the say TOMS Aerosol
and TOMS UV Reflectivity.
The... you know what I mean,
maybe they were
planned all along
but, you know,
they... they...
people thought of that
or it started out like,
you know, sometimes
one person's noise
is another person's signal
and, you know, you
start out showing,
we've got to get
rid of this stuff,
and then, no wait,
there's actually geophysical
information in there
and people figured it out.
When I asked about
the headquarters
to some of my folks
as well as a few
people in the field,
what are some of the
things that I should say;
one of my guys,
David Considine did a
Web of Science run and said,
okay, give me Nimbus-7
and the top 10 papers
that relate to atmospheric
science and meteorology,
and I think the largest
won by a factor of 2
was I think one
of the first TOMS
absorbing Aerosol
climatology papers.
You know, something
that wasn't...
you know, wasn't
supposed to be there,
but people figured it
out and went and did it,
and there's a whole
bunch of stuff that...
you know, good stuff
that came out of that,
because it was
a unique product.
You had the
Surface UV and say,
you know, taught you about
earth system science and 3D.
Well, that also began to
get us into applications;
there's probably other ways
that one... one could do
but, you know, once you
started getting Surface UV,
people could work out
into Surface UV forecasts
and actually begin
to think about,
you know, how people can
use that information in ways
that weren't anticipated.
So that's... oh, and then
combined products;
the TOMS and SAGE Residuals
that people used to infer
tropospheric ozone,
and... and that became...
people found this bulge out
over the tropical Atlantic
and then began to
investigate that.
So there's a whole
bunch of things
that... that came out
in different ways.
I... you know, I am personally
grateful to the Nimbus series,
you know, for...
for my career.
I arrived at Goddard
in December of 1983
to be the chemist in the 3D
Stratospheric Modeling Group,
whereas I would like to say
I was the right hand side
with all the dynamical terms
on the left hand side,
so I used to say, yeah,
call me P minus L.
But... and obviously,
you know to initialize
and evaluate the
chemistry in a 3D model,
so what would I do?
We've got ozone,
NO2, Nitric Acid,
one of the favorite
from LIMS,
got the N2O and Methane
from the SAMS,
got the ozone from...
ozone from SBUV.
I don't know how I would
have started network
if it weren't for Nimbus-7 and
for me the timing was great
because I think six months
after I came to Goddard
was when this really fat
issue of JGR was published,
they had all the validation
papers for Nimbus-7,
and you know that was one
of the most used journals.
And again, many
of the people here
and the predecessors are the
ones who really made that work.
And then when I
decamped to headquarters
to manage the Atmospheric
Chemistry Modeling
and Analysis Program
and I started getting
proposals from people,
well, I think about what are
some of the earliest proposals
that I remember getting,
and this is 1990 so
this is stuff lying,
but it was one of the
decade after launch.
Well, one was we
processed the LIMS data.
LIMS was seven months of data,
six and-a-half or so,
but yet one of the decade after
the data ended it was like,
how can we reprocess this?
Now there is a whole bunch of
stuff, new spectroscopy things
that people were in,
also the fact
that that the...
and this is something that's
even hard for me to grasp is,
they had to do a
lot of the stuff
with really kind of
ancient computing.
So it was hard
to process stuff.
So one of the things that
LIMS folks said were,
you know, we only process,
only use one-fifth of the data,
we didn't have the computing
cycles to use all the data
so now we can actually
use all the data
so they went and did that,
they reprocessed the LIMS data.
I remember a
proposal to go back
and use to get
Nimbus-4 BUV data,
because I think,
you know, the idea is,
that was close to a
decade before Nimbus-7
and if they can go back and
clean up the Nimbus-4 data
and make it as consistent as
possible within Nimbus-7 data,
then you could
start comparing,
you know, trying
to compare things
from the early 70s
to the late 70s.
I remember a proposal that came
in to look at the SCR data.
I think also from Nimbus-4,
and the idea there was it
was a... it was a infrared...
I never heard of
SCR at that time,
but there is...
it had that...
so I remember, it had
the shapre brand
and somebody said, let's go
look over Antarctica
because if may be we
can pull the Antarctica
ozone on that
from the mid-70s
and get some information
as to whether or not
there was an ozone hole,
you know, before the
Nimbus-7 data started,
that one didn't workout,
but I think it
showed the community
really creatively looking
to see what they could get
out of the historical data,
and I want to say
it didn't workout,
I should be careful.
They didn't get
the ozone data
but they think they
learned more about
the Infrared Radiative Transfer
over Antarctica
than one ever knew before,
and I think that became
exceedingly useful
as one looked ahead.
So that one may not have
worked quite the way...
it wasn't anticipated
but I feel like,
you know, it was
a good investment.
And then there were the
TOMS additional products
like the aerosols and
surface UV product.
And you know
that one I feel,
you know, may be a slight
degree of paternity
because I was small enough
to say yes to the proposal.
Frankly, I am sure they
would have done it anyway,
even if I haven't,
personally, it would
have been bootleg stuff,
but I am sure it made it
much easier for the people
to actually be able to say,
yes, we got that funded.
So as I feel like I am
involved in the drug trade,
because let's say,
I was a Nimbus user
and the Nimbus enabler,
and... but... in fact,
it's still there now,
as I put the word out
to some people and said,
you know, what are some of
the things that I could say,
and one of the
things that I got,
because it's a wonderfully
response from the community
as well as creative,
was a preprint...
it may actually be just a
manuscript copy of a paper
that's either out or
will soon be out in JGR
where people went back and
assimilated LIMS in SBUV
into the GMAO,
into the GS5 model,
and they actually looked
that they are able to
improve the quality
of the assimilation
with the data.
So now when 25 years after
the data were taken for LIMS
people are still
working with it,
and finding that it improves
the quality of the science
that they can do today.
So that's I think a pretty
phenomenal kind of thing
in the testament
to the work of everybody
associated with it.
So I guess I will stop.
I would personally like to
thank those who made it happen.
These are wonderful
legacy datasets
as well as pointing the pathway
to the future in so many ways.
I'd like to thank those
who continue to exploit it,
and the people who worked
with the subsequent datasets
because, you know,
answering these questions
that we have of either
it's just an evolution,
we lie that we get the most
out of all the datasets,
so for those people who
are doing that, thank you
and especially for...
you know, really for all those
who helped in doing this
so that the earth system
science that we know
is an integrated discipline
can exist today.
I don't know how that would
have happened without Nimbus.
So I will stop there.
Thank you!
[Applause]