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The Challenges of Modeling Climate
Change and Variability
Interview with Keith Dixon
July 18, 2007
(The following may contain unintelligible or misunderstood words due
to the recording quality.)
BARRY REICHENBAUGH: This is Barry Reichenbaugh
with the NOAA Research Communications Office. I'm here with Keith Dixon
at the Geophysical Fluid Dynamics Laboratory in Princeton, New Jersey.
Keith, welcome.
KEITH DIXON: Nice to chat with you.
BARRY REICHENBAUGH: Keith, I'm wondering if you could start out by just talking a little
bit about your role here, what it is you do.
KEITH DIXON: Well, at
GFDL, I have been here since the 1980s and my role at different times
is -- they've all been involved with modeling, using computers to model
the Earth's climate system. And, I focus mostly on decadal-to-century
time scale problems. And, a little bit more of a focus on the ocean's
role in the climate system.
BARRY REICHENBAUGH: Okay. For the benefit
of people who may not be real clear on what a model is, could you talk
a little bit about just the models that you do here, how that works?
KEITH DIXON: Well, in order to study a certain set of
climate science questions, we rely on computer models, and there are
these big computer programs, a series of mathematical equations.
And,
we need to use those because, unlike a chemist who maybe can do their
experiments in a laboratory using beakers and test tubes, well, we don't
have a twin planet Earth that we can use in order to perform experiments.
So, we need to create a virtual Earth. And, it's these series of mathematical
equations that encompass what we know about the Earth's climate system
and then we can run them as large programs on state-of-the-art super
computers and see how they represent the current climate and use them
to answer questions about how different things work.
Maybe in its most
basic way of thinking about it, we break down the climate into its four
major parts: the atmosphere, the ocean, sea ice, and land surface. And,
each of those four would essentially have its own model that we then
couple together, we say, so that they kind of interact with each other.
And, for each of those, we're interested in how energy
flows through them. You know, what the winds and ocean currents are,
how they move, how they transport heat and water. You know, looking at
the global water cycle.
And, they are basically based upon our knowledge,
the scientific community's knowledge about how the different parts of
the climate system work, what the different physical processes are, what
the governing equations are that determine how things move and how energy
flows.
So, in that regard, it's really a synthesis of observations
and theory in order to the models and then, through modeling, we try
to learn more about the way things work and compare them with the observations.
So, in each of those different parts, you know, the model
itself, you can think of it as broken up to a bunch of little boxes or
little cubes. We divide up the atmosphere and the ocean. So, in our current
models, there are several hundred thousand boxes that represent the three-dimensional
atmosphere. There are more than a million in the ocean.
And, at each
of those boxes, we use those equations in the computer program to calculate
how key factors evolve, how they change over time. Things like what's
the temperature? What's the humidity in the atmosphere or the salinity
in the ocean? What the ocean currents and winds are. What’s their direction,
their speed. How sunlight is being absorbed and reflected and where
it is. Are there clouds forming? Sea ice. Is it moving? Is it growing
or melting? And, you know, water on land, is it evaporating or how
much is moving to the sea via rivers?
So, with all those equations
and all those grid boxes, we have the model go through and they see
how things are changing, how the different boxes are interacting with
one another. All those computations are made and updated to represent
what has now happened at some time ahead, some minutes or hours later.
Update everything, and then we begin the whole process again. And,
it marches forward in time.
BARRY REICHENBAUGH: I guess my next question
is in terms of just how you, over time, are improving these models.
What goes into that? Could you talk a little bit about that process?
KEITH DIXON: Well, the models of today are much better
than they were when I first started at GFDL in the 1980s and we still
have a ways to go. We can continue to improve them. And, there's different
ways of judging how a climate model has improved depending upon the application
that you want to use it for.
And, as time has gone on, we have seen
that the number of people who are interested in the climate models
and what they are doing, that audience has increased. I guess we can
think of the improvements occurring in different ways, depending upon
the audience.
In one regard, it's the completeness of the models. In
another regard, it might be the model resolution, how small we make
those boxes. And then, maybe the ultimate test is how well those model
simulations over the past -- say, the last century or so -- match up
with what was observed. In all three of those categories, we have improved
the models over time.
In terms of completeness, they are more sophisticated
than they used to be. They are more complex. We try to have them more
fully represent a wider range of the physical mechanisms that are in
the model. So, you can think of it as adding more refined parts to
the model to make it more realistic.
On the model resolution, that's
really a thing that's dependent upon the computer power we have available
to us. Just like a high-resolution television will give you a better
picture of a digital camera with a lot of megapixels is better than
a coarser looking picture.
We can get a better idea about what's going
on in the climate if we have more smaller boxes making up the grid
in our models. But, that's computationally expensive. It takes a lot
more to make those computations at more boxes. So, we're really constrained
by the amount of computer we have.
And, finally, we can see what's
been happening over the past ten, 15 years and we then compare or benchmark
our models and we look at how the global, large-scale climate has changed
during the 20th century.
And, we can take our model and we can include
the facts that we think could help force some of what those observed
changes were. Changes in greenhouse gases, changes in atmospheric pollutants
and particles, volcanic aerosols, subtle changes in the solar output.
And, by putting all those factors in, we can see how our model responds
both globally and in the large-scale. Continents versus oceans. The
Arctic versus the tropics.
And, we can see that the models have gotten
much better over time in reproducing decade by decade those large-scale
variations that have been observed and then that'll give us more confidence
in what our models do.
BARRY REICHENBAUGH: You've been here for better
than 20 years. Can you put into some context the role of GFDL in modeling?
KEITH DIXON: GFDL has a very long and rich history in terms
of climate modeling. Back in the 1960s, Syukuro Manabe and Kirk Bryan
are credited with actually creating the first global coupled climate
model, one that incorporated the atmosphere and the ocean and the interactions.
In fact, that's such an accomplishment that its been recognized
both as NOAA as one of its top ten breakthroughs that have taken place
in NOAA during its entire history, and also in the journal Nature in
year 2006, GFDL's original climate model was cited, among other things,
as being one of the major milestones in scientific computing.
I mean,
some of the other things that were cited were things like the invention
of the first handheld scientific calculator, the creation of the Internet,
the development of the first CT scanner. So, it's the rich history,
it's been some very important things that have started here in the
'60s, continued through to today.
And, today, GFDL is still among the
premier institutions in the world that perform this sort of modeling
of the atmospheres, the oceans, the planet systems in general. And,
that's seen in its prominent role in major scientific assessments,
both international, things such as the Intergovernmental Panel on Climate
Change, as well as national assessments as well, things such as the
Climate Change Science Program.
BARRY REICHENBAUGH: Something that is, you know, generally
coming through with all the people I talk to here at GFDL is the enthusiasm
that they have for what they're doing. I'm wondering if we could just
shift the gears here a little bit and just talk about what prompted you
to go into science in the first place?
KEITH DIXON: I was interested
in science in general for about as long as I can remember. For example,
I think one thing that probably had an influence was I grew up in the
1960s. I was in grammar school when Neil Armstrong and Buzz Aldrin were
the first men to step on the moon. And, that just kind of like sparked
an interest in science in general.
And, as I got older, I realized that
while I was interested in, you know, astronomy, the planets, the space
program in general, that I got more of a focus maybe just on planet Earth
and things that I could see.
And, weather was the thing that I could
see and experience every day. And, there was probably, on top of it,
the interest that a lot of people that came through the meteorology route
have, at least those who grew up maybe in the northern part of the United
States, the whole fun of having days off from school due to big snowstorms
kind of sparks an interest in weather that sticks with you with awhile.
And, over time, it evolved into being interested in the research branch
of things.
BARRY REICHENBAUGH: Okay. Then, building on that, and how
did you end up in climate science?
KEITH DIXON: Well, I went and did
my college work, undergraduate and graduate, at Rutgers University in
the Meteorology Department, and I was lucky. I got to sample a few different
parts of meteorology there. I did some part-time radio broadcasting on
a series of commercial stations. I also did a little bit of consulting
work with the professor there.
But, I found that kind of the research
part, asking the questions and having the time to try to dig into them
and being part of a team that would tackle some big issue questions was
something that intrigued me the most. And, when I got the opportunity
to come here to GFDL, I grabbed it.
BARRY REICHENBAUGH: For people who
are considering a science career and wondering about opportunities, I
am wondering if you could just touch on where you see opportunities down
the road?
KEITH DIXON: Well, when I get asked by -- we have summer
interns that come by, and others who are interested in the field of science
in general or climate and weather, more particularly sometimes get the
question about what things are good.
Depending upon which branch they
find they have the most energy for -- and, that's probably the determining
factor. What gets your juices flowing. But, for the science, there's
certainly -- the mathematics part is a main thing. Being good, competent
at that is key. Some folks who have a real energy and get their juices
flowing from that can then find a number of different things to go into.
But, also, there is a certain thing about having an appreciation
for the scientific method if you want to get into the research side,
understanding the idea about how to pose proper questions that are testable,
repeatable, and coming up with reasoned approaches. Going back and constantly
questioning your assumptions in order to advance the science is a good
way to just kind of develop that thought process and in a kind of a rigorous
way.
And then, another thing that is sometimes overlooked and
that we all probably struggle with, one sense or another, is communications
as well. Whether if you're thinking of doing research where your primary
communications is through the written word, publishing scientific journals,
or whether someone might be interested in being a weather forecaster
on the air.
You need to have those communications skills in order to
be able to take what you know and let people know about it so it has
value.
BARRY REICHENBAUGH: Keith, thanks for
joining us.
KEITH DIXON: Thank you. It was a pleasure.