Lisa: The hardest part of EL Nino forecasting is probably the uncertainty that's due to
all the other factors that are going on at the same time.
(interviewees saying ENSO/EL Nino/La Nina montaged together)
Andrew: Basically, ENSO is that cycle between El Nino and La Nina
Michelle: ENSO stands for the El Nino Southern Oscillation and it is what we call a coupled
climate mode,
Miriam: For ENSO, that coupling is between the slow-moving ocean and faster-moving atmosphere.
Michelle: One of the reasons that it is important for ENSO to couple is that's why it lasts
so long there's this feedback between the ocean and the atmosphere to make it what it
is.
Miriam: Because it lasts so long, ENSO has far reaching effects across the world.
Elizabeth: El Nino is a global phenomena.
However, its impacts are at a local scale.
Andrew: Lots of impacts upon Australia during El Nino and La Nina.
So It really is a time that offers a lot of threats to both public safety and also our
farming communities as well.
Elizabeth: It has several impacts on food security.
You lose crops, you cannot transport the products and the access roads are damaged.
Miriam: So before we go too far, let's talk a little about how ENSO actually works.
Normally, or under 'Normal Conditions', the western tropical pacific is warmer than
in the eastern Pacific, which creates a gradient of high pressure in the east and low pressure
in the west.
This whole cycle?
It's called the Walker Circulation, describing how these equatorial winds, flow from the
high pressure down to the low pressure.
Ken: So the sea surface temperature along the equatorial pacific and the temperature
below the surface that is where the memory or the inertia of the whole system lies.
Miriam: And those sub-surface temperatures, can be shifted by things called Kelvin waves.
Elizabeth: The frequency and intensity of the Kelvin waves.
These waves are responsible for the transportation of the warm mass.
Miriam: A Kelvin wave travels from west to east along the equator below the surface of
the water, pushing down the separation between cool deep water and warmer surface water,
bringing warmer surface temperatures into the east.
Michelle: On occasion it is weather or this, you know, sub-seasonal phenomenon that cause
the winds to essentially kick-off, you know, an oceanic Kelvin wave which then can result
in an El Nino.
Lisa: So, for example if you have an El Nino event and you got warm anomalies in the eastern
Pacific and that weakened Walker Circulation, that's allowing heat content to be lost
effectively subsurface cold anomalies in the western pacific.
Miriam: And to reverse it?
Lisa: if there's enough energy left in that sub surface signal after that current event
is gone it can come to the surface and be the trigger for the next positive feedback—and
say into a La Nina event.
Miriam: In a La Nina event, the temperature of the Eastern Pacific decreases compared
to normal, strengthening the Walker Circulation.
So, we know what's actually happening, but how did we figure it all out in the first
place?
Lisa: The real game changer was the very simple model that Mark Cane and Steve Zebiak developed
in the 1980s.
Steve: The work was not particularly well accepted initially,
Mark: There was some tough months in there when we're, you know, our forecast was going
up and the world was not.
Miriam: And this was definitely a breakthrough in forecasting.
We had a working model, but it was really simple and eventually a model that simple
could be wrong.
Since then, a ton of work has gone into the different types of models and forecasting.
Michelle: The development right now with respect to ENSO is on the models, particularly on
improving the dynamical models.
Miriam: Okay, so there are two main types of models climate scientist use to predict
ENSO. statistical models –- that use all the historical information we've got about
ENSO to predict what'll happen in the future and dynamical models – that are based on
what we know about the physics of the earth.
Michelle: These are global climate circulation models that are run on big supercomputers
and they ingest tons of data from satellites and buoys and various other locations to try
and essentially initialize the model and then run it forward using the physical equations
that are our understanding of the atmosphere.
Miriam: Until recently, though, those dynamical models weren't as good as the statistical
models.
In a sense models based on statistics were just easier.
Lisa: Well the advantage of those [statistical models] is that they're a lot faster to
run that.
The characteristic shape of ENSO events will be captured.
The disadvantage is that it's very hard for them to distinguish one type of event from
another type of event.
To get that inter-event variability.
Andrew: The dynamical models, even some statistical models now are better than they've ever
been and really, I think, we have to trust them a lot more these days
Miriam: Though the models are improving - there are still a lot of challenges with making
an accurate prediction.
And that starts with getting good data.
Steve: To do a prediction you have to say something about what is the initial state
of the system that you're then trying to forecast the subsequent evolution of.
Mark: That depends on what the background state is, by which we just mean the climatological
state that varies over the course of the year from spring to summer to fall to winter.
If you don't get that right, then you're not going to get the predictions exactly right.
Miriam: A good model needs to know the conditions of the atmosphere, like how surface winds
are moving and how much rain there is in the equatorial pacific.
And it needs to have good information on the temperature across the ocean.
But sometimes, even that isn't enough.
Michelle: There can be some debate over how predictable is ENSO really.
Lisa: Certainly one of the limitations to predictability is the sensitivity to initial
conditions—it's also referred to as chaos—and with respect to something like an El Nino
forecast or a seasonal forecast when you're looking out that far, chaos can just refer
to the weather.
Miriam: And because of that, it is hard to tell how much more forecasting skill can improve.
Tony: For the last 10 years there's been very little improvement in the prediction
models.
It's possible that we can get a little bit better, but we believe there's an inherent
predictability limit.
And we may be near that limit.
Miriam: This gets especially muddied when we start to ask what is going to happen to
ENSO as the climate changes.
Mark: It may be that global warming is changing the background state in such a way as to change
the character of ENSO some, where it's going to peak.
Michelle: I think we are reliant on the models to some extent to understand whether climate
change will impact ENSO, but when you're in the model world, you better also have some
very good physical mechanisms to explain why El Nino to La Nina will become more frequent.
Tony: it's very debatable whether it will start having a systematic effect on the behavior
of ENSO.
Some models say yes.
Some models say not much.
Michelle: And one of the concerns I have is that climate change could impact ENSO but
it would take us, you know, a 100 years, 200 years to actually in the observations see
that.
Lisa: What we can say though is that some of the regional climate impacts may be altered
because of climate change.
So, in particular places that tend to get warmer, places that tend to have drought that
could be exacerbated by a warmer climate.
Miriam: And that's a legitimate worry, because ENSO has real, sometimes dangerous, effects
all over the world.
Mark: You can get all this rearranging heating in an El Nino event for the atmosphere and
that affects everything all over the globe Mark: We have a jargon word, teleconnection,
which only means that things are connected over a large region.
Miriam: And for ENSO those connections lead to a cascade of global impacts.
(overlapping voices describing impacts across the earth)
Ken: The difference in the impacts can be very very strong depending on the patterns
and the timing of the, of the events.
Miriam: At the heart of the story of ENSO prediction is finding ways to help society
prepare.
Michelle: We try to uncover, and sort of tease out, what is weather and what is climate.
Tony: You learn that ENSO affects the climate.
Therefore I must be interested in ENSO in order to be interested in seeing what governs
the climate Miriam: Because what governs the climate,
governs fundamental aspects of our everyday lives.
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