(Narrator) Our world is complex and dynamic.
We're only just beginning to understand the impact that human activities
have on its stability.
If we are to properly understand the cause and effect relationships
we need mathematics.
And one concern that affects us all
is the weather.
We now take it for granted that television,
radio or an app on our phone
will tell us what the weather is going to be.
And while the decision to wear a coat, take an umbrella
or cancel the barbie is important,
for farmers, emergency services and energy companies
the accurate predictions of the weather,
has far higher stakes.
(Peter McIntosh) The sort of people that depend on these forecasts.
Agriculture of course because they're a climate sensitive industry
but there are others as well, so forestry,
emergency services planning for droughts and for floods as well.
Also the construction industry, if they're planning big projects.
Whether it's a wet or a dry year can change the timing of those projects.
(Narrator) And mathematics is at the core of our ability
to predict those weather events.
(Peter McIntosh) Weather forecasts work
by solving the equations that describe the flow of fluids.
Very simple equations, like this, on a grid over the whole planet.
And the key thing is the point at which you start
and you get that from the observations.
The thing that has really improved is the way we use the observations
to start the weather models.
(Narrator) When, in 1922,
Lewis Fry Richardson developed numerical weather forecasting,
he envisaged lots of people, scribbling down calculations
about Newton's laws of motion as they apply to gases.
(Peter McIntosh) Today's numerical weather forecasts
use the fundamental ideas that Richardson came up with
back in 1922.
Very simple ideas, you take the equations of fluid motion,
and they apply to air as much as for water.
You solve them on a numerical grid that covers the planet.
You start them from some observations and you go into the future.
The equations are very similar,
although we know a little more these days,
the observations to start the forecasts are a lot better
and that's crucial and the computers of course are a lot faster.
He did it by hand.
(Narrator) There's a high reliance on maths
not just on day-to-day weather forecasting,
but for longer term seasonal forecasts.
Some of the models are doing very well
at predicting three or six months into the future
and they can get seven out of ten years right
in terms of saying whether it will be above or below medium rainfall.
(Narrator) Today's sophisticated maths-based weather models
mean the accuracy of a Bureau of Meteorology seven-day forecast
is equal to that of a three day forecast 30 years ago
and our ability to forecast severe events such as floods
has increased dramatically.
However, beyond ten days
the ability to accurately forecast individual weather systems,
using this method, rapidly decreases because of chaos.
It is now time to forecast climate, the average of weather.
This is where seasonal forecasting comes in.
Instead of just looking to the past as an estimate of future climate,
scientists have been using mathematical models
to predict the seasons ahead.
A new tool in the armoury is soon to be released
and is supported by the
Australian Community Climate and Earth-System Simulator
Numerical Weather Prediction system
from a partnership between the Bureau of Meteorology
and CSIRO with the Universities.
The Bureau's POAMA
combines traditional atmospheric readings,
with measurements from ocean, land-surface and sea ice,
plus simple observations,
to more accurately predict the next few seasons.
Sometimes the predictions have huge impacts on human lives.
How infrastructure can be built to cope with extreme rainfall like this
requires an understanding of the maths of extreme events.
(Aloke Phatak) Most people have heard of the normal distribution
or sometimes it's called the bell curve in the popular media,
and that's often used to model average temperatures,
average rainfalls, in fact averages of any kind.
We can't use that however to model extremes.
So we rely on something called the extreme value distribution.
What that allows us to do is, it allows us to use
whatever little data we have on extremes,
heavy rainfall, or extreme temperatures
and it allows us then to make projections
of how extreme we might expect events to be in the next 50 years,
in the next 100 years or the next 200 years,
depending on the application.
(Narrator) Along with the Bureau of Meteorology,
CSIRO statisticians and climate specialists
are working to ensure the best information
about the likely future frequency and severity of extreme rainfall
at particular locations is available for planners
and engineers to guide infrastructure.
(Aloke Phatak) It's important to be able to understand
how heavy we might expect rainfall to be in the future
because we want to be able to design our infrastructure
and protect our infrastructure
against the impact of extreme rainfall events.
(Narrator) While long-term forecasts will never be perfect,
the new breed of seasonal climate forecasts
and extreme events modeling
will give those who rely on
an accurate prediction of weather conditions
the best chance of coping with the uncertain future of our Planet.
(Aloke Phatak) It's hard enough to
model extremes for the current climate
with the positive data that we have now,
but we have some even more difficult challenges in the future.
The most important of these is I think
is to fuse projection of rainfall and temperature extremes
with global climate models,
with our current best models of extremes for the current climate,
in order to make reliable projections
of what's going to happen in the future.
(Peter McIntosh) You always try to overcome the computing limits.
Computers are not fast enough to do the things we would like to do at the moment.
Parameterizing the small scale processes that the
computer models don't explicitly represent
is a very difficult problem.
Using the observations that we have
most efficiently is a very difficult problem.
And all of those things rely on understanding the mathematics
and pushing the mathematics further.
[Music plays]