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1BBC SCIENCE

CLIMATE CHANGEPOST PRODUCTION SCRIPT

BBC SCIENCECLIMATE CHANGE

POST PRODUCTION SCRIPT

PART 1 OF 4

10:00:07 Woman This is the story of climate change.

10:00:12 Man But told in a way you’ve never heard before.

10:00:19 Man Because we’re not climate scientists, we’re three

mathematicians

Man And we’re gonna use the clarity of numbers to cut through

the complexity and controversy that surrounds climate

change.

10:00:37 Woman Understanding what’s happening to the Earth’s climate is

perhaps the biggest scientific endeavour this human race

has ever taken on.

Man From the masses of data we’ve chosen just three numbers

that hold the key to understanding climate change.

Woman 0.85 degrees

10:00:59 Man 95%

10:01:02 Man And one trillion tons.

10:01:06 Woman Just by looking at these crucial numbers we’re gonna try

and get to the heart of the climate change controversy.

10:00:24 Woman They are three numbers that represent what we know about

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the past, present and future of Earth’s climate.

10:01:18 Woman And it’s not just the numbers themselves that are

important, the stories behind them, how they are

calculated, are equally intriguing and revealing.

10:00:28 Comm We’ll see how the methods using everything from the

Moon landings

10:00:30 Woman To early twentieth century cotton mills and motor racing

have fed into the numbers we’ve chosen.

10:00:32 Comm These three numbers tell an extraordinary story about our

climate and take us to the limits of what it is possible for

science to know.

10:02:05 Opening titles CLIMATE CHANGE

BY NUMBERS

10:02:14

10:02:16 Man

VO

MUSIC IN

Every minute of every day all over the planet scientists are

collecting data on the climate. Around ten thousand

weather stations monitor conditions of the Earth’s surface.

Some twelve hundred buoys and four thousand ships

record the temperature of the oceans. And more than a

dozen satellites continuously observe the Earth’s oceans

and atmosphere.

10:02:50 Man

VO

All science starts with collecting data and when it comes to

our climate we’ve got masses of it, but what story about

our planet is all that data telling us?

10:03:03 MUSIC IN

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10:03:11 Woman

VO

Thousands of scientists are trying to answer that question,

their results are summarised in a series of huge reports by

the Intergovernmental Panel on Climate Change. The three

numbers we’ve chosen all come from the IPCC’s reports.

10:03:37 Woman Molly.

10:03:39 Hannah I’m Doctor Hannah Fry and I use numbers to reveal

patterns in data. I’m looking at one number that answers a

critical question, is climate change really happening?

MUSIC OUT

10:03:58 Hannah

PTC

Our first number is

Dr Hannah Fry

University College London

0.85 degrees. Now this number represents what we know

about our climate in the recent past because it’s the number

of degrees Celsius that scientists say our Earth has warmed

since the 1880s.

10:04:20

Hannah But how can they be so precise?

After all our climate is complex and extremely varied.

Temperatures change from season to season, place to place

and even minute by minute.

10:04:42

10:04:55

PTC As if it wasn’t hard enough to try and find an average

temperature of the Earth for now we also need to go back

in time and compare it to the average temperature of the

Earth in the past when we didn’t have the luxury of modern

measurement techniques.

MUSIC IN

10:04:59 VO Working out how the planet’s temperature has changed

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10:05:42

over more than a century is a huge challenge. It’s a bit like

trying to work out the route I’m taking across this park, if

you only had the route Molly is taking to go on. You have

to identify the trend, my path, from all those changing

temperatures, Molly’s path and it all starts with the quality

of the data. Now that’s not such a problem for the recent

past, but what about further back in time?

MUSIC OUT

10:05:45

10:05:53 VO

MUSIC IN

Up until the middle of the nineteenth century the

temperature record as measured by instruments is patchy

and unreliable and there is some controversy about how

you reconstruct temperatures before this time. But the

record improves from the 1880s due to the efforts of one

man.

10:06:27 PTC Now the key man in this story, the man with a plan, is a

guy called Matthew Fontaine Maury. Now Maury was a

lieutenant in the US Navy and from even when he was a

small boy was obsessed with mathematics and data and

analysis. But in 1839 Maury had a coaching accident

where he broke his thigh bone and dislocated his kneecap

and while he was recovering he spent his time studying

captains’ log books. And the data that he found there set

the path for his next fourteen years’ worth of work, so

much so that on the 23rd of August in 1853 he called

together a meeting of twelve countries surrounding the

North Atlantic, all to talk about one thing.

10:07:08

10:07:11 VO

MUSIC IN

He wanted to improve the way that data about the oceans

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was collected.

10:07:19 PTC Captains record all sorts of information in their log books,

things like wind speed and direction, or the speed and

temperature of the sea currents. Now this wasn’t just

interesting to Maury from a scientific perspective, but also

because it was something he could sell to commercial ship

owners.

10:07:38

10:08:10

10:08:11

VO

PTC

He found great commercial success from mapping the

position of major sea currents like the Gulf stream which

enabled ships to use the currents to travel faster. But there

was a problem; different sailors took the same

measurements in different ways. That was particularly true

for one of the measurements climate scientists are

interested in, sea surface temperature.

MUSIC OUT

Now the way to measure sea surface temperature is

actually surprisingly simple, all you do is chuck a bucket

over the side of the ship and get the temperature from it.

But the problem is that the result that you get actually

depends quite a lot on the type of bucket that you use, so

let me just take the temperature of this now and in the

meantime I’m gonna throw this guy over.

10:08:46 VO In the early nineteenth century some sailors used wooden

buckets, others used buckets made of canvas. This meant

that the measurements were not consistent.

10:09:01 PTC The wooden bucket’s coming out as a surprisingly warm,

er 15.1 and if we make a comparison the canvas bucket,

unlike the wooden bucket, isn’t insulated so things like, um

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the air temperature are gonna make a much bigger

difference so the temperature has dropped below 15.1

degrees.

10:09:20 VO It may not sound like a lot but even tiny discrepancies

undermine the accuracy of the data.

10:09:27 PTC Now Maury knew this and so at his conference in 1853 he

came up with a standardised way for everyone across the

world to measure sea surface temperature.

10:09:37

10:09:42 VO

MUSIC IN

He wanted everyone to use wooden buckets and designed

special forms for them to fill in with all their data. Maury

also introduced standardisation to air temperature

measurements on land. That’s why our 0.85 degrees

Celsius figure is measured from 1880, it’s the date from

which the temperature data is generally well standardised.

But despite Maury’s efforts the data was still far from

perfect, not everyone stuck to the rules, for example over

time canvas buckets made a comeback because they were

lighter, so there were still errors, some of which were

pretty obvious.

10:10:24

10:10:29

PTC So here is the sea surface temperature data between

MUSIC OUT

1880 and 1980. And the first thing that you really notice

about this graph is this huge spike that happens where it

looks like the sea surface temperature’s raised by 0.8

degrees Celsius. Or at least it looks that way until you

realise that this spike happened, er in 1941 when during the

Second World War understandably sailors didn’t much

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10:10:55

10:11:19

wanna go up on deck with a torch and a bucket to record

sea surface temperature levels. So instead during that time

they used, er the water that was coming in through the

engine room which is hence why the data is a lot higher.

Now after the Second World War people gradually started

returning to using uninsulated canvas buckets, but

unfortunately we don’t know who was using them or when.

And so in all of this big mess of data how do we get

accurate

MUSIC IN

temperature readings for land and sea from the past?

10:11:27 VO The answer is related to a mathematical technique that was

used to help solve one of history’s greatest challenges.

10:11:41 VO In a mission fraught with difficulties one of the biggest was

how to navigate a quarter of a million miles through Space

to the surface of the Moon.

MUSIC OUT

10:11:53

10:11:57 VO

MUSIC IN

It’s a feat of navigation all the more astonishing when you

consider how difficult finding our way around can be

even down here on the ground.

MUSIC OUT

10:12:07 PTC Working out exactly where you are on the Earth at any

point in time is actually a surprisingly difficult problem,

especially if you want really, really precise information.

10:12:18 VO It’s tricky because tracking opposition, just like measuring

temperatures over time, is prone to error.

10:12:26 PTC Not the easiest thing ever.

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10:12:28 VO Take dead reckoning, timing how long you’ve travelled in

a particular direction from your last known position.

10:12:35 Man About three miles an hour.

10:12:36 PTC Lovely, three miles an hour, hang on one second.

10:12:43 VO It’s easy to drift off course as inaccuracies build up.

10:12:48 PTC Hang on.

10:12:50 VO Even more high tech methods can get it wrong.

10:12:54 PTC Actually the GPS is putting us over there at the moment

which is less than ideal.

10:12:59

10:13:06

VO So when it comes to navigating the problem is which

measurement of your position do you trust?

MUSIC IN

In the 1950s a young Hungarian born mathematician,

Rudolf Kálmán, devised an elegant algorithm to solve this

problem.

10:13:17 PTC Kálmán’s method uses a matrix algebra, er and takes into

account all of the errors to give you the best possible

estimate of your position at any point in time.

10:13:30 VO

Video clips

So how does Kálmán’s method work? In 1969 NASA

gave it its ultimate test in the mission to land men on the

Moon. Navigating in Space poses particular challenges.

The spacecraft was being tracked by four radar stations on

9 BBC SCIENCE


Earth. Onboard instruments were also estimating its

position, but each of these measurements could be wrong.

So how could NASA be sure of Apollo Eleven’s position?

This is where Kálmán’s algorithm came in. Moment by

moment it compared each position measurement with the

others, looking for differences that fell outside the expected

margin. If the algorithm had found significant

disagreement the mission would have been aborted, but it

didn’t and the rest is history.

10:14:59 PTC So this process is now known as Kálmán filtering and has

been used in everything from, er cleaning up

MUSIC OUT

grainy video to looking for trends in economics. And a lot

of the underlying principles are exactly the same as you see

in the processes used for climate science. So, er knowing

when to trust your data and picking out when the errors are

big enough to flag up a deeper underlying issue, but the

process in climate science is

MUSIC IN

instead known as homogenisation.

10:15:33 VO

Video clips

Homogenisation has allowed climate scientists today to

clean up data gathered in the past. Unreliable

measurements can be corrected or discarded.

10:15:47 PTC So what homogenisation process is doing effectively is

taking all of the data from all of the weather stations and

comparing it on a day by day basis. Now in doing that if a

particular data set starts to look a bit unusual it will really

stand out.

10:16:05 VO You can see what happens when scientists homogenise a

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data set by looking at how they corrected the unusual jump

in sea surface temperature in the early 1940s.

MUSIC OUT

10:16:17

10:16:29

PTC So once you’ve applied this homogenisation process here is

what the sea surface temperature data will look like. So we

have the original data here, er in yellow and the cleaned up

version

MUSIC IN

also available in blue.

Now the first thing that you notice is that the big jump that

we had in 1940 has dramatically reduced, er there is still a

bit of a jump because there was an El Niño that year which

meant that the sea surface did actually warm. But the jump

that was down to the difference in measurements, the, the

error in the way that people were measuring, has been

taken away completely from the graph.

10:17:00 VO All the big scientific groups that work with climate data

use homogenisation methods like this to try and clean up

the records of past temperature.

10:17:12

10:17:27

PTC And it’s absolutely vital that you account for some of these

errors in measurement that have occurred in historical data

otherwise you’ve got no hope of finding any kind of

underlying patterns in your data. But inevitably as soon as

you start applying these mathematical

MUSIC OUT

recipes to clean things up other people will start accusing

you of building in biases into your data.

10:17:37 VO Perhaps the best defence against bias is scientists’ own

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10:17:52

scepticism. Many different groups work on climate data

using slightly different homogenisation methods and all are

subjected to searching scrutiny

MUSIC IN

by their peers. But even after homogenising the historical

data climate scientists face a further problem, gaps in the

temperature record. Even today we do not have

temperature measurements for the whole planet.

10:18:14 PTC If you look at where we have temperature data for, if you

split the Earth into a grid it becomes very obvious that

there are some areas where we have much more

information on than others.

10:18:25 VO The black squares show when we had hardly any weather

data at all.

10:18:30 PTC So if you take The Arctic for example it’s very obvious

there are almost no sample points in The Arctic.

10:18:36

10:18:44

VO The gaps in places like Africa and the Poles can affect how

we calculate the average temperature of the whole planet.

MUSIC OUT

10:18:44

10:19:06

PTC Now if you take an average across the whole of the Earth

and don’t take into account the fact that you have a lot less

data for The Arctic you’re gonna end up with a really

biased average and something that doesn’t really represent

the Earth properly. Now there is actually a mathematical

solution to this problem that climate scientists are

beginning to use, but it’s one that wasn’t even devised

MUSIC IN

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by a mathematician.

10:19:11

10:19:36

10:19:54

10:20:30

VO

Video clips

PTC

VO

The attempt to fill in gaps in the temperature data begins in

the gold fields of South Africa in the 1950s where a mining

engineer was grappling with a problem. Danie Krige was

in charge of the leases of the country’s very valuable gold

fields and was inundated by companies desperate to mine

them.

But until each plot of land had been mined he had no way

of knowing how valuable each area would be. What he

needed was a systematic way of working out how much

each lease was worth and so turned to spatial statistics.

To understand the challenge Krige faced I’ve come to gold

mining country, to Dolaucothi in Wales. All Krige had to

go on were a few scattered core samples that had been

taken across the gold fields as miners tried to find more

gold. He had to find a way of working out much gold there

was in each plot of land with just these few measurements,

just like climate scientists have to work out the temperature

in places where they don’t have measurements.

MUSIC OUT

10:20:31 PTC So what I’m gonna do here is show you how Danie Krige’s

method worked using these as my core samples.

10:20:39 VO Imagine each of these poles represents a core sample and

the number of lights indicates the amount of gold found in

it.

10:20:51

10:20:56

PTC So our first core sample is giving us a reading of sixteen

parts per million

MUSIC IN

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all the way up there into the red. And this core sample is

giving us a reading of only six parts per million.

10:21:14 VO Danie Krige’s samples were often around a kilometre

apart. Climate scientists have weather stations that might

be hundreds or even thousands of kilometres apart,

especially in regions like The Arctic. The problem in each

case is the same, how to fill in the gaps in the data.

10:21:35 PTC So one more core sample to do and then I can show you the

map. So our last reading is only giving us two parts per

million, so we’re still on the gold field but we’re at a much

lower grade of gold than we were before. But the real

question that Danie Krige wanted to ask was how can you

tell what happens in between the core samples, how can

you tell how much gold is in the middle?

10:22:05 VO His answer was to use maths to take into account both the

amount of gold in each sample and the distances between

them. So Krige’s method would take the first exciting

strike of gold and look at how far away the neighbouring

samples are, as well as how high the levels of gold found in

them are. This helps estimate how much the gold levels

drop off around each strike. The process is then repeated

over the whole field. It may not sound like it, but the

maths is relatively simple.

10:22:43

10:22:48

PTC Now it’s so powerful that this method has been used all

across the world in everything from looking at gold mines

to forestry and even temperature data and it’s even been

named after the great man himself, now known as Krigeing

MUSIC OUT

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10:23:00

10:23:02 VO

Video clip

MUSIC IN

Krigeing is now being used to throw new light on the

biggest recent climate change controversy, what’s

happened to the temperature of the planet since the turn of

the century? The issue is how you account for gaps in the

record of global temperature.

10:23:20

10:23:42

PTC If you take the UK Met Office’s Hadley Centre for

example and their data on the changing global temperatures

in the recent past they leave blanks in regions where they

don’t have any information. But if you look at the

temperature set you can see that it demonstrates an effect

that’s become known as the Pause which is the temperature

of the Earth doesn’t appear to have risen since the year

2000.

10:23:47 VO This Pause in the Earth’s rising temperature is

controversial. Some climate change sceptics say it shows

that global warming is not real, but most climate scientists

say they would expect pauses every now and again within a

warming trend. But whether there even is a pause depends

on how you account for the gaps in the temperature record.

10:24:13 PTC When this data set was Kriged by an independent scientist

in 2014 so that they could take into account the little data

that you have in The Arctic he found that the graph

changed.

10:24:26 VO Krigeing put more weight on the few temperature points

we have from The Arctic and there the temperatures are

rising fast. The impact of Krigeing on the original

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incomplete data is to turn the Pause into a small

temperature rise.

10:24:43 PTC Now you might think that this doesn’t necessarily represent

reality either, but it does demonstrate an important point,

what you do with your data has an impact on how you

make your conclusions.

10:24:55

10:25:30

10:25:57

VO

Video clips

It’s not to say that Krigeing The Arctic figures has really

shown that there isn’t a Pause, it remains an area of debate,

but techniques like this offer scientists the only way they

have to overcome the inevitable limitations of incomplete

data. It doesn’t matter how much effort scientists go to,

temperature data will never be perfect and the trouble is

mathematical manipulation of the raw data can look like

fiddling the figures. But the techniques that climate

scientists have used are well understood, they’re open to

scrutiny and they all lead in the same direction. Three

major research groups have contributed to the IPCC’s

reconstruction of past temperature. They’ve each used

slightly different methods to clean up the historical data

and account for gaps in the temperature record.

MUSIC OUT

10:25:57 PTC And here are their results. So in the top left hand side you

have the results from The Global Historical Climatology

Network, er top right you have the results from The

Goddard Institute of Space Studies, um and in the bottom

left you have the results from The Met Office’s Hadley

Centre. Now just these three graphs show pretty similar

results, they all seem to be showing a very similar shape,

especially when you take into account the fact that all of

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the groups were using different techniques.

10:26:30

VO

MUSIC IN

From there how did the groups arrive at an average

temperature rise? This bit is surprisingly simple.

10:26:39 PTC Now rather than all of the zigging and zagging the groups

put a line through each of their graphs and from there it’s

very easy to just read off how much the temperature has

risen.

10:26:50 VO These three lines show the trend in the average temperature

since 1880 for each data set.

10:26:59 PTC But the IPCC then took the average of each of these three

lines and come up with the value of 0.85 degrees Celsius,

the most accurate measure that we have for how much the

Earth’s temperature has risen by since 1880.

10:27:16

10:27:44

VO

Video clips

But that doesn’t mean it’s perfect, the exact figure is

always going to be uncertain.

Scientists have done their best to try and compensate for

imperfections in the historical temperature record. They’ve

applied mathematical record to patchy, unreliable and

erroneous data.

MUSIC OUT

10:27:45 PTC Now 0.85 degrees is itself just a symbolic figure. I could

have averaged the data in several different ways and ended

up with a slightly different figure every single time, but

that’s not really the point. Looking at how this number is

produced you can see that it doesn’t matter how you collect

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10:28:12

your data, how you measure your data, or how you treat it,

one point still stands overall, the Earth’s temperature has

been

MUSIC IN

rising in the last hundred and thirty years.

10:28:20

10:28:58

VO

Video clips

Different groups using different techniques, each

scrutinising the others, have all arrived at pretty much the

same conclusion. That’s why it’s now relatively

uncontroversial to say that the Earth’s temperature has

risen by just under a degree since the 1880s. There’s far

less agreement though on the answer to the big question all

this raises, why did the Earth’s temperature rise?

MUSIC OUT

10:29:00

10:29:16

PTC We can only look at a very different number, a number that

answers one of the most difficult and controversial

questions in the whole climate change debate. Just to what

extent is the rise in temperature caused by human activity

and to what extent is it caused by just natural fluctuations?

MUSIC IN

10:29:18 Video clip MUSIC IN

10:29:30 VO

Woman

Norman

I’m Professor Norman Fenton,

Hi there, how are you?

Hi

a mathematician and life long Tottenham Hotspur fan.

From financial services to transport and even football I use

numbers to work out the most likely causes of different

events.

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10:29:47

10:29:52

PTC Prof Norman Fenton

Queen Mary University of London

The climate change number I’m looking at is all about

cause and effect.

MUSIC OUT

The scientists have made a big statement, they say they’re

95% sure of the main cause of the Earth’s recent warming.

10:29:59

10:30:01 VO

Video clips

MUSIC IN

And that cause they say is us. All science involves

identifying not just what is happening, but also why it’s

happening. When it comes to the climate scientists say

they’re 95% sure that over half of the warming in the last

sixty years has been caused by humans. How can they be

so sure? Well by using statistics we can analyse the most

likely cause of something whether that’s success at football

or climate change.

10:30:37

10:30:50

PTC I’ve been coming to Spurs for over fifty years and I have to

say this isn’t one of their finest seasons, but like most fans

I’m pretty confident I know which factors are gonna be

most important for determining whether they’re gonna play

better or worse than expected

MUSIC OUT

in any given season.

10:30:53 VO Unsurprisingly, there’s no shortage of opinions here.

10:30:56 Man Definitely the manager, you know, the manager, they need

to respect the manager, the manager needs to have sort of

like respect to the players as well.

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10:31:02 Man If you’ve got the tactics right and you’ve got the players in

the right places where they should be.

10:31:07 Man Well you need a very good executive board, your players

need to stay very fit, your manager needs to be focused,

have a very good philosophy.

10:31:15

10:31:17

10:31:43

VO

Video clip

MUSIC IN

Beyond opinion there is a way to use maths to work out

which factors are the most crucial. It’s called an attribution

study and it’s what the IPCC did to arrive at their 95%

figure. All attribution studies start with identifying the

factors that might cause an outcome. Let’s take footballing

success.

MUSIC OUT

10:31:44 PTC Here I’ve got lots of statistics on all the Premiership teams

going back many seasons. It’s interesting when you look

at the league tables to see how the performance of a team

will vary from season to season. I wanna understand

which of many possible factors are the most important

causes of this. Is it the length of time the manager’s been

with the club? Is it the injury rate? Is it how much they

spend on players? I’m gonna put all those factors together

with many others and plot my own attribution study.

10:32:12

10:32:21

Video clip

VO

MUSIC IN

To work out why some teams win and some lose we need

the second part of the attribution study. The different

factors we’ve identified that could affect the team’s

performance are put into a mathematical model. It’s the

same process climate scientists use to try to work out what

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10:32:48

is driving climate change. I can now check the accuracy of

my model against teams’ past performance.

MUSIC OUT

10:32:50

10:33:09

PTC So what I’ve got here for example is I’ve taken one of the

teams, Manchester city and I’ve plotted the actual

performance in terms of points that they achieved in each

of the last few seasons. Now we look at what the model

would have predicted and you can see it’s actually a pretty

good prediction of what actually happened.

MUSIC IN

10:33:12 VO And this is true for all the teams in the Premier League.

Now I know I can trust my model I can move on to the

clever bit, isolating the factors that make the most

difference to the team’s success.

10:33:27

10:33:29

PTC I found that there was one factor which had

MUSIC OUT

far greater impact on performance than any other, the wage

bill. If I take out the wage bill factor it’s no longer a good

estimate at all, it’s quite a long way off and in fact we can

repeat that for all of the other teams.

10:33:47 VO Using the same methods as the IPCC I can even put an

actual figure on how big an effect the wage bill has.

10:33:59 PTC I can say there’s a 95% chance that if you increase the

wage bill by 10% there’ll be at least one extra point at

Premiership season.

10:34:09

10:34:10 VO

MUSIC IN

I can be so confident because the answer’s so clear from

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my model. But how can climate scientists be equally sure

of their results? After all what drives changes in the

Earth’s climate is one of the most complex puzzles

scientists have ever tried to unlock. Before trying to work

out the impact humans have, scientists have to account for

natural variations in the Earth’s climate.

10:34:40

10:34:42

10:34:47

PTC The key science involves a number of factors,

MUSIC OUT

all of which play a role in changing the climate. If this was

a court case

MUSIC IN

they’d be our suspects.

10:34:51 VO

Video clips

Many natural factors are known to cause changes to the

climate, they include the sun, the energy it emits varies and

this can change the temperature here on Earth. Volcanic

eruptions, the vast gas clouds they throw up can cause

sharp global cooling as they affect the chemistry of the

upper atmosphere and climate cycles like El Niño that can

cause global temperature fluctuations lasting many years.

But climate scientists say they’re 95% sure that recently all

these natural factors have been overshadowed by one other.

10:35:49

10:35:50

PTC For most climate scientists

MUSIC OUT

there’s one prime suspect in this case, us, and that’s

because of a colourless, odourless gas called carbon

dioxide that we’re pouring into the atmosphere. One of the

first people to try and unravel the role of carbon dioxide on

changing the Earth’s temperature was a depressed Swedish

physicist called Svante Arrhenius. Arrhenius wasn’t

22 BBC SCIENCE


interested in the Earth’s warming however, but cooling.

10:36:16

10:36:19 VO

Video clip

MUSIC IN

In 1894 Arrhenius’ marriage broke up. Searching for

distraction he set his mind to one of the great mysteries of

his time, the origin of the Ice Ages. Scientists had long

wondered how the great mountain landscapes of Europe

had been formed. Once the rugged valleys were thought to

be the relics of a biblical flood, but in Arrhenius’ time it

was realised that the Earth had been beset by periodic Ice

Ages over the last two and a half million years.

10:07:02 PTC On trips through Northern Europe he studied the vast

palatial landscapes that surrounded him and wanted to

know how the Earth could possibly have undergone such

monumental change. What had caused the planet to cool

down so dramatically?

10:37:21

10:38:06

VO Scientific understanding advances by developing theories

and then testing them. It was already widely accepted that

so called greenhouse gases worked like a huge blanket

around the Earth keeping it warm. Arrhenius’ developed a

theory that changes in the concentrations of these gases, in

particular carbon dioxide, might also have caused the

planet to cool. The only way he could test his theory was

to use maths to work out the relationship between changing

levels of carbon dioxide in the air and the Earth’s

temperature.

MUSIC OUT

10:38:07 PTC It was painstaking work; every calculation had to be

written out by hand, Arrhenius himself described it as

23 BBC SCIENCE


tedious, but eventually he had his answer. He predicted

that a halving of carbon dioxide in the atmosphere could

lower the temperature by over four degrees and perhaps

trigger an Ice Age. Almost as an afterthought he also

calculated that a doubling of carbon dioxide could increase

the temperature by the same amount.

10:38:36

10:38:42 VO

MUSIC IN

Eventually it would turn out that changing carbon dioxide

levels weren’t the main cause of the Ice Ages, but using

maths Arrhenius had established the crucial underlying

relationship between carbon dioxide in the atmosphere and

the temperature of the planet.

10:39:00 PTC Much of Arrhenius’ efforts and the related work that

follows can be summarised in one simple equation, this

enables you to calculate the heating effect that comes from

raising carbon dioxide above its base level. It’s one of the

fundamental building blocks of climate science.

10:39:22

10:40:17

VO The equation shows that the heating effect represented by

Delta F rises in proportion to the amount of carbon dioxide

in the atmosphere. Put simply, you can’t raise carbon

dioxide levels without heating the atmosphere. But there

are many factors that influence the climate, each with their

own equations. The rate of energy coming from the sun,

the cooling effect of volcanic eruptions, human pollution

from things such as industry and agriculture, ocean

currents, cloud cover, wind speeds, all of which influence

each other in a web of complex interactions. Unlike my

football study, modelling the climate is unbelievably

complicated, so how do climate scientists create a model

24 BBC SCIENCE


10:40:36

that accurately represents the complex interactions of all

these different factors? The answer comes from the very

earliest days of weather forecasting.

MUSIC OUT

10:40:37

10:41:01

Video clips

VO

MUSIC IN

One of the earliest pioneers of weather forecasting was a

man called Lewis Fry Richardson. At the start of the

twentieth century he set out to revolutionise weather

forecasting using maths.

10:41:21

10:41:26

PTC Our climate is governed by the circulation of the

atmosphere and Richardson recognised just how complex

this

MUSIC OUT

system was, declaring that the atmosphere is like London,

there’s more going on than anyone can properly attend to,

yet despite this complexity he wanted to find a way to

unravel its secrets.

10:41:38

10:41:43 VO

MUSIC IN

Richardson had an idea of how to do this that was

revolutionary. Using the rows of the theatre as his

template he thought of dividing the world into grid squares,

this would break the problem down into a series of discreet

and achievable tasks. He imagined positioning people

within each square would only have to solve the

calculations relevant to the weather in their area. A

director standing at the centre would take in the results of

all the calculations to form a forecast.

10:42:32 PTC Richardson made just one attempt to put his ideas into

practice,

25 BBC SCIENCE


10:42:3

10:42:44

MUSIC OUT

retrospectively trying to calculate the weather over Europe

for a particular day. But his calculations took him six

weeks to complete

MUSIC IN

and they were far from accurate.

10:42:48 VO Despite this failure Richardson was ahead of his time. By

dividing the world into grid squares he had made the

crucial theoretical advance that would not only

revolutionise weather forecasting, but also allow scientists

to model the climate. All that was needed was enough

computing power to put it into action.

10:43:15 PTC Fry Richardson had calculated that he’d need over sixty

thousand people using slide rules in order to predict the

next day’s weather before it arrived. I’m sure he wished

he’d had access to this, the world’s most powerful

meteorological super computer, part of the European

Weather Centre here in Reading. It may be noisy but it can

perform over one thousand trillion calculations every

second.

10:43:44 VO

Video clips

The world’s biggest super computers are now used to

model the climate. Just like Richardson they divide the

world into a grid and solve the complex equations

governing the climate for each square. As computers get

more powerful the squares get smaller and the models get

better at representing reality. No computer is ever

powerful enough to simulate it in as much detail as

scientists would like, but this method has allowed scientists

to build a model for factors that affect the climate, the

26 BBC SCIENCE


crucial second step of an attribution study.

10:44:23

10:44:26

PTC However impressive our super computers are,

MUSIC OUT

however much the climate models exploit the very limits of

our technology, climate modelling remains a simplification

which raises the question, how can scientists be confident

that their simplified models accurately capture reality?

10:44:44

10:45:04

10:45:53

10:46:18

VO

Video clips

When I made a model for football success I was able to

check it against the past results of dozens of teams.

But climate scientists have only one Earth and one set of

past data to check their models against, so they’re always

looking out for new opportunities to test their models.

MUSIC IN

In June 1991 they found a big one. On the Philippine

island of Luzon a volcano called Mount Pinatubo erupted.

It spewed twenty million tons of sulphur dioxide and ash

more than twelve miles up into the atmosphere. It was one

of the most devastating eruptions of the twentieth century.

But climate scientists at NASA realised it also offered a

chance to test their climate model. Could their model

predict the effects of the gases given off on the climate?

After adding the eruption into their model it predicted that

over the next nineteen months there would be an average

global cooling of around half a degree. As the real data

came in month by month it matched the model’s

predictions. It was good evidence that climate modelling

could be reliable.

MUSIC OUT

10:46:20

10:46:23 VO

MUSIC IN

Unfortunately opportunities to test the models against data

27 BBC SCIENCE


10:46:52

Video clip

are few and far between and as a mathematician I find that

frustrating. What’s reassuring is that the underlying

physics on which the models are based is robust, so despite

their limitations the models offer a powerful tool to

identify the main causes of warming. It’s a process of

elimination.

MUSIC OUT

10:46:52

10:47:05

PTC To show you what I mean let’s take the example of the sun.

If the cycles of the sun were a major cause of the rise in

temperature we’ve measured then what we should see

would be all the layers of the Earth’s atmosphere warming

together like this.

MUSIC IN

10:47:07 VO

Video clip

This is called a fingerprint, a characteristic pattern that

would point to the sun’s influence as the cause.

10:47:18 PTC What we actually have from the measurements of the past

sixty years is that only the lower levels of the atmosphere

have warmed while the upper levels have cooled.

10:47:28

10:47:37

VO

Video clip

So what we’re actually seeing in the atmosphere is an

entirely different fingerprint.

MUSIC OUT

10:47:39 PTC What the models show is that’s a pattern which only fits

well with the main cause of the warming being human

activity.

10:47:46

10:47:47 VO

MUSIC IN

That’s human activity primarily in the form of burning

28 BBC SCIENCE


10:48:26

10:48:27

Video clips fossil fuels that release carbon dioxide into the atmosphere.

And since the 1970s the human fingerprint has become

more obvious. From the loss of sea ice in The Arctic,

increasing frequency of heat waves to the warming and

acidification of the oceans, the models predict all of these

patterns only as a result of increasing greenhouse gases like

carbon dioxide.

MUSIC OUT

MUSIC IN

The evidence that human activity is the major cause of

recent warming is compelling. But the models can go one

step further and help us put a figure on the level of

certainty behind this statement.

10:48:46 PTC The yellow line on this graph is the real world data. This is

how much warming we’ve measured across the world since

1951, 0.6 degrees.

10:48:58 VO

Video clips

Firstly in red let’s look at how the climate models expected

the global temperatures to change when taking into account

all known factors. The shading shows the amount of

fluctuation around the average that they would expect to

happen. The most obvious features are a general rise, the

result of the increasing carbon dioxide levels with some

sharp dips caused by big volcanic eruptions.

10:49:33 PTC But look what happens if we run our models without any

human influences like greenhouse gases, so now only

natural forces are included in our model data. The line

doesn’t match the real data well at all. This is what the

model suggests our climate would be like if there was no

human impact on it at all.

29 BBC SCIENCE


10:49:56

10:50:17

VO

Video clip

The models say that without any human influence global

temperature would not have risen significantly over the

past sixty years. It’s as clear as taking the wage bill out of

my football prediction. The models also help scientists put

a figure on how certain they are of human impact on the

climate.

MUSIC OUT

10:50:18 PTC From the models they found there was a greater than 99%

probability that more than half of the warming was due to

human activity.

10:50:26

10:50:27

10:51:00

10:51:01

10:51:30

Video clip

VO

MUSIC IN

Given that high level of certainty how did the IPCC arrive

at its slightly lower 95% certainty figure? All of us who

work with mathematical models know that they’re

simplifications, so we have to take into account their

limitations. That’s why the IPCC downgraded its final

conclusion from 99% to greater than 95% sure that humans

have caused more than half the recent warming.

MUSIC OUT

MUSIC IN

All science proceeds by producing theories and then testing

them, but when it comes to our climate it’s impossible to

test the influence of different factors on the planet. That’s

why scientists have turned to maths to help model the

climate. It’s not perfect, but it is the only way to put a

figure on how sure we are the Earth’s warming is down to

human activity.

MUSIC OUT

30 BBC SCIENCE


10:51:32 Video clip

10:51:34 PTC Years of scientific research and statistical analysis have

brought us as far as 95% and that’s close enough for most

people to believe it. That just leaves the question, what’s

gonna happen with our climate in the future?

10:51:48

10:51:54 VO

MUSIC IN

I’m Professor David Spiegelhalter and I use numbers to try

to help organisations like the Health Service predict the

future. I’m looking at one number that aims to give us a

clear guide to how our actions now might affect the

climate.

10:52:15

10:52:30

10:52:32

PTC The number I’m looking at

Prof. David Spiegelhalter

University of Cambridge

is one trillion, this rather unimaginably big number may be

crucial to the future of our planet. It’s the best estimate

that climate scientists have made of the number of tons of

carbon that we could

MUIC OUT

burn before we

MUSIC IN

run the risk of causing what’s been called dangerous

climate change.

10:52:37 VO

Video clips

That’s defined as an average warming across the globe of

more than two degrees Celsius. All fossil fuels contain

carbon, when we burn them it converts this carbon into the

carbon dioxide that warms the atmosphere, so the trillion

tons figure puts a limit on the amount of fossil fuels we can

31 BBC SCIENCE


burn.

10:53:01

10:53:15

PTC In effect this gives the world a budget, it says that if we

want to avoid a two degrees rise then we can’t afford to

spend, or burn, more than a trillion tons of carbon and

that’s a total going right back to the beginning of

industrialisation.

MUSIC OUT

10:53:16

10:53:22

10:53:41

10:53:45

Video clips

VO A trillion tons sounds like a lot, but the trouble is we’ve

already burnt around half a trillion tons and that’s given us

almost a degree of warming and if we carry on the way

we’re going we’ll burn the other half a trillion tons in about

thirty years. The implications are profound.

MUSIC IN

We’ve already identified several trillion tons of fossil fuel

reserves buried inside the Earth, so to keep warming below

two degrees will probably mean leaving most of those

reserves in the ground. Before we take such drastic action

I’d like to know a bit more about the trillion tons figure.

Where does this number come from?

10:54:12

10:54:20

PTC And how much confidence should we have in it?

MUSIC OUT

10:54:20 VO The one trillion ton limit is based on being able to predict

the future. That may make it sound unscientific, but for

centuries people have been working on ways to make

predictions using statistics.

10:54:35 PTC The history of statistics and prediction has been driven by

incentives, in fact the first people who worked on

32 BBC SCIENCE


10:54:52

10:54:58

10:55:04

10:55:10

Video clip

PTC

VO

Video clips

probability and statistics were either advising gamblers or

pricing up pensions. So I think if you really want to know

who’s making good predictions look at people who are

putting their money

MUSIC IN

where their mouth is.

And there’s a lot of money in motor racing.

And a lot of effort to try to predict the future because

winning isn’t just about driving fast, it’s also about making

the right decisions, what to do as the race unfolds, the

weather changes and the unexpected happens. And this is

where prediction and statistics comes in. There are far too

many variables for the decision to be left to the driver, or

sometimes even to the people at the race track, it needs a

dedicated race strategist.

10:55:50

10:56:21

10:56:33

PTC

Video clip

PTC

Video clip

In the 2005 Monaco Grand Prix Kimi Räikkönen was in

the lead after twenty five laps when there was a six car pile

up. The safety car came out and the team had to decide

very quickly should Räikkönen come into the pits or

should they leave him out there until the race restarted and

this would decide whether he won or not. They didn’t

know what to do and then a two word email came in from

the chief strategist who was in England and the email said

stay out.

So Räikkönen stayed out and the people who came into the

pits got all jammed up so Räikkönen went on to win the

race and all because of the power of prediction.

10:56:35 Video clip

VO

So how did Räikkönen’s strategist predict the outcome of

different strategies?

33 BBC SCIENCE


10:56:41 PTC They used to just use gut feelings, just their instincts, but

now with huge amount of data available they can do

something much more sophisticated.

10:56:50

10:56:52

Video clip

VO

MUSIC IN

Throughout the race each car streams performance data

back to the team, from tyre fatigue to fuel consumption.

The team then plugs this data into a mathematical model of

the race.

10:57:09 PTC

Video clip

PTC

Video clip

They can constantly make changing predictions as the race

proceeds,

as the positions change, as the lap times change, they can

predict the

possible outcome if they do a particular action, you know,

for example just come in

for a pit stop. And then they can choose the strategy that

maximises

PTC the chance of the best possible result.

10:67:31 Video clip

VO

As Räikkönen’s victory shows the predictions made by the

models can be extremely powerful and it’s only possible

thanks to a mathematical technique that we now use for all

sorts of future predictions.

10:57:47 PTC This technique that motor racing teams use to decide what

strategy will maximise the chances of winning a race is

exactly the same as the technique I use for medical

predictions and climate scientists use to predict what might

happen to the planet.

34 BBC SCIENCE


10:58:02

10:58:05

Video clip

VO

MUSIC IN

And it’s all due to a stroke of misfortune that befell one

particular mathematician just after the Second World War.

10:58:10 PTC

Video clip

Coffee please. In 1946 brilliant mathematician and

physicist Stanislaw Ulam was struck down by a severe

bout of ill health, he was hospitalised for weeks and only

had the card game Solitaire for entertainment.

10:58:42 VO The aim of the game is to sort a randomly shuffled pack of

cards into four piles according to a set of rules, whether

Ulam could successfully finish the game depended on the

order of the cards he was dealt.

10:58:58

10:59:02

PTC As he played his instinct was to begin to pick apart the

game

MUSIC OUT

and analyse it mathematically. He became obsessed with

trying to predict whether a game would be successful.

10:59:11 VO Ulam hoped he could calculate the probabilities of different

outcomes from the very first deal, but he quickly realised

this approach would get him nowhere.

10:59:23 PTC The problem was there were just too many possible

combinations leading to ever increasingly complex

calculations and equations that became impossible to solve,

no matter how brilliant a mathematician you were.

10:59:36

10:59:40

10:59:42

VO

Video clip

But Ulam didn’t give up.

MUSIC IN

He came up with an entirely different kind of method to

35 BBC SCIENCE


solve the problem, in fact it was one that hardly involved

maths at all, let me demonstrate with an analogy.

10:59:55

11:00:00

11:00:01

11:00:04

PTC Ahead of me, between me and the wall, I can just about

make out a sheet of Perspex.

MUSIC OUT

There’s a hole cut out of the centre in a certain shape,

MUSIC IN

but from here there’s no way I can tell what that shape is,

but I can find out with a little help.

11:00:14 VO Imagine that working out the shape of the hole is

equivalent to Ulam trying to predict outcomes in Solitaire,

there’s no way I could work out the answer with maths, I

need to play the game. In this case the equivalent of a

round of Solitaire is a shot with a paintball gun.

11:00:35

11:01:12

PTC MUSIC IN

After a couple of shots I’ve got a few through against the

wall, but although I know there is a hole in the Perspex

I’ve still no idea what the shape is. It’s like after I’ve just

played a couple of rounds of the game, I’m still none the

wiser about what outcomes to expect. But if I do this …..

Now with enough shots I’m beginning to get a picture of

what the shape might be. Looks like a rough sort of

diamond to me, it’s great fun. This is the same principle as

playing the game thousands of times, with enough sample

runs we can begin to build an idea of what outcomes to

expect.

11:01:34 VO At first sight it sounds like no solution at all, who could sit

around actually playing Solitaire millions of times to find

36 BBC SCIENCE


11:01:50

11:01:53

Video clips

an answer? What turned Ulam’s ingenious idea into a

useful tool was his timing.

MUSIC OUT

The computer had just been invented, that meant you didn’t

have to play the game for real, instead it could be played

hundreds of times inside a computer and the computer

could then say which starting hands were most likely to

lead to a successful game. He called his technique the

Monte Carlo Method after the casino where his uncle made

so many repeated and random attempts to predict the

future. And it turned out to have uses well beyond

predicting the outcome of card games.

11:02:29

11:02:36

PTC The beauty of Monte Carlo is that even in complex systems

it tells us not only what is likely to happen,

MUSIC IN

but how likely it is to happen.

11:02:39 VO

Video clips

In climate science the equivalent of shooting the paintballs

is running climate models hundreds of times, each time a

model is run it comes up with a different prediction about

the future of the Earth’s climate. The results of many

different climate models can then be combined. As the

models are run over and over again we can see where the

results cluster.

11:03:10 PTC This is the Monte Carlo process in action, the pattern of

lines shows us a range of possibilities, but not only that,

where the lines are densest this is what the models are

saying is the most likely thing to happen. Of course it

doesn’t tell us exactly what the future holds, that would be

impossible, the future is inherently unpredictable, but the

37 BBC SCIENCE


Monte Carlo Method gives us an idea not only of what the

outcomes might be, but how likely they are. And this is

where our crucial number comes from.

11:03:43

11:03:58

VO

Video clip

The graph shows the model’s predictions of how much the

climate will warm as a result of us burning one trillion tons

of carbon; the most likely outcome is just below two

degrees Celsius of warming.

MUSIC OUT

11:03:59

11:04:01 VO

MUSIC IN

Now we understand where the one trillion tons figure

comes from we need to consider the second part of the

prediction. Why should we worry about a rise of two

degrees Celsius?

11:04:18

11:04:33

PTC When we think about what a small average rise in global

temperature might mean to us humans perhaps the first

thing to think of is weather because we don’t experience

climate on a day to day basis, we experience weather and

sometimes it can hit us really hard.

MUSIC OUT

11:04:38 VO

Video clips

Just a small average temperature rise can hide very

noticeable changes in weather, especially dangerous

extremes. As the average rises the tropics will experience

more devastating rain storms, whilst areas including the

Mediterranean will have more droughts. Britain will suffer

more flooding, but it’s not simply the fact that these events

might be more frequent that is a concern.

11:05:13 PTC It’s critical that we understand extreme weather events,

how often and how hard they might hit us and this is the

38 BBC SCIENCE


worry with a climate that might warm by as much as two

degrees, that it would disrupt that ability because the

method we use to predict extreme weather uses a particular

type of statistics that’s very sensitive to this type of change,

a method in fact that was developed for something quite

different.

11:05:39

11:05:43

Video clip

VO

MUSIC IN

In the early 1920s the cotton mills of England were a vital

industry, but the looms often sat idle for as much as a third

of the time. The problem was that cotton threads kept

snapping.

11:06:02 PTC Every snap could stop production for hours so they needed

to work out why the threads broke and what they could do

to stop it happening. Fortunately they had the good sense

to call in a statistician.

11:06:15

11:06:18

11:06:34

Video clip

VO

PTC

VO

MUSIC IN

The newly formed British Cotton Industry Research

Association charged with improving all aspects of the

industry dispatched one Leonard Tippit to investigate.

Tippit admitted he was woefully

inexperienced, but in the best traditions of British statistics

he managed to combine careful collection of data with

elegant statistical analysis.

He toured the mills of Lancashire carefully recording

breakage rates and studying the strength of individual

fibres. Common sense said that if the average strength of

the fibres in one thread was higher than another you’d

think there’d be fewer breakages. But Tippit discovered

that it wasn’t the average strength that was important, it

39 BBC SCIENCE


11:07:17

11:07:25

PTC

was the weakest thread that really mattered.

It’s like the old saying, a chain is as strong as its weakest

link. It’s the extremes that make all the difference

MUSIC OUT

11:07:28 VO Tippit’s breakthrough came when he realised he could use

the data he’d gathered about the strength of the most

common threads to predict how often the very weakest

threads would be found.

11:07:37

11:07:42 VO

MUSIC IN

In other words he’d invented a method of using numbers to

predict extreme events from the spread of less extreme

events.

11:07:53 PTC Tippit’s insights from the cotton industry led to what is

called extreme value theory and it turned out to be

amazingly powerful. What used to be considered just

unpredictable could be analysed mathematically.

11:08:08

11:08:14

VO

Video clip

And his breakthrough turned out to be vital in the

understanding of extreme weather.

MUSIC OUT

11:08:15

11:08:18

Video clip

VO

MUSIC IN

In 1953 a huge storm surge was driven down the North Sea

towards London, devastating coastal areas. Over three

hundred people died in Britain alone. After the floods it

was decided something had to be done to protect London in

case it ever happened again. It was time to put extreme

value theory to the test.

40 BBC SCIENCE


11:08:52

11:09:11

PTC This extraordinary piece of engineering was conceived in

the 1960s after catastrophic and fatal floods in 1953.

These really were extreme events, literally a perfect storm

when rare conditions combined to create a terrible night.

MUSIC OUT

11:09:12

11:09:14 VO

MUSIC IN

In order to ensure the Barrier would do its job the planners

had to predict the most extreme storm surge that could be

expected in the future, more extreme and unusual than

anything that had been seen before. Extreme value theory

together with classic British record keeping was the

answer.

11:09:35 PTC They had a century’s worth of data on extreme high tides

and using Tippit’s models this allowed them to gauge the

chance of events occurring that were so extreme they’d

never occurred before.

11:09:52

11:10:15

VO The Thames Barrier was built to stop a once in a thousand

years event and so far we’ve not seen a storm come

anywhere near testing its limits. But Tippit’s method has

an Achilles’ heel, its predictions are based on the

assumption that the future will be similar to the past.

MUSIC OUT

10:10:16 PTC Extreme value theory uses the frequency of fairly extreme

events to give us a good idea of the chances of really

extreme events, things we haven’t observed even. But the

problem with climate change is that the patterns alter.

11:10:35 VO When the planners were designing the Barrier they had a

hundred years of data about storms to base their prediction

41 BBC SCIENCE


of the thousand year’s storm, but if the climate changes the

pattern of storms may well change too and that will mean

the data on past storms will no longer be relevant. Without

it the predictions made by extreme value theory are

unreliable.

11:10:56 PTC The average shift might not actually seem that impressive,

but it’s what happens in the extremes that is so important to

us and these become a lot less predictable. We can’t just

tweak the extreme value theory.

11:11:10

11:11:13

11:11:32

VO

MUSIC IN

So as our climate changes not only are we likely to suffer

more frequent extreme weather we’ll also lose the tool that

has allowed us to prepare for such eventualities.

MUSIC OUT

11:11:33

11:11:35 VO

MUSIC IN

Climate scientists have used maths and statistics to give us

their most likely prediction of the future, sticking to a

trillion tons of carbon should cause less than two degrees

of warming. But given the inherent unpredictability of the

future and the imperfections of our climate models how

sure can we be that that prediction is right? With the help

of techniques like the Monte Carlo Method the climate

scientists have put a number on their certainty, they are at

least 66% sure, that means there’s a sting in the tail of the

trillion tons figure.

11:12:17 PTC Climate scientists tell us that if you burn a trillion tons of

carbon they can be 66% certain that warming should stay

below two degrees, but there’s another way of looking at

42 BBC SCIENCE


this, we could say that they think there’s a one in three

chance that warming will be more than two degrees.

11:12:36 VO So the rather sobering conclusion is that even if we burn

less than a trillion tons we’re not guaranteed to keep

warming below this level, yet we also know that it would

take huge changes to our lives to keep to the trillion tons

limit, so how should we react?

11:12:56 PTC It’s always really difficult to know what to do when we’re

uncertain about the future. Usually we might try to work

out the chances of something bad happening and do what

we can to avoid it, or to protect ourselves against it. So

there’s a very good chance we’ll get old and so we buy a

pension. There’s a small chance we’ll have a road accident

but we wear a seatbelt.

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VO

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In each case we weigh up the risk and the reward, that

calculation relies on the quality of information available.

Scientists have collected and analysed data, come up with

plausible theories and used mathematical models to make

predictions. But with the climate we can’t do experiments

to test those predictions, only time will tell how accurate

they are. And if we want to influence our future we can’t

wait to find out, we have to choose on the basis of what we

know now.

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11:14:08 PTC When it comes to the climate the scientists have done the

calculations for us, but now it’s up to us to decide what

action to take.

43 BBC SCIENCE


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