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Hello, I'm Lar Hesse Fisher

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and welcome back to

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MIT's climate change podcast.

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Today I learned climate.

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When a natural disaster

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hits a community, the

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first priority is to

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get people safe and to save

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what we can. But after

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the initial danger passes, the

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next steps can be confusing.

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What do we rebuild and

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what do we change? Could

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we better protect ourselves

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in the future? Will the same

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type of event happen to us

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again? As our climate changes, these

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questions are taking on a new

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level of urgency. Was that

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storm more intense because of

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climate change? And how might

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our response be different if

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we knew for sure? Our

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guest is with us today because

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he is pioneering an emerging type of

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climate science that aims to give us

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clear answers to these questions. My name

1:01

is Andy Pershing. I'm the vice president

1:03

for science at Climate Central. We're based

1:05

here in Princeton, New Jersey. We do

1:07

climate science and climate change communication. A

1:10

big part of what we try to

1:12

do is tell the local personal story

1:14

of climate change. And we often do

1:17

that through the lens of weather. So

1:19

trying to look at weather conditions around

1:21

the country, around the world, and help

1:23

shine a spotlight on this is climate

1:26

change. This is what it means to

1:28

live on a warming planet. For this episode,

1:30

we want to make sure that we're

1:32

really clear that even though weather is

1:35

closely related to climate, they're actually

1:37

not the same things. The weather

1:39

is the day-to-day, right? It's the

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app that you have on your

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phone that tells you if it's

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going to rain tomorrow. For meteorologists.

1:47

This also includes the exciting tiny

1:49

details of how a current of

1:51

warm air brings a rainstorm to

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a particular town on a particular

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afternoon. And a lot of people

1:58

who get into meteorology... That's

2:00

what they live for. They love

2:02

those details and understanding that process.

2:04

On the other side, you have

2:07

climate science. And climate science is

2:09

all about the average. It's about

2:11

the statistical properties of the weather

2:14

system. Our former education specialist, Sylvia

2:16

Sharf, once gave me a really

2:18

good analogy for weather and climate.

2:20

Okay, so think of your wardrobe.

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The weather helps you figure out

2:25

what to wear each day. but

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the climate helps you figure out

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what clothes to have in your

2:32

closet throughout the year. So those

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worlds had kind of been apart

2:36

for a long time and back,

2:38

you know, when I was in

2:41

grad school, we were told like

2:43

you can't connect anyone weather event

2:45

to climate change. And 10 or

2:47

15 years ago, that was true.

2:50

But now? We're now in the

2:52

world where every weather event we

2:54

have... is affected by climate change

2:56

and it's really a question of

2:59

how can you make that link,

3:01

how strongly can you quantify it,

3:03

how do we understand the connection

3:05

between climate change and this extreme

3:08

weather event. This is called climate

3:10

change attribution. The field of science

3:12

that lets meteorologists say confidently that

3:14

climate change has made a certain

3:17

weather event more extreme and by

3:19

how much. So what changed over

3:21

the last 10 to 15 years

3:23

to make climate attribution possible? Well,

3:26

we can start with the weather

3:28

itself. I think it's not a

3:30

coincidence that we've started to see

3:32

more attribution studies as we've started

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to see more conditions that just

3:37

could not have existed before, like

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longer heat waves, more intense heat

3:41

waves, bigger rainfall events, you know,

3:44

more powerful hurricanes, you know, hurricanes

3:46

that do things that they just

3:48

didn't use to do in the

3:50

past. You might be familiar with

3:53

the concept of trying to hear

3:55

the signal through the noise. It's

3:57

like trying to hear a song

4:00

on a fuzzy radio station. In

4:02

our case, the weather data, which

4:04

changes so much from day to

4:06

day, is the fuzzy static. And

4:09

the song is the impact of

4:11

climate change. And as climate change

4:13

gets stronger, that song, that signal,

4:15

is easier and easier to hear.

4:18

But we also need a good

4:20

radio. And scientists like Dr. Pershing

4:22

are developing scientific tools to parse

4:24

the climate signal from the weather

4:27

noise. Well we'll start with a

4:29

kind of weather event that really

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lends itself to climate change attribution

4:33

and that's heat waves. We have

4:36

really great data on temperature so

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what we will do is look

4:40

at the history of temperature at

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a location and we will look

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at how the range of temperatures

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that you're likely to observe at

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that location have shifted as we've

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warmed the planet up. In many

4:54

places around the world, we have

4:56

100 or 150 years of thermometer

4:58

records. And, as you might expect,

5:00

these data show us that most

5:03

of the world is experiencing more

5:05

and stronger heat waves in the

5:07

summer. But of course, our big

5:09

question is, how can scientists be

5:12

sure that that's due to climate

5:14

change as opposed to something else?

5:16

So if you think about there

5:18

are other things that we've done

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that affect the weather, so we

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build cities, cities are hotter, right?

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We've changed where forests are and

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we've turned forests into agriculture. That's

5:30

going to change the temperature properties.

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And so we try to account

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for those changes and then simulate

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taking today's world with the farms

5:39

and fields and trees and factories

5:41

and buildings back into this pre-industrial

5:43

climate. So let's pick,

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you know, we're here in Princeton,

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New Jersey. So what we'll do

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is we'll look at every day's

5:52

temperature from 1991 through 2020. So

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the way I think of it

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is that we're taking the environment

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here in Princeton, New Jersey of,

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you know, pretty close to today.

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of you know with I-95s you

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know a few miles that way

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and you know their farms over

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there. So that allows Dr. Pershing

6:13

and his team to see how

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the weather of modern-day Princeton has

6:17

changed over 30 years of global

6:19

warming. So if the world warms

6:22

by a tenth of a degree

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how many more 90-degree days does

6:26

Princeton get and how many fewer

6:28

days of snow? When that allows

6:31

you to do is to... essentially

6:33

remove the signal of warming. So

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now that we know how this

6:38

particular location responds to a change

6:40

in global temperature, we can actually

6:42

turn global temperature off and look

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at how frequently that temperature would

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occur if we hadn't put all

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of this carbon pollution into the

6:51

atmosphere. In other words, if you

6:53

know how Princeton responds to 30

6:56

years of global warming without all

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those complicating factors like new farms

7:00

and highways, you can extend that

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to see how it responds to

7:05

150 years of warming. And if

7:07

Princeton gets a heat wave, we

7:09

can ask two questions. How likely

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is it for Princeton to see

7:14

these temperatures today? And how likely

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was it for Princeton to see

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those temperatures if we had the

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climate of the 1880s before we

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were strongly warming the planet? But

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that's not the only evidence that

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attribution scientists use. They also consult

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something completely separate, climate models. I

7:32

think climate models are absolutely beautiful.

7:34

I think they're just one of

7:36

the neatest things that we as

7:39

humans have built, right? We are

7:41

able to take the Earth and

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put it into a computer and

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we're able to simulate a lot

7:48

of really complex dynamics. Climate models

7:50

simulate the physics of our climate,

7:52

how basic laws of the universe,

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like the conservation of energy and

7:57

momentum, affect weather features like temperature

7:59

and air pressure and they turn

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those laws into a series of

8:04

math problems. Computers then solve these

8:06

problems and recreate weather patterns over

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decades and across the entire globe.

8:10

Some of the first climate models

8:13

were developed in the 1960s. It

8:15

really took off in the 1980s

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and has kept going. And they

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were part of what allowed us

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to make a very strong case

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that humans were warming the planet.

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I like to say that we're

8:29

now living in the world that

8:31

was predicted by those early climate

8:33

models. And the neat thing about

8:35

a climate model is that if

8:38

your model is good, you can

8:40

add CO2 to it and you

8:42

can see how much warming you're

8:44

likely to get. But you can

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also simulate a world where we

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hadn't warmed things up. And so

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you can make these really direct

8:53

comparisons. So climate models use data

8:56

about Earth's physical systems and geography

8:58

to predict how our climate is

9:00

and will be changing. Now this

9:03

is different from observational studies like

9:05

our Princeton one, which use real

9:07

weather data to analyze how our

9:09

climate has changed. And if we

9:12

can bind both types of evidence,

9:14

we can start to say something

9:16

brand new about extreme heat waves.

9:18

Take for example July 2023, when

9:21

Phoenix Arizona had 19 straight days

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of temperatures over 110 degrees Fahrenheit.

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Now anyone could have told you

9:27

that that was unusual, but thanks

9:30

to this new field of climate

9:32

change attribution, we can now say

9:34

something else that the length and

9:36

the severity of this heatwave would

9:39

have been virtually impossible without climate

9:41

change. In today's world, that is

9:43

crucial information. It clarifies that we

9:46

need to go beyond just recovering

9:48

from these events and to start

9:50

expecting them. So our partners at

9:52

World Weather Attribution work very closely

9:55

with the International Red Cross Red

9:57

Crescent and they are very interested

9:59

in attribution science because it points

10:01

to the kinds of conditions that

10:04

they need to prepare for. They

10:06

can do things like set up

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cooling centers and heat action plans,

10:10

right, which are really important for

10:13

keeping people safe in hot weather.

10:15

And as scientists get better at

10:17

climate change attribution, they're starting to

10:20

apply it to not just heat

10:22

waves, but to all kinds of

10:24

extreme weather events. There's really interesting

10:26

work going on around hurricanes and

10:29

other kind of major like storms

10:31

like that. You have a number

10:33

of studies that have started to

10:35

come out around extreme precipitation events.

10:38

Lots of studies around drought and

10:40

the nice thing about drought. There's

10:42

not really a nice thing about

10:44

drought, but the things that make

10:47

drought easy to attribute is that

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they tend to be over a

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large scale, large spatial scale, and

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occur over a long period of

10:56

time. And so any time you're

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averaging over large chunks of space

11:00

and time, the statistical side of

11:03

the problem becomes easier. So research

11:05

groups have now looked back on,

11:07

for instance, a severe drought that

11:09

struck South Africa in the mid-2010.

11:12

We always knew that that drought

11:14

was very serious. And now we

11:16

also know that climate change made

11:18

it three times more likely. Now

11:21

wouldn't you want to know that

11:23

if you were a government official?

11:25

A city planner? If you sold

11:28

crop insurance? Heck, I mean, even

11:30

if you were a citizen trying

11:32

to make plans for your family.

11:34

In fact, there's really great survey

11:37

work that says that people are

11:39

hungry for this information. People are

11:41

really curious about climate change. They're

11:43

concerned about it. So we do

11:46

a lot of work to help

11:48

journalists, and especially TV meteorologists, to

11:50

connect the things that their local

11:52

community is talking about, to climate

11:55

change. So, you know, TV meteorologists

11:57

have this... very clear role to

11:59

play in terms of helping keep

12:01

people safe and prepared and then

12:04

we'll now come in with our

12:06

more detailed quantitative attribution approaches and

12:08

say actually today's temperature in Phoenix

12:11

is five times more likely because

12:13

of climate change. We're telling you

12:15

this is an event that's going

12:17

to become more likely and perhaps

12:20

more severe in the future. and

12:22

that this is something that you

12:24

should prepare for. It's about helping

12:26

to keep your family safe. It's

12:29

about helping to keep your community

12:31

whole and productive in the future.

12:33

That's the end of our episode

12:35

today, but if there's another aspect

12:38

of climate science or solutions that

12:40

you're curious about, we would love

12:42

to hear from you. Email us

12:45

at T.L. Climate at MIT.EDU or

12:47

leave us a voicemail at 617-253-3566.

12:49

We are always excited to hear

12:51

who you are and why you

12:54

listen to the show and what

12:56

questions you have that we might

12:58

be able to help answer. Today

13:00

I Learn Climate is a climate

13:03

change podcast of the Massachusetts Institute

13:05

of Technology. Aaron Kroll is our

13:07

writer and executive producer. David Loshansky

13:09

is our audio producer. Michelle Harris

13:12

is our fact checker. Grace Sawin

13:14

is our student production assistant. The

13:16

music is by Blue Dot Sessions,

13:19

and I'm your host and senior

13:21

editor, Lar Hesse Fisher. A big

13:23

thanks to Dr. Andrew Pershing for

13:25

speaking with us, and to you,

13:28

our listeners. Keep up your climate

13:30

curiosity.