Let's say you wanted to make a detailed computer simulation of a really complex system,

like the flow of water in a creek.

You'd need to know the position and movement of every little bit of water, a topography of

the contours of the stream bed and every rock in it.

The fish, the breeze blowing across the top, the dust that settles, the leaf that drifts down and lands on it,

the energy of the sun, the coming rain.

It's mind-boggling how much complexity is built into even the smallest natural phenomenon.

Now scale that up to a river.

And then a watershed.

The ocean it flows into.

And finally, the entire energetic fluid system between the Earth's crust and space.

That's air, clouds, ice, rock, ocean, life, us.

That's just a whiff of how complex Earth's climate system is to simulate.

Yet, as we've learned from the last 60 years of attempts to model the climate,

you don't need a minute level of detail to learn an awful lot about where we've been and where we're

going. But it's never been easy, and it's not getting any easier.

Welcome to the Quanta podcast where we explore the frontiers of fundamental science and math.

I'm Samir Patel, editor-in-chief of Quantum Magazine. Recently, we published a special issue on climate science called How We Came to Know Earth,

and one of the big features in the series was about the past, present, and threatened future

of our efforts to model the Earth's climate.

We're joined today by the author of that story, called How Climate Scientists Saw the Future

Before It Arrived, Quanta contributing writer Zach Savitsky.

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