Meet A Pioneer Of Modern Weather Prediction

Hey there, I'm Flora Lichtman and you are listening to Science Friday. Today in the podcast, a revolution in weather forecast. one of the scientists behind it. We have much more confidence in the prediction of climate 100 years from now than we have in 100 days weather.

Nowadays, the weather is right at our fingertips. It's definitely one of my most visited apps. But until about 40 years ago, scientists couldn't forecast the weather beyond 10 days. And that means they couldn't predict seasonal patterns. So you couldn't know how hot it was going to get in the summer or how much snow to expect in the winter. And without that, you can't plan for things like wildfires, droughts, or hurricanes.

But climate scientist Jagadish Shukla, who grew up in a village in rural India and saw how people's lives depended on this information, made it his mission to forecast seasonal weather events. And in doing so, he changed the course of modern weather prediction. He tells the story in his new book, A Billion Butterflies, A Life in Climate and Chaos Theory. He's a distinguished professor at George Mason University in Fairfax, Virginia.

And he was one of the lead authors on the 2007 report of the Intergovernmental Panel on Climate Change, which was awarded a Nobel Peace Prize. Shukla, welcome to Science Friday. Thank you. Let's start in the present. How good are we at predicting the weather today? I think that our three-day, five-day forecasts are really pretty good. 30 years ago we will not put much stock in the actual forecast five days ahead.

So thanks to this revolution in computing, in getting better models, getting a lot of observations from satellites. I think the weather prediction has been steadily improving and up to seven days it's pretty good but then it gets a little bit tricky after 10 days some people feel that even 15 days we can say something about. So it gets tricky at 10 or 15 days. Do you think that will change? Or is there a limit to how much we can?

That's a very good question. That's the origin of the whole world. Butterfly fact.

and Professor Lorenz at MIT, who was one of my advisors, he showed that no matter how good models we have, the nature of equations which predict the weather are such that even a small error in the initial condition can actually make the forecast not very useful as time goes further and he used the butterfly effect to say that as small as the flutter of a butterfly wings so now there will be a limit making weather protection. but I just

to make clear that we understand the difference between weather prediction and seasonal prediction and climate prediction. These are three different problems. processes are very different. Yes, what is the difference between weather prediction and sort of seasonal weather pattern prediction or seasonal prediction?

So the weather prediction is you start from today's initial conditions of the global weather and you try to predict Every three minutes what will happen after three minutes then six minutes nine minutes and then up to 24 hours and then up to ten days That's why we need supercomputers and then you are giving a very detailed structure of weather However, this breaks down after about two weeks.

10 days becomes not very useful but completely breaks down. What is meant by breakdown? Means your forecast will not be any different than if randomly I picked up a map. We know what it means to break down. We've all lived it because we've planned on the 14-day forecast and it didn't turn out that way. Exactly. But believe me, we're trying to cross that barrier.

Seasonal prediction is on the other hand predicting what will happen to the seasonal mean conditions. Will there be a rainy season, drought season, the real sort of contribution that came in my work was to recognize that the prediction of seasonal mean does not depend upon the initial conditions. It sounds like we can't do weather past 14 days, but...

we can do seasonal weather patterns. Like, will there be a monsoon or won't there be? And weather prediction means we are predicting day by day the actual sequence. Today, tomorrow, day after tomorrow, 12 hours later, up to 10 days. In seasonal prediction, you are predicting average of seasonal conditions.

June July August average DJF March April May that's what we use Because when you say butterfly effect cannot predict weather what we really mean is that we cannot predict the sequence correctly In seasonal prediction, the reason it is predictable is because now you don't have to worry about exact sequence so long as you can predict the average. and the average depends upon the boundary conditions like ocean temperature and land.

Well, I was going to ask, does climate change make predicting the weather or these seasonal changes harder? It makes actually these seasonal changes and weather makes the climate prediction harder. We really try to convey to people that we have much more confidence in a prediction of climate 100 years from now than we have in 100 days weather.

Why? It's amazing. Why? Because the climate change does not depend upon a small ocean and atmosphere and land interactions. It depends upon what we call external forcing. There are three external forcing, either sun. al volcán or amount of carbon dioxide we put in the atmosphere. So sun and volcanoes haven't done much at all but the amount of carbon dioxide we are putting in the atmosphere

is really very important in determining what will happen. So that's why if we know the carbon dioxide, we can tell you the climate with a lot of confidence.

I want to talk about current events. We know that federal cuts are affecting NOAA and the National Weather Service. There was news out last week that weather forecasting offices have to cut back on some data collection. What do you make of that? Are you concerned about that? I mean, you'll have to stop me once I go on on this, okay? It is so uncertain what is going to happen next. It is just devastating what is happening about the future of weather and climate protection.

I mean how to get better and in fact it will start getting worse. More people will die. More property will be lost. This is something we can predict without immoral. And I think that many of the weather and climate scientists And I have to include myself. We are losing sleep over where is this field going. Don't go away after the break. Dr. Shukla's childhood in India and how that led him to his life in science.

Monsoon affects every aspect of life. It affects music. It affects culture. Of course, it affects the cultural production. Stay with us. Support for Science Friday comes from the Alfred P. Sloan Foundation, working to enhance public understanding of science, technology, and economics in the modern world.

I want to talk about how we got here. So when you started your career, It sounds like there was this idea that you could not actually predict. seasonal patterns. Is that right? And this was the butterfly theory that had been sort of extrapolated out, right? It was the idea that there's too many variables. A tiny butterfly flapping its wings would create profound impacts. We could never understand a pattern. But you were like...

I don't buy that. I don't think that's true. Let me tell you why. So I had experience in my own life that in Indian monsoon, when there is a drought, everybody is suffering when there's a good monsoon year there's a lot of rainfall there's a lot of harvest and so on so if something is happening for the whole season and something is happening for the whole country of this scale

I just was not prepared to believe that a few butterflies can change that, if I want to use that word. And so, of course, my biggest challenge was first. So I come to MIT with this idea. And then I found out that the father of butterfly effect is a professor there and he is one of my advisors. I told my advisors that this is what I want to work and you know they both fully supported my idea.

And they said, look, we never said that seasonal predicts are not predictable. People interpreted that to mean that it's not predictable. So you just show me. So I said, so I launched a whole set of experiments and studies and showed. And one of the experiments is what I call billion butterfly experiment, is that, hey, I can show a condition where I change the initial conditions as if there were billion butterflies who are flapping their wings.

or billions of fish were changing the ocean wherever and then showed that nothing happened into the atmosphere. Why? It was because the ocean temperature had kept same in both of them. Got it. That was the biggest factor. That was the biggest factor. And when the result came, that gave me the confidence to say that, you know, there is predictability in the midst of chaos because now I was demonstrating that using the same language.

that the butterfly effect was used to show whether it's not predictable. You know, I want to ask you about this, the personal side of this, because I read this in your book and you're studying at MIT, you know, you're junior at this point. There's a prevailing theory that everyone basically takes as gospel. And you're like... I don't think so. Where did you get the guts to do that? I have been asked this question many times and this is not the only instance. There have been many other instances.

One of them being my great professor when I met him first time in Tokyo in a meeting I started arguing with him. And everybody in the audience thought this kid from India is crazy. I was 24 year old and he was the world's most famous meteorologist. At the end of the conversation, he actually came to my table and he said, I want to talk to you. That's how I came to MIT. So I think I have told you as before, it was a philosophical feeling.

then there has to be predictability. You cannot have millions, hundreds of millions of people's life depend upon seasonal wind prediction and nature saying, no, it's not predictable. So I've written in my book, I think that I had no deep knowledge. In fact, I had no knowledge of butterfly fat. As a matter of fact, some people claim that if you knew it, you would not have made such a stupid proposal. But I didn't know it and then I ended up going to prove it.

But I mean, you believed in your point of view, your philosophical point of view, but what gave you the confidence to believe in yourself? The observation that monsoon droughts persist for the whole season. the observations that droughts are over whole India. Such large scale persistent phenomena in nature is not weather, is not going to be and there has to be some predictability.

There has to be. So that part is religious, you can say, that God cannot be so cruel to millions of humanity. Tell me about where you grew up.

So I grew up in a very small village, no electricity, no road, no transportation. I walked barefoot till I was 12 or 14 to my middle school and high school. But somehow my father really wanted me to study science, except there was no science school anywhere near the village. So anyway, he finds a way. He gives me all the books for six years. I read this and there will be a test. And then I pass the test. So I moved to the science.

How did monsoons, these seasonal weather patterns, affect life where you lived? Monsoon affects every aspect of life. It affects music. It affects culture. Of course, it affects agricultural production. And agriculture is where the largest fraction of Indian population work. It's only now, in the last 15-20 years, that we are slowly getting other areas. So no, monsoon is a very integral part.

that influenced every fabric of Indian society. And what was it like in your village when the rains came? People just look at the clouds and say, oh my God, the rain has come. Everybody starts running and dancing. and get prepared to put the seeds, you know, the rice seeds and imagine if there's a drought, then it's a big problem.

And I'm guessing that the uncertainty about when those rains would come, if they would come, must have been existential. Absolutely, because the only thing they knew is the seasonal cycle.

It comes sometime in the end of June, sometimes, but which day, which week which will come? No. and it's so devastating where sometimes they say oh maybe there are clouds it will come they go and plow and then it doesn't come and i think that the uh it's changing now it has completely changed because we have this forecast with models and a system to inform people. And how does that manifest? What happens differently now? Well, it's different because they do their, you know, the plan.

Their seeds, they will know, just because they see a rain, it doesn't mean they will jump into the fields. They will know there will be forecast that is it going to be a sustained rain or it will be temporary. if it's going to be very hot and people are also changing the seats. Now you know you can take advantage of these weather forecasts to maximize the yield into the agricultural yield.

Your scientific career has been about finding predictability in the chaos. Do you try to do that with your own life to try to understand your own, you know, unpredictable story? If you look at the title of my book, A Life in Climate and Chaos, is just exactly what that means. And if you read the book, it basically runs parallel chaos in my life and chaos in climate system. It goes on.

I really wanted to do this because there are millions and millions of children in the villages and I wanted them to know it is possible. to be able to actually contribute, do things, even if you are in this very challenging situation. And it somehow comes out fine at the end. That's why you are interviewing me probably.

I mean, to bring it back to the butterfly effect, do you think that if you weren't born and raised in this village in India where the monsoons were so important, do you think you would... You would still be a climate scientist? Oh, no. I mean, it's hard to predict, certainly going backwards, but I always say, by the way, it's luck. I was the beneficiary of good luck and serendipity.

Things just happened. You know, I go to, the government of India sends me to Tokyo, and whom I met, the greatest meteorologist in the world. What's that adage, luck favors the prepared mind? Oh yeah, I've heard that. I don't remember exactly, but you're right. Luck just means gives you the opportunity, but then you do something to take advantage of that opportunity. Can I ask you to get a little philosophical with us? Finding predictability in chaos feels like a useful mantra for these times.

How do you suggest we apply that to our lives? Do you have any sort of life lesson that relates to that? Well, I'll give you a small example. One of my sort of philosophies has been never give up. And if you read the book, you will find that I have paid prices. for speaking out, for doing things, particularly about climate change. And I feel the same way now. When I teach my students, they say, we have so much climate anxiety.

And I said, solution to the climate anxiety is climate action. Get engaged, get involved. Find other students, make a community. You have to fight injustice. You cannot just give up. In the end of the day, either we succeed, but at least we feel we have done something. I think you'll see my book is dedicated to three of my grandchildren. I wanted them to know that I just don't talk about the climate change but I try to do something about it because I'm concerned about their future.

They are the ones who are going to get the brunt of the climate impacts. They are the ones who need to adapt to it. So I've always remained very upbeat and positive. in facing these problems. Although I have been hit hard and knocked down a few times, but I feel in the end it gives you much more pleasure just to have tried and failed, you know, as the saying goes, rather than not try.

I think that's the perfect place to leave it. Shukla, thank you so much for joining me today. Oh, thank you. Thank you very much. Dr. Jagadish Shukla is the author of A Billion Butterflies, A Life in Climate and Chaos Theory. That is about all we have time for. Lots of folks helped make this show happen, including... I'm Flora Lichtman. Thanks for listening.