Instant Genius - Can we predict the future of the climate?

Episode Date: December 4, 2023

The climate is notoriously unpredictable and hard to plan for, but can and should we try to understand its future, or simply prepare for what is to come. We spoke to leading climate scientist David Stainforth to find out. Learn more about your ad choices. Visit podcastchoices.com/adchoices

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Music just as the artist intended. Visit name, From BBC Science Focus magazine, this is Instant Genius, a bite-sized masterclass in podcast form. I'm Alex Hughes, a staff writer for BBC Science Focus. Today we're speaking to David Stainforth, a physicist and author of the new book predicting our climate future. David sits down to talk us through the world of climate change, not just what it is and how it's currently unfolding, but more specifically, how we are measuring it and how to know which information you should trust and not trust. Climate change is one of the biggest conversations of recent years,

so it seems somewhat strange to start here, but I think it's probably quite important for some clarity. What is actually bent by climate and what are the changes that we're talking about? That's a really good place to start. One of the issues for my book is I feel that we haven't really defined what we mean by climate or what we mean by climate change. And that's one of my frustrations about perhaps climate academia, that we're not really that precise about these things. And it means that when we try and get economists and mathematicians and physicists working together, we don't have a real answer to that. So I think there's a real problem there. For me, I would say climate represents what we should expect. It's what sort of weather we should expect,

but also wider things, what sort of behaviours of ecosystems we should expect. And climate change is a change in those expectations. But in particular, what we should expect is always a distribution. If you think about the weather tomorrow or the weather next week, there's a whole range of different behaviours that could occur. There's that distribution of different behaviours. And climate change is a change in that distribution. So it might be in the extremes, or it might be.

It might be in the average, it might be in some particular values of temperature that become more or less frequent. I think there's a tendency to think of climate change as only the catastrophic, but it's everything as any kind of change. Absolutely. And how it will affect society is in many different ways. And we tend to focus on the catastrophic, very understandably. But simply relatively small shifts in temperature or rainfall can mean that the products we can grow,

the agricultural products we can go or the health impacts can gradually shift and become really very significant. It's not always the extremes that matter. And apologies if this is making you try and answer something very complex of a very simple question, but how is it that we measure climate change and, you know, that we're studying and how's that sort of change does technologies develop? Again, there's so many ways of answering that. I think we tend to study climate change in a number of different ways. We look at the past.

One of the things we do is look at the past, whether that be the last 50 million years or the last 2 million years or the last 150 years. And we say, how has it behaved in that period? And we use that to try and deduce how it's going to behave in the future. So that's a kind of observational-based way of looking at it. The other major thing that we do in climate change studies

is we use computer models. And in the physical sciences, these are computer models of the atmosphere, ocean, cryosphere system. And we study them in great detail. So going on from that, there's been, I guess, a big push recently for Earth visualization engines. Could you go into those a little bit more and talk about what they are and how they could be an important tool for the future climate change? Yeah. So Earth virtualization engines are really the extension of these complex global climate models that became Earth. Earth system models and now we're calling them Earth virtualization engines.

It's essentially, the concept here is that if we throw enough technology at the problem that we'll be able to represent something that is equivalent to the real world climate system. And Earth virtualization engines is saying that we're going to make our climate models very high resolution, by which I mean perhaps one kilometer resolution, so that you're simulating the atmosphere of the Earth. at one kilometer resolution across the whole globe. That contrasts with, it used to be at about 100 kilometers, perhaps 10 years ago, it's about 50 kilometers now.

So when we simulate the 21st century, instead of simulating to a way that could just about tell the difference between Oxford and London, instead we'd be simulating in a way that we'll be able to tell the difference between your house and your friend's house a mile down the ground. So the idea there is that we'll be able to represent the behaviour of climate that much better by increasing that resolution. And there's a lot of people who think that that's the way to go,

that we will get something that represents climate realistically by doing that. I'm not one of those people because the atmosphere is not the only part of the system that matters. The oceans, the deep oceans, the cry-sphere, ecosystems, land ecosystem, ocean-ecosystem, ocean-eas. ecosystems, all these things matter, and they include processes that we don't fully understand. We certainly don't know how to represent, and we don't necessarily think that we could represent them, even if we had a one-kilometer model. So my own view is that by going to these Earth virtualization engines, we are creating something that's really good for studying atmospheric processes, but not actually that good at

telling us about what future climate will be. And worse than that, they look as though they are. So they drain a lot of resources and run the risk of directing society towards adapting to a future, which is actually just a model future. It's not, doesn't represent what we understand. It's like you reached into my brain and pulled out my thought, because the next thing I was going to ask you is if we can separate the human effects of climate change from natural occurrences, like natural increases in the temperature of the sea, So I assume in that sense, it's not so easy to separate those two things. It's all intertwined and it's hard to, I guess, predict based on those factors. Always. They're always intertwined. Yes. And we do need to consider it that way.

That's not to say that we can't identify that mankind's emissions of greenhouse gases have led to changes in the climate system, that they have led to global warming. We can know that really very well indeed. We know that the warming, we know that the warming, seen at the moment is largely human-induced warming. But that's very different to being able to identify whether the particular heat wave that happens this summer or that summer or this flood or that flood, or in particular just whatever the changes you see when you look out the window and you see the changing timings of spring and autumn and the plants that you see growing, you might notice changing in those. Are they due to human-induced climate change or are they due

to natural variability, it will almost certainly be a mixture of the two. For me, climate change, for us to understand and respond to climate change, well, we have to understand the uncertainties in what we know about future climate change. But I don't want to come across as a climate sceptic in any way. We can know about the existence of the threat. We know that it's going to be a very substantial change to human societies, very substantial threat to human societies. I mean, it's absolutely huge, and we can know that.

Nevertheless, what we actually want is to be able to paint pictures of what those changes mean for individual societies on the ground. Only that way can we engage people in why you might want to change behavior, why you might want to change society. Those sort of predictions are much, much harder. And how do we go about with those sort of predictions? Typically, we go about them through that sort of climate models, Earth system models, Earth virtualization entities. That's the typical way of doing them. I think in my book, what I'm talking about is to say, actually, they're just really fascinating, deep challenges about how we go about using those models and how we go about linking the physical models to economic models and models of society. And they are really, really interesting challenges.

They're kind of, they're to do with the philosophy of science. they're to do with the maths of non-linearity, and they're to do with the physics and economics of reality. And I don't think we've really addressed them. But, I mean, in this podcast, you cover some quite tremendously exciting things. And I would argue that studying climate change is as exciting. It's as exciting as the search for dark matter in the universal, the search for the origins of consciousness.

The things we don't know how to do. And they're kind of, many of them related, to how we use our models. So we tend to use our models as saying, we've built a model of the climate system, so we can treat it as if it's equivalent to the climate system. But we can't. And the maths of non-linearity tells us that.

So we have to look at cleverer ways of using our models. And that means using them to explore possibilities of the future instead of aiming at a single prediction and saying, that is what it's going to be. Instead of it being so much a case of trying to make a prediction of, yes, this is our exact future down to the day, this is what this exact occurrence will be, it's a case of looking forward and thinking, okay, this is what is likely, this is a possible future and let's just prepare for what can come. That's right. That's exactly the case. The difficulty is that there are a number of sources of uncertainty in what that possible future can be. Some of them are to do with the maths of non-linearity, sort of chaos theory, which gets very exciting. But some of them are to do with the relationship between models and reality, which also has an aspect of maths involved and the maths of non-linearity.

Where you've got the butterfly effect that says, if you don't know the state of the weather today, you are limited in how much you can say about the weather next week. There's also a sensitivity that says if your model is possibly even just a slight bit wrong, if it just misses one small element, it could be that the predictions it makes in 50 years time could be very substantially wrong. And this is something that Erica Thompson has called the hawk-moth effect. So you've got the butterfly effect and you've got the hawk-moth effect. Where we stand at the moment is that we've got a whole collection of different. climate models, but there's still only 30 or 40 of them. There are hundreds of thousands,

millions of possible versions of the models of the climate system, and they could behave, they could simulate future climate change in very, very different ways. What we need to do, and one of the big challenges and exciting challenges in climate size today is to work out how we explore that space of possible models to give us the range, the domain of behavior of physical climate in 50 to 60 years time. Ambition comes in all shapes and sizes. At First Citizens Bank, we roll with your goals because we're built for what you're building. Fit for your ambition for Citizens Bank.

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and unforgettable listening experiences at home. Try it for yourself at a focal powered by name boutique. Visit focal powered by name.com for more information. One thing that I'm curious, branching off of that, is, I mean, as you're fully aware, climate change is very, divisive, you know, people have opinions on it on every spectrum possible. Is there, I guess, a level of concern where if you make very accurate predictions and they don't come true or that they don't match up, that it maybe makes the sides of climate feel a little bit shaky to those

people that already aren't so sure in it? Absolutely. I think that's absolutely the case. And we've seen that somewhat in the past, in the period from about 2000 to roughly 2012. you could argue that global mean temperature didn't increase that much. And so there was a big argument at that time saying, well, maybe climate change is stopped. Maybe you don't need to worry about it. I think for those of us working in climate science, nobody ever thought that. The reasons to expect warming come down to basic physics of energy conservation and the radiative behavior of carbon dioxide and the like. So nobody expected that. But that wasn't something that we'd made clear beforehand. So people were surprised that we weren't seeing this monotonic year-on-year increase. And they quite reasonably thought maybe this calls into doubt where the climate change is serious. So I do think being honest and clear about the uncertainties is absolutely crucial. At this point, I haven't for quite a while.

It's been huge amounts of money that's been poured into time, research. Is there an argument that this time and money should be spent on planning for the future, making these graphs, trying to better understand what's going to happen, or that we should be thinking more in a preventative measure? Should we be making flood defences? Should we be planning for a world that is affected by climate change? I think we should definitely be planning for a world that is affected by climate change. We already see the evidence of climate change taking place. and we know that the consequences of climate change are going to get worse. We should be preparing for that, and we should be trying to avoid as much further climate change as we can. However, my view is that if you're to do that,

we need to roll into the social sides of climate change. To do that requires us to carry populations along with us. people have to see why climate change matters to them. And that means presenting climate science and climate policy and climate economics in terms that are relatable to individuals on the ground. So how will climate change affect our society? And I think making those connections across disciplines to paint pictures of what the world will look like under different scenarios of Greenhouse gas. is absolutely crucial if we're going to be able to respond to climate change, at least in democratic countries,

because we can all say, hey, we don't like climate change, we want to mitigate climate change, we'd like our government to do that. But once that starts involving changes on the ground that we maybe are not totally comfortable with, we always like things to stay as they are, particularly if it involves costs that take funds away from other things, we want to do with society, then people start questioning whether that's actually what they want to do.

And I think where academia is failing is that we're not painting those pictures of what climate change means to individuals on the ground. I think we see it as, oh, you might get flooded, or you might have a heat wave. And I think a lot of people in society think that's serious, but it's very difficult to believe it's going to hit you or there's a sense in which, well, surely we can build flood defences and we can put in air conditioning. It's not going to be that bad. I think it probably will be that bad, but I don't think we've painted the pictures of quite what that looks like. If I may say one other thing in a slightly related way, I think this aspect of uncertainty is also important for communication

because most people throughout society are familiar with uncertainty, may expect uncertainty from scientists and from specialists in all sorts of fields. I think in climate science, the climate sceptics in the early 2000s were successful in making it undesirable for us to talk too much about uncertainty because it seemed to undermine the argument that we needed to act. But I think it's really important to talk about the uncertainties we have in climate science because that's what engages people with, it provides the credibility in the science that we're putting across. And it's also really interesting. So is it a case of, I guess I define it as

maybe a PR problem that, you know, that we see climate change in a certain way and it's, for some people, there's a blockade to understanding it because it's so scientific to others. that, you know, there's a lack of connection to the end result of saying, you know, that's not going to happen. Is it just a case of peeling all of that back and presenting in a way that the world really understands? I think it is in a way that the world understands. But I don't think we should expect most people to understand climate science or to want to understand climate science. People have really diverse interests. I suspect listeners to your podcast maybe do want to understand climate science, but I don't think most people in society do. So it is a matter of

making it real to people and individuals. And I think that involves, I mean, I'm a climate scientist, a physicist by background, but I also work on climate economics nowadays and climate policy and also a bit of philosophy of climate science. I think there's a need to make those links across the academic disciplines so that we take the uncertainty in the physical sciences and use that effectively in our assessments of economics, but also then take that and portray what it means for society. So I don't know what it's going to mean for society. These studies haven't been really done very well. But I am concerned. when people talk about concerns about climate change being focused on floods or heat waves,

I think climate change will affect almost every aspect of society because we will be needing to fight the consequences of climate change in many areas, whether that's local floods, local heat waves, or whether it's inability to access certain types of foods or breaks in supply change across the world, which drag down our economy. All these things are likely to mean that we're constantly firefighting, if you'll excuse the expression, to keep our societies running in a normal way. And in doing that, it means we're going to drag down the ability to do all the other things we want to do in society, whether that's provide free education to all under 18-year-olds, whether it's our ability to provide healthcare across the board, or whatever it might be. It's

Whatever you care about, it's likely that climate change will impact that. But I don't think it's reasonable to go out to society and say, you should care about climate change. It should be, you should care about whatever you care about, but climate change is likely to be impacted that. So it's less so about the giant floods and the meteoric situations and more about here's why climate change affects absolutely everything in your life. Absolutely. I wanted to go back to the, I guess, the more scientific science. of things quickly, because as I'm sure you're aware, AI and all forms of artificial intelligence have had a big year, and it's kind of had this rapid expansion and expansion in funding.

Is that something that you see having an impact on the way that we measure and understand climate change going forward? It is. I think you'll have both a positive and negative impact. I think there are many positives. There are many ways in which AI technologies can be huge. valuable in helping us understand climate change and helping us respond to climate change. There are aspects of processing data, of seeking out aspects of the data that we have in terms of observations in the past and the like. But you mentioned Earth virtualisation engines earlier. There's a lot of discussion at the moment about how AI technologies can process weather

forecasts as well or better than the big models at the moment. That's a very exciting development. How do we use that? I think, though, there's also great excitements that runs from that and says, hey, we can use the AI to tell us what the future is going to be to paint these pictures that I've been talking about. I don't believe that's the case, and I think we are likely to mislead ourselves in the excitement of rushing towards AI and could well get ourselves into an even worse situation. And the reason I say that is that the problems of climate prediction, the problems of describing our worlds in 270 or 2100,

are questions of information content. It's a question of do our models actually contain the, could they possibly contain the information to be able to make those predictions? And if they don't contain certain feedback processes, if they don't contain perhaps information about certain ecosystems, then the information simply isn't in those models. And however clever your AI system is in processing the data from those models, it cannot produce the information that we're looking for.

And it's the same when we look at observations at the past. We might have paleo observations from 100,000 years ago or 10,000 years ago, or we might have really detailed data from the last 170 years from the Industrial Revolution and the like. But those are observations of the planet as it changes in a state that is really completely different to what we're expecting to see in the future. So the physical processes that are taking place are likely to be based on different interactions of processes from those we'll see in the future. And again, AI is so good at identifying and processing data. It's seeking out data. But if the information, we know a priori, which we do, that the information is not

in that data set, then AI simply cannot produce the types of predictions, the type of pictures that we're looking for. So if we use it cleverly, it will be great. I'm afraid I'm fairly pessimistic that we will get so excited about saying, oh, we can do everything we want it, everything we're looking for, that we will actually use it badly. And that will go. guides us towards misadaptation of society and lead us into an even worse situation. So I think from the disconversation, in my mind, there's two, I guess, fields of this. There's the general public and then there's the science study. And I think in the general public side, there's this idea that, you know, we see climate

changes, floods and end of the world, which, you know, there is parts of that. but there is also, as you were saying, how climate change affects every single part of your day, every single part of your life, and it's that side of it that we don't really explore much. Then on the science side, there's this fear of climate prediction and having too perfect of a model without it actually working

and maybe just more thinking, what is the likely possibility, and what does the future look like? Do you think overall that there is maybe just this idea that climate change is so focused on the end result, you know, the floods and this exact predicament that we don't actually look at where we are now and, you know, the, I guess, more day-to-day issues that come with it. I think that's absolutely, yeah.

I think that's absolutely the case. I think there's real risk there. The day-to-day now, but also the day-to-day in the future, though real conceptual challenges to understanding climate change in the future at the detailed societal level. I'm not talking about a big global change level. And that requires imagination. It requires us to think across disciplines, whether that be oceanography or atmospheric physics or hydrology

or agricultural science, economics, policy studies. It's a matter of thinking across these and having the imagination to make jumps of logic. And when I talk about this, I have a sort of anecdote here. I gathered back in 2008 at the time of the financial crisis just after the financial crisis. The Queen Elizabeth went to LSE and asked them why this financial crisis not been predicted since it was so big. And they went away and gathered a group of experts and came back the next year and said,

well, it was principally due to a lack of imagination among some very clever people to really examine the risks to the system as a whole. And I think we have exactly the same thing in climate change. We are not bringing the discipline together, and we're not encouraging people to be imaginative in terms of what it means for society, but also for the physics. When we think about climate physics, we think about, well, feedback processes and climate sensitivity and how a cloud's going to change. But how clouds are going to change is not just a matter of clouds.

you would think that it would automatically be about studying clouds. Only it is about how clouds behave, but clouds respond to the circulation patterns. The circulation patterns respond to the ocean temperatures respond to the ocean temperatures respond to circulation patterns in the ocean and also ocean biogeochemistry and how it takes up carbon dioxide and the like. It is all one system and we need to think about it as all one system. Thank you for listening to this episode of Instant Genius. That was David Stainforth talking about climate predictions.

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