Two main things have happened over the last 20 years. So computers have got much faster. As you get more compute, you can include more details. If you include more details, then you’re going to be closer to the reality. And then remote sensing, the amount of information that we have generated over the last 20 years from both NASA and other agencies, satellites, has been incredible.

We have the series measurements tracking the energy fluxes at the top of the atmosphere. We have MODIS, which has been tracking cloud changes. It’s really been a golden age for observations. Over the last 20 years, that’s radically changed how we understand what’s happening and how confident we are that our predictions are skillful and relevant.

You’re listening to A Climate Change, this is Matt Matern, your host. I’ve got Gavin Schmidt on the program. Gavin’s a noted climatologist, climate modeler, director of the NASA Goddard Institute for Space Studies in New York. You know, one of the things he took over that post from Dr James Hansen and around 2014 and everybody knows James Hansen, who famously warned Congress about global warming back in the 80s. So you stepped in some big shoes to fill, and are filling them quite well.

So kudos to Dr Schmidt. And you know, just to give you a little background on, you know, his education, Oxford PhD at the University of College of London, and applied math post doc at McGill, which my dad went there for a little chemistry master’s degree eons ago, author of 100 studies in peer reviewed journals science and nature, co authored a book climate change, picturing the science with a foreword by Jeffrey Sachs. And welcome to the program, Gavin.

Well, thank you for having me.

Well, tell us a little bit about the work that you’re doing over at the NASA Goddard Institute in New York, because I didn’t even realize it there was a NASA program in New York. So news to me.

Oh, well, news to many people. In fact, we’re not a very large part of NASA. We don’t launch rockets from the roof or anything, but we’ve been at the forefront of climate modeling, understanding why things are changing, how things are changing, how they’re going to change in the future. For many decades now, one of the main things that we do, which is not everything that we do, one of the main things we do is build and develop climate models.

These are the kinds of models that go into the IPCC reports that that are being used to project, you know, what might be happening in the future, to allow us to prepare, to allow us to mitigate those changes, and that we’ve been working on this kind of modeling light, as you mentioned, since the 1980s way before I got there.

And so I’ve kind of inherited this program and like, you know, we hopefully we’ve taken it forward, but the idea is that you really want to capture the essential processes of what happens in the climate system, and then the essential changes and how those changes work their way through the system, things like changes In the emissions of aerosols from marine shipping, changes in the sun’s radiation on a solar cycle time scale, impacts of big volcanic eruptions.

That changes, of course, to atmospheric composition, greenhouse gasses, carbon dioxide, methane and the rest of it. And then see what the fingerprints of those change are. Those changes are so that, then you can look in the observations and say, Hey, are we seeing what we expect to be seeing? You know, what do we how well are we doing that? How skillful is that? And therefore, how, how confidently we can we can predict? Can we predict what’s going to happen in the future?

Well, tell us a little bit about for a space tech geeks out there, what kind of tools do you have floating up in the atmosphere and maybe in the ocean and all over the place that are giving you the measurements that you’re relying upon in doing this modeling?

The kind of modeling we’re doing is a little bit different from weather forecasting, right? So weather forecasts use the same basic kind of structure of models, and they ingest all the information they can find, you know, for today, so that they can make a better prediction for tomorrow, next week, etc.

We don’t use data in quite the same way. We use data observations to try and pin down what the essential process is, how clouds form, how much evaporation changes, if the temperature changes or the humidity changes, we try and extract out those processes, how how reflective sea ice is when it’s wet or when it’s dry, or when there’s been new snow that’s fallen on top of it, and we encapsulate those things into into the.

Our translations, formulas, code, and then we try and see how that whole system works. And then the other kinds of observations that we’re comparing against other are the observations of big emergent properties of the system, how the clouds change when you have an El Nino event or a La Nina event, how the trends of clouds are changing. Those are made up of many, many, many different processes all happening at once.

And we’re trying to see with these models whether we can capture that emergent property of the of the observations in the emergent properties of these models, and then make a link between those things. So we use remote sense data from NASA and from other agencies. We use in situ data. We use special kind of campaigns that are very targeted on you know, there was a mosaic exhibition in the Arctic looking at the physics of sea ice and the oceans and the atmosphere above it.

You know, we take information from these field campaigns, from the remote sensing, from in situ observations, from the boys, and then use all of it as much as we can to both improve the model and then to evaluate the changes that we’re seeing over time.

And in terms of since you started doing this, to where we’re at today, what kind of improvements in the science Have you seen that have made you believe that It’s more reliable or less reliable?

No, it’s more reliable than which is which is good, right?

No, it’s more reliable. There are two main things have happened over the last 20 years. So computers have got much faster. That is by far the biggest thing, because as you get more compute, you can include more details. If you include more details, then you’re going to be closer to the reality that helps a lot. And then remote sensing, the amount of information that we have generated over the last 20 years from both NASA and other agencies satellites, has been incredible.

We have the series measurements tracking the energy fluxes at the top of the atmosphere. We have MODIS, which has been tracking cloud changes. We have MLS that’s been looking at water vapor changes in the stratosphere.

We have the grace missions that have been tracking the loss of ice from the ice sheets. All of those things are going into the mix. And it’s really been a golden age four observations over the last 20 years, that’s radically changed how we understand what’s happening and how confident we are that our predictions are skillful or and relevant.

And in terms of those predictions, have they changed markedly since you started doing the modeling? Meaning, does it look worse for us or better for us than you know, 20 years ago?

So I mean, the interesting thing is the if you go back even to the 1970s and you ask people at the global scale, you know, what do you predict as we are increasing the amount of carbon dioxide in the atmosphere? And I even going back to the 1970s those predictions were very skillful. In the 1980s they got more complicated, but, but were, but didn’t really change in the global mean picture and and that has been constant.

So, so in some sense, we’re predicting the same things that we were predicting, you know, 4050, years ago, and they have, in fact, by and large, been born out. But we’re now able to predict a lot more things, right? We’re now able to predict things I like, the changes in extremes of rainfall intensity, the changes in the statistics of heat waves, the changes in the sea ice, the changes in the Southern Ocean.

And that’s come about because we’ve increased the complexity of these models, and we’ve been able to verify how well they do against a much deeper bench of climate statistics than just the global mean temperature, which, as I mentioned before, has been well predicted for many, many years, but we’re doing a much better job now at predicting the far field effects of An El Nino event, or changes in the El Nino events, or, you know, what happens to storm tracks? What happens to the intensity of storms?

All of those things are now kind of within the scope of the models in ways they really weren’t 30 or 40 years ago.

So in terms of working on the variability of ocean circulation, which you’ve done a lot of work on what are those models telling us, and should we be extremely worried based upon what you’re seeing?

Well, yes, the basic issue, I mean, as you’re well aware, is, you know, as you increase the amount of greenhouse gasses in the atmosphere, that slows down the emission of energy to space, which means that there’s an energy imbalance. There’s more energy coming into the system than is leaving.

Most of that energy is ending up in the ocean, where it can, where it where it leads to marine heat waves, sea level rise, melting of the sea ice, melting of the Antarctic ice shelves, which all had to see it to sea level again, the warmer oceans. Are fuel for storms, particularly in the tropics, the intensity of storms has increased the intensity of rainfall associated with these storms, not just tropical cyclones, but but frontal systems everywhere.

That’s increasing. And so we’re seeing, you know, increased intense rainfall pretty much everywhere. And all of these things are, you know, consistent with our understanding of what has been driving this and what has been happening in at the local scale.

The big difference from from 30 years ago is, I think that the signals really had only kind of started to emerge at the global mean, the global average level. I went there and quite clear, you know, from from the 1980s onwards, but, but nobody lives in the global average, right?

You know, like everybody lives in a very local, regional kind of environment. And for a long time, you know, people were saying, people like me, so myself, was saying, Well, you know, global warming is happening, but everyone’s saying, Wow, global warming everywhere else. It’s just so much noise.

What’s happened now, and particularly in the last five years, is that the signal in the global mean has become so large, right, that it’s extremely clear, but it’s so large, it’s large enough now that it’s having a reflection in the weather and the impacts at a very, very local level, right? And so climate change used to be something a little academic, a little esoteric.

That’s no longer the case. Climate change is having real impacts, you know, every day, and you know, we’re seeing we’re seeing that in the analyzes of the rainfall from Helene. We’re seeing that in the analyzes of La wildfires. We’re seeing that in the analyzes of the Pacific Northwest heat wave we’re seeing that in the analyzes of the sea level rise and increased storm surges that we’re seeing in Miami and in Newport and in, you know, all up and down the west coast the East Coast.

So one of the things that you know your bio talks about is astrobiology, and maybe you can explain for everybody, how that fits into the work that you’re doing, that’s kind of interesting.

So astrobiology is really the study or the thinking about what we might be able to detect when we might be able to see in extraterrestrial environments that might be related to life elsewhere. And obviously that has been one of the main drivers of our desire to explore the universe. Are we alone, right? You know, what else is going on?

And we have this, I think this fundamental understanding, a wish for us not to be alone, for us to be able to find other civilizations, other forms of life in the universe. But to do that, we have to. There’s a lot of stages that you have to go through.

You know, we have to, we have to explore the other planets in the solar system. We have to detect other planets around other stars. We have to characterize what’s going on on those planets. You know, what kind of climates do you have if you’re in a in a tidily locked orbit around a red giant?

That’s a very different kind of cosmic circumstance than the Earth. But it turns out, you can still have a habitable zone. You can still have situations where you could have liquid water on the on the surface of the planet. And you know, given that we’re looking for the most part for life that somewhat resembles ours, right, liquid water is one of the key ingredients to having that be there.

And so understanding the climate of exoplanets is not that different conceptually than understanding the climate of the Earth. And so there’s, there’s a very clear link between the models that we developed for the earth that have been informed by so much information that we can then use those models to explore the climates of other planets or other exoplanets and and say, you know, which one should we concentrate on? That might be the most earth like that might be the most convivial to to life. And then we have this kind of concept of searching for what are called techno signatures, right?

Can you detect the impact or the or the entrails or the fingerprints of other technological civilizations, right, that we might conceivably be able to communicate with?

You know, what kind of fingerprints do they leave in the kinds of things that we could observe, either from space telescopes or in the sediments of Mars, or conceivably even the sediments of Venus, what would we look for? And one of the things that that we worked on, which is kind of using, is, what are the fingerprints that we’re leaving behind, right?

So, you know, we’ve heard about the radio wave that has, that has emanated from Earth that would, in fact, be detectable from nearby, nearby solar systems. But what about other other things that we’re leaving behind? You know, people think about relics, but I we’ve been thinking much more about the geophysics, right? So what are we leaving behind in the ocean sediments? What are we leaving behind?

The kinds of things that we look for when we go back in time over the earth, you know, we’re leaving behind a massive perturbation in the carbon cycle. That’s very, very clear. In the isotopic signature of the carbon that that we’re putting out, where we created global warming, that’s going to be very clear in the ocean center, we’re creating a layer of plastic debris that will literally cover the entire ocean floor in a thin and but but very clear and distinct plastic layer.

We’re changing the amount of minerals and metals that we’re mining, and that’s all ending up in the ocean as well. You know, the the the amount of gold that we’re putting into the ocean because of the mining of gold, and then the use of gold within electronics and manufacturing has increased the amount of gold that’s going into the ocean by orders of magnitude.

All of these things will be, will be visible in the future. So if you think about a future paleoclimatologist, of some visiting species coming to earth, they will be able to see, even if we don’t do anything more than what we’ve already done, they will see our fingerprint.

They will see our signature and they may wonder, why the heck were they using so much plastic? Why were they? I think that they will be quite puzzled.

Yes, like when they had alternate materials, they clearly had it within their reach to have cleaner energy and have a cleaner environment, yet they chose to live this collect. There’s a very interesting kind of consequence of what you just said, almost all of our detectable fingerprints are in some sense a waste.

Right? Sending radio waves into space is a waste of energy. We’re not doing it to do that right? Filling the oceans with our garbage is a waste. It’s resources that we’re just throwing away. Carbon dioxide is a waste product from the burning of fossil fuels, all of the things that we can detect, they’re accidental. They’re signatures of our unsustainability. If we were to become a society that was much more sustainable, then our fingerprint on the environment, on the earth, on the cosmos, would become much smaller. And one of the interesting kind of solutions to the Fermi Paradox.

So the Fermi paradox is, you know, if you think that the universe is very old, which it is, and if you think that there are millions upon millions of exoplanets, which there are, and then you think that, well, you know, life can’t be that difficult to create, right? Then the paradox is, why have we not already seen evidence of alien civilizations or alien life?

If you know the, you know the galaxy is billions of years old, that’s a very, very long time, surely somebody would have come by, somebody would have left. And we’ve not, we’ve not detected anything. And so Enrico Fermi said, Well, you know why that seems a puzzle. What’s the cause of that puzzle?

And there’s been a number of theorized reasons why we haven’t detected anybody else. One is we are simply alone. This is we are a unique and but nobody really likes that. That answer. Another one is, yeah, no. Life pops up. Civilizations pop up. But there’s a great filter. There’s something that prevents civilizations and life from becoming, you know, a galaxy wide phenomena.

The difficulties are faster than light travel. So you can get away with that with robotics, perhaps nuclear power, or nuclear weapons or or, you know, energy like pollution, you know, maybe, maybe we just everybody pops up and then they just kill themselves because they pollute their own environment to such a degree that they can never really sustain it.

And then there’s another one, which I, which I which philosophically, I prefer, is that for civilization to be really, really long lived, right?

Not, not the few 100 years that we’ve had here, but really long a million years civilizations, you cannot possibly have an unsustainable civilization. You have to recycle everything. And the reason why we haven’t detected any of these civilizations is because they leave no trace. And so that’s the kind of the sustainability solution to Fermi’s Paradox and and that kind of comes into, you know, what does the Anthropocene look like?

Right? Because everything that we’re doing in the Anthropocene is predicated on absolutely huge amounts of waste, waste that’s affecting the ecosystems, waste that’s affecting the ocean, waste that’s affecting the atmosphere, or even our kind of near, near Earth environment, all of those things, if we have ambitions to be a million year long civilization, you know, none of those things can be sustained for very long at all. Right?

We’re heading for a quite shorter run based upon the trajectory that we’re on, right? So tell us a little bit. About coming back to earth a little bit tell us a little bit about the Arctic. And certainly we all are reading more and more about how fast the climate is changing in the Arctic, and it’s much faster than it is in the temperate zones that most of us live in.

Well, that’s exactly right. And so this was one of the things that was predicted very, very early on, that the the land would warm faster than the oceans, hemisphere would warm faster than the southern hemisphere, and the Arctic would warm fastest to warm. And as the data has come in, those those predictions have been well, well validated, and we are indeed seeing temperatures in the Arctic warming at about three, three and a half times as fast as the global mean, right?

So this last year, you know, we, we probably exceeded 1.5 degrees Celsius above the pre industrial for the first time in a single year. But in the Arctic, the warming has been three times that. It’s like four and a half five degrees Celsius. So that’s, that’s like seven, eight degrees Fahrenheit.

That’s a huge, huge shift in what happens there. You know, obviously the Arctic, oh, well, it’s cold. It’s not quite as cold as it was, but like at the margins, what you see is, you know, in the spring, the ice goes away faster in the in the autumn, it doesn’t, it doesn’t arrive so early, the the season for ice roads in Alaska has shrunk by about 100 days over the last 30 or 40 days, right?

I mean, that’s a huge shift in how you get around, what you do, how you live, how you hunt for the indigenous folks there. And then that has, that has knock on effects even even in the temperate zones. You know, melting of the ice in Greenland raises sea level everywhere.

And so we can see it, particularly along the along the east coast, we see we’re seeing the fingerprints of the warming Arctic in sea level rise, in emissions of of carbon and methane from permafrost melting regions. We’re seeing it in, in ecosystems. We’re seeing it in the biosphere there.

Well, you’ve written about the methane imperative and and the need for us to cut our methane emissions, you know, tell us why that’s so important, and what are we doing? And how can that be speeded up?

If, if, at all, right, I mean, so the, the dominant greenhouse gas that we’ve changed is, is carbon dioxide, but then the, the second most important one is methane. And methane has both direct effects. So, you know, it’s a greenhouse gas in all itself, but it also changes the chemistry of the atmosphere, and it produces bad ozone, right?

So ozone in the in the lower atmosphere, which is toxic. And you know, you don’t want any of that in the in the lower atmosphere. You want ozone in the stratosphere. That’s the way the ozone layer is. But this is, this is different. This is, this is much more of a greenhouse effect. And so methane changes affect both criteria pollutants, like like ozone and smog, but also they have a direct effect on on the climate as well.

And so if you add up how much temperature change the methane has caused over this period, it’s about half a degree Celsius, right?

So that’s about a third of the temperature changes that we’ve seen. It can be attributed to to methane. So if the methane levels that we have have more than doubled since the pre industrial right? So since the 19th century, it was around 700-800 parts per billion, and now it’s close to 2000 parts per billion, right?

So that’s a huge increase. It’s driven by a number of different things, so oil, gas, coal, infrastructure, mining, leaks, all of those things contribute quite a lot. Landfill is a big contributor, because you have, you know, kind of anaerobic stuff that’s happening in the in the landfills, and if that’s allowed to get into the atmosphere, then that adds to the to the methane in the atmosphere.

And then you have agriculture. So agricultural emissions of methane mostly due to large herbivores, particularly cows and sheep, which have a kind of fermentation that goes on in their stomach, that force that gets them produced to produce a lot of methane, mostly burps.

So, so cow burps and sheep burps are a big deal. And you think, wow, it’s just a cow, just a sheep. But it turns out that we have increased the amount of of biomass in cows and sheep by huge orders of magnitude compared to the pre industrial levels of ungulates and things like bison. We have far more sheep and cows than we ever had bison, for instance, that’s enough to shift the balance in methane in the atmosphere.

So so anything that you can do to reduce methane, by reducing leaks in fossil fuel infrastructure, by adjusting the diet of animals too, so they produce less methane, all of those things by capping landfills and using the methane that’s. Coming off landfills as biogas to power homes and industry. All of those things are very helpful to bringing down the level of methane.

And because methane doesn’t last in the atmosphere as long as carbon dioxide, it means that action now on methane can have an effect that’s much quicker than reducing carbon dioxide emissions. But obviously you have to do that as well. So these things are not should not be played off against each other, but they are both ways in which we can minimize climate changes in the future.

I’ve read recently about Nitro. I think it’s nitrous dioxide that has is even more powerful than than methane?

As far as a but it turns out that’s only increased by about 15% since the pre industrial so that is a that is a an issue, but it’s in terms of what its contribution has been to the global warming so far, it’s much more.

Okay, well, one of the things that you know I’ve read about you is that you were involved in the attribution science, or, you know, the science of attribution, And I think that’s going to become a big thing in the coming years, because as a trial lawyer, I’m thinking damages, I’m thinking causation, I’m thinking that polluters are going to be called to account in courts of law eventually.

Yes, yes. There was a very interesting workshop at Columbia that we’re right close to that looked at in quite some detail. So this was, this was effectively lawyer led right and and these folks who’ve been involved in ongoing lawsuits, some not successful, some successful, and some still, still in play related to to exactly that issue, to what extent can you demonstrate that actions of polluters causing recognizable harm, and finding people with standing to make those make those claims.

And there’s a lot, there’s, I mean, there’s a there’s a lot of very deep legal thinking that’s going into this. And they are kind of working, I guess it’s a kind of a CO production working with a lot of climate scientists to be able to make that the causal links that that are required in in such a lawsuit.

And there’s, there’s, there’s been some, some very interesting work recently, one, one thing that’s, one thing that’s, that’s kind of interesting is work that that is being done to to attribute climate changes not to the kinds of things that we have traditionally done, which is like, you know, attribute it to carbon dioxide, to aerosols, to methane, to land use change, but to companies, and particularly the scope three emissions of the large fossil fuel companies.

And if you start to say, Okay, well, how much carbon dioxide has been put into the atmosphere because of the actions of Saudi Aramco, Chevron, BP, ExxonMobil, and then you say, Okay, well, that’s your contribution to the carbon dioxide changes. Here are the climate damages that are associated with those things. And then here’s the link between. Here’s that causal chain between your scope, three emissions, the changes in the climate, the damages, and here’s the person that’s been damaged.

And like kind of tying all of those different steps together with as as thorough science as you can, as you can do. It’s getting very close to being able to say, Company X you are responsible for, why?

Trillion dollars of damage, of which you know, some portion of it is this person here, who’s who’s suing you. You have to pay your your share, and it’s a very impressive development of that kind of legal edifice that I think is, yeah, that’s not going away.

Yeah, I think that it’s certainly part of the piece of the puzzle. Because, quite frankly, why we’re in this situation is because fossil fuel companies and society at large had not valued the cost of pollution, and so this, this is essentially rectifying that by saying, hey, there was a cost to pollution.

You knew what the cost was. Exxon you studied it in the 80s. You knew that these effects were going to come. You had that your own. You know, you predicted it accurately. Your science was good. You knew the disaster was afoot, and you proceeded ahead, you know, without any regard for the consequences. Our society has for hundreds of years, said the person who does that is responsible for the damages, right?

So, I mean, the interesting thing is that, you know, you can still be responsible for damages, even if you did it inadvertently. There are other issues, I think, with legal efforts to hold the oil companies to account for the climate misinformation and disinformation they put into the system over the years.

But I think that’s somewhat separate to the attribution. Of their actions to real damages, because it doesn’t really matter why they did it or whether they were knowledgeable about it, they’re still responsible.

That is a very good point. I think I’m gonna put you on the legal team. Well, you know some of the work that you’ve done regarding ocean warming, written about acidification and that the if the combination of that relation, causation from bottom, trolling of a the fishing industry. Tell us a little bit about your study on that front, the big picture on climate change and what’s causing, you know, the big changes.

You know, it’s pretty well and so, so we’re doing a lot of work, kind of, I mean, I would not marginal, but we’re, you know, we’re doing work on the on the smaller terms, we know where most of the carbon dioxide is coming from, and but we, like kind of, you know, as we, as the models become more complete, as we start to think about different things going on, we can get to the smaller terms.

And so one of the things that that we were looking at recently was the impact of bottom trawling, which is not great, even in its own context, right? You know, you’re looking at the continental shelf, you’re kind of like, you know, grabbing everything that is literally sitting on the bottom. You get a lot of bottom feeding fish, which is the point, but you also destroy a huge amount of habitat for things that you don’t really care about. So there’s a very large bycatch associated with that.

And you end up with, you know, you know, very, very large, effectively, biological deserts at the bottom of the ocean. But one of the aspects of that is that you’re also taking that sediment, and you’re taking it, and a lot of it is very, you know, it’s fish poop, right? That’s falling down, algae, plankton, you know, very high and very high in organic matter, and, you know, is settling down, and then it kind of decays on the bottom.

But you’re taking all that, you’re throwing it back up into the column, where it decays in the column, and then it adds back carbon dioxide into the ocean, and then that feeds back into the carbon dioxide the surface, and then that leads to outgassing. And so by doing a lot of bottom trawling, you’re actually, it’s a small source, but you’re adding, you know, more carbon dioxide into the atmosphere again.

So, you know, if you needed more reasons to think that water trawling was not a good thing to be doing, then, you know, this is like one extra little bit that says, oh, it’s also impacting the climate.

Yeah, it’s pretty tragic. The things that are going on in the ocean in terms of overfishing, and you know now they’re talking about mining, which sounds like a disaster in the making, one of the things that I’ve read a little bit about is the phytoplankton population and the risk to the phytoplankton based upon all the things that we’re doing. And maybe you can talk a little bit about those risk factors?

I’m not, I’m not really an expert on phytoplankton.

So outside of your scope, okay.

That’s a little bit, yeah, I I’m let me, let me not pontificate without too much foundation.

Yeah, well, tell us a little bit about what are the things that you are working on right now that you think are particularly, You know, valuable in this whole conversation?

Sure. I mean, I mean, talk about a couple of, a couple of things. One is, we know that the that the ice sheets are losing mass, right? We have, we have direct measurements of the gravity of of these ice sheets that say that the mass and the ice sheets is going down.

What? What does that mean? That means that the ice that was in the ice sheet is now in the ocean, and that’s a large enough amount of water to start affecting ocean circulation, to start affecting sea ice, to start affecting stratification currents. And so we’re working on a project to try and upgrade everybody’s estimates of those impacts so that we can capture that when we’re doing, you know, kind of our historical simulations for what has happened, and then do that better attribution, and then, you know, for our projections into the future, so that we can include, you know, the increases in melt from Greenland, for instance, perhaps impacting the North Atlantic.

So that’s, that’s like a kind of a process based thing that we’re doing, but you know, perhaps kind of more interesting to your to your listeners, is we’re working a lot with machine learning, and we’re we’re looking at machine learning to try and improve the climate models, to calibrate them better to the observations, because it turns out that with these models, you have A lot of parameters that you don’t really know what what number you should pick.

You know, you have some range but, but you don’t know what number to pick, and you don’t know how they interact all the other different numbers. And that’s a very, very large problem. It’s a very big data problem. You know, 10s to hundreds of degrees of freedom. That’s a massive phase space to be, to be looking for. And we’re using machine learning to kind of short circuit that and find the best calibrated models that we can in ways that we never would have been able to do manually, just by kind of like tweaking tweaking parameters to see what happens.

So that’s extremely useful, and that’s allowing us through a kind of a process of emulation of the model. Works to expand the number of models the uncertainty in the models like quantify the uncertainty in these models, and then make better predictions going forward again, using emulators to explore a much broader range of scenarios than we’ve been able to do so far.

So that’s essentially AI that you’re using to it’s not chat GBT or any of these large language models that that spend their time hallucinating.

You know, people email me, Oh, I loved your paper from 2017 on blah, blah, blah. And I’m going, I never wrote that paper, the kind of thing that I might have done, but I didn’t, and I and then you guys like, yes, thank you for your for your comment. Where did this reference come from? Oh, at Chatgpt. Tell me. What about it? It’s like, you know, yeah, anyway, so you don’t be using that for anything scientific, but the techniques of machine learning, in dealing with very, very large data sets, extracting out the patterns and then kind of encapsulating that in a very efficient way, those are, those are real gains, and and they allow us to do things that we were never really able to do before we had that technology.

So, so there are real, there are real gains to be made from machine learning applied to the climate problem. But it isn’t, but it isn’t, you know, asking chat GBT, what the temperature is going to be like in july 2025 or something.

That’s fascinating. Well, I really appreciate having you on the show. And in particular, you know, one of the things that popped out to me was your view on, you know, sustainability of looking back, if a culture looks back at us and says, Hey, you know what? What would they see?

And then also, if we want to be that culture that survives, we’re going to have to be sustainable. And I think that that’s kind of a good message to put out there. Hey, if we want to have that for ourselves and our future, you know, we have to go in that direction. Disaster is the other alternative. Really, there’s there’s two, and there’s that there’s no real choice, right?

You know, we talk about sustainability, right? But we don’t really talk about sustainability with a kind of cosmic time horizon and, and I think, I think we should, you know, and you know, going back to things that Carl Sagan or or Neil deGrasse Tyson have said, you know, you we’re just like one, they were all pale blue dots, like, kind of floating in the cosmos.

And, you know, our problems don’t really amount to a hill of beans compared to everything else that’s going on. But if we want to persist, we have to think in that very, very long term way, because that tells us how we will persist. It isn’t the way that we’re carrying on now, right?

The indigenous societies, I guess talked about seven generations out. I don’t know if we’re going to make it seven generations out, given our current thinking, but we certainly got to alter it further and further out, so we’re taking a longer view of what what the future looks like.

And I was kind of, I drive a hydrogen car, and Toyota has 100 year plan for rolling out hydrogen, and that’s kind of mind blowing in our in our corporate world, to think 100 years out, but that’s really short term thinking. That’s myopic. 100 years with myopic.

Yeah. I mean, one of the advantages of working for NASA is that it’s totally within scope to think about scales, the size of the galaxy, and time scales, the length of the life of the universe, but also at the same time, thinking about processes in clouds that happen on the micrometer, millisecond time scale, and all of those things from microseconds to millions, billions of years, kind of like within our scope, to think about, to explore and to learn from.

And I’ve been enormously lucky to have been in this position and and you know, hopefully we can continue to do that well.

Thank you again for your great work at NASA and so many other things that you’ve done, like the blog, real climate, we didn’t even talk about that, but everybody check that out and check out, what Dr Schmidt is doing at NASA.

Certainly we wish you well going forward with all the great work that you’re doing, because it does give hope for humanity that we do have organizations like this that are doing such great thinking and great work.

Thank you so much.

To learn more about our work at A Cliamte Change and how you can help us reach our goal planting 30,000 trees in the Amazon this year, visit aclimatechange.com. don’t forget to subscribe to our podcast on Apple, Spotify, YouTube or wherever you get your podcasts. If you like this episode, please share it with a friend. See you next time.