The Past and Future of Climate Models: Conversations with Warren Washington and Geeta Persad

This episode, part of our new season about the often unexpected stories behind climate data, features conversations with two scientists involved in the wide-ranging field of climate modeling, from its origins in the first half of the 20th century all the way to the latest developments and uses of these important tools.

WISCON, the annual feminist science fiction and fantasy conference:

More on Ramesh’s Mario analogy, via his Twitter feed.

For more information on our two guests, Dr. Warren Washington and Dr. Geeta Persad, please see the links below:

Dr. Washington’s website and his autobiography, Odyssey in Climate Modeling, Global Warming, and Advising Five Presidents.

Video Oral History with Dr. Warren Washington by Oregon State University

Dr. Geeta Persad’s website and the publication she mentioned on the different effects of emitting identical aerosols in different parts of the world:

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For a full transcript of this episode, please see below.

Jacquelyn Gill
Like a lot of you, I started a garden this year. It’s been fun, but the results are mixed. While I am an ecologist, I’m nowhere near as good at growing food as I am at reconstructing the lives of long-dead ice age trees. Right now, I’m trying to figure out why my peppers are stunted, and what to do with the powdery mildew trying to take down my squash. I’m kind of like an over-involved deity, fussing over my little world. I bring, or withhold, rain. I smite Japanese beetles and I praise the bees. But mostly, I brood. And that’s because there are so many things that I have to pay attention to in my little domain! Soil, water, disease, pests, sunlight, nutrients. And I’m only responsible for 72 square feet. Part of my problem is that back when there was still snow on the ground, I spent a lot of time mapping out my beds and thinking about what I wanted to grow and researching companion planting, but not enough time thinking about how to make each of my little plants happy once the seeds sprouted.

It reminds me of when I was on a panel about world-building at WisCon, which is this fantastic feminist science fiction convention in Madison, WI. There were a lot of writers in the audience, and afterwards, one of them came up to me and she thanked me for helping her appreciate the complexities of a planet’s climate and ecosystems. She told me she’d been spending so much time figuring out how to power a generation ship that it hadn’t occurred to her that the colonists would need to survive when they arrived. (Elon, I hope you’re taking notes!).

It really stuck with me, though. Because whether you’re in charge of a raised bed or an entire planet, the Earth is pretty dang complex. It’s dynamic, with deeply interconnected components — oceans, the atmosphere, ice, our position relative to the sun, the kinds of plants that grow on land, even cow farts — all of it’s connected, and it’s constantly changing.

So the fact that we can put all of this complexity into a computer model and accurately capture what’s happening with the Earth’s climate? I think that’s one of the marvels of the modern world. And models don’t just help us understand how the world works now. A model basically allows us to run the experiments that just aren’t possible at the scale of the entire planet. They basically convert our understanding of the physics behind how Earth operates, into math: how the atmosphere transfers energy between different parts of the globe, how clouds reflect and absorb energy, or why some parts of the planet are rainforests, and others are deserts. Once you have these rules set up, you can start to play with them, and see what happens. Computers have come a really long way since the first climate models were developed in the 60s, but what’s remarkable is that even these early models did a really good job of capturing the complexities of our climate. A lot of things have changed since then — computers no longer take up entire rooms, for one. They’re not programmed with punch cards. But one thing hasn’t changed: they still take people to program them and make decisions about which experiments to run. Climate models are massive team efforts.

So for this episode, we’ll be talking to two different people who have spent their careers working with climate models: first, we’ll talk to a scientist who broke ground — both as the second African American ever to get a PhD in atmospheric science, and who worked on one of the very first climate models. Then, we’ll be talking to a woman who’s working on cutting-edge questions about how aerosols affect climate in different parts of the world. We wanted to give you a sense of what it’s like to work with these big, complex, and fun tools — tools that not only help us understand what’s happening to our planet, but that can also help us to imagine what our future could look like.

Ramesh Laungani
Welcome to Warm Regards, I’m Ramesh Laungani, a plant ecologist from Doane University in Nebraska.

Gill
I’m Jacquelyn Gill, an ice age ecologist and associate professor at the University of Maine.

Laungani
For the first part of this episode we spoke with Dr. Warren Washington to learn about how early climate models were built, and to understand what it was like to be one of the first African-American scientists doing this type of research. Dr. Washington is a distinguished scholar at the National Center for Atmospheric Research. Dr. Washington’s career as a researcher has spanned more than 50 years and he has had presidential appointments under the Carter, Reagan, Clinton, and Bush administrations. In 2010, he was awarded the National Medal of Science by President Obama, the nation’s highest science award. We spoke to Dr. Washington by phone and so there might be some portions of the conversation that are harder to understand. If so, check out the transcript of the interview that is linked in the show notes.

Gill
Well, thank you so much for taking the time to talk with us. I’m really excited to hear from you. As one of the first climate modelers out there, you started this work before there was really even a field called climate modeling. I’d love to hear about your personal pathway to science and how did you end up working in this field?

Dr. Warren Washington
Well, I started just by accident to actually get into this area. I was a physics major at Oregon State University. And at that time, meteorology courses were taught as part of the physics program. And my thesis advisor was contacted by people at Stanford Research Institute in 1959. And they were looking for a student who could work on a project of building a computer model of the atmosphere. So I thought it was an interesting topic, so I accepted and spent the summer at Stanford Research Institute. And at the end of the summer, I asked the more senior people, where could I go to get a PhD in this field? And they listed about five colleges that were starting to get programs started. And the most attractive one for me was at Penn State where there was a professor by the name of Hans Panofsky, who actually his father, was a good friend of Albert Einstein. That’s another story. And so I went to Penn State and finished up in 1963 and NCAR the place where I was routinely starting to do work, was looking for someone like me who had some experience in this area. And I was hired in 1963.

Laungani
So Dr. Washington, I’m curious to know what did those first climate models look like? You know, what were the computers like then? What were the technological limits for the types of questions you could ask what those early first climate models?

Washington
Well, let me go back to something like 1904, when a Norwegian scientist came up with the idea of solving the equations that essentially govern the climate and the weather. He actually spelled out how to go about this. And nobody actually tried to solve these mathematical equations because there just aren’t any simple sort of solutions to them. You have to use kind of brute force computational methods. And then a researcher by the name of Lewis Richardson of England actually wrote down the equations in some great detail. And as a person who didn’t want to take part in World War I, but he wanted to help out by being an ambulance driver. In between the battles he actually tried to solve these mathematical equations on a hand calculator, which was a major challenge. It turned out that his forecast was in error, because of the input data that he put into the model. But he didn’t sort of scare off anyone trying to solve these mathematical equations until the first electronic computer was made available in 1949. And the scientists knew that they needed to have a computer that was capable of doing many calculations all at once. A small group was put together by a famous mathematician by the name of Neumann, and he actually led the team to solve the mathematical equations and make the first simulation of the climate and the forecast. And it turned out that first forecast was pretty good in terms of a 24 hour forecast. And that gave a boost to improving on the model and actually solving on the equations and in various ways. So,, I think I got into this field fairly early. I wasn’t actually the first person who did this type of calculation, but I was part of a very small group at the National Center for Atmospheric Research in Boulder, Colorado.

Laungani
So with those models that you are working on, it seems like clearly there’s a long history here. But with those models that you were working on, what was the goal of those first models and, and how did those goals change over time when you were there?

Washington
Okay. Well, I think that the first goal was to actually build a model that was able to reproduce the climate of the earth. And so there was a lot of experimenting on various different ways of carrying out the calculations. So I think that was really only three groups that were formed at the time that we joined. And most of them of the first few groups were very small and efforts involving three or four people at each of the groups.

Gill
It sounds like those early models weren’t designed necessarily to test hypotheses about human global warming, but rather just to see if we could understand the atmosphere using, you know, the basic principles of physics. Do you have any personal memories of those early days working on that first model where maybe you just sort of had like a light bulb moment or was it a longer slower process?

Washington
Our early use of the models to examine climate change were fairly simple, in the sense that we didn’t have good estimates of how the carbon dioxide, for example, increase is going to be. So we did kind of a first order approximations, for example, we would immediately double carbon dioxide or gradually do experiments where we gradually increased the carbon dioxide. And that allowed us to kind of get some idea of the effect of increased carbon dioxide on the climate in terms of very, complex changes of precipitation, winds, features like the Indian monsoon, or changes in the ocean temperature and so forth. And at the same time, we kept repeating these various experiments until we got very good data on how how carbon dioxide for example was changing. And we put that into our models and had a more realistic simulation of future climates.

Gill
And what did it feel like to work on these first models? Did you ever have a moment where the model results, you looked at them and you just felt this tremendous sense of accomplishment? Did you have a sense of how important it was at the time? Any sort of personal memories or stories of exciting moments or frustrating or disappointing moments?

Washington
Well, I think that it was mostly good news in those early days. We would put together our model and we would, you know, simulate the weather and the temperature and wind structure, and we would then do a comparison with observation. And we were very pleased to sort of see that the wind structures were right for the right season. And what was emerging for us was the fact that the simulations did a lot of things right. And we were very pleased about that. If I can just sort of back up with this a little bit now. On the first computer that we ran on was so slow that for us to calculate one day of the climate took one day of computer time. So it was kind of disappointing. It took us quite a while to get it say a month or a year, but as the computers became faster and became faster, but fairly quickly that the computers would speed up such that we every two years or so we’d have a new computer, and it would be twice as fast as the previous one. And so over time we got substantially faster than teachers that were able to solve the equations, even though, as the model got more and more complicated and more features were added, for example, we could put in, sea ice over the Arctic and the Antarctic areas. And we could put in some very much detail in terms of vegetation, in terms of the moisture that’s held in the soils. Or we could actually do aerosols in the atmosphere. And one of the big challenges was to get through the clouds roughly right. So all of these things came at the same time that we were doing experiments at the same time improving the models with added features.

Gill
I’d like to shift gears a little bit to talking about some of the policy and advocacy work that you’ve done, which is also very extensive over your career. You’ve advised different presidents on climate change from both sides of the aisle. What was it like navigating the different political priorities of different administrations in terms of science and climate change research?

Washington
I got a call starting with the science advisor for Jimmy Carter, I think in1977, to join an advisory panel called the Advisory Group on Oceans and Atmosphere. And this group actually looked at a lot of issues, including climate change. And then I was reappointed by Carter for another six years to serve the administration of Ronald Reagan. So there’s a tremendous change in between the Carter administration and the more conservative Ronald Reagan administration. But anyway, progress was made to sort out the problems and the policy issues. During the Clinton administration, I was appointed to the National Science Board, which is the governing board for the National Science Foundation. There were 24 members. and they elected me chairman of the board for four years. And I had the tough job of helping convince the Congress to increase on the budget for the National Science Foundation and to be active in dealing with science issues as part of the National Science Board. One of the things that took place while I was on one of these advisory committees was under President Bush, the first President Bush. He and his administration put together a new way of tackling this problem, having representation of all of the science agencies that were involved in dealing with climate issues and weather issues. And they actually came up with something called the US Global Change Research Program, which actually set up a very organized sort of governmental approach to climate change, and to answering questions that were still remaining about climate change. So I credit a Republican administration for putting all of this together. Even though President Trump feels that climate change is not a serious issue, but I can assure you that a lot of the career officers even in this present administration are wedded to keeping the research going. So I’ve had a good life contributing not only to the science but to science policy.

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Laungani
Dr. Washington, you were the second African American scientist to receive a PhD in Meteorology. What was that experience like? I ask because on certain levels it feels like a lot has changed, but we also see that there’s a lot of progress that still needs to be made particularly around diversity and inclusion in the sciences. So what was that like for being sort of a pioneer in this avenue as well in the field of meteorology?

Washington
Well I have kind of a long history even before I became a scientist. I grew up in Portland, Oregon. At that time, African Americans couldn’t stay in hotels and certain restaurants and so forth. And so I became the Vice President of the Youth Council for the NAACP when I was in high school, which is interesting. And then when I went to Oregon State, I was one out of 10 or so African-Americans at Oregon State.Most of the other ones were on the football team. And I can remember going to see the president with a group of students to complain to them about the segregation of sororities and fraternities that were associated with the university. So coming to Boulder was pretty much the same, there wasn’t very few African Americans and Hispanics. And I took part in various civic action activities, um, following my earlier examples of dealing with being African American. Remarkably enough, and I can sort of feel that in the science community, I felt quite accepted. I’m sure there were some people that objected to me being a scientist or something of that sort, but I didn’t feel that there were major impediments to me to be a successful climate researcher or scientist. I think over the years, I felt quite well accepted. I suppose the people that were overly concerned about African Americans being in certain fields and so forth was a problem, I just sort of ignored those situations, and sort of did the best I could. Not only trying to do excellent science, but also do good to help the professions out.

Laungani
I know for me as a scientist, it was really impactful to see another South Asian ecologist, because it helped me sort of see a role model.Have you interacted with other students who are interested in getting into this field, or do you feel like you’ve played that role as not just a mentor, but a role model for those students? And if so, what advice have you given them around sort of overcoming potential systemic barriers in science or meteorology or climatology?

Washington
Well, I talk about diversity, you know, in the broadest sense. And I think that all the groups all the way from Native Americans to Latinos, African Americans, Asian Americans, and so forth, have made contributions and the future is bright for all of these various groups to make or to actually carry out research and do do interesting things that will improve our knowledge about how the world works as well as how things like climate work. I think I was the first African American to get the National Medal of Science award in my field. I was the second African American, and I’m really pleased to see during the Obama administration that he’s appointed, other minority groups to the National Science and Technology awards. Now it turns out that probably most of my students that I’ve mentored over the years have been Caucasians, but, but I tried to set up programs and I set up scholarships at three different colleges. But I’ve also given awards to a lot of different people who excelled in their fields. I think it’s important to say that all of these new fields that are opening up are really providing careers for scientists who could make contributions, and they have. I listened to a lecture yesterday of Marshall Shepherd was one of the people that you had interviewed during the podcast. He was one of the students who I mentored, even though he wasn’t exactly in my field, he did interact with me over the years and I encouraged him to do his research and he’s gotten to be very popular and very accomplished.

Gill
So I often speak with a lot of students and other young people, young activists and climate advocates, and many of them often feel, you know, frustrated or depressed about the current political reality when it comes to climate change. Since you’ve had this experience of really working and advocating for climate policy, basically since we first really started to understand that the world was warming because of us, what advice do you have for the current generation? Do you, they often feel like we’ve taken two steps forward only to take five steps backwards. How would you advise them to stay motivated?

Washington
Well, that’s, that’s a good question. In fact, this afternoon I’ll be mentoring some students, and I think that they are still idealistically feeling that they’re getting into an exciting field. I try to tell them that the science really is probably going to keep ongoing and that this is an area of research, which is going to have a bigger and bigger effect as has our problems with climate change arise and become major factors if we don’t start, you know, doing things to solve the problem. And even though they have some feeling of disappointment in general about the present administration, that they feel that there is opportunity to do research and that the number of people that come into the field has increased substantially because of their concern about climate change and the way they wanted to do something positive to solve the problems.

Gill
Well, thank you so much for your time with us today. I learned a lot and it was a pleasure talking to you. Before we close, is there anything else that you would like us to know about you or your work? Or something maybe we didn’t get a chance to ask you about that you would like our listeners to know?

Washington
And, um, I, uh, I feel very pleased with how my life was turned out. I’m at 84 years old in August. can still make contributions especially in the area of mentoring and giving lectures and so forth. And it’s just sort of sad to sort of see in the news that science is being attacked by certain individuals in ways that are really harmful for our nation and for the world. Um, but efforts like yours of getting out the words using podcasts are just one of the ways in which people can make contributions. And I think that we need to keep these efforts going.

Laungani
Well, Dr., Washington let me reiterate, thank you again so much for taking the time to talk with us. Um, I was sitting here listening to your stories and to your experience and my, my jaw was just hitting the floor. So thank you again for taking the time today.

Washington
Well, thank you very much. And I’m really impressed with the fact that these podcasts help to get the word out and hopefully will help to educate people well with all different types of backgrounds.

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Justin Schell
This is Justin Schell, the producer for Warm Regards. As we explore the often unexpected stories behind climate data this season, we’re also collecting data stories from you, our listeners. Here’s this week’s story.

Thelma Young-Lutunatabua
My name is Thelma Young-Lutunatabua and I’m the Associate Director of Social Media at 350.org. And when I saw your post about climate data and climate graphs, I immediately had so many stories come in to my head. With my day job, I basically wake up in the morning and think what’s the story of climate change today and how can we use digital channels to tell that. For me personally, there’s definitely so many moments where a graph has just shaken my heart. And I do have a pretty thick skin when it comes to horrific climate news. It’s just something I’ve had to build up over the years. But I remember recently there was a graph around the decrease in Arctic sea ice this year in comparison with other years. And I saw that and my heart just sank, because for me, when I see that, I think about the ramifications around the world. I live here in Fiji, and so where, you know, discussions on sea level rise is an urgent and ongoing question. And so I remember after seeing that graph, just having more awareness in my mind about what sea level rise might look like. So whenever I’m walking on the beach or driving along the coast, I think, okay, what, what will this look like, you know, if the waters rise three feet. And so sometimes things like that, they just really stick with me and really help me unfortunately understand the full dynamics and the weight of what we’re dealing with.

Schell
We’d love to share your data story on Warm Regards. You can leave us a 90 second voicemail by calling 586–930–5286 or record yourself and email it to us at ourwarmregards@gmail.com. Make sure to say who you are and where you’re from.

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Laungani
To get a sense of the state of climate models today and what its like working with them, we spoke with Dr. Geeta Persad. Dr. Persad is a climate scientist at the University of Texas at Austin. She thinks of climate models as a digital encapsulation of everything we understand about how the climate system works.

I often explain to my students how climate models have improved through time by comparing them to Mario from the Mario Brothers video game series. When Nintendo first came out, Mario was really blocky and only was able to move from side to side, but through time the graphics got better, Mario became more detailed, and he gained all sorts of new skills & abilities, and now you can practically count the hairs on his mustache. Just like Mario, the climate models have gotten more skillful & more fine scaled over time. When we spoke with her we asked her what she thought about this analogy.

Dr. Geeta Persad
It’s actually a fairly good analogy. Climate models have improved over time for a bunch of different reasons. One of them is that we keep learning more and more about how the climate system actually works and as we start understanding new processes, we’ve started putting those processes into the models one by one. And then the second thing is that the computer systems that we use to run these climate models have also gotten much better over time. They’ve gotten faster, it’s gotten cheaper to run more complex models. And so we’ve also improved in our ability to do some of the mathematical calculations or being able to do things at higher resolution that wasn’t possible on the old computer systems is now possible on the newer computer system because they can run so much faster.

Gill
These models are massive team efforts. Where do you fit into the broader climate puzzle?

Persad
So my particular expertise is in understanding, first of all, atmospheric physics broadly, so how the atmosphere transfers energy between different regions of the planet, how it forms clouds, how it forms precipitation, how it interacts with the land surface and the ocean surface. And then within that I specialize in understanding how particle air pollution, so things like soot or sulfur dioxide that comes out of volcanoes or out of smokestacks, how those influence some of those transfers of energy and processes in the atmosphere. So that’s my particular niche, but over my career I’ve worked with people who think about the eddies in the ocean and how those impact how energy is transmitted from the tropics to the poles. And I’ve worked with people who try to understand how irrigation affects moisture transfer from the land to the atmosphere. So one of the things that I really enjoy about working in climate models is that you’re encouraged to interact with people who have expertise in all of these different aspects of the climate system that you might not have expertise in, so that you can make sure that you’re thinking about that full picture when you’re doing research.

Laungani
We don’t have the luxury of waiting a century to see how accurate model projections made today will be, so how do we know if a climate model is accurate and is realistic?

Persad
The companion of having really strong, robust models is having really strong, robust observations of the climate system also. We use those observations of the climate system to tell us about the range of conditions that we tend to see in the atmosphere or on the ocean or on land. And then we use that to help us design the way that we put those processes into the models, in addition to our sort of fundamental understanding about the physics.

Gill
So you have these incredibly complex tools, and you’re trying to model an even more complex climate system. For folks who may be unfamiliar with this process, how do you go about validating that model works well enough that you can confidently project what could happen in the future?

Persad
So when the models actually spit out some simulation of what the climate system looks like, we can do things like hindcasts, where we basically simulate the past, which we already have observations of in the climate model. And then compare what that looks like to the observations that we have of those periods for those regions or for those processes that we might care about. And so that’s another way that we validate that these models are actually doing what we think that they should be doing. So at this point, climate models have been around for long enough that we have papers that were published in the 1980s and 1990s that projected what the trajectory of, for example, climate change would look like over the next 20 to 30 years. And now we’ve actually run that natural experiment and we can compare what actually happened with what those models predicted. And they were spot on on a lot of the things that really mattered.

Laungani
So though we understand things like the basic physics of the atmosphere, what are some of the data that goes into a climate model that we are less certain about?

Persad
In order to project what’s going to happen a hundred years into the future, you have to be thinking about and telling the model something about all of the inputs that might influence temperatures a hundred years into the future. So that includes things like what humans are going to emit into the climate system over the next hundred years, which is obviously something that we don’t actually have a crystal ball on. So there’s a huge enterprise that actually has been running alongside the development and improvement of the physics of the climate models, which is these sort of socio-economic models that try to build plausible scenarios for the choices that humans might make going into the future. And the way that those two communities have interacted is that generally because we don’t have a crystal ball about what humans are going to put into the atmosphere, the folks who are working on the socioeconomic models try to come up with a sort of suite of potential futures that all seem plausible under our current understanding of how humans make choices and the type of technologies that are going to be available to us. And then that suite of potential futures all gets fed into the climate models. And so we have a bunch of different trajectories of what could happen over the next hundred years. But the reality is there are a lot of things that we can’t know. You know, I think there’s a really valid question of whether, for example, we would have predicted the development of fracking as a technology 20 years ago and had known what that would’ve done to carbon dioxide emissions or to coal use, for example. So that’s why we do a bunch of scenarios and try to treat that as some range of what might happen, with the recognition that there might be things outside of that range that we’re not going to be able to predict.

Gill
It sounds like one of the biggest sources of uncertainty in climate models is not that we don’t understand basic physics, but that people are just as complex as the earth system. What a lot of folks may not realize is that models allow us to ask really interesting questions about what might happen in the future, depending on the particular choices that we make as humans.

Persad
So you’ve given me the perfect intro into a paper that we just put out last year that attested essentially that. You can test these hypothetical questions in climate models to ask that question of if you emit a chunk of soot or sulfur dioxide in China versus say in the US, how different is the climate impact? And you actually see pretty big differences in the climate impact on the order of three to five times more climate impacts from emitting the same thing in one place versus another. We could have very different trajectories of who’s emitting these different pollutants that could change at least some aspects, likely not all, but some aspects of how the climate system responds to those emissions as well.

Laungani
That’s super interesting and it seems like you’re getting a finer and finer scaled picture of what’s driving our climate So what do you think is next for climate modeling?

Persad
One of the big frontiers is trying to understand how we can make climate models more useful for the types of applications that they’re increasingly being used for outside of the climate science community. As these climate models have gotten better, as the data has gotten more accessible over time, there’s been a huge growth of local governments and corporations who want to be able to use that data to make plans for where they’re going to put investments and how they’re going to build infrastructure and so on. But if you think about the history of how those climate models were developed, those were originally developed by someone who just wanted to understand how does the climate system work and what happens to the top of atmosphere temperature, when I put a chunk of CO2 in, which is a really different question, then how high should I build my bridge? So I think one of the big frontiers for climate modeling is trying to figure out, okay, are there ways that we can use climate models to ask some of these more applied questions more effectively?

Gill
This feels like a really exciting development to me — especially thinking about the long arc of climate models as a tool — how we started off just trying to understand how the world worked, before “anthropogenic climate change” was even a concern that was front and center in peoples’ minds. And now you’re talking about how to provide super specific forecasts for, say, Maine’s blueberry growers, or the ski industry in Colorado. So how do models need to adapt to meet these new needs?

Persad
We know, for example, that climate models are probably not that great at projecting, for example, regional precipitation. And that’s something that a lot of planners really care about. But we know that there are limitations in climate models but are there ways of asking the question a little bit differently in a climate model? Are there ways that we could be investing more in validating or improving certain processes in those models to make them more beneficial for those particular uses? I think that’s a big conversation that needs to happen. There’s also the potential for sort of diversification in what we try to optimize climate models for. Might we want to invest in some types of models that are more designed for answering these theoretical questions, whereas maybe we focus other models on being able to answer these more applied questions, which might require a different optimization. So that’s a big conversation happening in the community as well.

Laungani
So if climate models are so useful, why are they so often misunderstood or even dismissed entirely?

Persad
One straw man argument that I hear used a lot is that because climate models get one specific thing that the person constructing the straw man argument has cherry picked wrong, because the models get that one thing wrong, they therefore are wrong about all of the other things that matter? I mean on the first hand it’s just a logical fallacy. We know what the limitations are and what the problems are. Aanytime someone is saying something based on model evidence, they are saying it with a full understanding of what the model is doing well and what it’s doing not well. And so cherry picking one thing that’s wrong with a model does not invalidate all of the things that climate models can be really beneficial for understanding.

Gill

So it sounds like what you’re saying is that even though this is an imperfect tool, it’s still a really powerful one?

Persad
Even with all of the uncertainty that we know exists in what climate models are telling us about the future and the reality that there are some things that they’re not going to be able to predict with certainty, they are still giving us really valuable information. And we know from all of the hindcasting that we’ve done and all of the ways that those models have been borne out as having been right over the last several decades that these models are telling us really important information that we can be using to make better decisions that are going to reduce harms for people.

Laungani
In your opinion, what do you think is a really powerful aspect of the ability of climate models to make projections about the future?

Persad
I am a huge fan of science fiction and fantasy and so I love the idea of imagining these alternative worlds where we had made different choices or these sort of what if questions and climate models are an amazing tool for getting to ask all of those questions. So I am down for any research track that lets me ask things like what if we followed a Mad Max future or what if we were in Blade Runner, what would the climate system look like? When I imagine what the world could look like in a hundred years, it would be a world where we have slowed down climate change enough that we can start adapting to it. That we have time as humans, as all of the other species on the planet, to change our behaviors and adapt as we need to, to survive and thrive in that new future. Because I think one of the things that is particularly troubling about the trajectory we’re on right now is just how quickly the world is going to change in ways that we’re not going to be able to adapt to. Rather than imagining some utopian future where we go back to a climate system of the past, I prefer to imagine that, okay, chances are humans are going to keep making decisions that have some impact on the climate system. But ultimately what we have to do is figure out ways to slow down those impacts as much as possible so that we can manage them and understand them as they are happening and make sure that we are making the right trade offs when we make those choices.

Gill
I think this is really cool, because it sounds like you’re saying that climate models can also be a source of hope. They help to remind us that it’s our choices that will shape the climate of the future — and that future doesn’t have to be a dystopia.

Persad
Blade Runner and Mad Max are obviously not the only two examples. I think I really appreciate that climate models let us envision different ways that the future could evolve and test out what that means for human impacts, for prosperity, for species that we care about. And that gives us the opportunity to start making decisions now that are going to put us on which of those future paths we think align with our values. And I think that is a huge boon that we get from these tools that we would not even be able to start thinking about otherwise.

[music]

Laungani
Warm Regards is produced by Justin Schell. Joe Stormer creates our transcripts, and Katherine Peinhardt is our social media maven. Music for this episode comes from Blue Dot Sessions. You can find a transcript of this episode, listen to previous episodes, and find links to subscribe on the podcast platform of your choice on our brand new website, WarmRegardsPodcast.com. Also, something that really helps more people learn about the show is if you leave a quick review or rating, especially on Apple Podcasts. We’d love to hear what you think about our new season! You can reach us at ourwarmregards@gmail.com our find us on Twitter at @ourwarmregards.

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