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Not Cool Ep 10: Stephanie Herring on extreme weather events and climate change attribution

Published
1 October, 2019

One of the most obvious markers of climate change has been the increasing frequency and intensity of extreme weather events in recent years. On the tenth episode of Not Cool, Ariel takes a closer look at the research linking climate change and extreme events — and, in turn, linking extreme events and socioeconomic patterns. She’s joined by Stephanie Herring, a climate scientist at the National Oceanic and Atmospheric Administration whose work on extreme event attribution has landed her on Foreign Policy magazine’s list of Top 100 Global Thinkers. Stephanie discusses the changes she’s witnessed in the field of attribution research, the concerning trends that have begun to emerge, the importance of data in the decision-making process, and more.

Topics discussed include:

  • Extreme events & how they're defined
  • Attribution research
  • Risk management
  • Selection bias in climate research
  • Insurance analysis
  • Compound events and impacts
  • Knowns and unknowns

References discussed include:

We've seen more people start to ask the question, "Is there a linkage between that impact of climate change and some kind of socioeconomic factor?" — building this bridge between the pure climate change science component and actually connecting that to, "Why does it matter to the world? Why does it matter to people and humans and our societies?"

~ Stephanie Herring

Transcript

Ariel Conn: Hello, and welcome back to Not Cool, a climate podcast. I’m your host, Ariel Conn. Today, we’re starting something of a two-parter about the extreme events that we’re already starting to see as a result of climate change. We’ll talk today with Stephanie Herring, a scientist with NOAA, looking at extreme events a little more broadly, and then on Thursday, we’ll hear about compound extreme events from Jakob Zcheischler who’s at the University of Bern in Switzerland. I say this is something of a two-parter because both Stephanie and Jakob both go beyond just extreme events. Today, Stephanie will also talk about risk management, insurance analysis, selection bias in climate research and much more, all related to climate change, of course.

Stephanie is a scientist and senior advisor with National Oceanic and Atmospheric Administration’s (NOAA) Center for Weather and Climate in Boulder, Colorado, where she specializes in extreme weather and weather-related events and climate services. She is the lead editor of the annual Bulletin of the American Meteorological Society report, Explaining Extreme Events from a Climate Perspective, which is aimed at understanding the physical drivers behind extremes and how risk exposure to extremes events is changing over time.

Stephanie, thank you so much for joining.

Stephanie Herring: Thanks for having me.

Ariel Conn: The first question that I have for you before we get into your work is just: what is climate change? We hear a lot of terms thrown around: We hear climate change, global warming, ocean acidification. We know there's problems related to plastics that are somehow connected to climate change but separate. So I was wondering if you could just real briefly explain what these different things are and how they're connected.

Stephanie Herring: Sure. So global warming refers specifically to the fact that because human-caused activities can release greenhouse gases into the atmosphere, it has caused a long-term warming trend across the planet. And that long-term warming trend is what we call global warming.

Climate change is the consequences of that long-term global warming, and it has other impacts on the climate system. And that is what we refer to as anthropogenic climate change. So it's beyond just the warming factor, but also changes in ocean temperature have been caused by that; Some of the work that I look at, changes in extreme events, and those would also be changes that would be a consequence of climate change.

Ariel Conn: Okay. So let's go ahead and switch to the work that you do. How do you define an extreme event?

Stephanie Herring: That's actually a very interesting question because there is no one definitive definition of an extreme event. If you ask the National Weather Service or the World Meteorological Organization — you know, these societies that think about these things — there's no one definition. So there's a meteorological extreme, which generally gets set to the extreme extremes, or the top one to three percent of what we would see in terms of being extreme.

But some people also draw that line, say, at the top 10%. So for me personally, the way I tend to look at extreme events is that they can either be extreme from a meteorological or climatological perspective, as in it was an extreme physical phenomenon, but also because of extreme impacts. And so even certainly within NOAA, I think we've cast that definition more broadly to not just be a meteorological extreme but potentially also having an extreme socioeconomic impact as well.

Ariel Conn: That's really connected I think to the next question I have: that is, exactly how extreme does something have to be to be considered extreme? For example, the Midwest had a lot of rain this last spring, but it might not have been one specific event that dumped a lot of rain — it was over an extended period of time.

Stephanie Herring: Yeah, so any event has to be defined in some way by space and time, and you could have an extreme event be an extreme annual global average temperature. So you're looking across the planet; You're looking at the temperatures across the planet over the course of a whole year and finding the warmest year on record. That could be considered an extreme event.

Alternatively, it could be the amount of precipitation that fell within one hour over Houston during a hurricane. And so I think that when you use the term “event,” one of the things that we do in our field is we require people to be very specific about defining that event. What region are you talking about, and what's the time period that you're talking about? And if you don't have those two things, then you don't have an event definition. And people actually spend a lot of time thinking about what is the definition of their event that they are looking at from a research perspective?

Ariel Conn: So hurricanes seem like obvious extreme events if they're severe enough. If you have a five-year drought, could that be considered an event?

Stephanie Herring: Yes.

Ariel Conn: Okay. So something else that I wanted to clear up before I start asking a little bit more details about your work: in some of the papers, I read about ocean heat events and terrestrial events and atmospheric events, and I was wondering if you could explain what the differences are between those — or how it's connected.

Stephanie Herring: So again, this really goes back to the definition of the event you're looking at. So not only is it in time and place, but what exactly are the physical phenomenon that you're looking at? Is it temperature, and if so, are we talking about a temperature in the air over a city, or the temperature of an ocean and looking at sea surface temperature? So needing to very clearly define an event before you can then go forward and make a statement about what happened is incredibly important, and we do actually spend a lot of time thinking about that. 

Because it'll be interesting: two people will come forward and say, "Oh, I looked at precipitation from Hurricane Harvey." And you'll see three different papers come out that looked at precipitation of Hurricane Harvey. And that's the title of their papers. If you look at how they define the event, they all use slightly different time periods, so what day to what day; slightly different geographic regions, so someone might've looked at the whole region of the Gulf; somebody might've looked at just the region where it stalled. Both of those are legitimate papers about Hurricane Harvey, but they define the event from their research perspective in a very different way.

Ariel Conn: Does that make your job more complicated? How do you deal with that?

Stephanie Herring: It can make it more complicated in the sense that when you're trying to compare two different results from two different papers that maybe seemingly looked at the same event, you need to actually make sure they did look at the same event, not just the name and what appeared in a headline, but from a scientific perspective, were they looking at the same thing? Were they actually asking the same questions?

It's actually really helpful if multiple groups who are independent look at the same event and then we can see how their answers may differ or be the same. And if they don't actually define the event the same way, they're not technically looking at the same event. It can make things a little bit tricky, but it also makes it, I think, more interesting because then you can really see where different methodological approaches have different benefits in terms of the information that they're able to provide.

Ariel Conn: More specifically to some of your work, you've been working on papers titled Explaining Extreme Events from a certain year from a Climate Perspective for a few years now. How long have you been doing that?

Stephanie Herring: Since 2011. BAMS Explaining Extremes 2011 was our first report.

Ariel Conn: Okay. What have you seen change over the years?

Stephanie Herring: I would say a couple things. One, potentially less interesting for the broader community but interesting to me, has been really the explosion in the number of people who have been able to engage in attribution work. And I think this is actually true across a lot of climate fields that rely a lot on modeling, is that the computational power, just the technology and the ability to run climate models and have access to all this different data information has really expanded. And so there's been an incredible leveling of the playing field within the research community as to just who can and can't do this work.

It used to be a much smaller group because you needed to be at a facility that had high-performance computing power, could run models, or had access to model data. And now you can be almost anywhere and do a lot of this research. And so previously, when we first started this, a lot of the research was simply coming out of either North America, Europe, Asia, Australia; And I've seen an increase in the number of papers coming from other nations, which I think is exciting, because there's a lot of selection bias in terms of which events get researched or not.

The selection bias previously was scientists actually are people and tend to be interested in events that they may have had personal experience with, or maybe their country had personal experience with. So most people, for example, who looked at the recent European heat wave came from European labs. Not surprising. So it's nice to see, as we see more researchers from different parts of the world getting into this field, we're seeing more papers about events from different parts of the world, which personally is exciting.

The other piece of it is that we've seen more people start to ask the question not only of, "Can I do an attribution event analysis? Can I understand whether climate change played a role in this specific event," but, "Is there a linkage between that impact of climate change and some kind of socioeconomic factor," building this bridge between the pure climate change science component and actually connecting that to, "Why does it matter to the world? Why does it matter to people and humans and our societies?"

And so that field is loosely being called impact attribution, and we're seeing more and more papers along those lines. And early on, there weren't that many. So I think that's also exciting to see how people are trying to connect climate change research to real-world issues and challenges people are facing. And the other piece I think that was just a couple of years ago was that basically the way climate change attribution science works is that, in general, the basic methodology is that you look at a world in a model where climate change has not occurred, so it's a control planet.

We can't replicate that without having a model, and we compare that to the world that we actually live in. And we can actually test, and we know what that world looks like because we have observations and we take records of our environment now. And so we can look at the two models and understand, "Okay, what was the risk of that event occurring in a world without climate change, and what's the risk of that event occurring in a world with climate change?"

And the statistical approach is actually taken from the public health community. So an example that might make more intuitive sense is, say you're looking at the risk of smoking and lung cancer. So you can take a group of people who haven't smoked and a group of people who smoke and assess, "What's the different risk of any individual in those two groups getting lung cancer?"

When you take that same statistical approach, actually, and apply it to our climate models — there's obviously some nuance there, but in general, the principles apply. And what we're seeing now is that we are finding more events that we simply cannot replicate in a world where human-caused climate change hasn't happened. In particular, we're seeing this for heat events now, which is that we knew the risk of heat events was increasing, and I think within the climate change attribution community, we knew that someday we would cross this threshold. I personally thought that was going to happen much later than it did. I wasn't so much surprised at the result — we knew that was coming; I think we were a little surprised at how soon it showed up in the data.

Ariel Conn: So I'm a little bit torn because I wanted to follow up with this idea that we're seeing events that couldn't happen without climate change, but before I go there, I actually want to take a little bit of a step back and ask if you could explain what climate change attribution science is.

Stephanie Herring: Sure. Attribution is just the general process of trying to understand what the cause of something is. And in climate change attribution research, what we're trying to do is understand what the causes were of a particular event. The question we go in asking is, "Did anthropogenic climate change impact the intensity, frequency, or geographic distribution of this event, however it's defined?" There's actually a lot of different levels of climate change attribution. Specifically, the work that I'm part of is looking at that from the perspective of extreme events. Is climate change playing a role in changing the intensity, frequency, or geographic distribution of extreme events?

Ariel Conn: Okay. The other question that I had sort of lumped with this is, how is that then applied to risk management?

Stephanie Herring: So I'm not personally in the risk management space. That being said, I think that where I see it having applications is that one of the things we're trying to do is not come up with a binary answer of yes or no. That might be what you see in the paper, but that's not the point of the research.

The point of the research is actually to quantify that change in risk. So what we're trying to do is understand how much — not whether or not, not a yes or no — but how much can we quantify change in risk of a particular event type happening in a particular location? From that perspective, the other part of that is then again to look out into the future and say, "Okay, from pre-industrial climate to today, the risk has changed by X." And using the same processes, we can then look out into the future and understand, "Here's what we would expect in the future. This is the trend or the path that we're on. This is how we would expect the risk to change going forward."

And then I think that information would be used in the same way that lots of other weather and climate information is used, regardless of whether it's linked to climate change or not. NOAA provides weather and climate data to all different kinds of sectors to help them understand what the state of the climate is so that they can use that in planning all different types of decisions.

So the energy sector is one example where NCEI — the part of NOAA that I work for, the National Centers for Environmental Information — held a stakeholder engagement workshop with the energy sector. And one of the big questions they had was, "Hey, we have all this infrastructure, and it's sitting in a flood plain today. I need to rebuild it. I'd rather not rebuild it in a flood plain. Can you tell me where the flood plains are going to be, not only today — my infrastructure needs to last 50 to 70 years — so not only do I not want to build it in what's not a flood plain today, I want to build it somewhere that's not going to be a flood plain in 50 years. Where's that spot?"

Ariel Conn: So you were mentioning earlier that one of the things that's surprised you is that we're seeing more of these extreme events sooner than you were expecting?

Stephanie Herring: We're seeing a higher quantity of events that couldn't have happened without climate change; I would say that what we're also seeing over all these years is that the number of events that have some climate change signal to them seems to be increasing. I'll give the huge caveat that the number of reports that are out there, it's very difficult to do any kind of real statistical analysis because there's a huge selection bias, like I said. We're not randomly looking around the Earth and saying, "Okay, we're going to randomly select extreme events from around the planet and then look at them." Scientists pick which events are interesting to them and again, that generally selects for events that have happened in the developed world or have had a major socioeconomic impact. So, not random.

Ariel Conn: To me, it seems like every new report that's made that gets public attention seems to be getting worse and worse. And so if that's the case — and maybe it's not, but if that is the case — what sort of impact does that have on the suggestions that you then give to people who want to make sure they're not building in a flood plain?

Stephanie Herring: We provide the data and information, and I think that on the end of the decision maker, they are the ones who really decide ultimately how that data and information is going to get applied to their particular decision. I will back up one second though. When we talked about extreme events and whether there's an extreme event, for the purposes of those extreme events that are being influenced by climate change — back to the public health analogy: Extreme events is sort of like the meteorological equivalent of cancer.

There's a lot of different types of cancer out there, and different cancers mean different things and they're treated in different ways. Extreme events are actually the same way. So we kind of bundle them together, but an extreme heat event is not the same thing as an extreme tornado, for instance. And scientifically, our ability to attribute climate change to how the risk profiles may have changed is also not the same.

We are very good and we have very high confidence in looking at extreme heat events. We have almost no confidence in looking at tornado events because we do not understand how climate change is really going to change tornado dynamics in the future; We also don't have a very good observational record of tornadoes — and when I say good, I mean back, you know, 150 years. Really, the tornado record is robust, probably starting in the '70s and '80s, post-satellite, because before that, they would happen and maybe someone would write it down, but maybe not.

Tropical cyclones suffer from the same issue with the observational record, whereas with heat precept, we have excellent observational records that go back quite a long time. There's all kinds of paleoclimatological records; There's tree rings: We have very good information to understand how the global climate and global temperatures have changed over time. We don't have that for a lot of other event types, and so the more confidence we have in the observational record and the better understanding we have of how climate change is going to impact an extreme event type, the more confidence we can have when we do an attribution analysis.

Ariel Conn: So as someone who is not studying climate change, I find myself and a lot of the people that I hang out with, talk to, et cetera — anytime anything weird happens, we're like, "Oh, climate change." And I'm guessing that's probably not always the case.

Stephanie Herring: Here's the thing. It may be the case, or it may not. We don't know. I think it's not so much that, "Is climate change impacting tornadoes?" Maybe, but I don't have any evidence to show you that it is. So it's not that it's not; Just because scientists haven't found it doesn't mean it doesn't exist, right? But we don't have the body of knowledge and the body of research to be able to confidently back up that statement. So you and your friends at cocktail parties: you may be right, but I can't prove it.

Ariel Conn: Okay. Okay.

Stephanie Herring: I do think there's a distinction between the two, as to what we can confidently validate with our scientific methods and our research and our data and our models, and the fact that there may be impacts happening today, and we may not know about them until the future when our data and our models and our scientific methods and our toolkit gets more robust, and we're able to look at tornadoes. I think someday we will be able to. It's just not today.

Ariel Conn: So a personal one that I'm interested in: Colorado very recently recorded the largest hail it's ever had. Is that one of those that's, "We don't know if it's connected," or do we know that it is connected?

Stephanie Herring: No. Hail is a tough one. We do not have the ability at this time to do a robust attribution analysis on any one event. We are starting to increase our understanding of what drives hail events and how those drivers might be impacted by climate change, which is step one. But we're not at the point where you can confidently say, "Oh, well, let me take a look at that for you and get back to you in a week," and say, "Yep, climate change played a role in that one," or, "No, it didn't." We're not there yet.

Ariel Conn: Okay. Your most recent extreme events paper, you quoted someone else's piece later on, saying, "Small deviations from estimations of future costs have considerable financial consequences." Is that something you can elaborate on?

Stephanie Herring: I think I was quoting Rebecca Owen at the time, and I actually just spoke at the Society of Actuaries Conference about this because from an actuarial perspective, simply repeating what she would probably say, the point she was trying to make in regards to public health is that when looking out into the future, you make these small estimations — and you can think of it like a pie — where, early on, a small 15-degree difference in something a couple years out: the deviation is very small from what you had predicted.

But once you get further and further out in time, that early minor error propagates. So 10 years out, 15 years out, now you're talking about millions and billions of dollars in difference in what you estimated versus what an actual cost might be. So that was the point that she was making from a health care perspective.

Ariel Conn: That was cost of health care related to climate change then?

Stephanie Herring: Yeah. So she and I did some work trying to see if we could look at insurance claims and relate them to heat events — and there has been a lot of work done in this area to show that during specific heat events, different types of claims go up. And one of the big ones that get looked at are related to people who are diabetic, so a lot of kidney-related issues, because during heat stress events, it can cause challenges to people's organs if you're already compromised in that respect. Heatstroke is actually not that big of a deal because generally, the tail of a heatstroke event is relatively small.

But if you have someone who is normally on dialysis and you throw them off of their steady state, the tail of medical costs from that to recover can be six months, seven months, eight months. That's one of the reasons that they are very interested in understanding: how do heat events and other types of extreme events drive insurance costs? What's the tail? And not only after the event, what do those look like? And so we were trying to understand what kind of changes we expect to see in our insurance claims data.

Ariel Conn: Interesting. All right, so you say you're not an actuary, but you did write an article in —

Stephanie Herring: Society of Actuaries.

Ariel Conn: Yes. And I read the article, and I had some questions for you from that. So how do we prepare and build resilience to these events and mitigate their impacts on people and property?

Stephanie Herring: Being very clear that I'm not speaking for NOAA or anything like that, I think that fundamentally — and this is why I am very passionate about the NOAA mission: I think that what we do is we provide that data and provide that scientific basis to make more informed or better informed decisions — I think that a huge part of this is making sure that data and that science has a seat at the decision-making table. There's lots of different variables that go into any decision a community, a family, or a country is making. And the data and the information is one piece of that, but it's an important piece. So personally, I feel like it behooves all of us if we not only continue to make sure that we are able to provide the best available data and information about what the world looks like today and what we think it's going to look like in the future, but that, more broadly, we welcome that information into the decision-making process.

And I would say that for the vast majority of interactions that I've had with people in the decision-making space, there's a huge appetite for this information, to understand, "What is my risk?" and whether that be for a personal decision or whether for a business trying to make economic decisions. I don't presume to know all the different factors that need to go into any particular decision in any particular sector. But I do believe that any of those decisions will be more informed if they allow the science to have a seat at the decision-making table.

Ariel Conn: I think it was one of the papers that you were working on: I've seen lots and lots of graphs showing how hot everything is getting, and the temperature extremes are getting hotter and hotter. And yet, one of the things that struck me most was seeing a graph showing that we really hadn't had any cold extremes lately. I was wondering if you could talk about what we're seeing on that end.

Stephanie Herring: That's a super, super interesting question from a science perspective. What we've seen is that — globally — is that there are almost no more regions across the planet that now experience cold extremes. I know you're not going to be able to use this because it's a picture, but this basically is a record to date. So you can imagine that — the first record is just the first record. The second one is either your new extreme heat or your new extreme cold. And then what you see starting in the 1920s is that, wow, extreme heat events seem to take over.

And then this is where we're at today, which is that as a proportion of the surface of the Earth — if you take the Earth and chop it up into grid boxes and look at how many of these grid boxes experienced a cold extreme over the course of any year; This data I think is from a couple of years ago now, 2015. So this year, there was like literally one grid box over the entire planet that experienced a cold extreme, whereas in a stable climate, you would expect 50/50. That's just not what we're getting, and it hasn't been that way for a long time.

So cold extremes are becoming rarer and rarer across the planet, which is what we would expect, but it's been really interesting, in particular — I don't know this data globally, but in North America what we've really seen is that average daytime temperatures are increasing. What we're seeing increase faster is average nighttime temperatures. Where you would expect things cool off in the evening, what we're seeing is that those average nighttime temperatures aren't cooling off as much as they used to be. There's definitely geographic variation. If you dive down to any particular location in the US, you will find exceptions to that, but overall, it's become a trend.

Ariel Conn: When you're talking about the nighttime temperatures not decreasing, is that because the earth itself is warming? Or is there something else happening?

Stephanie Herring: There's not a definitive answer to that. There's still a lot of discussion going on as to what's driving that. Certainly, we expect there to be fewer cold extremes. We expect nighttime temperatures to rise. Why are they rising faster than daytime temperatures? There's still scientific conversations around what the drivers are.

Ariel Conn: I have a couple examples here of maybe unexpected problems that occur because of, say, an extreme event — for example, when you have a drought. I think it's pretty obvious that if there's a drought, there's less water for agriculture; That's a problem. But apparently because there's less stagnant water for mosquitoes to breed in, the chances increase that they're going to end up around birds that have West Nile virus because they're all hanging out at the same limited water supply. And thus, you can see an increase of West Nile virus. And I was wondering what sort of connections you've seen that have surprised you?

Stephanie Herring: The climate change and human health aspect is a big one, but would I consider that surprising? Not particularly.

Ariel Conn: Maybe it's only surprising because I hadn't thought about it yet.

Stephanie Herring: Well, one that I think was brought to my attention recently that I don't think I had given consideration to in the past was the impact of compounding events. I was one of the co-authors for the US National Climate Assessment's Climate Change and Human Health Report, and I coauthored the chapter on extreme events.

And one of the things that came out of that, that I had not given attention to until we brought in some people from the public health community, was actually the compounding cascading events. And that was one of the things they were interested in. They were like, "Yeah, we know it's going to flood. We know it's going to have all these different individual events. What happens when they happen back-to-back?" Because they said that's really when things start to become catastrophic for them from an infrastructure perspective and a health perspective.

And that I thought was fascinating and is not an area that we understand well. If you're seeing changes in frequency and intensity, are we seeing more, for example, extreme precipitation events or extreme storms followed by extreme heat? Because a lot of times during those extreme precipitation events or other type of extreme storms, they're losing power. This was one of the examples that was brought up in our report, was power was lost and that in and of itself was bad. But it was a week later, they had a heat wave, and no one had access to air conditioning. This was in the South.

So when you have those kind of back-to-backs, how that's really when all of a sudden the infrastructure that we rely on — everyone prepares for, "Oh, okay, a flood. Here's what we're going to do," or, "Here's a particular extreme event. Here's our emergency plan." But when those emergency plans are thrown off because another extreme event is following immediately on its heels, that hits this tipping point from an emergency planner perspective that I hadn't been aware of. Again, one of those things where you're like, "Yes, of course, that makes sense."

But again, I define my little event and I look at that and I think about the impacts of that particular event without saying, "Oh, what if there's another event right on the heels of that or overlapping with that? Then what happens?" And I think that's an interesting perspective and again, the research I don't think addresses that very well. So it's kind of an unknown for us: How are cascading events changing?

Ariel Conn: I think that connects really nicely to the next question I have for you. We've been talking about this off and on, but if you were to, say, pick a couple questions that haven't been answered yet that you really think would be helpful for us to figure out, what would those be? What are the unknowns that you really wish we knew?

Stephanie Herring: I don't know if I'd want to answer any one particular question, but one of the things that I wish we had was the perfect observational record. I feel like that is foundational to answering so many other questions. Extreme events, by their very nature, are very rare. And so if you don't have an observational record that can capture enough of them to actually look at, then it's very difficult to approach this field of research and have a lot of confidence in your results because the events you're looking at are so rare.

And this is why I think it's so important to continue to invest in monitoring our Earth system and collecting all this data: is because without it, you can't understand why perturbations occur. You can't understand what effect the climate change is having on a variety of different factors. You might not even understand how the climate is changing. And so I wish that we had that, because then I could answer a ton of questions.

Ariel Conn: That's fair.

Stephanie Herring: So I'm cheating a little bit.

Ariel Conn: No, that's fair. I think that works. So, a sort of depressing question: We keep hearing about all the things — like, we need to cut global emissions; We need to make all these changes; It's not happening fast enough. For the most part, we want to be optimistic. But what does happen if we don't get global emissions cut in time?

Stephanie Herring: So I think part of the reason it's important to address climate change is because we don't fully know. We know some of the things that are invariably going to happen. Obviously, the continued rise in global average temperature, Arctic sea ice melt, species migration/ extinction. We know what things are dependent on the factors that we're able to be aware of, and I think that there's actually an interesting piece of this in the IPCC report on the 1.5 degrees. So, I think there's a lot of great research in there about the things that we sort of know about, and the predictions that are in there; And I wouldn't presume to know more than the authors of that report.

But for me personally, I think what's a little bit scarier is what we don't know. There's so much that, in terms of our predictions from 30 or 40 years ago and looking at the world that we have today, and I think that we've seen some of those predictions overshot by reality, so not realizing how fast the planet was going to warm; how quickly we would see some of these changes in extreme events; this idea that climate change was something that was going to impact us in the future. The future is today. It's happening now. And so what's the full breadth of those impacts? How different will life be and how different will our world be? We don't know fully.

We have a lot of research that's happening and trying to get a handle on that. Like I said, the IPCC has done a good job on this, and I wouldn't presume to know more than those authors, but I also think that there's an X factor that I think is maybe even more daunting. I do think it's important for people to individually remember that even though these seem like very big, daunting problems, I truly do believe that we all have part of the solution in our own hands. And that in terms of preparing for a lot of these changes and extremes that we're expected to see — a lot of that preparedness, a lot of that resilience, again, people actually have a lot of power to prepare and adapt and make themselves and their communities and their homes and their country more resilient. And so I do think that it's very actionable information; It doesn't just need to be this exercise in scientific research — that it's actually something that people can act on.

Ariel Conn: Okay. And so I think this is probably connected then: what gives you hope?

Stephanie Herring: I think that, in our country, there's a growing, at least, acceptance of the fact that climate change is real; It is being caused by us. And I think that's the first step to being able to then take action. I also do think that humans have proven to be, so far anyway, pretty amazing and ingenious in their creativity. And so I'm hopeful that there will be someone or some group or some entity that will find new and creative ways to look at this problem and how to solve it that we're just not even thinking about today, that there's other solutions out there that maybe next generation or new technology or new advancements will help us unlock.

Ariel Conn: All right. Well, I think that's it for me. Is there anything else?

Stephanie Herring: That's good. Thank you.

Ariel Conn: All right. Thank you.

On the next episode of Not Cool, a climate podcast, we’ll go deeper into the problem of extreme events with Jakob Zscheischler, who looks at what happens when these events occur right on top of each other.

Jakob Zscheischler: For a long time, people have looked at these extremes individually: We have experts on heat waves, experts on droughts. But for impacts, combinations of extremes are particularly harmful. And if we estimate occurrence probabilities from only one type of extreme, then we might underestimate the risk when the heatwave and the drought occur together.

Ariel Conn: If you enjoyed this episode of Not Cool, please take a moment to like it, share it, and leave a good review. And please join our climate conversation on twitter using #NotCool and #ChangeForClimate.

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