The reason to talk about risk is two fold. First of all, risk provides a construct to make rational decisions and I'm gonna describe that in just a second. And the second reason is that I think we all understand intuitively what risk is. We understand it in the context of buying car insurance to avoid the risk, or to mitigate the risk of an accident. We may not avoid it, but [COUGH] if we were to get [COUGH] in an accident presumably, if our car is damaged, we'd be able to get it fixed and so on. Avoid some of the liabilities and things like that. So, I think we intuitively understand risk. So if we can start talking about climate change in the context of risk, then maybe we can also start having a more intelligent conversation by avoiding all that sort of ideological odor that seems to accompany any discussion of climate change. So those are the two reasons that I wanna talk about risk. So before I actually talk specifically about some of the characteristics of risk in the climate system, which is where I'm going with this, what I wanna do is talk about risk in general. So what I'd like to do is ask you to imagine two cases. So in this first case, now imagine that this farm is in a floodplain of a river and that river floods frequently. It floods every two or three or four years, something like that. And further, imagine that because this floodplain is really, really wide, that river can flood, but the water never gets really, really high. It never gets say, more than a meter high. Now this farmer has been living here for a long time. Maybe he's been living here and farming here for 30 years and he's seen this over and over and over again. And in fact, his family had been here for a long time and they had a smaller house and they had seen this. And the mitigating action, the insurance, if you will, was pretty obvious. Build a berm around the farm. So this guy takes out his bulldozer and he builds a berm around his farm. And it's not very expensive, but it's the insurance, it's the mitigating action that avoids the risk. So he builds a berm that's say, two meters high. And voila, his farm doesn't flood. So he understood, he saw this, he experienced this event over and over and over again. The mitigating action was pretty obvious and it wasn't very expensive. Here is a farm in a floodplain, and this is that proverbial 100-year flood. And so this guy's been living here for another 30 years and it's never happened before, never had a flood of this magnitude. And also this farm is in a river valley, a much narrower river valley, so that potentially the water could rise significantly. And he's never occurred to him, because he's not experienced this flood. He had no concept that this could happen. It never occurred to him to take mitigating actions. And even if he were to take mitigating actions, I think you can see that whatever those actions would be, they'd be very expensive. So the result is this catastrophic damage to his farm, and I raise these two issues, because they illustrate this concept of risk. So risk depends on the probability of an event occurring and it also depends on the magnitude of the potential consequence. And it also depends on what mitigating actions one takes, be it building a berm or buying insurance or whatever. And furthermore, as you probably know, it's governed by our beliefs, our knowledge. It's some judgment. How much car insurance we take, there's no magic number for that. This depends on our judgement, on how much risk we're willing to take. So that's the nature of risk. As the mechanism for making sensible decisions, we can talk about probabilistic risk assessment and equate that with, as the product of the probability of an event occurring and the magnitude of the potential consequence and that's what that is. So that's what provides us with a construct for rational choice. So on the left here is a graph, we've got consequence increasing. On the far left, probability on the increasing on the abscissa. So a high-risk event would be one that is likely to occur and the consequence would be dire. And a low-risk event would be just the opposite. The consequence would not be dire and the probability would be low. And that gives us choices. So if on the right, we got probability times consequence. In other words, the level of risk. Now imagine, if there is an event that, for whatever reason, is a high-risk event and you don't take any action and the event occurs, you're screwed. On the other hand, if you do take action and the event occurs, then there's no impact and we're very smart. Whereas if we take no action and there's no impact on the lower right, we're lucky. And if we take action, but there's no impact, we can say we're dumb, because we had to pay for the action, even though the event didn't occur. So that's what I mean by a construct to make sensible choice. And I've used these rather unscientific terms, if you will, to illustrate again, the fact that this is not science. There's a lot of judgment and there's a lot of personal beliefs embedded in making choices as far as risk is concerned. So there are several things that I wanna talk about. First of all, I wanna talk about why the future is unknowable. And the reason that I want to talk about this in the context of climate is because risk is the mechanism that we deal with an uncertain future. If we knew the future, we wouldn't have to deal with risk at all. Well, we know this is gonna happen. Either we deal with it or we don't deal with it. That's not a problem. But the fact is that if there's an uncertain future, the risk is the way that we deal with it. And that's why I wanna make this point about the uncertainty in the future in terms of climate. I wanna talk about why risk differs for different classes of impacts in the climate system. How risk is governed by extremes, I wanna talk about something called tail risk. And finally, I wanna talk about the special characteristics associated with really large events, climate catastrophes. The future. So in this diagram on the vertical axis or the ordinate, we have probability of exceeding two degrees above preindustrial global surface air temperature, preindustrial temperature by the year 2100. So this is probability goes from 0 to 100%. And on the abscissa, this is a plot of the cumulative carbon dioxide emissions for the year 2000 to 2049 and that's in gigatons of carbon dioxide. In other words, billions of tons of carbon dioxide. So that goes from 800 to 2,500 gigatons of carbon dioxide, just to put that in perspective. We today, we're producing about 30 gigatons of CO2 per year in emissions from the burning of fossil fuels and agricultural activity. So we have this colored band and what that is the climate sensitivity for a whole bunch of climate models for actually 23 climate models. Most of them fall in that band. So what that means is that for certain emissions, the climate model indicates a certain probability of exceeding this two degree centigrade temperature above preindustrial. So these climate models then, using all these climate models, this is in essence some measure of the uncertainty of the science, because all the climate models are different. Now it's not precisely a measure of the uncertainty in the science, which we don't actually know. And there's something not included in this, which I'm gonna get to later on. But it is some measure of the uncertainty in the science. So let me expand on that a little bit. So in other words, let's say in this first 50 years of the 21st century, 14 years of which is already gone, we emit a 1,000 gigatons of carbon dioxide. So the climate models indicate that there's some range of probability of exceeding this 2 degrees above preindustrial temperature ranging from 10% to 42%. Do you see that? Just to make things simple. So that's this measure of uncertainty in the science. This qualitative measure of the uncertainty of the science. Just to make this a little bit simple, instead of taking this range now, I wanna consider this black line, which is an illustrative case. Let's just forget about the range and just now take the black line an illustrative case. And let's do that, so that we can consider other possible emission scenarios, if you will. So you can see that if instead of 1,000 gigatons of CO2, we cut global emissions by 80% from the 2010 level. The probability of exceeding two degrees of preindustrial by 2,100 would be 20%. On the other hand, we see that if the developed world cut emissions by 80%, but the developing world actually increased emissions by 1%. We would have a 34% chance of exceeding that 2 degree temperature. On the other hand, if we continued emissions at 2008 level, we would have a 42% probability of exceeding the 2 degrees centigrade temperature. And finally, if emissions grow by 2% per year, which is more or less the path that we're following these days, there's an 89% probability of temperatures exceeding the 2 degree above preindustrial. So what I hope is an obvious point is that I've just given you a whole bunch of scenarios and we don't know which scenario is gonna happen, we have no idea. There's no way that you can tell me that it's more likely that we're going to move along constant 2008 emissions or grow by 2% a year. And so there is this uncertainty in emissions and the reason for that is pretty obvious. The uncertainty in emissions is because emissions and thus, energy use depend on technological developments. They depend on political developments. They depend on socioeconomic evolution. They depend on all these things that none of us really know anything about in terms of being able to predict, so that's why the future's uncertain. There's certainly scientific uncertainty, but the other uncertainty, which is probably a lot larger than the scientific uncertainty is an uncertainty of how the world is gonna evolve in terms of us. We can talk about impacts such as say, significant by diversity loss or significant loss in sensitive ecosystems. These are things that are occurring now and not may be significant, but some people would say, they're significant. Whether or not they're significant, they're occurring now. What are the consequences to society? Well, I would argue that at the moment, they're mild. The consequences of loss of biodiversity, the consequences of loss of sensitive ecosystems, while certainly not desirable by any stretch of the imagination. They're not bringing society to its knees. And so we can list a number of potential impacts of climate change that range from 100% probability, because they're occurring now to risks that become progressively less probable. And that's what this list is suppose to be. So I'm on the first column from occurring to less likely, that's this decrease in probability and the next column happening now to happening decades out. So there are some impacts that as I say, are happening now, such as loss of biodiversity. But there are other impacts such as significantly more severe droughts, which are probably a decade. Maybe a couple decades out to fewer water supplies, which are probably even further out to really catastrophic events such as Huge sea level rise, which are even further out in time. Okay, so we can rank all these impacts in terms of their probability of occurrence, how far out in the future they're gonna be, and also the extent to which they're gonna affect society. Okay, from a mild impact to society to a really catastrophic impact such as the reduced food supplies and famine due to drought, at the same time, over most of the world. So that's why you need to separate out these impacts and think about the risks for individual ones. It's because that climate change is permeating through the entire environment around us and it's affecting everything, if you will. So the points are that climate change, as I just said, pervades our world and it results in numerous kinds of impacts. The truly catastrophic risks are more likely in the distant than the immediate future and climate change plays out on a whole wide range of time scales. And I say this because it plays out specifically on time scales. Some of it plays out on time scales that are not easily understandable to us because of our psychological makeup, because of our [LAUGH] timescale. Or the timescale that we understand the world to be operating on is not the timescale the climate is operating on, at least parts of the climate system. Which of course is one reason that these risks in the distant future are rather difficult to deal with. Okay now let's talk about how risks are governed by extremes. To do that I'd like to talk about a very interesting event, namely the 2003 summer heat wave that struck Europe. This is a very, very intense heat wave, I'll just point out in a second, it was responsible for some estimate of 35,000 to 50,000 deaths, it was most severe, basically over France. Now this plot, the vertical blue lines are a mean summer temperatures from a number of sites in Switzerland and these data are from 1864 to 2002. So every summer you've got an average temperature, right, for a number of cities in Switzerland, and of course that's where they keep excellent records so that's probably why this is on this plot. And so that's what all those vertical blue lines are and then there's, the average, by the way, of all those is 17.2 degrees, and then there's a normal distribution around that 17.2 degrees. Now a normal distribution is a distribution of events that is a consequence of a perfectly random phenomenon. And so 68% of all those events are in plus or minus one sigma of the mean, and 95% are within two sigma 99.7 of the events are within three sigma and so on and so forth. So what you can see here is that distribution of summer temperatures is not a perfect normal distribution, but it's not too far from a reasonable normal distribution. The red line labeled 2003, of course, is the summer temperature. It's 5.4 standard deviations from the mean, which if you know anything about standard deviations, the likelihood of that happening in [LAUGH] any kind of a random circumstance is basically zero. So it was a very, very unusual event. Now what's gonna happen? Let's talk more about extremes in the future, so [COUGH] let's look at this diagram. The top panel, now, is a model and what we wanna do is ask ourselves or a given emissions scenario, what will the summer temperatures in Europe look like? Okay, and so let's find a model that actually works. So first thing we want to do is test that model as best we can and that's what the upper panel shows. So we run this model between the years 1961 and 1990, given the atmospheric CO2 contents, and it returns a summer temperature for every year, and that's the purple vertical lines. The average there is 16 point something or other degrees, so it's producing an average that's a little cooler than the observed, but it's not too different from the observed. Okay, now we've established that we have a model that is giving some reasonable results. Let's choose an emissions scenario, that is to say, let's make an assumption about what future emissions are going to be. This particular assumption is a high mission scenario. And let's now ask that model to predict, to calculate what the temperatures are gonna be for the last 30 years of the 21st century, and that is the second panel from the top. So, those are the vertical red bars, okay, so the first thing you can see is the distribution's far, far wider so there's much, much more variability. The second thing that you can see is that the average summer temperature in the last 30 years of the 21st century is now not too distant from that summer temperature in 2003. And the third thing you can see is the heat waves in the last 30 years of the century are gonna be far hotter than the heat wave in 2003. So that's what we mean about extremes. We've got to consider the extreme rather than the average conditions. Tomorrow's extreme could be much larger than today's. And third and very important point is that the extremes are typically local in these kinds of events. We've gotta talk about local extremes not global extremes because you can talk about two degrees centigrade rise above pre-industrial, but that's a global thing, right? That averages everything, so it's not very meaningful in terms of talking about risks. So now, what we have plotted here, on the ordinate, is the probability density versus the climate sensitivity to doubling of the CO2 content Of the atmosphere. Now there's several curves here. Let's just consider that green curve for the sake of convenience. All right? Now I want to describe what that means. Okay, so we're using a model. And we're saying that we're going to double CO2 content and the model returns a global temperature. Okay? And you do that over and over and over again, and it returns different global temperatures. So what the probability density means is that the sensitivity of CO2 three degrees, so what that's saying is that the probability is 50%. This gives a 50%, let's say it's right there, this gives a 50% probability. Okay? So 50% of the time, the climate model is returning three degrees. Okay. 2% of the time, the climate model is returning about 25. Excuse me. 25% of the time, the model's returning two degrees. 10% of the time, the model's returning five degrees. But the reason I point this out is this huge, huge tail, this long tail on the positive side. Where does this tail come from? The tail is a statistical consequence of any system, be it climate or anything else that has positive feedbacks. Okay, that's a consequence that's characteristic of any system that has positive feedbacks. And almost all of the feedbacks in the climate system are positive. And that's why the climate system has this long tail on the high temperature side of the probability density curve. This tail is really important, because it means there is some finite probability that climate change could be very extreme. Some finite probability in the models that climate change could be very extreme. Now, this didn't show up in that first set of figures I showed you about when I was talking about the uncertainty in the future, and the reason it didn't show up is because there was a cutoff on probability in that diagram, I don't know what it is offhand, maybe 10%, or something like that. But there's a cutoff. But I just wanna emphasize that the special thing about this is that it's a fundamental characteristic of the climate system because it has positive feedbacks. And now let me talk about the final point that I wanted to raise and that's the special risks associated with what I would call climate catastrophes. So what you see here is a map showing the offsets associated with the 2011 Tohoku earthquake in Japan, which as you know, was one of the largest earthquakes in the last 100 years. So, the first unusual event here was a very, very large earthquake. And as you well know, what happened in that earthquake is that it resulted in displacement, sudden displacement of the ocean floor and that resulted in a huge tsunami. And as you well know then this tsunami flooded the Fukushima power plant, for reasons unknown, the diesel generators were underground. Needless to say, below the flood waters. So, they stopped operating and cooling waters stopped to the reactors. And three of the reactors, then, melted down. So, this was the third cascading consequence. There was an explosion. And the fourth cascading consequence was the dispersal of radioactive debris over a large area, resulting in quasi-permanent evacuation of many people. So this is the principle that you see commonly in very large earthquakes of so-called cascading consequences. These unexpected consequences, completely unexpected consequences, that happen with these very large events. Right? And so I would submit that catastrophic climate events have that same property. I'm just imagining this, but I can imagine that there is, again, a drought that affects the seven large food growing areas in the world that results in a global famine. That could result in something very unexpected like a global war. It's not out of the realm of possibility. Maybe it's unlikely, just like the destruction of a nuclear power plant from an earthquake is unlikely, but that would be an example of a cascading consequence. Okay. So to summarize then, climate change, I believe, should be properly understood as an issue of risk. It's certainly not an issue of science anymore. The major uncertainty in the future is the growth of emissions, and the reason for that is that emissions and energy use depend on technological and socioeconomic developments, political developments, and so on and so forth. I made the point that the risks are associated, the different parts of the climate system have different risks. And this is simply a consequence of the fact that the climate system permeates through the whole environment. We can thus rank these risks in terms of their probability. In terms of how far out they are. In terms of the nature of the threats. We talked about the importance of extreme events in climate risk. I talked about tail risk and how that's a fundamental characteristic of the climate system. And finally, I tried to make the point that large climate events probably have this characteristic of cascading consequences.