E5: TIL about uncertainty


How do we make choices in the face of uncertainty? In this episode of TILclimate (Today I Learned: Climate), MIT professor Kerry Emanuel joins host Laur Hesse Fisher to talk about climate risk. Together, they break down why the climate system is so hard to predict, what exactly scientists mean when they talk about “uncertainty”, and how scientists quantify and assess the risks associated with climate change. Although this uncertainty shrinks every day — as researchers refine their work, computing power grows, and models improve — what we do and how quickly we act will ultimately come down to how much risk we are willing to accept.

Kerry Emanuel is an MIT Professor of Atmospheric Sciences and the co-founder and co-director of the MIT Lorenz Center. In 2006, he was included in Time Magazine’s “100 People who Shape Our World”. Through his decades of experience studying the atmosphere and earth’s climate, Prof. Emanuel focuses on trying to quantify the risks of these anthropogenic (human-caused) changes, especially focusing on hurricanes.

For more short climate change explainers, check out: www.tilclimate.mit.edu.



Special thanks to Tom Kiley and Laura Howells.
Produced by the MIT Environmental Solutions Initiative at the Massachusetts Institute of Technology.

KE: [00:00:00] [00:00:00] If we have a temperature increase of about 6 degrees Centigrade it may be catastrophic. The probability is not large, but it's not zero, and it's not tiny either. And so you have to think about that.

LHF: [00:00:16] Welcome to TIL Climate, the show where you learn about climate change from real scientists. My name is Laur Hesse Fisher, and today we’re talking about … risk and uncertainty.

If you’re anything like me, then you want an easy answer about climate change. How will it affect my family, my business, my country? When will this happen? How much do I really need to change?

When we interviewed MIT Prof. Kerry Emanuel about hurricanes, we also spoke about where the uncertainty is in climate change, and he told us how he speaks with business leaders and politicians about risk.

To really get into this, there’s two things you should [00:01:00] know. The first is -- the Earth’s climate is complicated.

KE: [00:01:06] We're dealing with a very complex system. Many many interacting components: the transmission of radiation through the atmosphere, wind, the coupling with the ocean, ocean circulation, the land surface, the whole biosphere, which interacts with all of that…

I would say it rivals say the human body in complexity. We have all these different subsystems, you know, like we have hearts, and livers, and intestines.

And if those parts start to function differently or, God forbid fail, it's going to affect the whole organism in ways that even today in some ways medical sciences doesn't perfectly understand.

Just as the earth's climate has these subsystems, and how they interact with each other's complex.

LHF: [00:01:54] The second thing you should know is, that it’s hard to map that complexity.

KE: [00:01:59] When we [00:02:00] talk about a climate model, we’re really talking about an algorithm, which is a way of solving a very complex set of equations that govern the behavior of the system. And those equations are not just pulled out of thin air. They're actually the equations that we know govern the behavior of physics.

LHF: [00:02:20] If we wanted to create a perfect model how every part of the human body works, you’d have to know what’s happening on the nano level, like, the subatomic level, for everywhere in your body. It’s kind of the same for our climate system:

KE: [00:02:35] To make a perfect model of the system, you would have to be able to calculate things as small as a cubic centimeter or so or maybe less to do that. And we have nowhere near the computational firepower to do that.

LHF: [00:02:51] A good example of this is clouds. As we know from our previous episode with Prof. Dan Cziczo, the particles that help clouds [00:03:00] form behave very differently depending on where they are in the world. But, as powerful as computer climate models are, even clouds are, for the moment, just too small for the models to take into consideration.

KE: [00:03:12] Clouds are very very important. But the clouds may be 10 kilometers across you can't resolve that with today's climate models. They’re too small, and yet if the climate model didn't have some representation of them, it wouldn't work. And so we have to tell the climate model that they're there.

LHF: [00:03:33] You had written that there are roughly 40 climate models used by different organizations around the world, and they all give somewhat different predictions on climate change. Why do they differ from each other?

KE: [00:03:44] They all make different assumptions about what's happening on scales that are too small for them to actually compute. And it is a way of dealing with, it's not by any means a perfect way, but it is a way of dealing [00:04:00] with uncertainty. So you have different groups making different assumptions about how to do this, running different models, and comparing them.

LHF: [00:04:09] What’s neat is that this is an essential part of science. If we don’t know something for sure, then we want scientists to take different assumptions of what could be, and run them through their models, so we can see what the most common outcome would be. It’s like getting quotes from different contractors, or advice from multiple consultants: you hear what each of them say, compare them, and then use that to build a picture of what to do. This is like what the scientific community does, and they’re really transparent about it.

KE: [00:04:40] One of the most fascinating and interesting and useful parts of science is actually quantifying our own ignorance, quantifying the level to which we’re uncertain.

Let me take an everyday example: if I were to tell you as an atmospheric scientist that the temperature tomorrow, the high temperature, in Boston would be 50 [00:05:00] degrees, but it might be as warm as 53 or as cold as 47, most people understand that the you know you can't make a perfect weather forecast, that there's uncertainty in it. And that doesn't mean that we don't know right? It will be somewhere in that range.

LHF: [00:05:17] As a side note, Prof. Emanuel isn’t saying that climate change is like weather. Weather is like your mood, while climate is like your personality; you might generally have a sunny disposition, but you’re going to feel grouchy sometimes. In the same way, weather may change day to day, but it’s guided by something much larger and more constant, the climate.

OK back to Prof. Emanuel.

KE: [00:05:41] Good scientists are careful to quantify the uncertainty whenever they say anything about the future, whether it's a weather forecast or climate projection. It's absolutely essential to the final step that everybody really needs and wants, which is an assessment of the risks [00:06:00] associated with climate.

LHF: [00:06:02] Risk… if we aren’t sure if something really bad is going to happen, we think of it in terms of a risk. Like our house flooding or us getting an expensive medical bill. It’s why we buy insurance.

Because climate change also comes with a level of uncertainty, it’s helpful looking at it in terms of risk.

This next part is less about the science of climate change and more about how decision makers, and really all of us, can think about risk… What Prof. Emanuel says here might stick with you more than anything else in this podcast series so far.

KE: [00:06:38] When we make decisions about risk, we rarely make decisions based on the most probable outcome. Let me take a really simple example, you're walking your daughter to school, you got come to a busy intersection across which is the school bus, which has just pulled in, and you’re little bit late.

Now, you can let your little girl run for [00:07:00] the bus, and let's say in your own mind there's a 2% probability she'll be run over on the way.

LHF: [00:07:06] OK I know that’s a little dark, but we’ll continue with the example…

KE: [00:07:10] If she doesn't run you'll have to take her to school because she's going to miss the bus. Now the most probable outcome is that she could be fine, and yet that's the last thing you do. And all that illustrates is that to get the risk you have to take into account two things: the probability of the outcome and how expensive, not necessarily in monetary terms, the various outcomes are.

LHF: [00:07:37] So so how likely it's going to happen, and how bad it would be if it did happen?

KE: [00:07:40] Yeah, that's right. Both you have to take into account both.

Well, that's a metaphor for the climate system too. The most probable outcome the way we see it is if we double carbon dioxide will have a temperature increase of about 3 degrees C.

LHF: [00:07:56] An increase like this comes with some really dramatic impacts.

KE: [00:08:00] [00:08:00] You have to start moving structures that are right on the coast Inland or putting them up on pilings. You have to change your agricultural practices. You have to deal with huge immigration pressures because there are parts of the world which are already agriculturally marginal who will cease to be able to do any agriculture at all. So those people are going to want to move. So you have to deal with that. We're already dealing with it. And it's disruptive, but it's not so far catastrophe.

LHF: [00:08:30] The thing is, a catastrophe is inside the realm of possibility.

KE: [00:08:35] If it's five degrees Centigrade or 6 degrees Centigrade it may be catastrophic.

Catastrophic is going to kill you, or it's going to really harm civilization if we're talking about the whole world.

The probability of it being 6 degrees centigrade is not large, but it's not zero, and it's not tiny either. It's somewhere down there. Maybe it's low probability, but it's also a low probability that your daughter will be [00:09:00] run over if she runs for the school bus. You still have to think about it.


LHF: [00:09:09] Scientists have created a range of scenarios of what may happen with climate change.

Some people who look at the data think that our society should prepare for what scientists say is most likely to happen. And some people think that we should look at the best or worst that could happen, even if it’s unlikely.

When reading about climate change or listening to advocates or policymakers, you can try to understand which scenario they’re planning for here. Because what we do and how quickly we act, will differ a lot depending on which future we’re planning for.

So, what about you? What world do you think our society should prepare for? The unlikely one where climate change doesn’t really impact much at all? The likely disruptive future? Or the [00:10:00] unlikely catastrophe?

You can tweet us @tilclimate. And if you’re interested in how scientists talk about these different scenarios check out our show notes on tilclimate.mit.edu. Thanks for joining us today on TILclimate, and thanks to Prof. Emanuel for speaking with us. I’m your host Laur Hesse Fisher from the MIT Environmental Solutions Initiative, and I’ll see you next time.

An educator guide for this episode can be found below.

For more information on climate risk, check out:
The work of Prof. Emanuel:

Information about predicted levels of warming and impacts of that warming:

An overview of climate change:


Educator Guide

Created by Olivia Burek, Alyssa Farkas, and Aaron Krol, with thanks to Sarah Hansen and MIT Open Learning


The following questions can be used to encourage your students to reflect on, extend, and apply what they’ve learned from the podcast episode. Re-use and remix them as writing prompts, discussion guides, or ideas for project-based learning in your classroom.


Critical Thinking

  • How does uncertainty make it more complicated to create policies in response to climate change? To what degree should uncertainty and risk be considered? Does the existence of uncertainty make a scientific matter any less real or important to act on? Explain your reasoning.
  • Professor Emanuel discusses the two factors people use to assess risk: “the probability of the outcome and how expensive, not necessarily in monetary terms, the various outcomes are.” What are the advantages and disadvantages of looking at climate change in terms of risk? How does this perspective affect decision-making? In particular, how do decision-makers try to measure the costs of different possible outcomes? Who is making these decisions now? Do decision-makers face the same climate-related risks as other people? Who should be making these kinds of decisions?
  • Think back to a time when you had to consider uncertainty and risk when making a decision. How did you weigh your options? What were some skills you used to make your decision? Were those strategies useful, and would you use them again next time? How could you apply these skills to decision-making about actions related to the environment, either in your personal life or on a larger scale?


  • With the Paris Agreement, the United Nations set a goal to limit warming below 2 degrees Celsius. How did the UN choose this limit? How might uncertainty have played a role in this decision?
  • Research the “Representative Concentration Pathway (RCP)” emissions scenarios. What are these scenarios, who develops them, and why? What is the worst-case scenario for a temperature increase due to climate change? And the best-case scenario? When talking about climate policy, scientists and policy makers often distinguish between “mitigation” and “adaptation.” Mitigation includes actions that prevent future effects of climate change or make them less severe, such as reducing greenhouse gas emissions. Adaptation includes actions that protect people and environments from damage caused by climate change, like building sea walls to protect vulnerable coastlines. Consider the difference between mitigation and adaptation. Should they be balanced differently under different emissions scenarios? Is there any scenario for which planning should include mitigation or adaptation, but not both? How does uncertainty about the effects of climate change enter into decisions about balancing mitigation with adaptation?
  • Research in more detail what climate models are and how they are created. Why is it so hard to accurately model the climate? How do scientists deal with these challenges? Is it okay, or even beneficial, for different scientists to make different assumptions in their climate models? How do scientists show that their assumptions are reasonable?


  • Different climate models show a range of possible futures for our planet, depending both on actions we take and on natural factors that are hard to predict. In looking at these possible futures, how should we decide which scenario to prepare for? Do you think emphasis should be placed on worst-case or best-case scenarios? Both? None? Why? How might looking at different scenarios cause us to choose different policies in response to climate change?


  • While many technologies that could help prevent the worst effects of climate change already exist, some scientists are working on new technologies that might do even more. For instance, some believe that a new version of nuclear energy called fusion power could provide clean electricity at a lower price than either fossil fuels or current renewable sources. Other scientists are trying to build devices that could directly remove carbon dioxide from the atmosphere. However, none of these future technologies are guaranteed to work. 
    Imagine that you are a policymaker at the UN. Renewable energy has been expanding in recent years, but it is increasingly hard to meet the UN goal of a global temperature rise no higher than 1.5 degrees Celsius. While looking at how else you could lower emissions, you think of the possibility of investing in undeveloped technological breakthroughs, which could potentially help, but are not accepted for use yet. How would you decide the best way to invest your limited resources? You could invest only in proven technologies that exist today, only in future breakthroughs, or some combination of both. What kinds of uncertainty should you consider with regard to these choices? Which would you choose and why?


Need additional open educational resources related to the topic of uncertainty in climate change? You may find these free teaching materials from MIT OpenCourseWare (ocw.mit.edu) helpful:

Science and Policy of Natural Hazards
Level: Undergraduate
This course, taught by Professor Kerry Emanuel, Professor Stephane Rondenay, and Jane Connor, covers the policy implications of natural hazards. Educators have access to the syllabus, lecture notes, assignments, and a list of links to resources on earthquakes, hurricanes, tornadoes, and the assessment of natural hazards in general.

Environmental Policy and Economics
Level: Undergraduate
This course, taught by Dr. Hunt Alcott, examines government’s role in environmental regulation. Educators have access to the syllabus, reading list, assignments, and notes and slides from the course’s lectures on topics such as cost-benefit analysis, risk and liability, and climate change policy.

Uncertainty in Engineering
Level: Undergraduate
This course, taught by Professor Daniele Veneziano, focuses on the application of probability and statistics to engineering, Educators have access to the course syllabus, lecture notes, assignments, and PDF files on topics such as the effect of wind loads on buildings, the relation between the duration and intensity of storms, and the prediction of earthquakes.