The effect of population growth on climate change impacts

Global human population is currently at approximately 7.5 billion people and increasing by about 1.1% per year. However, the rate of growth of the population growth rate itself is decreasing so world population is expected to level off somewhere near 10-11 billion people around the year 2100. This leveling-off is encouraging from a sustainability perspective but an extra 3 billion people is still quite a bit for the earth system to support.

Since everything humans do requires energy and since our energy system still largely relies on fossil-fuels, the number of people on the planet has a large effect on projections of the impact of global warming. This is why having ‘one fewer child’ has been noted as the single most significant lifestyle decision people can make in terms of reducing their carbon footprint.

This raises a couple questions:

1) How much worse do we expect climate change impacts to be due to this 3 billion-person increase in population?

2) How much faster would we have to ‘decarbonize’ society in order to offset the impact of adding these 3 billion people?

We can get first-order answers to questions like these using the type of simplified equations that go into ‘Integrated Assessment Models’ like the Dynamic Integrated model of Climate and the Economy. In these simplified models of the environment and society, the impact of climate change is quantified by the ‘damage function’ which expresses the damage caused by global warming in terms of a fraction of global gross domestic product (GDP). (The damage function is extremely uncertain but its estimates are becoming more empirical).

Using this framework, we can compare the climate change impacts in a world where population grows from 7.5 billion to 10.5 billion by 2100 (scenario 1, red line below) to a scenario where global population stays steady (scenario 2, blue dashed line below). In these situations, I am considering a middle-of-the-road projection where CO2 emissions continuously drop (panel e) but not fast enough to keep up with the ambitious goals of the Paris Accord.


Comparing the population (panel a) and the climate change impact (panel h), we can see that the additional 3 billion people increases the negative impact of climate change from approximately 1.3% of GDP (blue dashed in panel h) to 1.5% of GDP (red line in panel h) in 2100. This doesn’t seem like a huge difference, meaning that offsetting this difference might not be an insurmountable challenge. So what else could we change in order to offset this additional 0.2% of GDP damages?

We hear about several possible ways that society could go about decarbonizing; from consuming less, to increasing energy efficiency, to transitioning from fossil fuel to renewable energy sources. In fact, along with changes in population, these things represent all the possible avenues by which humanity can reduce carbon dioxide emissions. These features are described quantitatively with the Kaya Identity which breaks down carbon dioxide emissions as:


The four terms of the Kaya Identity are plotted in the first four panels above (panels a-d).

This tells us that in order to offset the climate change impact of the 3 billion-person increase in population (a) we need to have either a smaller increase in consumption (b), a larger decrease in energy intensity (c), or a larger decrease in the amount of CO2 we emit per unit of energy (d).

Globally, material consumption – and its flip side production (b) – have been increasing by about 1.4%/year and is expected to continue to grow at a growing rate over the remainder of the century. Energy efficiency (c) has been increasing (or energy intensity has been decreasing) by about 1-2%/year and apparently, this is expected to continue until at least 2040. The carbon intensity of energy (d) – transitioning from fossil fuel to renewable energy sources – is where most policy discussions center and thus I will single-out that term here.

As the baseline, I have assumed that carbon intensity of energy will decrease by 1.5%/year, which is a middle-of-the-road estimate. So the question becomes, how much more of a decrease in carbon intensity do we need in order to offset the increase in population?

The black dashed line (scenario 3) illustrates how this can be achieved. It shows that, in order to have the same impact (panel h), carbon emissions intensity would need to shift from a growth rate of -1.5%/year to -2.1%/year. So, from a climate perspective, the impact of the additional 3 billion people can be offset by what seems like a relatively modest change in the rate of decrease in carbon emissions intensity. Hopefully, this is not an illusion and this level of decarbonization of the energy system proves to be both technologically and politically feasible.

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Can humanity maintain perpetual economic growth?

…to understand modern economic history, you really need to understand just a single word. The word is growth. –from Sapiens (2014)

Humanity is far more materially wealthy today than any time in the past and our collective wealth continues to explode:

Picture1From Wikipedia: World Economy.

This material wealth has made it possible to achieve great increases in human well-being measured, for example, by the increase in lifespanincrease in food availabilityreduction in povertyreduction in infant mortalityreduction in a myriad of diseases, etc.

One question that has occupied the minds of environmentalists for decades, however, is: “Can this economic growth be maintained indefinitely, and what happens when we run up against physical limits to growth?”

Yuval Noah Harari’s book Sapiens has what I consider to be a profound section (Chapter 16: The Capitalists Creed) in which the fundamental aspects of the modern economy are described from first principles. Harari uses a simple example that I think is particularly illuminating in that it shows how our current system not only produces growth but depends on constant growth to survive.


Harari describes a situation involving a general contractor, a banker, and an entrepreneurial baker who is dreaming of starting a bakery.

The contractor has $1,000,000 and decides to deposit it in the bank (‘panel a’ above). The banker thus has $1,000,000 that he would like to make more money with by investing it.

The baker thinks she has a great business plan for a bakery but she cannot make her dream a reality without a loan. She goes to the bank and pitches her plan, requesting a loan of $1,000,000 to construct her bakery. The banker is convinced that the bakery will be a good investment and loans the $1,000,000 to the baker (‘panel b’ above).

The baker then hires the contractor to build the bakery for a price of $1,000,000. The contractor follows through, making the bakery a reality (‘panel c’ above).

Here’s where it gets interesting.

The contractor now has an additional $1,000,000 which he decides to deposit in the bank, giving him a total of $2,000,000 in the bank (‘panel d’ above).

Look what just happened: the $1,000,000 simply exchanged hands from person to person, but seemingly out of nowhere, the contractor ends up with $2,000,000. An extra $1,000,000 was just created out of thin air!

Where does the extra $1,000,000 come from? It comes from the future. Specifically, the difference between the total amount of real money ($1,000,000) and the amount of money that the contractor has in his account ($2,000,000) is attributable to the future income of the baker. In other words, the banker believes that as time goes on, the bakery will be successful and the baker will repay the loan with interest. So eventually, if the contractor asks to withdraw his $2,000,000, the money will be available. The whole system is based on borrowing from the future in order to finance the present.

Harari notes that under current US banking law, banks are allowed to loan ten times more money than they actually have on their books. That means that at any given time, over 90% of banks’ assets haven’t actually been created yet – we are all just collectively assuming that they will be created in the future. This system only works if the future is always able to produce more wealth than the present, allowing the cycle to be maintained. In other words, the system requires perpetual growth or it will collapse.

The economy can grow due to the discovery of new resources, the growth of the labor force, improvements in technology or increased productivity due to increased specialization.

Over the past couple hundred years, these things have outpaced their limiting factors, allowing wealth to explode. But it is difficult to see how this can be sustained forever. We can’t grow the labor force indefinitely, there are not infinite material resources (at least not on earth) and there are limits to what specialization can achieve.

Technology is perhaps the most difficult thing to put a limit on and there are many futurists who expect technology’s exponential growth to continue to the point of a technological singularity.

Despite this, it is difficult to see how we will not eventually reach fundamental limits on growth that will undermine the very basis of the system we have created. Geoffrey West has pointed this issue out in his book Scale (touched on in his TED talk and also described in Bettencourt et al., 2007). He notes that so far, society has continuously been bailed out by innovations that have allowed us to continue to grow exponentially (actually super exponentially):


So basically, if the wildest predictions regarding the ‘technological singularity’ do not come to pass, we will eventually run up against limits where growth can no longer be maintained and the foundation of the global economic system will be fundamentally undermined. (This is hardly a new realization and it has spawned entire fields of thought such as Post-growth and Steady-state economics)

It should be noted that environmentalists have been warning about unsustainable growth of human population and resource consumption for a long time. High-profile predictions of collapse due to unchecked growth have been made since at least Malthus’s An Essay on the Principle of Population in 1798. There were also high-profile predictions of imminent disaster in the 1960s and 1970s epitomized by Paul R. Ehrlich’s The Population Bomb in 1968 and the Club of Rome’s The Limits to Growth in 1972.

These writings warned of imminent catastrophes that have not been realized. Technological innovations and the continuous discovery of new resources have allowed the system to maintain itself, resulting in the amazing growth in wealth I highlighted above.

But does the fact that growth has been maintained historically, imply that growth can be maintained indefinitely into the future? I see no reason why the latter should follow from the former. Physical limitations of the environment and the fact that material recourses are finite would seem to suggest that growth cannot be maintained indefinitely. If that is the case, society should seriously consider how to gradually transition from our current system to a more sustainable one. This certainly seems preferable to having to build a new system from scratch after the old one has collapsed.

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Change in temperature variability with warming

We have a new paper out in Nature Climate Change on potential changes in natural unforced variability of global mean surface air temperature (GMST) under global warming.

News and Views piece
Duke press release

Unforced GMST variability is of the same order of magnitude as current externally forced changes in GMST on decadal timescales. Thus, understanding the precise magnitude and physical mechanisms responsible for unforced GMST variability is relevant for both the attribution of past climate changes to human causes as well to the prediction of climate change on policy relevant timescales.

Much research on unforced GMST variability has used modeling experiments run under “preindustrial control” conditions or has used observed/reconstructed GMST variability associated with cooler past climates to draw conclusions for contemporary or future GMST variability. These studies can implicitly assume that the characteristics of GMST variability will remain the same as the climate warms. In our research, we demonstrate in a climate model that this assumption is likely to be flawed. Not only do we show that the magnitude of GMST variability dramatically declines with warming in our experiment, we also show that the physical mechanisms responsible for such variability become fundamentally altered. These results indicate that the ubiquitous “preindustrial control” climate modeling studies may be limited in their relevance for the study of current or future climate variability.

Another principal finding of our study is that global warming may cause local temperature variability to increase over low-to-mid latitude land regions at the same time that global temperature variability dramatically decreases. This represents a cause for concern, as it is precisely these low-to-mid latitude land regions that are characterized by the highest human population density and biodiversity.

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Credibility through honesty about uncertainty

An argument that I often encounter is that uncertainties in climate science shouldn’t be publicly emphasized since that will make it harder to inspire action on proposed climate policies. It is thought that publicly highlighting a lack of knowledge/understanding on some aspect of the science provides ammunition to anthropogenic climate change skeptics and thus should be avoided.

I agree that highlighting scientific uncertainty in isolation is misleading because it fails to convey that scientists are very certain about a lot of fundamentals. However, I believe that being honest about uncertainty, and yes even highlighting it, is precisely what builds the credibility that is necessary for the public to trust science in the first place.

As an example, which string of statements (A or B) inspires more trust/credibility?

A.1 The Earth has a greenhouse effect that keeps it warmer than it would be otherwise
A.2 Humans are burning fossil fuels that increase greenhouse gas concentrations
A.3 These increasing greenhouse gas concentrations are warming the planet
A.4 This warming is likely to increase stress on crops at low latitudes
A.5 Assuming current agricultural practices, this could have a substantial detrimental impact on crop prices and/or food availability in the future but crop and economic models have many known problems and are inherently uncertain


B.1 The Earth has a greenhouse effect that keeps it warmer than it would be otherwise
B.2 Humans are burning fossil fuels that increase greenhouse gas concentrations
B.3 These increasing greenhouse gas concentrations are warming the planet dramatically
B.4 This warming will cause global crop failures and food shortages in as little as a decade or two
B.5 These food shortages will create millions of climate refugees that will destabilize the global social/political order

Clearly, A sounds more credible and it is also much more scientifically justifiable. However, I often see climate-action activists preferring to use narratives much more along the lines of B. The argument goes that people need salient, specific, alarming examples in order to get them to pay attention to the issue.

That may be the case, but I would argue that any extra attention that is garnered by using B is more than offset by the risk of losing credibility.

What happens when a dramatic prediction like B.5 does not come true? In the mind of the public, the credibility underpinning the entire chain (B.1, B.2, B.3, and B.4) is undercut. If on the other hand, uncertainty is emphasized where it is appropriate (A), the entire chain is not as vulnerable to being dismissed. In other words, concerns about crops may not materialize as envisioned (A.4 and A.5) but that wouldn’t undermine A.1, A.2 and A.3.

Anthropogenic climate change skeptics distrust scientific conclusions about climate change at least partially because they contend that uncertainties are being underemphasized. Thus, true ‘ammunition’ for anthropogenic climate change skeptics comes from deemphasizing, rather than emphasizing uncertainty.

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The fact illusion: Objective truth is elusive in (climate) science


Science is the best system humans have ever created to address questions about how the world works and no other paradigm is better at moving us towards objective truth. However, contrary to a popular notion, science can rarely be thought of as an authoritative body that simply swoops in and declares various statements as fact or fiction, true or false. Instead, science is a loosely-defined activity, conducted not by a central authority but by a myriad of competing organizations and individuals all over the world. Thus, our collective confidence in various scientific conclusions inevitably has to result from the subjective weighing of evidence rather than deference to a supreme authority.

The central reason why science has a hard time giving us the “facts” that we desire is that the world is immensely complicated and the available data is generally insufficient to allow us to rule out all alternative explanations. Another reason is simply that scientists are people and people can be swayed by internal emotions and/or external social forces that can lead them towards misplaced conclusions.

When it comes to predicting the future of the Earth’s climate and society we know the least about the things that we care the most about. A survey of predictions of the future, even (or especially) by experts, reveals that prediction is perhaps the most difficult task that humans routinely engage in.

All sides of any debate should acknowledge the fundamental limitations of our knowledge and embrace humility. If we were able to do this it would diffuse some of the tensions and move us from impasse to productive discussion that could lead us closer to the truth.

We want simple, we want “facts”

It may essentially be the case that science can tell us that it is a “fact” that water is made of hydrogen and oxygen. There are many other claims that can, for all intents and purposes, be considered facts as well. However, in contemporary discussions on contentious issues, we generally imagine that science can provide us with facts that are just as authoritative as ‘water is made of hydrogen and oxygen’. This is not the case.

The notion that science would be able to provide us with facts and definitive prescriptions on societally-relevant issues is a very attractive one. It is attractive because humans tend to be ‘complex-world-phobic’ and ‘simple-world-philic’. We are all attracted to simple models of the world that are built on unquestionable facts.

As an example of this simple-world-philic aspect of human nature, consider the relationship between people’s perception of the severity of human-caused climate change and their perception of economic benefits of green energy policies. In principle, these should be independent issues and a person’s opinion on one should not necessarily predict their opinion on the other.

Many people argue that human-caused climate change will have a catastrophic negative impact on the earth and thus human well-being and many people also argue that green energy policies (e.g., taxing carbon emissions) will have a catastrophic impact on the economy and thus human well-being. However, these arguments are hardly ever heard coming out of the same person’s mouth (quadrant D below). Similarly, many people argue that the concern over climate change is overblown and many people argue that green energy policies will be a boon to the economy by creating clean-tech jobs. But again, these are hardly ever the same people. Why is this? I think it is just a manifestation of people wanting the world to be simple. We don’t want conflicting information, nuance or shades of gray. We want nice neat conclusions, in other words, we want “facts”.



Is science the Vatican or The Wild West?


Since people desire facts and since most important contemporary issues rely to some degree on scientific conclusions it was perhaps inevitable that a notion of “Science” (proper noun with a capital S) would emerge where Science is thought of as the official arbiter of facts. Many people imagine that Science is an authoritative body that can swoop in, perform its magic, and definitively deem some controversial statement to be fact or fiction, true or false. I think of this view of Science as being somewhat Vatican-like in that it conceptualizes science as a hierarchical, centralized authority that should not be questioned.

This Vatican notion of Science not only comes from our innate simple-world-philia but is also taught to us in our education system. People tend to be taught science in school as if science is simply a catalog of conclusions that have been deemed to be true rather than a way of looking at the world and asking questions.

When I was in high school, I held this Vatican-like view of science. The more I learned about science the more confident I was in science’s ability to produce facts (I was moving from A to B in the diagram below).

Once I reached graduate school, however, I started doing science and I realized how messy the process is and just how complicated the real world is. I realized that the idea that Science is magic and can swoop in and declare facts was extremely naïve. This realization has caused me to move from point B to point C in the diagram below.



Going through graduate school also revealed to me that the Vatican notion of Science is a very poor model. It turns out that science is not governed by high priests who can authoritatively separate fact from fiction. In reality, the scientific process is decentralized with groups and organizations around the world competing with each other to come up with the best and most complete descriptions of reality. There are not strict rules that constitute how scientific questions should be framed and there are fundamental disagreements between groups and individuals on how to go about asking and answering questions. In this way, science is much more like the lawless American Wild West than it is like the Vatican: decentralized authority, no definitive rules, everyone free to make their own argument.

At first glance, it may seem like a weakness that science is more like a free-for-all than a definitive authority. However, this aspect of scientific inquiry is actually one of its greatest strengths. The world is simply too complicated, and human beings are too cognitively flawed, for some central organization to play the role of arbiter of truth. It is much easier to arrive at the truth through a free market of ideas where everyone is able to put forward their description of the world. Eventually, the descriptions that survive the most attacks from others are the ones that we have the most confidence in.

So, it may be the case that science has an over-rated ability to produce unquestionable facts, but this hardly means that science can’t tell us anything. Many ideas have been shown to be robust to so many attacks, that they can be considered to be true beyond any reasonable doubt. For climate science these include the fundamentals that the greenhouse effect exists, humans are increasing greenhouse gasses which are warming the planet substantially, and there are substantial negative impacts associated with this warming.

I find that the Vatican notion of Science is commonly held on both the political left as well as the political right in the United States and that this model frames how the politics of climate change get discussed. The primary difference between the right and the left is not on how they conceptualize science but how much legitimacy they give Science. The far left tends to articulate that imminent catastrophe from human-caused climate change is a Scientific fact. Given the perceived legitimacy of Science on the left, it is thought to be either insane or evil to question this (panel A below).

The political far-right, however, does not grant that Science has legitimately earned its authority. Rather, they tend to think of Science as a corrupt organization, built and populated by their ideological opponents (panel B below). In this view, it is quite noble to push back against fraudulent, ideologically-driven Science and doing so makes one comparable to Galileo.

The conversation regarding climate change could be defused quite a bit if people realized how flawed the Vatican notion of Science is. The left would have to discontinue the strategy of using “facts” as a bludgeon to end debate and the right would have to admit that conspiracies and collusion are simply not possible in such a decentralized process (panel C below).

Screen Shot 2017-07-31 at 3.30.14 PM

“Facts” about the future

Many aspects of climate science revolve around projections of what human and natural systems might be like in a century. It would be ideal if we could agree on “facts” about what will happen in the future but this is just wishful thinking. Much of the problem comes from the things we care most about suffering from compounding uncertainty.

Also, projections of the future are most prominently promulgated by the relevant experts and Interestingly, uncertainty may be underappreciated by experts precisely because they are experts. People often assume that there is a monotonic relationship between knowledge on a given subject and ability to predict outcomes related to that subject (i.e., people imagine going from A to B to C in the diagram below as they gain expertise/knowledge on a given subject).


However, a lot of subjects suffer from fundamental uncertainty that you simply cannot get around by increasing your expertise/knowledge. This causes the ability to predict to ‘saturate’ (point B to C’ above). Therefore, an expert may imagine that they are at point C when they are really at point C’ and thus be especially overconfident in their ability to predict.

A salient example of this phenomena is seen in sports analysts, like the American college basketball analysts that are featured prominently every March on CBS and ESPN. These analysts almost certainly have much more expertise/knowledge of American college basketball than the general public. After all, these analysts generally grew up playing countless hours of basketball, being exposed to many playing/coaching styles. Most of them played and/or coached college basketball themselves and thus they have intimate knowledge of what goes on behind the scenes. Many of them have personal connections with current players or coaches. Finally, it is their full-time job to watch games and discuss various team’s strengths and weaknesses.

You might think that all of this knowledge/expertise would translate into a supreme ability to predict the Final Four of the NCAA basketball tournament. However, every March this experiment is conducted every April we find that the predictions from the analysts scarcely do any better than the average person who casually submits a bracket to their office pool.

It turns out that for college basketball a little knowledge goes a long way and all the additional knowledge that the TV analysists have only moves them from B to C’ rather than from B to C. This is because after a little bit of knowledge you run up against fundamental uncertainty that expertise cannot help you defeat. We see this overconfidence of experts over and over again in a variety of fields (See Nate Silver’ The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t and Philip E. Tetlock’s Expert Political Judgment: How Good Is It? How Can We Know?).

It may be objected that the above analogies are irrelevant to climate science since the climate system is a physical system and is thus less complicated than a basketball tournament or political elections that involve predicting human behavior. For one thing, the effect of policy prescriptions for the mitigation of climate change do involve predicting human behavior. Regardless, even if we restrict our analysis to predictions of the physical world, it is simply not clear how much trust we can put in these predictions. This is because we have never made, for example, a 75-year-out regional drought forecast before and thus we have never had an opportunity to be humbled by poor predictions.

All this is to say that predictions of the future have to be taken as being only loosely constrained. Of course, uncertainty cuts in both directions (our predictions could be more pessimistic or optimistic than turns out to be justified). Additionally, all this uncertainty also applies to any forecast of economic calamity that would supposedly come about due to a proposed green energy policy.

Ideology and “fact” finding

Science being more like The Wild West than The Vatican makes it much more difficult to corrupt since there is no central authority from which decrees are produced. However, the collective sociopolitical attitudes of the scientists themselves can influence scientific thinking on a subject and can be another obstacle for finding the truth.

Many climate scientists are open about their environmentalist views. Most of these scientists would claim that their emotion/advocacy fundamentally stems from the science itself (panel A below). Of course, the exact opposite claim is made by opponents of climate action who assert that most mainstream climate scientists are simply liberal activists and that their scientific results spring from their ideology, not the other way around (panel B below).


The problem with this contrarian view (panel B) is that it ignores two of the most fundamental driving forces in science:

  • To ultimately be proven correct by history. Nobody wants their legacy to be that they were part of an epic scientific blunder.
  • To advance one’s career by showing the errors of other scientists

Wild West science works as a free-market endeavor in the sense that everybody is essentially free to question everyone else’s work. The best way to make a name for yourself in science is to show that some established conclusion or paradigm is incorrect. Therefore, there is actually a huge incentive to challenge any idea that makes it into the mainstream. This is why you see high-profile research that purports to find little relationship between human caused climate change and various other phenomena:


Articles with titles that contain phrases such as “little change”, “no increase”, “unlikely to increase” would be impossible in right wing’s notion of Vatican Science and would be unlikely to come about if scientists felt that their primary thrust was to advance a political agenda.

Having said that, scientists are humans and humans are social beings who are influenced by the zeitgeist of their proximate culture. Unfortunately, as political polarization has increased in the United States, many of us are becoming more and more hermetically sealed into our ideological bubbles where our ideas are not challenged and we only hear from other people who agree with us. I do worry that this phenomenon has the power to influence the collective research output and communication of climate science.

Climate scientists tend to be overwhelmingly on the left end of the political spectrum and tend to be ideologically attracted (or at least unopposed) to policies associated with climate change mitigation. For example, I have seen the following cartoon used by climate scientists to defend their advocacy for climate action policies:


The way the bullet points are phrased it is difficult to disagree with them but in reality, there are legitimate concerns about potential deleterious effects of variously proposed climate policies. This is primarily because everything we materially value is made possible through affordable energy and many climate-action policies have the effect of increasing the price of energy. Much is made of various hockey-stick like charts that show negative impacts of climate change but an honest discussion requires grappling with the positive hockey sticks that affordable energy from fossil fuels have produced (like the amazing increase in lifespan, increase in food availability, reduction in poverty, reduction in infant mortality, reduction in a myriad of diseases, ect., that have been achieved).

The primary problem with the above cartoon is that climate-action policies might not lead to a “better world” by themselves (i.e., regardless of the consequences of human caused global warming). Thus advocates of this cartoon seem unaware that part of their sympathy for climate-action policies could be due to their ideological alignment with more progressive policies in general. People on the political left tend to have more biophilic tendencies than those on the political right. They tend to be more distrustful of corporations and capitalism as a means of distributing resources. Finally, they tend to have more faith in the ability (and right) of central or governments to regulate the private sector and to redistribute resources. None of the above values have anything to do with the physical science of climate change but these values make it more likely that people on the political left will support climate-action policies that protect the environment via government regulation.

The fact that climate scientists tend to be overwhelming on the left end of the political spectrum then leads to a social situation among scientists where it is very easy to agree with the political-ideological norms of the left and it makes it more taboo to question the severity of human-caused climate change. It means that scientists will feel some pressure (at least subconsciously) that their work should support the “good side”.

The attack on climate science from explicitly political organizations and individuals makes the situation even worse. In a purely Wild West science, scientists would feel no reservations about attacking the mainstream scientific view within a community (panel A below). Constant attack from the inside is what makes the mainstream view robust and gives us confidence that it is indeed correct. However, attacks on climate science from prominent politicians and outspoken political commentators have the effect of reorienting climate scientists such that they feel it is their duty to defend (rather than attack) the mainstream view (panel B below).

This is an unfortunate situation because scientists are smart enough to construct persuasive arguments in defense of most things. Thus, orienting scientists in defense of the mainstream view gives the outward appearance of enhanced legitimacy but in reality, it makes us less confident that the conclusions are correct (because the conclusions are being subjected to less scientific attacks).



Thus, in Wild West science, there is a tug-of-war between wanting to conform to social norms/ideological convictions and the desire to advance your career by challenging established conclusions (figure below). I believe that desire to be proven correct and to advance one’s career by showing others to be wrong is ultimately stronger than the desire to conform to the “good” side and this is ultimately why we can have confidence in the findings of science in general and climate science in particular.


To conclude, there is no Vatican Science that can swoop in and declaratively put controversial statements into binary categories of true or false. This is especially the case for predictions about the future. Science has its flaws (as all human endeavors do) but its decentralized nature and its incentive structure make it very difficult to corrupt. Ultimately, we must all exercise our own best judgment when weighing evidence and trying to better understand the world. If we could appreciate these things, it might make our public conversations about controversial issues a little bit less toxic and a little bit more productive.

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Climate Science for People Really in a Hurry 2 – Economics

This is a video summary of the findings in Burke et al., 2015 regarding the relationship between temperature and Gross Domestic Product (GDP) and how this relationship affects our projections of how global warming will impact the economy

Video Series:
Climate Science for People Really in a Hurry 1 – Basics

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Modeled vs. observed global temperature: with and without ‘makeup’

modeled and observed global temperature with and without makeupGlobal average surface air temperature is one of the most well-recognized metrics of contemporary climate change – hence the term ‘global warming’. One reason for this is that many impacts of climate change are expected to be proportional to the amount of global average warming that occurs over the next several decades to centuries. This is why, for example, the Paris Accord explicitly states climate change mitigation goals in terms of global average temperature.

Projections of global temperature are often based on the output from physical global climate model simulations and thus there is great interest in the agreement (or lack thereof) between modeled and historically observed global temperature.

Official reports (like the IPCC report), tend to present the comparison of modeled and observed global temperature in a format like that shown in ‘panel a’ above. This plot shows the model-mean and the model-spread (+/- 2 standard deviations) of global average temperature since 1861 (black) compared to observations (yellow). Various possible future scenarios are also shown (red, magenta, blue, cyan) which differ due to different assumptions about how much greenhouse gasses humanity might emit.

In ‘panel a’ there appears to be quite a bit of agreement between modeled and observed global temperature from 1861 to the present and thus this seems to provide compelling visual support for climate models’ ability to simulate/project global average temperature in the future.

However, I think that it is important to point out that part of this visual support comes from some nontrivial ‘makeup’ being applied to the comparison. Firstly, these temperature time series are all expressed as anomalies relative to a 1986-2005 baseline period (and then re-zeroed to be relative to preindustrial temperatures). This has the visual effect of forcing the models to essentially agree with each other and to essentially agree with observations over this 1986-2005 time period. Secondly, the spread around the model-mean value is calculated after the anomalies are taken which has the visual effect of minimizing the range of modeled temperatures. Overall, this results in an impressively small model spread around observations over the historical record and a relatively constrained spread for each of the individual future projections.

The raw model output, without this ‘makeup’ applied, is shown in ‘panel b’ above. In ‘panel b’, the y-axis is the absolute value of simulated and observed global average temperature in Kelvin. It is still the case that observations are more-or-less in the middle of the model simulations, but it can now be seen that the range of simulated values for absolute global average temperature is pretty large (~2.5C). In fact, this range is approximately as large as the amount of warming that we might expect to see over the remainder of the 21st century.

Does this matter? from a visual perspective, ‘panel b’ seems to inspire less confidence in our projections of future warming than ‘panel a’ does. However, the relevant question is: do model biases in the absolute value of temperature have a strong relationship with potential model biases in the projection of temperature change?

It seems as though the magnitude of the model biases in global average temperature do have some relationship with the magnitude of modeled future warming. However, these biases do not matter so much that they would seriously undermine the model projections over the next century or so (see discussion around Fig. 9.42a In Ch9 of Working Group I in the 5th IPCC Report; and discussion around Fig. 2 and Appendix B in Hawkins and Sutton, 2016). Therefore, I think it is reasonable to compare modeled and observed temperature change the way it is done in ‘panel a’ as long as we don’t completely forget about ‘panel b’.


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Defending science at the People’s Climate March

I accepted an invitation to speak at the San Jose People’s Climate March on April 29th, 2017 and I have reproduced what I said below. *Note that I do not necessarily endorse the People’s Climate March policy platform and I would not wish to defend any statements other than my own*.

Good afternoon. My name is Patrick Brown and I am a climate scientist.

I would like to say a few words today in the name of celebrating science – and in defense of science’s ability to inform society on issues of critical importance – like climate change.

Now as most of you know, the primary agent of current climate change is increasing levels of carbon dioxide from the burning of fossil fuels.

I want you to think about whether or not you would know this without modern science. Could you surmise this on an intuitive level?

Carbon dioxide is a colorless, odorless, tasteless gas. But despite its invisibility to our senses, the methods of science have allowed us to identify its existence and eventually measure it in the atmosphere.

The methods of science also allowed us to figure out that carbon dioxide contributes to what would become known as the greenhouse effect, and thus it can affect global temperatures.

When we began burning fossil fuels to power our societies, there was no intuitive reason to think that emissions of this invisible gas might be able to affect the global climate.

There was no intuitive reason to think that burning coal in Pennsylvania could contribute to sea level rise in Sydney….Yet we now know that this is the case.

In order to discover truths about our world that are beyond our intuition, we need to allow science to flourish freely.

let’s imagine for a moment that across the world, free scientific inquiry had been overtly suppressed over the last several centuries.

If free scientific inquiry had been suppressed, we wouldn’t be able to measure the temperature of the planet:

We wouldn’t know that the atmosphere is warming (as measured by a global network of weather stations, satellites, and weather balloons).

We wouldn’t know that the oceans are warming (as measured by ships, buoys, and satellites)

We wouldn’t know that the Earth’s ice is melting: sea ice, alpine glaciers and the Greenland and Antarctic ice sheets

And we wouldn’t know that global sea levels are rising

If we had accepted the stifling of free scientific inquiry we wouldn’t be able to ask questions about the future.

We would have no idea, for example, that if we were to burn all available fossil fuels, that would be sufficient to melt the entire Antarctic ice sheet over the next several thousand years – 6 million cubic miles of ice.

This would be enough melting to dramatically reshape the world’s coastlines.

This location where we stand would be under water, it would turn the California Central Valley into an inland sea, and it would It would essentially remove Florida from the map.

If we accepted the stifling of science we wouldn’t know that the rates of global warming under a ‘business as usual’ future are at least 10X faster than any global climate change experienced over the past 65 million years.

Finally, if we had stifled free scientific inquiry, we wouldn’t know how difficult it will be to limit global warming: We wouldn’t know that in order to simply stabilize global temperatures, we need to reduce carbon dioxide emissions by 80%.

Now, fossil fuels are not all bad – there is a reason that we have been using them. Everything that we materially value requires energy and historically, fossil fuels have provided the most affordable way to produce that energy.

This has led to successes that should not be ignored: large reductions in infant mortality, reduced rates of many horrible diseases, reduced poverty at a global scale, and robust increases in average lifespan.

But If science had been stifled, we would only know about the salient benefits of fossil fuel use and we would be totally ignorant to the dangers of burning fossil fuels.

Now, science has no “unquestionable truths” and as a scientist, I spend a great deal of my time questioning what other scientists think.

This skeptical aspect of science is precisely why we have so much confidence in scientific conclusions: Our confidence in the conclusions comes from the conclusions surviving challenge after challenge.

Thus, I have no problem with anyone challenging any scientific conclusion, including the findings that I just laid out.

BUT…but…If you want to question a scientific conclusion, you need to have good evidence (Preferably written up in a scientific paper and submitted to a scientific journal for peer review).

So I DO have a problem, when politicians or anyone else in power, have the hubris to cavalierly dismiss scientific conclusions out of hand – essentially dismissing hundreds of millions of cumulative hours of careful scientific work – simply on intuition.

and yes, referring to global warming a “Chinese hoax” fits into this category.

To conclude, I want to emphasize that free scientific inquiry, unencumbered by ideological opposition of those in power, is what has made it possible for us to understand the non-intuitive dangers of fossil fuel burning.

Namely that an invisible gas called carbon dioxide, that is produced from burning fossil fuels, is the primary driver of current climate change and that without curbing our emissions of this gas, we will experience rates of global change that are truly exceptional in the geologic record.

Therefore, any politician who engages in the suppression of inconvenient scientific conclusions or who has the hubris to dismiss those conclusions on intuition is being woefully irresponsible.

And that irresponsibility should be punished by damage to their reputations and a price paid at the ballot box.

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Climate Science for People Really in a Hurry

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2016 Update to our ’empirical unforced noise’ analysis

This is an update to our 2015 Scientific Reports paper: Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise. The paper used a novel statistical estimate of unforced variability that was derived from reconstructed and instrumental surface temperature records. We used our statistical estimate of unforced variability to aid in our interpretation of recently observed temperature variability (more info here).

Our paper used global temperature data through 2013 since that was the most recent year in the major global temperature datasets at the time that the paper was submitted. Below I update Figures 2 and 3 from the paper, incorporating the data from 2014-2016.


Figure 2 updated through 2016.


Figure 3 updated through 2016.

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