Tag Archives: climate science

Paul Krugman explains how to break the climate policy deadlock

Paul Krugman — Nobel Laureate economist, #5 on Prospect magazine’s 2015 list of the world’s top “thinkers” —  gives us powerful advice about the climate policy debate in his August 12 NYT op-ed (similar to this from a February column).

Paul Krugman

Paul Krugman. Creative Commons license.

Here’s how I would approach the issue: by asking how we know that a modeling approach is truly useful. The answer, I’d suggest, is that we look for surprising successful predictions. General relativity got its big boost when light did, in fact, bend as predicted. The theory of a natural rate of unemployment got a big boost when the Phillips curve turned into clockwise spirals, as predicted, during the stagflation of the 1970s.

So has there been anything like that in recent years? …Were there any interesting predictions from … models that were validated by events?

In fact he is discussing his own field, macroeconomics — but this insight has deep roots in the philosophy of science and applies as well to climate science. Predictions are the gold standard for validating theories. In The Structure of Scientific Revolutions (1962) Thomas Kuhn described failed predictions that undermined dominant paradigms (e.g., the Michelson–Morley experiment) and successful predictions that helped establish new paradigms (e.g., the orbit of Mercury). He said…

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Nassim Nicholas Taleb warns us about climate change

Summary:  This is the second post looking at statistician Nassim Nicholas Taleb’s insights about “ruin” risks, and what they tell us about climate change. Here we look at his warning about climate change and two factors he ignores: the duration of the climate risk window and the odds of a climate disaster. The danger is real but the stories that we face certain doom are wild exaggerations, which make rational preparation more difficult. The previous post was Nassim Nicholas Taleb looks at the risks threatening humanity.

Cover of "Turning the Tide On Climate Change" by Robert Kandel

Cover of “Turning the Tide On Climate Change” by Robert Kandel (2009).

Yesterday’s post examined a methodology developed by a team including Nassim Nicholas Taleb for identifying “ruin” risks, where the result is non-recoverable for global civilization — or even the biosphere (described in “Mathematical Foundations for the Precautionary Principle“).

They wrote a note applying their method to one of the major risk debates of our time: “Climate models and precautionary measures” in Science and Technology, in press. The authors are brilliant, and it states with unusual clarity common arguments for radical and immediate action to fight climate change. Here’s the core of their analysis (it’s worth reading in full).

“Those who contend that models make accurate predictions argue for specific policies to stem the foreseen damaging effects; those who doubt their accuracy cite a lack of reliable evidence of harm to warrant policy action. These two alternatives are not exhaustive. One can sidestep the “skepticism” of those who question existing climate-models, by framing risk in the most straight-forward possible terms, at the global scale. That is, we should ask ‘what would the correct policy be if we had no reliable models?’

“We have only one planet. This fact radically constrains the kinds of risks that are appropriate to take at a large-scale. Even a risk with a very low probability becomes unacceptable when it affects all of us –– there is no reversing mistakes of that magnitude.

“…While some amount of pollution is inevitable, high quantities of any pollutant put us at a rapidly increasing risk of destabilizing the climate, a system that is integral to the biosphere. Ergo, we should build down CO2 emissions, even regardless of what climate-models tell us.

“…This leads to the following asymmetry in climate policy. The scale of the effect must be demonstrated tube large enough to have impact. Once this is shown, and it has been, the burden of proof of absence of harm icon those who would deny it.”

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Science into agitprop: “Climate Change Is Strangling Our Oceans”

Summary:  The public policy debate about climate science shows the dysfunctional nature of the US media. It’s one reason why making effective public policy has become difficult or impossible. Here’s another example of how propaganda has contaminated the news reporting of this vital subject, looking at stories about a new study of our oceans.

Oxygen loss in the oceans

Image courtesy Matthew Long, NCAR. It is freely available for media use.

NCAR’s press research accurately describes the paper: “Widespread loss of ocean oxygen to become noticeable in 2030s” (although it omits a crucial detail, mentioned below). Phil Plait at Slate turns this into agitprop:  “Climate Change Is Strangling Our Oceans“. His conclusion: ““messing with {the ocean} habitat is like setting fire to your own house. Which is pretty much what we’re doing.” Maddie Stone at Gizmodo also has a sensational headline “The Oceans Are Running Low on Oxygen” (the paper says nothing like that; for example, “detectable change” does not imply a “low” level).

To see how science becomes sensational propaganda let’s start by looking at the paper — “Finding forced trends in oceanic oxygen” by Matthew C. Long et al, Global Biogeochemical Cycles, February 2016. Ungated copy here. It is interesting and valuable research about climate dynamics. The abstract…

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Imagine the horrific fate of the losers after the climate policy debate ends

Summary: The appropriate public policy response to climate change is one of the great issues of our time, driving one of the longest yet inconsequential debates in modern US history. Yet everything comes to an end, eventually. This post speculates what that end might mean for the activists and scientists on each side if they lose. The consequences of defeat might mar the lives of ten thousand people in America (more around the world), yet has been little discussed.

Are you now, or have ever been, a climate denier?

Burning of Anne Hendricks as a Witch in 1571. Engraving by Jan Luyken (1685).

Burning of Anne Hendricks as a witch in 1571. Engraving by Jan Luyken (1685).

The US public policy debate about climate has run for 28 years, starting the clock from James Hansen’s famous Senate testimony. Although the results have been meager, I suspect it’s like a geological fault. Massive forces moving but locked together, with the stress accumulating year by year. People live on it, complacent since nothing has happened. Then …boom.

There are many possible intermediate outcomes, such as slow political and climate change over generations. We remember the exciting outcomes — ice ages and revolutions — but slow evolution is the most frequent outcome. But sometimes the extreme outcomes become unusually likely. I believe climate is one of them. The political debate has become a game in which nobody claims the pot. It grows to immense size as both sides bet more than they can afford to lose. Each confident of victory; neither prepares for possible ruin. It’s a commonplace in military history.

The outcome will result from a combination of weather and politics, contingent on random (or unpredictable) events. Whatever the outcome, the long-term fate of 21st century climate change might mock it. The good guys often lose in politics.

Here are guesses about some “tail outcomes”, two possible extreme outcomes that illustrate the stakes in this now deadlocked political debate. Either the climate science institutions — and climate scientists — win, or the skeptics win.

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We can end the climate policy wars: demand a test of the models

Summary: This is the last of my series about ways to resolve the public policy debate about climate change. It puts my proposal to test the models in a wider context of science norms and the climate science literature. My experience shows that neither side of the climate wars has much interest in a fair test; both sides want to win through politics. Resolving the climate policy wars through science will require action by us, the American public.

Global Warming

Ending the climate policy debate the right way

Do you trust the predictions of climate models? That is, do they provide an adequate basis on which to make major public policy decisions about issues with massive social, economic and environmental effects? In response to my posts on several high-profile websites, I’ve had discussions about this with hundreds of people. Some say “yes”; some say “no”. The responses are alike in that both sides have sublime confidence in their answers; the discussions are alike in they quickly become a cacophony.

The natural result: while a slim majority of the public says they “worry” about climate change — they consistently rank it near or at the bottom of their policy concerns. Accordingly, the US public policy machinery has gridlocked on this issue.

Yet the issue continues to burn, absorbing policy makers’ attention and scarce public funds. Worst of all, the paralysis prevents efforts to prepare even for the almost certain repeat of past climate events — as Tropical Storm Sandy showed NYC and several studies have shown for Houston — and distracts attention from other serious environmental problems (e.g., destruction of ocean ecosystems).

How can we resolve this policy deadlock?  Eventually, either the weather or science will answer our questions, albeit perhaps at great cost. We could just vote, abandoning the pretense there is any rational basis for US public policy (fyi, neither Kansas nor Alabama voted that Pi = 3).

We can do better. The government can focus the institutions of science on questions of public policy importance. We didn’t wait for the normal course of research to produce an atomic bomb or send men to the moon. We’re paying for it, so the government can set standards for research, as is routinely done for the military and health care industries (e.g., FDA drug approval regulations).

The policy debate turns on the reliability of the predictions of climate models. These can be tested to give “good enough” answers for policy decision-makers so that they can either proceed or require more research. I proposed one way to do this in Climate scientists can restart the climate change debate & win: test the models! — with includes a long list of cites (with links) to the literature about this topic. This post shows that such a test is in accord with both the norms of science and the work of climate scientists.

We can resolve this policy debate.  So far America lacks only the will to do so. That will have to come from us, the American public.

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Milton Friedman’s advice about climate models, & how to win the policy debate

Summary: The vital public policy debate over climate change is deadlocked. This is the sixth in a series about ways to restart the debate — and resolve it. This post gives Milton Friedman’s advice about the role of predictions as the gold standard for validation of theories. This implies that the key to policy action is testing climate models, the only means to give a majority of the public confidence in their forecasts.

“For such a model there is no need to ask the question ‘Is the model true?’. If ‘truth’ is to be the ‘whole truth’ the answer must be ‘No’. The only question of interest is ‘Is the model illuminating and useful?'”

— G.E.P. Box in “Robustness in the strategy of scientific model building” (1978). He also said “All models are wrong; some are useful.”

Milton Friedman

Milton Friedman.

The debate about public policy for climate change has deadlocked. There are many factors at work, but two stand out as unnecessary problems — as “own goals” by scientists. First they didn’t provide information about data and methods to their opponents (there are always opponents to such large public proposals). Second they didn’t provide compelling proof that climate models’ predictions are reliable — often ignoring the large literature about validation of theories and models.

This series suggests that we restart the debate by better using our knowledge about the methodology of science — especially about models, the embodiment of theories. Box’s insight above applies strongly to debates about policy, where decision-makers are seldom masters of the subject — and so must rely on scientists’ insights.

Previous chapters looked at suggestions about testing models from Paul Krugman, Daniel Davies, and Karl Popper. This post examines a seminal essay by Milton Friedman about the use of theories. Like Karl Popper, he sees predictions as the gold standard for validation of theories. Theories’ value lies in their ability to make accurate predictions, not the degree of their fidelity to nature. That is, abstractions and simplifications are useful if they improve predictions; additional complexity or detail is not useful if it fails to enhance predictions.

Friedman was discussing economics, but these excerpts apply with equal force to climate science.

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Karl Popper explains how to open the deadlocked climate policy debate

Summary: Many factors have frozen the public policy debate, but none more important than the disinterest of both sides in tests that might provide better evidence — and perhaps restart the discussion. Even worse, too little thought has been given to the criteria for validating climate science theories (aka their paradigm) and the models build upon them. This series looks at the answers to these questions given us by generations of philosophers and scientists, which we have ignored. This post shows how Popper’s insights can help us. The clock is running for actions that might break the deadlock. Eventually the weather will give us the answers, perhaps at ruinous cost.

“Confirmations should count only if they are the result of risky predictions; that is to say, if, unenlightened by the theory in question, we should have expected an event which was incompatible with the theory — an event which would have refuted the theory.”
— Karl Popper in Conjectures and Refutations: The Growth of Scientific Knowledge (1963).

“I’m considering putting “Popper” on my list of proscribed words.”
— Steve McIntyre’s reaction at Climate Audit to mention that Popper’s work about falsification is the hallmark of science, an example of why the policy debate has gridlocked.

This graph creates a high bar for useful predictions by climate models

Global fossil carbon emissions

From the Department of Energy’s Carbon Dioxide Information Center.

What test of climate models suffices for public policy action?

Climate scientists publish little about about the nature of climate science theories. What exactly is a theory or a paradigm? Must theories be falsifiable, and if so, what does that mean? Scientists have their own protocols for such matters, and so usually leave these questions to philosophers and historians or symposiums over drinks. Yet in times of crisis — when the normal process of science fails to meet our needs — the answers to these questions provide tools that can help.

A related but distinct debate concerns the public policy response to climate change, which uses the findings produced by climate scientists and other experts. Here insights about the dynamics of the scientific process and the basis for proof can guide decision-making by putting evidence and expert opinion in a larger context.

A previous post in this series (links below) described how Thomas Kuhn’s theories explain the current state of climate science. This post looks to the work of Karl Popper (1902-1994) for advice about breaking the gridlocked public policy debate about climate change. At the end of this post is the best-known section of his work about this.

Popper said scientific theories must be falsifiable, and that prediction was the gold standard for their validation. Less well known is his description of what makes a compelling prediction: it should be “risky” — of an outcome contrary to what we would otherwise expect. A radical new theory that predicts that the sun will rise tomorrow is falsifiable by darkness at noon — yet watching the dawn provides little evidence for it. Contrast that with the famous 1919 test of general relativity, whose prediction was contrary to that of the then-standard theory.

How does this apply to climate science?

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