Guest essay by Michael Cochrane
Of the many important issues clamoring for the attention of world policy-makers and government officials, global climate change is among the most controversial. Its existence, likely effects on the environment, probable causes, and possible solutions have all been highly politicized. Many on the political left consider it the defining issue of our time, while many on the political right are highly critical of what they perceive as “junk” science undergirding the assertion of dangerous anthropogenic (human caused) global warming (AGW).
Policy solutions undertaken to deal with AGW, on the premise that it is dangerous (DAGW), will have massive monetary and non-monetary costs to society. Such high costs demand a correspondingly high degree of certainty regarding the likelihood of possible future scenarios. In particular, the scientific community must be able to show, with a very high level of confidence, that reducing or ceasing human activity associated with greenhouse gas emissions will stop or reverse global warming. If this is not possible, policymakers should assume that DAGW is essentially unstoppable and consider defensive measures (adaptation) as the most prudent policy approach.
One way to cut though the noise on climate change and help policy makers think clearly and rationally about governmental responses to the risks of global warming is to develop a risk or decision-scenario model. This can help senior policy makers explore alternative scenarios and decision outcomes before actually taking steps to commit national resources or enter into agreements with lasting economic effects.
Probability trees are valuable tools for modeling the potential outcomes of a succession of events. Each path along the tree from the origin to a terminal node—from root to tip of branches—describes one of potentially dozens of possible outcomes. Each node in the tree describes a possible event with two (or more) outcomes having a given probability of occurrence. A scenario is described by tracing a sequence of events along a path from the origin to a terminal node. The likelihood or probability associated with each path or scenario is found by multiplying the probabilities of all the event nodes along that path. The total probability for all possible paths described on the tree should sum to one.
Building a Climate Change Policy Decision Model
The following climate change policy model is designed to help us explore a range of scenarios associated with different answers to a sequence of questions fundamental to the issue of global warming and that must be addressed prior to proposing policy solutions. The questions are:
1. Is the earth actually warming? A summary of modern climate history suggests that from 1979 to the present there has been “a large disparity between surface thermometers, which show a fairly strong warming, and independent temperature readings of satellites and balloons, which show little warming trend” (Singer & Avery, 2007, p. xv).Rigorous data analysis (Heller, 2016) and application of statistical methods that control for heteroskedacity and autocorrelation (McKitrick & Vogelsang, 2014) suggest that apart from a step-wise change in global average temperature (GAT) around 1977 there has been no statistically significant warming trend since ~1958 or earlier.
2. If the earth is warming, is this actually a problem? There is some disagreement over this question, with global warming activists citing the potential for rising sea levels, more extreme weather events, famines and other catastrophes. Other scientists, however, argue that rising atmospheric CO2 levels and warming attributable to it may actually have net beneficial effects such as longer growing seasons, expanded growing ranges, increased plant growth, increased food production, and reduced morbidity and mortality from cold snaps. (Davis, 2005) (Singer & Avery, 2007)
3. If the earth is warming, and this is a problem, to what extent is human activity causing the warming? This question gets at the heart of the issue. Many environmental activists think human activity (i.e., burning of fossil fuels and other activities that generate CO2 and other so-called “greenhouse gases”) is the primary cause of global warming, while others believe warming is largely or wholly a natural, cyclical phenomenon primarily caused by solar cycles, ocean current cycles, and the eccentricities of the earth’s axial tilt and orbit. (Singer & Avery, 2007)
4. If human activity is the primary cause of global warming, will reducing this activity also reduce global warming? The assumption undergirding environmental policies such as the (now obsolete) Kyoto Protocol, the “Clean Power Plan” in the U.S., and the global climate agreement negotiated in Paris in late 2015 is that if anthropogenic CO2 causes warming, then reducing the output of anthropogenic CO2 will retard the warming trend. Many scientists reject the deterministic view of the relationship of anthropogenic CO2 and climate change assumed by such policies, arguing that there is a high degree of uncertainty associated with understanding the effects of changes in atmospheric CO2. (Posmentier & Soon, 2005)
5. If human activity is not the primary cause of global warming, is it still possible to stop it? Posing this question acknowledges the existence and the problem of climate change, but forces consideration of alternative solutions.
Each of the five questions is modeled in the probability tree (Figure 1) by an event node with two possible outcomes. There are six unique paths through the tree resulting in a total of six outcomes. Four of the outcomes require some type of policy response or proposed solution. Table 1 lists the model outcomes along with a suggested high-level policy approach or solution strategy.
The next step in preparing the probability tree model is to assign probabilities to each of the five events in the tree. This might best done by eliciting estimates from subject matter experts, who should be able to ground their estimates in an understanding of the current state of knowledge in their field and offer persuasive empirical evidence for any hypotheses or theories underlying their judgments. However, the beauty of a decision model is that one can still learn a great deal about appropriate policy responses by experimenting with a range of different probabilities and observing the degree to which the outcome values are sensitive to changes in the event probabilities.
Figure 2 shows the probabilities associated with the first two questions. Although satellite and radiosonde data show no statistically significant warming over the last twenty years, and the possibility that warming since ~1960 is limited largely to a stepwise rise around 1977 with no long-term trend either before or after (McKitrick & Vogelsang, 2014), much of the scientific community argues that the earth has generally been warming over the last several decades. We have, therefore, elected to assign a probability of 0.9—near certainty—that the earth is warming.
Although there is not a broad consensus regarding the degree to which global warming will be a problem for humanity, and such palaeoclimatologists and palaeoecologists as Hubert H. Lamb presented evidence that warmer periods were healthier for all kinds of life on Earth, including humans (Lamb, 1965), the prevailing opinion among environmentalists and climate activists today seems to be that, on balance, a warmer environment would be a net negative outcome for the world, so again, to be conservative in our estimates, we have assigned a probability of 0.9 that global warming is a problem. Figure 2 now shows events one and two in sequence, with their associated assumed probabilities.
The issue of whether global warming is blamed on what is called anthropogenic carbon dioxide forcing (i.e., human activities such as burning of fossil fuels) seems to be more of a political than a scientific one. Most scientists appear to acknowledge that human-based greenhouse gas emissions contribute something to climate change, but the key question is whether anthropogenic CO2 forcing is the primary cause. There is debate over whether there is a strong scientific consensus on this question. However, for purposes of this initial modeling effort, we will give the benefit of the doubt to anthropogenic CO2 forcing and assign it a high probability of 0.9. Figure 3 shows the first three events in the probability tree.
If human activity is the primary cause of global warming, the next to last event models the question, “Does reducing the level of human induced greenhouse gas emissions retard or reverse the advance of global warming?” If human activity is not the primary cause of global warming, the final event models the question, “Is it still possible to stop global warming?” Figure 4 illustrates how we would model these questions in our decision tree.
We assign a probability of 0.5 to event four to reflect the level of uncertainty and indifference in the scientific and policy community about whether this is actually possible. We will eventually perform a sensitivity analysis on this probability distribution.
If the primary causes of global warming have nothing to do with human activity, it is highly likely we will be unable to intervene effectively in the complex climate system to reverse a warming trend. Therefore we assign a very low probability of 0.1 to event five.
In the completed model, we multiply the probabilities for each event along each of the six paths through the tree.[1] The resulting probability distribution at the six triangular terminal nodes reflects the relative significance of each of the outcomes.
Interpreting Model Results
Because we have already associated likely policy solutions to four of the six model outcomes, we can now associate the relative probabilities (or likelihood of occurrence) to the policy responses. In Table 2, we can see that, although current policy approaches and defensive measures both score the same if human activity is the primary cause of global warming, defensive measures are also an important response to the relatively small probability that we cannot stop global warming (given that it is not caused by human activity). Consequently, we combine these two scores for the Defensive Solutions policy response for a probability of 0.44. The most appropriate policy solution given this particular model would be those that direct national resources toward measures to defend the country against potentially devastating effects of climate change, e.g., rising sea levels or more frequent or severe droughts.
[1] The compound event probability distribution generated by the probability tree is based on the assumption that each of the event probabilities following the initial one is a conditional probability based on the prior event outcome.
Sensitivity Analysis
The probability scores for the top two policy responses are fairly close. So one of the first questions we must ask is, “how would the event probabilities in the model have to change for these scores to be equal?” Since the model is formulated in Microsoft© Excel™ we can use the “goal seek” function in the data tools menu to explore this possible outcome. We set the terminal probability score for “current policy approaches” to 0.4 and let the goal seek algorithm find the corresponding probability distribution for event four (reducing human activity). The model outcome “reducing human activity fixes global warming problem” must have an assigned probability of 0.55 or higher for current policy approaches to equal or exceed the scores for defensive solutions (assuming all other probabilities in the model are held constant). This is clearly visible in Figure 6, which shows that the these two general policy approaches are highly sensitive to changes in the probability that reducing human carbon dioxide emitting activities also reduces global warming.
Figure 7 shows the degree of sensitivity of the two major policy approaches to changes in the probabilities for event five. There is no point across the range of probabilities for this event at which the probability score for defensive solutions drops below that of current policy approaches. This is because the defensive solutions policy is also the appropriate response for the outcome in which global warming cannot be reversed given that human activity is not a primary contributor.
Figure 8 addresses model sensitivity to the probability associated with event three: whether human activity is the primary cause of global warming. As with event five, the model is insensitive to changes in event probability across the range of possible probability settings (again assuming all other event probabilities are held constant).
Varying the probabilities of events one and two has no bearing on the relative movement of the outcome probabilities scores we have been observing. This is because any change in these probabilities is applied uniformly across all the event probabilities downstream from these nodes.
Conclusions
The degree to which reducing anthropogenic CO2 forcing correspondingly retards global warming is the major driver of policy solutions. Our model shows that it does not matter whether human activity is actually the primary cause of global warming (90% probability). The currently advocated global environmental policies exemplified by the Kyoto Protocol, Cap and Trade laws, and the recently negotiated Paris climate agreement assume a deterministic relationship between global warming and anthropogenic CO2 forcing that operates in both directions. In other words, if humans caused it by their activity, they can “un-cause” it by reducing or ceasing that activity. This may not be the case. Our modeling effort suggests that we must be at least 55% certain that reducing human activity will cause a corresponding reduction in global warming before we even consider the current regulatory policies advocated by the environmental movement.
It should also not be overlooked that, even assuming a model heavily weighted toward problematic global warming caused by human activity, there is still an almost twenty percent probability that warming either is not happening or won’t be a significant problem if it is.
The cost of policy solutions undertaken to deal with the threat of climate change will be massive and will entail both monetary and non-monetary costs to society. Any benefit to society from such policies must be weighed against those costs. Not wanting to overly complicate an initial policy model, we intend to explore such a cost/benefit analysis in future research.
The likely high costs of climate change mitigation policies demand a correspondingly high degree of certainty regarding the likelihood of possible future scenarios. In particular, the scientific community must be able to show with a very high level of confidence, that reducing or ceasing human activity associated with greenhouse gas emissions will reverse global warming. If this is not possible, policymakers should assume that global warming is essentially unstoppable and consider defense measures as the most prudent policy approach.
Michael Cochrane, Ph.D., Engineering Management and Systems Engineering, is Founder of Value Function Analytics, a consulting firm that helps clients achieve their objectives by helping them to think about values. Also a writer with World News Group, he has expertise in statistical modeling and analysis.
Works Cited
Davis, R.E. (2005). Climate Change and Human Health. In P.J. Michaels, Shattered Consensus: The True State of Global Warming (pp. 183–209). Lanham, MD: Rowman & Littlefield.
Heller, T. (2016). Evaluating the Integrity of Official Climate Records. Paper presented at the annual meeting of Doctors for Disaster Preparedness, online at http://realclimatescience.com/wp-content/uploads/2016/07/Evaluating-The-Integrity-Of-Official-Climate-Records-4.pdf.
McKitrick, R.R., & Vogelsang, T.J. (2014). HAC robust trend comparisons among climate series with possible level shifts. Environmetrics 25(7): 528–547.
Posmentier, E.S., & Soon, W. (2005). Limitations of Computer Predictions of the Effects of Carbon Dioxide on Global Climate. In P.J. Michaels, Shattered Consensus: The True State of Global Warming (pp. 241–281). Lanham, MD: Rowman & Littlefield.
Singer, S.F., & Avery, D.T. (2007). Unstoppable Global Warming: Every 1,500 Years. Lanham, MD: Rowman & Littlefield.
and ppl trying to pass off models as empirical data and ppl trying to pass off gambling as engineering and ppl trying to pass off fantasy as science.
Help those scientists, who for personal benefit, promotion and money promoting that insane agenda (and most cases knowingly !)
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The planet has been warming for thousand’s of years ,well before humans had any influence at all .
We have had warmer temperatures ,higher levels of CO2 that brought greater plant growth so why was that not only ok but very positive? Now humans use some of the fuel laid down from those warmer periods and it’s considered bad ? Any global warming we get is a good while it lasts .
We all know this isn’t about global warming though the flim flam salesmen and some politicians continue to try to dupe the people that like to be lied to . The politicians knew along time ago that most scientists do not
share the doom and gloom of failed climate models and the grease balls trying to pitch it . But they do need more sources of money so “saving the planet ” works for them .
This systems approach is sensible.
Often CAGW skeptics are derided for arguing along the following lines:
1. It’s not happening.
2. If it is happening, it is not us causing it.
3. If it is happening, it is not dangerous.
4. If it is happening and dangerous, there is nothing we can do about it anyway.
But, those who would so deride fail to note that any one of those links being true negates all of their arguments. It is a perfectly valid cascade of possibilities, each of which need to be considered.
1. Really how clearly can we see what is happening at this point? Those are horrible data sets, with different methodologies, instruments, conditions, people, time spans, positions, altitudes… etc
2. If we later clearly show it is happening, can we be sure of the cause? Is it human activity? Or other.
3. And, if it is happening, how certain are we that it is dangerous? Engineering can deal with a lot of sea level rise issues, and over 100 years people can move. And now drought fears have been supplanted by flooding rain fears in many areas, will that increase food production and water supplies?
4. If it is happening and dangerous, can we prevent it? Elaborate artificial trading systems and artificial markets WILL NOT be the answer except to banks and financiers. Carefully applied alternative energy supplies (nuclear) and mitigation plans would seem a sensible approach.
As Homo Sapiens (and all other life) is doomed in the long run (the Sun will expand to fry everything on Earth) it’s merely a matter of time. We are but a mini-lightning-bolt in paleo-history. Any other interpretation is mere hubris. Come today, gone tomorrow to join the dinosaurs. I’m sure all the extinct species lived their lives to the fullest, so why not us?
How many generations forward do we — doomed to die within the next century — really care about? We will be gone. And so, the pragmatic horizon of our thinking/policking/activism is — what? — 2 generations max.
Leave it to our successors, with their framework of reference = 2 generations, to iterate their way forward.
Mother Nature will fix it … her way! Don’t worry, be happy!
My thoughts exactly. To Father Earth (Gaia, if you must) all life is just a miniscule, temporary and vulnerable scum on the rocks. It has no consequence or meaning.
Excellent post. I hadn’t thought of applying decision tress to climate change.
Seismic engineers use decision trees to assess earthquake hazard but in this case the branches of the tree are probability distributions (normal, log-normal, Gumbel, etc.) and the result at the end of each branch is a probability distribution that can be used to estimate the earthquake hazard.
“Policy solutions undertaken to deal with AGW, on the premise that it is dangerous (DAGW), will have massive monetary and non-monetary costs to society. Such high costs demand a correspondingly high degree of certainty regarding the likelihood of possible future scenarios.”
This is not a truly valid logical construct it seems to me because climate is already “dangerous”, and “global cooling” is potentially even more dangerous, which might be offset by any AGW. Simply treating all “danger” from AGW as if calamitous/catastrophic ignores the possibility that it’s gonna be a net negative, but not bad enough to warrant “massive non-monetary costs to society”.
opps, I meant “massive monetary and non-monetary costs to society …”
Good post and comments (Ristvan). Fairly basic decision theory MBA 101. Problem is the decision makers do not want a perfectly logical approach to evaluating probabilistic risk because it does not fit the outcome they want. Maybe an MBA in the White House would force the EPA to use it in their policy analysis; rather than having the EPA handcraft the analyses to fit the outcome desired.
An imaginary problem can be solved using any solution. This is the genius of the anthropogenic CO2 hysteria which has been sold as settled science, using political pseudo science. If there wasn’t a problem to begin with, it becomes much easier to solve.
I forgot to add “Maybe an MBA in the White House would force the EPA to use it in their policy analysis; rather than having the EPA handcraft the analyses to fit the outcome desired”
(… by a left wing former Chicago law school assoc. prof. / constitutional law lecturer, community organizer.)
First, Michael (Cochrane), thanks for a clear and well written article. However, I fear you’ve made a classic mistake when you say:
The mistake you’ve made is best expressed in the old adage,
Quoting the opinions of “environmentalists and climate activists” in this is as foolish as asking your barber if you need a haircut. Both environmentalists and climate activists obviously believe that a few degrees will bring Thermageddon … and their jobs depend on people believing that “warm = bad”.
However, for almost every kind of life, including us humanoids, warmer is better. And you don’t have to guess at the results, we’ve run the experiment. Read sometimes about how much fun the Little Ice Age was for humans and cows and birds and fishermen and all kinds of life.
At the worst, the very worst, I’d assign a fifty / fifty probability that warming will improve the world. My real guess would be 90 / 10 in the opposite way you have it—in other words, a ninety percent chance that warming will be overall beneficial, just as it has been in the past. To give it 90 / 10 in the direction you’ve claimed is to ignore the actual facts of history.
And of course … if we take warm / cold as fifty / fifty, the eventual odds at the end of the line change hugely.
Perhaps you could discuss the implications of how this would change your results, as a bit of valuable sensitivity analysis …
Regards,
w.
He stated early on that he was going to give the warmists every benefit of the doubt so that the results would be the absolute best case for them.
He then went on to show that even using such assumptions, it still was not possible to justify the changes the warmistas want.
Thanks, Mark, but I fear you miss my point.
There is no way, benefit of the doubt or not, that there is a 90% chance that warming is going to be a big problem. In fact, the planet has been warming now for about three centuries without any climate catastrophes of any kind.
Therefore, it is giving them the full benefit of the doubt to say it is 50-50 … because HISTORY SAYS OTHERWISE. History says warmth is beneficial … and there are plenty of retirees in Florida who don’t mind at all that on average it is not the dreaded 2°C warmer in Florida, it’s more like 10°C warmer or something.
I’ll give the warmists the benefit of the doubt as far as 50 / 50 …, but I’m not rolling over and playing dead.
Best regards,
w.
All depends on what the probabilities are. The chosen values reflect the ignorance of decision makers, not the real state of the science and technology.
GIGO in terms of working out what we should do: only useful in deciding what we probably will do if ignorance prevails
People… you have to realize the the use of cascading probability charts — no matter how the chart is worded, no matter if the branches are flipped or flopped, no matter what a ‘majority’ number of right-side derivations ‘suggest’ — is a thumb sucking exercise if any number of people buy into the issue that there is existential risk. Unfortunately the concept of existential risk has been compromised.
I’ll simplify by presenting two reduced charts,
Climate ‘mitigation’ for CO2 and sea level:
Existential risk? NO; Attention-getting? YES; Action? YES —> people are stupid.
Meteor impact ‘mitigation’ using all available technology starting at dawn of Space Age
Existential risk? YES; Attention-getting?NO; Action? NO —> people are stupid.
It’s stupid all the way down.
Whilst it was a nice idea to try to quantify the extent of the futility of climate change policy the answer is that the best way to determine what future policy should be is to get governments ask the voters the following question. Do you think that governments should take measures that will substantially reduce living standards increase the cost of living, cause thousands of people to die from energy property, and deprive developing nations of cheap energy ?This will be done in a probably futile attempt to resolve a problem which probably doesn’t exist because a warmer climate is probably a net positive benefit. The costs will be so great that funds available will be diverted from endeavours to feed the world, provide better global health solutions and care for those who can’t look after themselves.
Put in that perspective doing nothing is the best policy , and that’s a certainty.
Great article. I wonder if any of our rulers have looked at the problem this way? Silly question! The IPCC say that it is not possible to predict a future climate so I suggest that the first probability be set no higher than 0.5. As there are three possiblities (hotter, no change, colder; possibly) 0.33 would be a better figure.
My major problem with this article relates to the probability of using some technical solution that motivates or eliminates the problems that arise.
This is the biggest reason almost all long term predictions fail. An assumption of exponential continuation of the problem and an assumption that our technology is the same. I would say another thing to consider in this case is poor thinking about mitigations using existing technology.
I wrote a blog showing how both the club of Rome in the 80s which used sophisticated computer models, backtesting to “prove” model formulas and smart people have failed to produce models that work for more than a year without becoming extremely inaccurate. https://LogicLogiclogic.wordpress.com/category/climate-change
My main point here is that this model above shows only a 1% chance that technology will make this problem if it is a problem go away. That is close to 50 times too small. The reason I say this is that we are on an exponential curve of understanding everything from energy to chemical and physical processes that makes nearly any problem look solvable.
How difficult is this global warming problem? Each of the “impacts” has been studied poorly. Virtually no time has been put to looking at mitigstions available even with today’s technology. For instance, heat deaths in France were 15000 one year. 3 years later a bigger heat wave killed 10 people. Simple measures like fans and drinking water and going to air conditioned places for some people reduced the death rate by 99%. In a similar way many of the problems suggested have got existing solutions if they transpired.
The biggest technological changes coming are related to power and energy production and consumption. Solar energy and other energy sources are coming online and reducing costs yearly in a predictable way. It is extremely unlikely we are producing or using energy in the same way 50 years from now. The computer models all assume scenarios that co2 which is currently growing at 2ppm / year expands up to 10ppm / year when it is incredibly unlikely we will even continue the 2ppm for the century.
It’s important to note how transitory this problem is. We will eventually stop producing as much co2. Co2 levels will fall in the next century or possibly even in this century. Nobody knows how fast they will fall once we stop producing as much co2. The point is that the temperatures will fall after that. Therefore this is a problem this century maybe. The question then becomes how bad is it that we do all we are doing for a problem that may not happen and for which it will last a decade or two?
There is the issue that has been pointed out before that the technology and money we have in the future is more plentiful. This means trying to solve a problem with inferior technology is both much more expensive and difficult as well as possibly massively more expensive using money that could be used better and produce more growth that makes solving the problem in the future easier. By spending vast amount of money we stunt our future and hurt our children more than bequeathing onto them a problem which may be easily fixed in their time.
Almost all future predictions have failed miserably because they didn’t anticipate changing technology and the options it gave people to substitute or expand whatever was needed to circumvent the problem.
In some cases we don’t even realize we are doing things that are positive. Seeding the atmosphere with co2 has increased agricultural productivity by 30% in the last 70 years. We would not want to reduce co2 levels in the atmosphere now even if we had the choice. Billions might starve if we reverted to lower co2 of 1945. This was one of those unanticipated things.
Another thing to factor into the model above is that in previous millennia and even millions of years ago temperatures were warmer and nothing bad seemed to happen. In fact for most of the evolution of life that exists today temperature on earth was 8 degrees or more hotter and everything evolved and prospered during these times. The chances that 0.5, 1 or even 2 or more degrees will cause catastrophic impacts on life are negligible given this fact alone.
I think you might also add a “public choice” node: there is a difference between what government intends to do, and what it actually ends up doing, so would a purported policy of CO2 reduction actually reduce CO2? How much more do we need to deflate that when speaking globally -. Just because a domestic policy might call for reduction, does that mean global players will abide? What would the cost of that enforcement look like?
There are no inductive inferences
Karl Popper