I am not a climate scientist. I'm a nuclear engineer. But having spent over thirty years at Oak Ridge National Laboratory (ORNL), I know good science and good R&D technique when I see it. I'm frequently asked my views on the global climate change debate. During my years at ORNL, I "rubbed elbows" with a number of outstanding scientists involved in climate research and simulation. I approach the issue from the perspective of someone schooled and experienced in the application of the Scientific Method, and one who is intimately familiar with the challenges of understanding and simulating large, complex systems.
So, with some reservations, I'm going to (finally) share my views here. In a Question & Answer interview format.
QUESTION 1: Do I believe the climate is changing?
ANSWER: Of course! During the not-too-distance past, the "temperature" of the earth has been both much hotter and much colder than it is now and has been during my lifetime. Most of the wildest swings in temperature predate significant human populations and the industrial revolution. Witness:
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| History of Earth's Temperature (Ref: Glen Fergus @ http://commons.wikimedia.org/wiki/File:All_palaeotemps_svg.svg) |
QUESTION 2: Do I believe humans and human activities are a major driver of climate change (i.e. do I believe in Anthropogenic Warming"?
ANSWER: I'm agnostic on this issue. I've examined a robust sample of the available scientific information on anthropogenic warming. When examined objectively and in the context of issues I'll note below, it simply isn't conclusive. I'm NOT saying we humans aren't driving climate change. We might be. But the available evidence, viewed in context, isn't compelling (at least to me and many technical professionals like me).
Given the emotional charge surrounding this issue, I do feel compelled to offer a bit of my reasoning with regard to why I'm agnostic about Anthropogenic Climate Change. My reasoning, as simply as I can compress it here comes down to:
1.
HISTORY:
As noted above, the Earth's climate has been both much hotter and much colder than it now is – and these swings obviously had nothing to do with human activities. Therefore, it is reasonable to believe the earth's temperature should continue to vary with time.
2.
KNOWLEDGE: The phenomena and mechanisms determining the Earth's climate are extraordinarily complex, and our understanding of many of these mechanisms is rudimentary at best. The various phenomena are coupled in extremely complex ways. Viewed from an engineering perspective, the system contains both "positive" and "negative" feedback effects, and both linear and non-linear phenomenon. It is neither a closed or an open system, but some hybrid of the classical definition of these systems. I spent much of my career simulating extraordinarily complex nuclear reactors and severe accidents in nuclear reactors. That's kid's play compared to the challenge of simulating the complexity of the earth's biosphere and it's climate.
3.
MODELS: Our climate change models simply "aren't there yet". We cannot yet accurately predict climatic temperature changes for one-two decades – much less a century or more. (Heck, we can't accurately predict the temperature in East Tennessee a few days in advance.) As evidence, I'll simply point out that only a couple of some ninety major climate change models used by the global climate simulation community accurately predicted the "pause" in climatic temperature escalation we've witnessed during the past fifteen years or so. You can easily overwhelm yourself with articles about this development by "googling" "climate models" and "pause". Here's a compendium of predictions assembled by
Roy Spencer (with whom I have no affiliation):
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| Compilation of Global Climate Model Predictions vs. Observed Data (Ref. DrRoySpencer.com) |
The errors between the predictions and the actual observed global temperatures have grown over the past ten years of so. (Some in the climate modeling community have attempted to explain away the poor correlation between the predictions and the observations by citing any number of unexpected natural phenomena that were responsible for the differences.
But doesn''t that actually support my point?)
I know from decades of complex simulation work, that the best indicator of one's understanding of a phenomena is one's ability to predict the future behavior of that phenomenon. Judging by that standard, we have a long way to go in climatic modeling. The problem is no-doubt some combination of missing physics and phenomenon, physics for phenomena that are modeled incorrectly, missing or incorrect feedback loops, and spatial and temporal smoothing/averaging schemes.
George Box said, "all models are wrong but some are useful". Sherrell Greene says, "... and the only way to know which models are useful is to get the data." (Oh... and one other thing I learned during my simulation career is that often the most important thing one gains from a simulation isn't the answer, but rather the ability to ask more intelligent questions.) This leads to the next issue...
4.
DATA: Our climate data sets aren't yet sophisticated enough to validate the models. It is virtually impossible to validate climatic models in the classical engineering sense of the term. The problem has to do both with the specific parameters (variables) the models predict (spatially and time-average variables) and the limitations of the parameters we can actually measure and the data we can actually collect. Put simply, due to the enormous geospacial and temporal data averaging/smoothing required in the simulation models, it's extraordinarily difficult to define a data collection paradigm that accurately samples the actual parameters the models are calculating. After all, what is "the Earth's average temperature"?
This challenge is not unlike having a model that predicts the "average heart rate" of an American. Exactly what data does one collect (and where and when does one collect it), to obtain a suitable data set for validation of the model's predictions? And once we have the "average heart rate", how do we interpret and use the information? When you can't actually measure what you are predicting, you are forced to synthesize values for the predicted parameters from parameters you can measure. This "data synthesis" problem as been the source of countless pains and sorrows in the simulation business since the inception of computer simulation. Data measurement uncertainty, instrument bias, spatial averaging, time averaging, data interpolation, and data extrapolation of actual measured values can be the devils' workshop (wittingly or unwittingly). One simple case in point: Steve Goreham, the Executive Director of the Climate Science
Coalition of America (with whom I have no affiliation) has shared
two posts (
here and
here) that articulate the common-sense concerns many have
today with the prevailing "scientific community" (whatever and whomever
that is) view on global warming...
5.
ORGANIC "PRESSURE" IN THE CLIMATE RESEARCH ENTERPRISE. There are many, many fine scientists conducting climate change research. They are professionals of the highest skill and integrity. (I believe the vast majority of researchers fall into this camp.) However, any "society" produces more of what it rewards. In the scientific research community, one of the most important metrics of professional success is the level of research funding one secures and sustains. And in this, the squeaky wheel does usually get the grease. Speaking as one who spent over thirty years in the federal research complex, I know
it is far easier to attract and sustain research funding to attack an imminent crisis, than it is to attack a slowly evolving issue with uncertain consequences. The result of this reality is that the "organic" pressures (often subliminal) within the international climate research enterprise will naturally tend to promote an atmosphere of doom and gloom. It is simply a fact that many of those in the scientific community who
most loudly trumpet the scourge of man-made climate warming are the
one's whose careers depend on the flow of national and international
dollars into climate change research. (Cautionary Note: this doesn't, by the way, mean the doom and gloomers are wrong – just that one should maintain an healthy scientific skepticism about the entire matter.) This relates to my final issue...
6.
DOGMA vs. THE SCIENTIFIC METHOD. Finally, I'm extremely concerned about the
defensive and unprofessional attitude some in the climatic research community take with regard to those who question the status quo or their definition of the scientific community's "consensus opinion" on climate change. (The emails revealed via the highly-publicized and unethical hack into the emails of the Climate Research Unit at the University of East Anglia in 2009 spotlighted this type of behavior.)
Be careful when the first response to questions or criticism by anyone claiming to represent the scientific
community is to disrespect,
disparage, and otherwise question the intelligence or honesty of the
one posing the question. This is a sure sign the "expert" has abandoned the Scientific Method in favor of his or her adopted dogma.
QUESTION 3: What should we do about climate change?
ANSWER: First, we should continue our climate simulation and climatic data collection activities. Simulation models are the ultimate laboratory for integrating our knowledge and testing hypotheses – but only when the correct data is available for validation of the models.
Beyond that, the answer to this question really deconvolves into a series of other questions:
- How credible are are current long-term climatic predictions (and in particular, are they sufficiently credible to inform and/or drive national and international policy decisions)?
- Presuming current global warming predictions are credible, what are the implications of these predictions for humans & the biosphere (barring a change of course)?
- What can we really do about the factors that may be driving climate change?
- What are the negative and beneficial impacts of global climate change, and WHO/WHERE are the "winners and losers" (and there are both) if the dire global climate change predictions are true?
- What are the cost/benefit parameters for identifiable mitigative actions?
At this point, I'm prepared to say that pumping more carbon dioxide into the atmosphere isn't a good idea. I just don't know how bad the consequences of doing so actually are in light of all the other uncertainties, unknowns, and known factors impacting global climate change. So it's almost impossible to quantify the "cost/benefit" ratio of various proposed climate change mitigation actions. Thus I'm skeptical about the wisdom of extremely costly mitigative actions.
Frankly, I'm also skeptical we can do much, on a global scale, to reduce net green house gas emissions over the next few decades. We
should extract every reasonable benefit from new behaviors and
new technologies. But, we must stay grounded in "the possible" rather
than in a dreamworld that will never be. Fossil fuels are king and will remain so (globally) for many decades. Clean coal technology isn't here yet.
So the most important question may well be:
- How can we best adapt to expected climate change scenarios?
I'm encouraged by signs that the dialog is beginning to shift to this question (see:
today's post by Uri Friedman and Narula at theAtlantic.com ).
Well, this post became much longer than I had planned. To sum it all up,
- Yes, the climate is changing,
- It isn't clear humans are the major contributors to the change, and
- I feel our time and treasure is best spent seeking realistic strategies to adapt to the most probable climate change scenarios, rather than pursing unrealistic and costly schemes that have little real chance of reducing net global green house gas emissions to the levels many in the climate change community feel are required to halt global warming.
Above all, respect the Scientific Method. It keeps us honest.
Just Thinking,
Sherrell
