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What Can a Non-Scientist Do?

by Orrin H. Pilkey | August 4th, 2008
posted by Erica Rowell (Editor)


Permalink | 7 comments
Googling almost any aspect of global warming returns such a dizzying array of opinions, what’s a non-scientist to think? Reporters and scientists are trying to provide some guidance. Here’s my advice.

Last week New York Times reporter Andy Revkin sparked an online conversation about the difficulty of covering “conflicting findings” of ongoing research in climate science. The folks at Realclimate.org picked up on this thread of “journalstic whiplash,” noting how news coverage of a scientific discussion on, say, global warming and hurricanes can come off as “ping-pong across the media” and give the sense that “scientists are more divided on the basic questions.” My own experience of researching a book on sea-level rise has led to a related question: how should the general public (including members of the press) parse the nuances of scientific argument?

The blizzard of opinions, offered in mainstream media and across the Internet, stretch from the negative to the positive, the cynical to the passionate, the well documented to the anecdotal. It’s no wonder polls show that non-scientists believe scientists are in a state of disarray about human-induced global warming. In reality, although there are some differences over details as well as unfolding discoveries as more aspects are studied, the vast majority of scientists agree about the nature and cause of global climate change. How can people without Ph.D.s in climate science separate the wheat from the chaff? It’s not easy, but here are some rules of thumb.

Avoid the Manufacturers of Doubt.

There is a large group of mostly nonprofit organizations dedicated to debunking global warming and its human connection. These include among others Heartland Institute, George C. Marshall Institute, American Legislative Exchange Council, Frontiers of Freedom, Competitive Enterprise Institute, American Enterprise Institute, Cato Institute, Property and Environmental Research Center, Heritage Foundation, and the Center for the Study of CO2 and Global Change. These and other assemblages of deniers can usually be identified by their energy-related (i.e., oil and coal companies) or libertarian sponsorship.

Sometimes their statements have an element of truth, and occasionally they speak the whole truth, but I recommend that non-scientists give their prolific works little credibility. There are also some prominent naysaying individuals who should be disregarded, including climatologist Patrick Michaels, geologist Don Easterbrook, and Fox News Junk Science commentator Steve Milloy.

Ignore Declarations From Non-Scientists.

Recently, a prominent astronaut was quoted as saying that global cooling was about to commence because of changes in solar radiation. Maybe so and maybe not, but a skilled pilot is not necessarily an expert on climate change. Holly Fretwell (astoundingly) declared in a children’s book on global warming (The Sky’s Not Falling, page 34) that the melting of the world’s ice sheets wouldn’t have much effect on global sea levels. Fretwell, an economist, may be off by more than 200 feet of sea level rise –- enough to wipe out many coastal cities around the globe!

Beware of Long-Term Conclusions Based on Short-Term Events.

Evidence that global climate change is occurring is necessarily long-term — decadal at a minimum. A single storm, a warm winter or two don’t mean anything. The spectacular disappearance of the Antarctic and Greenland Ice Sheets just in the last five years (and its potential for sea-level rise) is impressive, but continuation for another five years will make it more so.

Be Cautious With Results from Mathematical Models.

Much of the evidence for global warming is based on mathematical models. The mathematical sophistication of such models should not be disconnected from the realities of nature. Recently, a scientist testified before Congress that his models indicated we have 10-12 years to reduce CO2 concentrations globally. Maybe so and maybe not. With all the atmospheric uncertainties involved in the models, perhaps the scientist should have said we need to reduce CO2 output ASAP.

Listen to Researchers but Use Common Sense.

Non-scientists are best advised to give media reports from global climate change researchers the highest credibility. Their results, however, must be viewed in the context of common sense. Recently NPR reported a glaciologist had discovered on a Greenland glacier that a process of ice degradation was not as important as generally assumed. The scientist believed his work indicated that global sea-level rise would be less than anticipated. Maybe so and maybe not, but one glacier does not a global trend make.

Orrin H. Pilkey is a James B. Duke professor emeritus at the Nicholas School of the Environment.

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7 Comments

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  1. Daniel Wedgewood
    Aug 13, 2008

    Hello Professor Pilkey, How many people have PH.D.s in climate science? You mention that the vast majority of scientists agree about the nature and cause of global climate change: how many agree, and how many disagree? There is a logical fallacy called “argumentum ad populum” (“appeal to the majority” is one of its common names). It states that a proposition is not true just because many or all people believe it to be true. Why should we believe all of those climate scientists, unless they provide us with proof? In your section “Be Cautious With Results from Mathematical Models,” why should we change the results of the mathematical models to ASAP, because of the uncertainties you describe? Why not add another 10 years onto the estimate? And, if we can’t use mathematical models effectively to help assess climate change, what can we use? You seem to be saying in your article that anyone who disagrees with adverse effects of global climate change should be distrusted; while anyone who agrees with it should be trusted. Is that true? How does a person establish the credibility of a given source of climate information? It can’t be because of their associations (that’s a fallacy called “guilt by association”) – what is the criteria? Disclaimer: I do happen to believe that global climate change is an issue, but I choose to put it into the category of “probable” until someone can prove it to me. I am also willing to act positively on issues I consider “probable.” Thanks, Dan ” title=”Questions and Comments

    • Orrin Pilkey
      Aug 14, 2008

      Thanks Dan for your comments. Of course I don’t have exact numbers but all polls and other evidence indicate very wide acceptance in the scientific community of the “nature and cause of global climate change”. One of the more meaningful lines of evidence was presented by Naomi Oreskes, in a widely quoted paper Beyond the Ivory Tower: The Scientific Consensus on Climate Change in Science Magazine. She examined more than 900 technical papers in the peer reviewed literature and found 75 % agreed that humans play some role in global change and not one of the other 25% directly disagreed. The physics of CO2 makes it’s addition to the atmosphere a certainty to create a greenhouse effect. Remember that my statement was advice to non-scientists. If they really want to sort out the wheat from the chaff, first of all throw out the professional doubters. These are organizations and individuals funded for and dedicated to proving global warming doesn’t exist. These are people who publish both garbage AND valid science but always to cast doubt. Scientists can sort it out but the neighborhood grocer, to whom I addressed my comments, doesn’t have a clue. Guilt by association is not a fallacy in this context. As regards mathematical models I accept the results of models in a qualitative sense. That is I believe they can show trends and if the models clearly show an important trend than immediate action is justified. Finally if you are not convinced by the weight of the scientific evidence available at present, your intention to wait until someone provides you with proof will be a long and dreary one. ” title=”response to reply

      • Daniel Wedgewood
        Aug 14, 2008

        Professor Pilkey, I feel I’ve done you a disservice. I didn’t recognize your name, and so I did some research on you and your career. Besides being a distinguished professor, it also happens that you’re a somewhat prolific author. I found a bunch of books, papers, articles, reviews, and criticisms scattered around the Web. Which of your books would you recommend reading in order to get a good summary of the state of climate change issues and proposed solutions? – Dan” title=”A Good Book?

        • Orrin Pilkey
          Aug 18, 2008

          My little corner of climate change research has to do with critical review of mathematical models of earth surface processes and sea level rise impacts. You might wish to take a look at my 2007 book, Useless Arithmetic and perhaps an article in Global and Planetary Change, 2004, 43, 157-1711.” title=”global change

  2. Anonymous
    Aug 14, 2008

    Professor Pilkey – Re you comment about mathematical models, I am not sure I fully agree with your characterization. An important comment that needs to be made is that the mathematical models (be it climate models or models of other phenomena) are nothing more than a mathematical construct (albeit simplified) of our understanding of the underlying physical principles. So when we say the mathematical models are uncertain, what we are really saying is that our physical understanding is uncertain. I am concerned that comments such as yours leave the impression that mathematical climate models are in some way distinct from our physical understanding of the climate system. ” title=” Mathematical models

    • orrin Pilkey
      Aug 18, 2008

      Thank you for your comment. Your discussion is an issue that I discuss in detail in a 2007 book written with my daughter Linda Pilkey-Jarvis entitled Useless Arithmetic. If I understand you correctly you are saying that the accuracy of models of earth surface processes is in direct proportion to our knowledge of such processes. Presumably when we understand the processes perfectly our models will be perfect. But one problem with this is that we can’t accurately know the forces that make a natural process run. Let me use my favorite example: the moving of sand on beaches; a critical process for predicting how long artificial beaches will last. Even if we understood the process of moving beach sand, we cannot accurately model the future movement of beach sand because we can’t predict what the driving forces will be like in the future. As a substitute for such knowledge, modelers of most earth processes assume that the processes of the last month, year, decade or century will continue as before. But on beaches, storms move most of the sand. We don’t know when and where future storms will occur, and we don’t know their intensity, frequency, direction and duration. And since our knowledge of future driving forces, ie storms, will not improve, the accuracy of our predictive modeling can’t improve beyond a certain point. This is why I believe models of earth surface processes cannot accurately predict the future in an applied or practical sense. Such models are best viewed qualitatively (providing directional, trends, and order of magnitude answers) and in that sense they can be very valuable. ” title=”global warming

      • Prasad Kasibhatla
        Sep 17, 2008

        Dr. Pilkey – Your reply re my question on models raises a couple of issues. Saying that the forcing are inaccurate is very different from saying the models themselves are equally inaccurate (something I realize that you don’t directly say, but is implied in your post). And the obvious next question related to the specific issue of climate models is to what degree are the forcings uncertain and at what time scale. My sense is that the climate modeling community has made a great deal of effort to characterize and quantify the ‘internal’ uncertainties of climate models, as well as the uncertainties related to uncertainties in ‘external’ forcings. And I would further argue that it is possible to make informed policy decisions taking output from these models along with the associated uncertainties into account, not just qualitatively, but quantitatively as well.” title=”mathematical models

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