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  Home » Mediarology » Testimony
Stanford University
  Stephen Schneider Testimony

Testimony of Stephen H. Schneider
Professor, Department of Biological Sciences
Stanford University
July 10, 1997
Climate Change: Cause, Imapcts and Uncertainties

I. Does Natural Variability Explain All Climate Change?

Twenty thousand years ago, a mere blink in geologic time, a visitor to the now-productive Corn Belt of Illinois would not be sitting in the heart of the world's foremost granary, but rather open spruce parkland forest, where many of the tree species seen are the same kinds that are found today 500 to 1,000 miles north in the Boreal Forests of Canada. Similarly, if we could somehow have been flying over the Great Basin we would have seen the massive fossil lakes, some stretching hundreds of miles like former Lake Bonneville in Utah, and the now-fossil beaches (currently visible flying into Salt Lake City Airport or over Mono Lake) from those high water stands that date back ten to fifteen thousand years ago. The Ice Age, which at its maximum some 20,000 years ago was about 5 degrees to 7 degrees C (around 100F) colder than our current global climate, disappeared in, what is to nature, a relatively rapid period of about five to ten thousand years. The average rate of temperature change from the Ice Age to the current 10,000 year period of relative climate stability, our so-called Holocene Interglacial, is about 1 degrees C change for every thousand years. Of course there were more rapid periods embedded within this time frame, but I'm only giving the sustained average rates.

Not only did such change correspond with radical alterations to the ecosystems of the earth, but have been implicated in the extinction of what is known as the charismatic megafauna (woolly mammoth, saber tooth tigers, etc.). Fossil pollen evidence tells us that the vegetation habitats during the more "rapid" parts of the transition from ice age to interglacial around ten to twelve thousand years ago saw what paleoclimatologists call "no analog habitats," that is, combinations of pollen abundances which do not exist on earth today. All of this change was natural, of course, and there are two reasons for mentioning it in our context. First, to remind us that the climate and ecosystems change by themselves, without need of humans (the latter is what we call anthropogenic causation), and, two, that climate change of about several degrees on a global average basis is a very significant change from the point of view of natural systems.

Explanations of the Ice Age vary, the most popular one being a change in the amount of sunlight coming in between (a) winter and summer and (b) the poles and the equator. These changes in the distribution of seasonal or latitudinal sunshine are due to slow variations in the tilt of the earth's axis and other orbital elements, but these astronomical variations alone cannot totally explain the climatic cycles. If these orbital variations and other factors (such as the increased reflectivity of the earth associated with more ice) are combined, our best climate theories (embodied through mathematical models that are comprised of the physical laws of conservation of mass, energy and momentum) suggest that the Ice Age should have been several degrees warmer than it actually was -- especially in the Southern hemisphere. What could account for this extra cold? Perhaps the models are not sensitive enough, that is they do not respond sufficiently to a change in so called "radiative climate forcing," that is the change in the amount of radiant energy coming to the earth from external factors like orbital variations or extra ice. Another (more likely, I think) possibility is that something else also changed at the same time.

These theories can be better reconciled with what happened between ice ages and interglacials if one assumes that several watts of energy over every square meter of the earth were taken away in the ice age by some other mechanism at a global scale. But what could be such a mechanism? The obvious candidate would be a change in the composition of the earth's atmosphere which affects both its reflectivity and its heat trapping capacity (e.g. decreases in the well-known greenhouse effect or increases in atmospheric dust). But what evidence is there that greenhouse gases, for example carbon dioxide, methane, nitrous oxide, or water vapor, had lower concentrations 20,000 years ago than in the interglacial? About fifteen years ago that evidence came through loud and clear from the ice caps of the world. Air trapped in these glaciers provides a library of the history of the earth's atmosphere back some 200,000 years. It shows that during the past two ice ages carbon dioxide concentration was about 40% less and methane half of the average value during the current and penultimate interglacials. It also shows that since the Industrial Revolution carbon dioxide has increased beyond any levels experienced in the past 150,000 years (at least) by nearly 30% and methane by 150% -- two figures that virtually no knowledgeable scientist disputes are a result of so-called anthropogenic emissions which are driven by increasing numbers of people pursuing higher standards of living and using technology to achieve those growth-oriented goals.

If the carbon dioxide and methane decreases in the last ice age helped to explain the ice age coldness, can they tell us something about how the anthropogenic increase of these gases due to human activities might cause climate change in the future? The answer is "not directly," for it is possible that there are other factors we have not accounted for in the ice age story that could well have been involved, and there are still many unanswered questions associated with the Ice Age cycles. It is simply a circumstantial bit of evidence which suggests that it is more consistent to explain the ice ages with the heat trapping power of the greenhouse effect existing at the magnitudes currently envisioned by most scientists -- i.e. a doubling of CO2 would raise surface temperatures by about 3 degrees C plus or minus 1.5 degrees C. This is known as the "climate sensitivity range." The magnitude of climate sensitivity that helps to explain the ice age coldness best is 2-3 degrees C. If the best estimate were ten degrees warming, which is twice the value at the high end of the climate sensitivity range thought by the mainstream of scientist today (e.g.. IPCC 1996a), then the ice ages should have been even colder than they were. On the other hand, if the earth would only warm up by half a degree or less if CO2 doubled, then it would be tougher to explain the magnitude of the ice ages without finding some other mechanism not yet understood. Of course, the latter is possible, but what other lines of circumstantial evidence or direct evidence do we have for estimating climate sensitivity?

We know from quite literally thousands of laboratory experiments and direct measurements, millions of balloon observations and trillions of satellites data bits, that the basic structure of the energy flows in and out of the earth's atmosphere are relatively well understood. We know that water vapor, carbon dioxide, or methane trap enough energy on the earth to warm the surface up about 33 degrees C (60 degrees F) relative to that which would occur in their absence.

This well known natural greenhouse effect is not under dispute, and has been known for a century and a half. Nor is the 0.5 degrees C (plus or minus 0.2 degrees C ) globally averaged warming trend at the earth's surface over the past century in dispute. In dispute is whether a small increment since the Industrial Revolution in this envelope of greenhouse gases, which our calculations tell us should have trapped about two extra watts of energy over every square meter of Earth, would produce a noticeable response (i.e. a "climate signal"). The debate over whether that signal has been detected has been intense lately and this intensity has been based upon significant new pieces of evidence - - albeit each piece is circumstantial -- and a few loud, well-publicized denials that the totality of evidence has any meaning. In the absence of clear, direct empirical evidence, one often has to use either circumstantial evidence, or incomplete bits of direct evidence with uncertainties attached. When the preponderance of such evidence gets strong enough, then most scientists begin to accept, tentatively of course, the likelihood of causal connections. Some people shed their skepticism at different levels than others, so naturally there will be a cacophonous debate over whether a climate signal has been detected, let alone whether it could be attributed to human activities. One can always find some scientist who will want 999 out of a 1000 probability of certainty, and others who will accept the proposition at eight or nine chances out of ten. This is not science, but a value judgment about the acceptability of a significant, but not conclusive, body of evidence. The scientific job is to assess (A) what can happen, and (B) what the odds are of it happening (see, for example, this discussion in Chapter 6 of Schneider 1997a). Let me discuss this process further.

I have mentioned the ice ages since this is a "natural experiment" that we use, not to forecast the future, but to build understanding of climate processes and to validate the tools that we do use to forecast the future -- that is, our climate theories embodied in mathematical models. Are there any other such natural experiments? The answer is "yes there are many," the two most prominent being (1) episodic volcanic eruptions which throw dust in the stratosphere that reflects for a few years a few watts per square meter of solar energy that otherwise would have reached the lower atmosphere and (2) the seasonal cycle. Let's consider volcanic eruptions first. Volcanic dust veils should cool the planet. In fact, the last major eruption, Mt. Pinatubo in 1991, was forecast to cool the earth's lower atmosphere on the order of several tenths of a degree by a number of climate modeling groups -- in advance of the actual data to confirm -- and indeed, that is roughly what happened. However, it could be argued that a few tenths of a degree cooling, or warming for that matter, might be a natural fluctuation in the earth's climate system, and indeed, fluctuations of that magnitude are a part of the natural background "climatic noise." How then could we distinguish the climatic signal of the volcanic eruption from the noise of the natural variability? In any one eruption it is difficult to do so since the signal to noise ratio is about one, i.e. the magnitude of the cooling expected is about equal to the magnitude of the natural fluctuations in non-volcanic years, and therefore for any one event we cannot have very much confidence that a signal has been observed. So the fact that the Pinatubo results showed up about as predicted doesn't, by itself, give a lot of confidence, although as a circumstantial bit of evidence is quite useful. However, another volcanic eruption in 1983, El Chich¢n, was also followed by several tenths of a degree cooling, as was the effect after Mt. Agung in 1963 or Mt. Krakatoa in the Victorian period.

In other words, by looking at the results of several volcanic eruptions and compositing, a number of scientists (including Mass and Schneider, 1977) used this technique and discovered that indeed there was a clear and obvious correlation which suggests that when a few watts of energy over every square meter of the earth is removed by volcanic dust veils in the stratosphere, the lower atmosphere will indeed cool by a few tenths of degrees -- the very magnitude predicted by the same computer models that we use to forecast the effects of a few watts per square meter of sustained heating from global warming.

What other natural experiments might we have to test climate sensitivity? My favorite is one that happens every year -- the seasons. Winter predictably follows summer, being some fifteen degrees colder in the Northern Hemisphere and five degrees colder than summer in the Southern Hemisphere. The reason the Southern Hemisphere has a smaller seasonal cycle is because it has much more ocean than land, and water has a higher heat retaining capacity than land or air. Since a season is not long enough for the planet to reach an equilibrium temperature change, therefore, the more land dominated Northern Hemisphere has lower heat capacity and thus a larger seasonal cycle of surface temperature. How well do the climate models do in reproducing this change? The answer is "extraordinarily well." Although what the absolute temperatures models may simulate can be off by as much as five or six degrees in some regions of the world for some seasons, the models' capacity to reproduce the amplitude of the seasonal cycle of surface air temperatures, by and large, is quite good. (It is less good for other variables, however, particularly hydrological systems.) Now, if we were making a factor of ten error by either overestimating or underestimating the sensitivity of the climate to radiative forcing, it would be difficult for the models to reproduce the different seasonal cycle surface temperature amplitudes over land and oceans as well as they do. This is another piece of circumstantial evidence suggesting that current estimate of climate sensitivity is not off by a factor of ten, as some "contrarians" assert. Indeed, indirect evidence like ice ages, volcanic eruptions and the seasonal cycle simulation skills of models are prime reasons why many of us in the scientific community have for the past twenty years expected that "demonstrable" (e.g.. see p.11 of Schneider and Mesirow, 1976 -- in which I projected just such a change) anthropogenic climate change was not unlikely by the 21st century.

In summary, then, in my opinion it is unlikely that natural variability is the explanation of all climate change, especially that which has been documented in the 20th century. However, since much of the debate over detection and attribution of human- caused climate change hinges on the projections of climatic models, it is necessary to have at least a cursory understanding of how they work. Although it is impossible to treat more than the highlights of the nature and use of climatic models in a dozen pages, I nonetheless offer the following section in the hopes of reducing somewhat the confusion that may exist in many peoples' minds after listening to the often acrimonious and technically complex debate over climatic models and their credibility.

II. Overview Of Climate Modeling Fundamentals

Engineers and scientists build models -- either mathematical or physical ones -- primarily to perform tests that are either too dangerous, too expensive, or perhaps impossible to perform with the real thing. To simulate the climate, a modeler needs to decide which components of the climatic system to include and which variables to involve. For example, if we choose to simulate the long-term sequence of glacials and interglacials (the period between successive ice ages), our model needs to include explicitly the effects of all the important interacting components of the climate system operating over the past million years or so. These include the atmosphere, oceans, sea ice/glaciers (cryosphere), land surface (including biota), land sub-surface and chemical processes (including terrestrial and marine biogeochemical cycles), as well as the external or "boundary forcing" conditions such as input of solar radiant energy (e.g., see IPCC, 1996a).

The problem for earth systems scientists is separating out quantitatively cause and effect linkages from among the many factors that interact within the earth system. It is a controversial effort because there are so many sub-systems, so many forcings and so many interacting complex sets of processes operating at the same time that debates about the adequacy of models often erupt.

Modeling the Climate System. So how are climate models constructed? First, scientists look at observations of changes in temperatures, ozone levels and so forth. This allows us to identify correlations among variables. Correlation is not necessarily cause and effect -- just because one event tracks another doesn't mean it was caused by it. One has to actually prove the relationship is causal and explain how it happened. Especially for cases where unprecedented events are being considered, a first principles, rather than a purely empirical-statistical approach is desirable. However, observations can lead to a hypothesis of cause and effect -- "laws" -- that can be tested (for example, see Root and Schneider, 1995). The testing is often based on simulations with mathematical models run on a computer. The models, in turn, need to be tested against a variety of observations -- present and paleoclimatic. That is how the scientific method is typically applied. When a model, or set of linked models, appear plausible, they can be fed "unprecedented" changes such as projected human global change forcings -- changes that have not happened before -- and then be asked to make projections of future climate, ozone levels, forests, species extinction rates, etc.

The most comprehensive weather simulation models produce three dimensional details of temperature, winds, humidity, and rainfall all over the globe. A weather map generated by such a computer model -- known as a general circulation model or GCM -- often looks quite realistic, but it is never faithful in every detail. To make a weather map generated by computer we need to solve six partial differential equations that describe the fluid motions in the atmosphere. It sounds in principle like there's no problem: we know that those equations work in the laboratory, we know that they describe fluid motions and energy and mass relationships. So why then aren't the models perfect simulations of the atmospheric behavior?

One answer is that the evolution of weather from some starting weather map (known as the initial condition) is not deterministic beyond about 10 days -- even in principle. A weather event on one day cannot be said to determine an event 20 days in the future, all those commercial "long-range" weather forecasts notwithstanding. But the inherent unpredictability of weather details much beyond ten days (owing to the chaotic internal dynamics of the atmosphere) doesn't preclude accurate forecasts of long-term averages (climate rather than weather). The seasonal cycle is absolute proof of such deterministic predictability, as winter reliably follows summer and the cause and effect is known with certainty.

Grids and Parameterization. The other answer to the imperfection of general circulation model simulations, even for long-term averages, is that nobody knows how to solve those six complex mathematical equations exactly. It's not like an algebraic equation where one can get the exact solution by a series of simple operations. There isn't any known mathematical technique to solve such coupled, nonlinear partial differential equations exactly. We approximate the solutions by taking the equations, which are continuous, and breaking them down into discrete chunks which we call grid boxes. A typical GCM grid size for a "low resolution" model is about the size of Colorado horizontally and that of a "high resolution" GCM is about the size of Connecticut. In the vertical dimension there are two (low resolution) up to about twenty (high resolution) vertical layers that are typically spanning the lowest 10 to 40 kilometers of the atmosphere.

Now, we've already noted that clouds are very important to the energy balance of the earth-atmosphere system since they reflect sunlight away and trap infrared heat. But because none of us have ever seen a single cloud the size of Connecticut, let alone Colorado, we have a problem of scale -- how can we treat processes that occur in nature at a smaller scale than we can resolve by our approximation technique of using large grid boxes. For example, we cannot calculate clouds explicitly because individual clouds are typically the size of a dot in this grid box. But we can put forward a few reasonable propositions on cloud physics: if it's a humid day, for example, it's more likely to be cloudy. If the air is rising, it's also more likely to be cloudy.

These climate models can predict the average humidity in the gridbox, and whether the air is rising or sinking on average. So then we can write what we call a parametric representation or "parameterization" to connect large scale variables that are resolved by the grid box (such as humidity) to unresolved small scale processes (individual clouds). Then we get a prediction of grid box-averaged cloudiness through this parameterization. So-called "cumulus parameterization" is one of the important -- and controversial --elements of GCMs that occupy a great deal of effort in the climate modeling community. Therefore, the models are not ignoring cloudiness, but neither are they explicitly resolving individual clouds. Instead, modelers try to get the average effect of processes that can't be resolved explicitly at smaller scales than the smallest resolved scale (the grid box) in the GCM. Developing, testing and validating many such parameterizations is the most important task of the modelers since these parameterizations determine critically important issues like "climate sensitivity." The climate sensitivity is the degree of response of the climate system to a unit change in some forcing factor: typically, in our context, the change in globally-averaged surface air temperature to a fixed doubling of the concentration of atmospheric carbon dioxide above pre-industrial levels. This brings us to one of the most profound controversies in earth systems science, and one of the best examples of the usefulness, and fragility, of computer modeling.

The Greenhouse Effect. If the earth only absorbed radiation from the sun without giving an equal amount of heat back to space by some means, the planet would continue to warm up until the oceans boiled. We know the oceans are not boiling, and surface thermometers plus satellites have shown that the earth's temperature remains roughly constant from year to year (the interannual globally-averaged variability of about 0.2 C or the 0.5 C warming trend in the 20th century, notwithstanding). This near constancy requires that about as much radiant energy leaves the planet each year in some form as is coming in. In other words, a near-equilibrium or energy balance has been established. The components of this energy balance are crucial to the climate.

All bodies with temperature give off radiant energy. The earth gives off a total amount of radiant energy equivalent to that of a black body -- a fictional structure that represents an ideal radiator -- with a temperature of roughly -18 C (255 K). The mean global surface air temperature is about 14 C (287 K), some 32 C warmer than the earth's black body temperature. The difference is due to the well-established greenhouse effect.

The term greenhouse effect arises from the classic analogy to a greenhouse, in which the glass allows the solar radiation in and traps much of the heat inside. However, the mechanisms are different, for in a greenhouse the glass primarily prevents convection currents of air from taking heat away from the interior. Greenhouse glass is not primarily keeping the enclosure warm by its blocking or re-radiating infrared radiation; rather, it is constraining the physical transport of heat by air motion.

Although most of the earth's surface and thick clouds are reasonably close approximations to a black body, the atmospheric gases are not. When the nearly black body radiation emitted by the earth's surface travels upward into the atmosphere, it encounters air molecules and aerosol particles. Water vapor, carbon dioxide, methane, nitrous oxide, ozone, and many other trace gases in the earth's gaseous envelope tend to be highly selective -- but often highly effective -- absorbers of terrestrial infrared radiation. Furthermore, clouds (except for thin cirrus) absorb nearly all the infrared radiation that hits them, and then they reradiate energy almost like a black body at the temperature of the cloud surface -- colder than the earth's surface most of the time.

The atmosphere is more opaque to terrestrial infrared radiation than it is to incoming solar radiation, simply because the physical properties of atmospheric molecules, cloud and dust particles tend on average to be more transparent to solar radiation wavelengths than to terrestrial radiation. These properties create the large surface heating that characterizes the greenhouse effect, by means of which the atmosphere allows a considerable fraction of solar radiation to penetrate to the earth's surface and then traps (more precisely, intercepts and re-radiates) much of the upward terrestrial infrared radiation from the surface and lower atmosphere. The downward re- radiation further enhances surface warming and is the prime process causing the greenhouse effect.

This is not a speculative theory, but a well understood and validated phenomenon of nature. The most important greenhouse gas is water vapor, since it absorbs terrestrial radiation over most of the infrared spectrum. Even though humans are not altering the average amount of water vapor in the atmosphere very much by direct injections of this gas, increases in other greenhouse gases which warm the surface cause an increase in evaporation which increases atmospheric water vapor concentrations, leading to an amplifying or "positive" feedback process known as the "water vapor-surface temperature-greenhouse feedback." The latter is believed responsible for the bulk of the climate sensitivity (IPCC, 1996a). Carbon dioxide is another major greenhouse gas. Although it absorbs and re-emits considerably less infrared radiation than water vapor, CO2 is of intense interest because its concentration is increasing due to human activities. Ozone, nitrogen oxides, some hydrocarbons, and even some artificial compounds like chlorofluorocarbons are also greenhouse gases. The extent to which they are important to climate depends upon their atmospheric concentrations, the rates of change of those concentrations and their effects on depletion of stratospheric ozone --which in turn, can indirectly modify the radiative forcing of the lower atmosphere thus changing climate -- currently offsetting a considerable fraction of the otherwise expected greenhouse warming signal.

The earth's temperature, then, is primarily determined by the planetary radiation balance, through which the absorbed portion of the incoming solar radiation is nearly exactly balanced over a year's time by the outgoing terrestrial infrared radiation emitted by the climatic system to earth. As both of these quantities are determined by the properties of the atmosphere and the earth's surface, major climate theories that address changes in those properties have been constructed. Many of these remain plausible hypotheses of climatic change. Certainly the natural greenhouse effect is established beyond a reasonable scientific doubt, accounting for natural warming that has allowed the coevolution of climate and life to proceed to this point ( e.g., see Schneider and Londer, 1984). The extent to which human augmentation of the natural greenhouse effect (i.e., global warming) will prove serious is, of course, the current debate.

Model Validation. There are many types of parameterizations of processes that occur at a smaller scale than our models can resolve, and scientists debate which type is best. In effect, are they an accurate representation of the large-scale consequences of processes that occur on smaller scales than we can explicitly treat? These include cloudiness, radiative energy transport, turbulent convection, evapotranspiration, oceanic mixing processes, chemical processes, ecosystem processes, sea ice dynamics, precipitation, mountain effects and surface winds.

In forecasting climatic change, then, validation of the model becomes important. In fact, we can not easily know in principle whether these parameterizations are "good enough." We have to test them in a laboratory. That's where the study of paleoclimates has proved so valuable ( e.g., Hoffert and Covey, 1992). We also can test parameterizations by undertaking detailed small-scale field or modeling studies aimed at understanding the high resolution details of some parameterized process the large-scale model has told us is important. The Second Assessment Report of IPCC (IPCC, 1996a) Working Group I devoted more than one chapter to the issue of validation of climatic models, concluding that "the most powerful tools available with which to assess future climate are coupled climate models, which include three-dimensional representations of the atmosphere, ocean, cryosphere and land surface. Coupled climate modeling has developed rapidly since 1990, and current models are now able to simulate many aspects of the observed climate with a useful level of skill. [For example, as noted earlier, good skill is found in simulating the very large annual cycle of surface temperatures in Northern and Southern Hemispheres or the cooling of the lower atmosphere following the injection of massive amounts of dust into the stratosphere after explosive volcanic eruptions such as Mt. Pinatubo in the Philippines in 1991.] Coupled model simulations are most accurate at large spatial scales (e.g., hemispheric or continental); at regional scales skill is lower". [sentence in square brackets added]

One difficulty with coupled models is known as "flux adjustment"-- a technique for accounting for local oceanic heat transport processes that are not well simulated in some models. Adding this element of empirical-statistical "tuning" to models that strive to be based as much as possible on first principles has been controversial. However, not all models use flux adjustments, yet nearly all models, with or with out this technique, produce climate sensitivities within or near to the standard IPCC range of 1.5 to 4.5 C. Flux adjustments do, however, have a large influence on regional climatic projections, even if they prove not to be a major impact on globally-averaged climate sensitivity. Improving coupled models is thus a high priority for climate researchers since it is precisely such regional projections that are so critical to the assessment of climatic impacts on environment and society (e.g., IPCC, 1996b; IPCC, 1997).

Transient versus Equilibrium Simulations. One final issue needs to be addressed in the context of coupled climate simulations. Until recently, climate modeling groups did not have access to sufficient computing power to routinely calculate time evolving runs of climatic change given several alternative future histories of greenhouse gases and aerosol concentrations. That is, they did not perform so-called transient climate change scenarios. (Of course, the real Earth is undergoing a transient experiment.) Rather, the models typically were asked to estimate how the Earth's climate would eventually be altered (i.e., in equilibrium) after CO2 was artificially doubled and held fixed indefinitely rather than increased incrementally over time as it has in reality or in more realistic transient model scenarios. The equilibrium climate sensitivity has remained fairly constant for over twenty years of assessments by various national and international groups, with the assessment teams repeatedly suggesting that, were CO2 to double, climate would eventually warm at the surface somewhere between 1.5 and 4.5 C. (Later on we will address the issue of the probability that warming above or below this range might occur, and how probabilities can even be assigned to this sensitivity.)

Transient model simulations exhibit less immediate warming than equilibrium simulations because of the high heat holding capacity of the thermally massive oceans. However, that unrealized warming eventually expresses itself decades to centuries later. This thermal delay, which can lull us into underestimating the long-term amount of climate change, is now being accounted for by coupling models of the atmosphere to models of the oceans, ice, soils, and biosphere (so-called earth system models -- ESMs). Early generations of such transient calculations with ESMs give much better agreement with observed climate changes on Earth than previous calculations in which equilibrium responses to CO2 doubling were the prime simulations available. When the transient models at the Hadley Center in the United Kingdom and the Max Planck Institute in Hamburg, Germany were also driven by both greenhouse gases (which heat) and sulfate aerosols (which cool), these time evolving simulations yielded much more realistic "fingerprints" of human effects on climate( e.g., Chapter 8 of IPCC, 1996a). More such computer simulations are needed to provide high confidence levels in the models, but scientists using coupled, transient simulations are now beginning to express growing confidence that current projections are plausible.

Transients and Surprises. However, such a very complicated coupled system like an ESM is likely to have unanticipated results when forced to change very rapidly by external disturbances like CO2 and aerosols. Indeed, some of the transient models run out for hundreds of years exhibit dramatic change to the basic climate state (e.g., radical change in global ocean currents). Thompson and Schneider (1982) used very simplified transient models to investigate the question of whether the time evolving patterns of climate change might depend on the rate at which CO2 concentrations increased. For slowly increasing CO2 buildup scenarios, the model predicted the standard model outcome: the temperature at the poles warmed more than the tropics.

Any changes in equator-to-pole temperature difference help to create altered regional climates, since temperature differences over space influence large-scale atmospheric wind patterns. However, for very rapid increases in CO2 concentrations a reversal of the equator-to-pole difference occurred. If sustained over time, this would imply difficult to forecast, transient climatic conditions during the century or so the climate adjusts toward its new equilibrium state. In other words, the harder and faster the enormously complex earth system is forced to change, the higher the likelihood for unanticipated responses. Or, in a phrase, the faster and harder we push on nature, the greater the chances for surprises -- some of which are likely to be nasty.

Noting this possibility, the Summary for Policy makers of IPCC Working Group I concluded with the following paragraph:

Future unexpected, large and rapid climate system changes (as have occurred in the past) are, by their nature, difficult to predict. This implies that future climate changes may also involve "surprises." In particular these arise from the non-linear nature of the climate system. When rapidly forced, non-linear systems are especially subject to unexpected behavior. Progress can be made by investigating non-linear processes and sub-components of the climatic system. Examples of such non-linear behavior include rapid circulation changes in the North Atlantic and feedbacks associated with terrestrial ecosystem changes.

Of course, if the Earth system were somehow less "rapidly forced" by virtue of policies designed to slow down the rate at which human activities modify the land surfaces and atmospheric composition, this would lower the likelihood of non-linear surprises. Whether the risks of such surprises justify investments in abatement activities is the question that Integrated Assessment (IA) activities are designed to inform (IPCC, 1996c). The likelihood of various climatic changes, along with estimates of the probabilities of such potential changes, are the kinds of information IA modelers need from earth systems scientists in order to perform IA simulations. We turn next, therefore, to a discussion of methods to evaluate the subjective probability distributions of scientists on one important climate change issue, the climate sensitivity.

Subjective Probability Estimation. Finally, what does define a scientific consensus? Morgan and Keith (1995) and Nordhaus (1994) are two attempts by non- climate scientists, who are interested in the policy implications of climate science, to tap the knowledgeable opinions of what they believe to be representative groups of scientists from physical, biological and social sciences on two separate questions: first the climate science itself and second impact assessment and policy. Their sample surveys show that although there is a wide divergence of opinion, nearly all scientists assign some probability of negligible outcomes and some probability of very highly serious outcomes, with one or two exceptions, like Richard Lindzen at MIT (who is scientist number 5 on Fig. 1 of Morgan and Keith).

In the Morgan and Keith study, each of the 16 scientists listed in Table 1 were put through a several hour, formal decision-analytic elicitation of their subjective probability estimates for a number of factors. Figure 1 shows the elicitation results for the important climate sensitivity factor. Note that 15 out of 16 scientists surveyed ( including several IPCC Working Group I Lead Authors -- I am scientist 9) assigned something like a 10% subjective likelihood of negligible (less than 1 C) climatic change from doubling of CO2. These scientists also typically assigned a 10% probability for extremely large climatic changes --greater than 5 C, roughly equivalent to the temperature difference experienced between a glacial and interglacial age, but occurring some hundred times more rapidly. In addition to the lower probabilities assigned to the mild and catastrophic outcomes, the bulk of the scientists interviewed (with the one exception) assigned the bulk of their subjective cumulative probability distributions in the center of the IPCC range for climate sensitivity. What is most striking about the exception, scientist 5, is the lack of variance in his estimates--suggesting a very high confidence level in this scientist's mind that he understands how all the complex interactions within the earth-system described above will work. None of the other scientists displayed that confidence, nor did the Lead Authors of IPCC. However, several scientists interviewed by Morgan and Keith expressed concern for "surprise" scenarios -- for example, scientists 2 and 4 explicitly display this possibility on Figure 1, whereas several other scientists implicitly allow for both positive and negative surprises since they assigned a considerable amount of their cumulative subjective probabilities for climate sensitivity outside of the standard 1.5 to 4.5 range. This concern for surprises is consistent with the concluding paragraph of the IPCC Working Group I Summary for Policymakers quoted above.

IPCC Lead Authors, who wrote the Working Group I Second Assessment Report, were fully aware of both the wide range of possible outcomes and the broad distributions of attendant subjective probabilities. After a number of sentences highlighting such uncertainties, the Report concluded: "nevertheless, the balance of evidence suggests that there is a discernible human influence on the climate." The reasons for this now-famous subjective judgment were many, such as the kinds of factors listed above. These include a well validated theoretical case for the greenhouse effect, validation tests of both model parameterizations and performance against present and paleoclimatic data, and the growing "fingerprint" evidence that suggests horizontal and vertical patterns of climate change predicted to occur in coupled atmosphere-ocean models has been increasingly evident in observations over that past several decades. Clearly, more research is needed, but enough is already known to warrant assessments of the possible impacts of such projected climatic changes and the relative merits of alternative actions to both mitigate emissions and/or make adaptations less costly. That is the ongoing task of integrated assessment analysts, a task that will become increasingly critical in the next century. To accomplish this task, it is important to recognize what is well established in climate theory and modeling and to separate this from aspect that are more speculative. That is precisely what IPCC (1996a) has attempted to accomplish.

III. Assessing The Impacts Of Climatic Change Projections

One of the most dramatic of the standard "impacts" of climatic warming projections is the increase in sea level typically associated with warmer climatic conditions. An EPA study used an unusual approach: combining climatic models with the subjective opinions of many scientists on the values of uncertain elements in the models to help bracket the uncertainties inherent in this issue. Titus and Narayanan (1996) -- including teams of experts of all persuasions on the issue -- calculated the final product of their impact assessment as a statistical distribution of future sea level rise, ranging from slightly negative values (i.e., a sea level drop) as a low probability outcome, to a meter or more rise, also with a low probability (see Fig 2). The midpoint of the probability distribution is something like half meter sea level rise by the end of the next century.

Since the EPA analysis stopped there, this is by no means a complete assessment. In order to take integrated assessment to its logical conclusion, we need to ask what the economic costs of various control strategies might be and how the costs of abatement compare to the economic or environmental losses (i.e. impacts or damages as they are called) from sea level rises. That means putting a value -- a dollar value of course -- on climate change, coastal wetlands, fisheries, environmental refugees, etc. Hadi Dowlatabadi at Carnegie Mellon University leads a team of integrated assessors who, like Titus, combined a wide range of scenarios of climatic changes and impacts but, unlike the EPA studies, added a wide range of abatement cost estimates into the mix. Their integrated assessment was presented in statistical form as a probability that investments in CO2 emissions controls would either cost more than the losses from averted climate change or the reverse (e.g., Morgan and Dowlatabadi, 1996). Since their results do not include estimates for all conceivable costs (e.g., the political consequences of persons displaced from coastal flooding), the Carnegie Mellon group offered its results only as illustrative of the capability of integrated assessment techniques. Its numerical results have meaning only after the range of physical, biological and social outcomes and their costs and benefits have been quantified -- a Herculean task. Similar studies have been made in Holland by a Dutch government effort to produce integrated assessments for policy makers. Jan Rotmans, who heads one of their efforts, likes to point out that such modeling of complex physical, biological and social factors cannot produce credible "answers" to current policy dilemmas, but can provide "insights" to policy makers that will put decision-making on a firmer factual basis (Rotmans and van Asselt, 1996). Understanding the strengths and weaknesses of any complex analytic tool is essential to rational policy making, even if quantifying the costs and benefits of specific activities is controversial.

William Nordhaus, an economist from Yale University, has made heroic steps to put the climatic change policy debate into an optimizing framework. He is an economist who has long acknowledged that an efficient economy must internalize externalities (in other words, find the full social costs of our activities, not just the direct cost reflected in conventional "free market" prices). He tried to quantify this external damage from climate change and then tried to balance it against the costs to the global economy of policies designed to reduce CO2 emissions. His optimized solution was a carbon tax, designed to internalize the externality of damage to the climate by increasing the price of fuels in proportion to how much carbon they emit, thereby providing an incentive for society to use less of these fuels.

Nordhaus (1992) imposed carbon tax scenarios ranging from a few dollars per ton to hundreds of dollars per ton -- the latter which would effectively eliminate coal from the world economy. He showed that, in the context of his model and its assumptions, that these carbon emission fees would cost the world economy anywhere from less than 1 percent annual loss in Gross National Product to a several percent loss by the year 2100. The efficient, optimized solution from classical economic cost-benefit analysis is that carbon taxes should be levied sufficient to reduce the GNP as much as it is worth to avert climate change (e.g. the damage to GNP from climate change). He assumed that the impacts of climate change were equivalent to a loss of about one percent of GNP. This led to an "optimized" initial carbon tax of about five dollars or so per ton of carbon dioxide emitted. In the context of his modeling exercise, this would avert only a few tenths of a degree of global warming to the year 2100, a very small fraction of the 4 C warming his model projected.

How did Nordhaus arrive at climate damage being about 1 percent of GNP? He assumed that agriculture was the most vulnerable economic market sector to climate change. For decades agronomists had calculated potential changes to crop yields from various climate change scenarios, suggesting some regions now too hot would sustain heavy losses from warming whereas others, now too cold, could gain. Noting that the US lost about one third of it's agricultural economy in the heat waves of 1988, and that agriculture then represented about 3 % of the US GNP, Nordhaus felt the typically- projected climatic changes might thus cost the U.S. economy something like 1% annually in the 21st century. This figure was severely criticized because it neglected damages from health impacts (e.g., expanded areas of tropical diseases, heat-stress deaths, etc.), losses from coastal flooding or severe storms, security risks from boat people created from coastal disruptions in South Asia or any damages to wildlife, fisheries or ecosystems that would almost surely accompany temperature rises at rates of degrees per century as are typically projected. It also was criticized because his estimate neglected potential increases in crop or forestry yields from the direct effects of increased CO2 in the air on the photosynthetic response of these marketable plants. Nordhaus responded to his critics by conducting a survey, similar to that undertaken by Morgan and Keith, but this time focused on the impacts of several scenarios of climatic change on world economic product -- including both standard market sector categories (e.g., forestry, agriculture, heating and cooling demands) and so-called non-market amenities like biological conservation and national security.

When Nordhaus surveyed the opinions of mainstream economists, environmental economists and natural scientists (I am respondent #10, in Nordhaus, 1994), he found that the former expressed a factor of twenty less anxiety about the economic or environmental consequences of climate change than the latter (see Fig.3 -- Scenario A is for 3 C warming by 2100 A.D. and Scenario C for 6 C by 2100 A.D.). However, the bulk of even the conservative group of economists Nordhaus surveyed considered there to be at least a ten percent probability that typically projected climate changes could still cause economic damages worth several percent of gross world product (the current US GNP is around five trillion dollars -- about twenty percent of the global figure). And, some of these economists didn't include estimates for possible costs of "non-market" damages (e.g., harm to nature). One ecologist who did explicitly factor in non-market values for natural systems went so far as to assign a ten percent chance of a hundred percent loss of GNP -- the virtual end of civilization! While Nordhaus quipped that those who know most about the economy are less concerned, I countered with the obvious observation that those who know the most about nature are very concerned.

We will not easily resolve the paradigm gulf between the optimistic and pessimistic views of these specialists with different training, traditions and world views, but the one thing that is clear from both the Morgan and Keith and Nordhaus studies is that the vast bulk of knowledgeable experts from a variety of fields admits to a wide range of plausible outcomes in the area of global environmental change -- including both mild and catastrophic eventualities -- under their broad umbrella of possibilities. This is a condition ripe for misinterpretation by those who are unfamiliar with the wide range of probabilities most scientists attach to global change issues. The wide range of probabilities follows from recognition of the many uncertainties in data and assumptions still inherent in earth systems models, climatic impact models, economic models or their synthesis via integrated assessment models (see Schneider, 1997a,b). It is necessary in a highly interdisciplinary enterprise like the integrated assessment of global change problems that a wide range of possible outcomes be included, along with a representative sample of the subjective probabilities that knowledgeable assessment groups like the IPCC believe accompany each of those possible outcomes. In essence, the "bottom line" of estimating climatic impacts is that both "the end of the world" and "it is good for business" are the two lowest probability outcomes, and that the vast bulk of knowledgeable scientists and economists consider there to be a significant chance of climatic damage to both natural and social systems. Under these conditions -- and the unlikelihood that research will soon eliminate the large uncertainties that still persist -- it is not surprising that most formal climatic impact assessments have called for cautious, but positive steps both to slow down the rate at which humans modify the climatic system and to make natural and social systems more resilient to whatever changes do eventually materialize.

IV. Policy Implications

What Are Some Actions to Consider? Decision making, of course, is a value judgment about how to take risks -- gambling, if you will -- in the environment-development arena. Despite the often bewildering complexity, making value choices does not require a Ph.D. in statistics, political science or geography to comprehend. Rather, citizens need simple explanations using common metaphors and everyday language that ordinary people can understand about the terms of the debate. Once the citizens of this planet become aware of the various tradeoffs involved in trying to choose between business-as-usual activities and sustainable environmental stewardship, the better will be the chances that the risk- averse common sense of the "average" person may be thrust into the decision-making process by a public that cares about its future and that of its planet, and knows enough not to be fooled by simple solutions packaged in slick commercials or editorials by any special interest.

What are the kinds of actions that can be considered to deal with global change problems like climate change. The following list is a consensus from a multi- disciplinary, business, university and government assessment conducted by the National Research Council in 1991. It is encouraging that this multi-discipline, ideologically diverse group (including economist Nordhaus, industrialist Frosch and climatologist Schneider) could agree that the United States, for example, could reduce or offset its greenhouse gas emissions by between 10 and 40 percent of 1990 levels at low cost, or at some net savings, if proper policies are implemented. Here is the Council's entire suggested list:

(1) Continue the aggressive phaseout of CFC and other halocarbon emissions and the development of substitutes that minimize or eliminate greenhouse gas emissions.

(2) Study in detail the "full social cost pricing" of energy, with a goal of gradually introducing such a system. On the basis of the principle that the polluter should pay, pricing of energy production and use should reflect the full costs of the associated environmental problems.

(3) Reduce the emissions of greenhouse gases during energy use and consumption by enhancing conservation and efficiency.

(4) Make greenhouse warming a key factor in planning for our future energy supply mix. The United States should adopt a systems approach that considers the interactions among supply, conversion, end use, and external effects in improving the economics and performance of the overall energy system.

(5) Reduce global deforestation.

(6) Explore a moderate domestic reforestation program and support international reforestation efforts.

(7) Maintain basic, applied, and experimental agricultural research to help farmers and commerce adapt to climate change and thus ensure ample food.

(8) Make water supply more robust by coping with present variability by increasing efficiency of use through water markets and by better management of present systems of supply.

(9) Plan margins of safety for long-lived structures to take into consideration possible climate change.

(10) Move to slow present losses in biodiversity.

(11) Undertake research and development projects to improve our understanding of both the potential of geoengineering options to offset global warming and their possible side-effects. This is not a recommendation that geoengineering options be undertaken at this time, but rather that we learn more about their likely advantages and disadvantages.

(12) Control of population growth has the potential to make a major contribution to raising living standards and to easing environmental problems like greenhouse warming. The United States should resume full participation in international programs to slow population growth and should contribute its share to their financial and other support.

(13) The United States should participate fully with officials at an appropriate level in international agreements and in programs to address greenhouse warming, including diplomatic conventions and research and development efforts.

This NRC (1991) assessment produced a remarkable list, considering the diversity of the participants' backgrounds and their varying ideological perspectives. But in the crucible of open debate that permeated that assessment activity, self-interest polemics and media grandstanding are incinerated. This group didn't assert that catastrophe was inevitable, nor that it was improbable. We simply believed that prudence dictates that "despite the great uncertainties, greenhouse warming is a potential threat sufficient to justify action now."

Integrated assessments of the policy options offered by the National Research Council Report are actively being pursued with a variety of models.

It is interesting that this comprehensive list of 13 recommendations from the National Research Council report still ignored two fundamental aspects: the desperate need for (1) an intelligent, non-polemical public debate about global change and (2) interdisciplinary public education that also teaches students about whole systems and long-term risk management, not only traditional areas of isolated specialization.

Environment and (or versus) Development? While the NRC report did acknowledge the importance of international dimensions of global change policy making, it was still largely a developed country perspective. Developing countries often have very different perspectives. First of all, LDCs are struggling to raise literacy rates, lower death rates, increase life expectancy, provide employment for burgeoning populations and reduce local air and water pollution that pose imminent health hazards to their citizens and environments. Protecting species or slowing climate change are simply low on their priority lists as compared to more mature economic powers like the OECD nations. It is ironic, even if understandable, that LDCs put abatement of global change disturbances so low on their priority lists despite the fact that nearly all impact assessments suggest that it is these very countries that are most vulnerable to climatic change, for example.

There is a phrase in economics known as "the marginal dollar." In our context it means that given all the complexity of interconnected physical, biological and social systems, climate abatement may not be perceived as the best place to invest the next available dollar so as to bring the maximum social benefit to poor countries. I have heard many representatives of LDCs exclaim that until poverty is corrected, preventable disease stamped out, injustice redressed and economic equity achieved, they will invest their precious resources on these priorities. My response has been that climatic changes can exacerbate all of those problems they rightly wish to address, and thus we should seek to make investments that both reduce the risks of climate change and help with economic development (transfer of efficient technologies being a prime example). It is a great mistake, I believe, to get trapped in the false logic of the mythical "marginal dollar," for it is not necessary that every penny of the next available dollar go exclusively to the highest priority problem whereas all the rest (particularly problems with surprise potential and the possibility of irreversible damages) must wait until priority one is fully achieved. To me, the first step is to get that marginal dollar cashed into small change, so that many interlinked priority problems can all be at least partially addressed. Given the large state of uncertainty surrounding both the costs and benefits of many human and natural events, it seems most prudent to address many issues simultaneously and to constantly reassess which investments are working and which problems -- including global change -- are growing more or less serious.

It takes resources to invest, of course, and since the bulk of available capital is in developed countries, it will require international negotiations -- "planetary bargaining" it has been called -- to balance issues of economic parity and social justice with environmental protection. Such negotiations are underway under U.N. auspices, and will likely take many years to work out protocols that weigh the diverse interests and perceptions of the world's nations.

There is a lively debate among economists, technologists and environmentalists about what are the most cost-effective strategies for abating carbon emissions which also can reduce potential impacts of climatic changes to below the undefined "dangerous" levels referred to in the Framework Convention on Climate Change language. Most economists argue that some policy to "internalize the externality" of potential climate damage is already appropriate, reflecting the recommendations already published by the National Research Council in 1991. Environmentalists usually argue that major efforts to spur immediate abatement of carbon emissions are necessary if climatic changes less than one more degree Celsius are to likely be avoided (which they typically define as "dangerous"). Most economists, on the other hand, often argue that new technologies will be able to accomplish carbon abatement more cheaply in the future as such technologies are discovered and deployed (Wigley et al, 1996). Thus, their logic suggests that a cost- effective time profile of abatement would be to postpone most carbon reductions until later in the 21st century. This seemingly implacable debate will echo in Kyoto chambers, I am sure, in December 1997.

My colleague, the Stanford University economist Lawrence Goulder, and I have used state-of-the-art economic modeling tools to study this debate, and conclude that both the stereotypical environmentalist (who argue to abate now) and economist positions (abate later) are actually not incompatible, but complimentary! We show (please see the Appendix in which our submitted Commentary to Nature magazine is reproduced) that although the economist view that future abatement is likely to be cheaper is probably correct, so too is the environmentalist argument that current actions are urgently needed, since such technologies referred to in economic cost-effectiveness studies won't simply invent themselves. In other words, policy actions to help induce technological changes are needed now in order to bring about a profile of cost-effective abatement in the decades ahead. We also address the relative economic efficiency of alternative policy instruments: contrasting carbon taxes versus research and development subsides. Although we recognize the political reluctance of many to embrace any new taxes, in truth, most economic analyses show that a fee for the use of the atmosphere (currently a "free sewer") will reduce incentives to pollute, increase incentives to develop and deploy less polluting technologies, and can be more economically efficient than other policies -- particularly if some of the revenues generated by a carbon tax were recycled back into the economy. R&D subsidies can be economically efficient, our conventional economic analyses suggest, to the extent that current R&D markets are already subsidized or otherwise not optimally efficient -- a likelihood.

Therefore, it is my personal view that all parties should recognize that potential damages to a global commons like the Earth's climate are not mere ideological rhetoric, nor are solutions necessarily unaffordable. Moreover, " win-win" solutions in which economic efficiency, cost-effectiveness and environmental protection can happily co- exist are possible -- if only we put aside hardened ideological positions.

V. Personal Observations On The Global Warming Media Debate

A very intense, too-often personal and ad hominem , media debate has attended the global warming problem in the past five years. As a participant in this process, I can attest to the frustration one experiences in seeing a complex scientific problem with many policy implications often trivialized into an ideological boxing match in which polar extremes are pitted against each other and the work of the vast bulk of the knowledgeable community is marginalized. A baffling array of claims and counter claims appears, particularly in op-ed pieces, and a general state of public confusion is fostered. It is my belief that this confusion does not reflect the ordered state of knowledge, in which many aspects of the climate change issue enjoy strong consensual views, other aspects are considered plausible, whereas yet others are clearly (to insiders at least) highly speculative. Public dialogue would be much richer if we all strove to separate out what is well known from what is speculative, an effort not attempted often enough in most public accounts of the issue. How is this best accomplished?

For twenty years the scientific community, or at least the broad cross section scientific community represented by the deliberations of the National Research Council, IPCC and other international assessment groups, have suggested that if CO2 were to double and be held fixed, then at equilibrium (i.e. the change in steady state after a few hundred years) the earth's temperature would warm up some one and a half to four and a half degrees centigrade -- the uncertainty, as noted earlier, in this climate sensitivity range largely being associated with the well recognized processes that we treat crudely in our climate models, mostly clouds and water vapor. The reason that very few scientist set the climate sensitivity range above four and a half degrees or below one and a half degrees is primarily because of natural experiments such as ice ages, volcanoes and seasonal cycles, as well as other technical questions dealing with theory and modeling (see IPCC 1996a for details). Nevertheless, a few have asserted, some with very high confidence, that global warming from CO2 doubling would only cause a few tenths of a degree C equilibrium temperature rise, and even have argued that certain processes that they can name, but cannot demonstrate to have global scale effects, would be responsible for this diminishing effect (e.g. Lindzen, 1990). Such debates (e.g. see Schneider, 1990) are very difficult for the lay public to penetrate, and even for relatively skilled but still non-professional observers, they are hard to follow. It is for such reasons that groups like the National Research Council or The World Meteorological Organization and the United Nations Environment Program have called a community of scientists holding a spectrum of views, but all knowledgeable in the basic art, to meet together to debate the relative merits of various lines of evidence and to provide assessments which give the best guess as well as a judgment for the ranges of uncertainty of a variety of climate changes, as well as their potential impacts on environment and society and the costs of mitigation from alternative policies. Indeed, the Intergovernmental Panel on Climate Change (IPCC 1996a, b, and c) is now the premier such assessment activity and represents the effort of hundreds of directly involved scientists and thousands of indirectly involved scientists, industrialists, NGOs or policy makers who serve as reviewers and commentators.

The IPCC Peer Review Processes Let me contrast the IPCC process with that of some of its critics. In July of 1996 an extraordinary meeting of about six dozen climate scientists from dozens of countries took place. It was the third installment of a process to write a Second Assessment Report for the IPCC. This meeting, in Asheville, North Carolina, was designed to make explicit the points of agreement and difference among the scientists over exceedingly controversial and difficult issues, including the signal detection and attribution chapter -- the most controversial. Chapter 8 was controversial since new lines of evidence had been brought to bear by three modeling groups around the world, each suggesting a much stronger possibility that a climate change signal has been observed and that its pattern (or fingerprint) is much closer matched to anthropogenic caused changes than heretofore believed. Scientists are by nature a skeptical lot, and typically submit their work for peer review before publishing. When scientists have new ideas or new tests, as the dozen or so representing these modeling groups in fact had, they typically write a journal article and submit it for publication. The journals, peer reviewed of course, typically send the article out to two or three peers, who write anonymous reviews, (unless the reviewers have the courage to confess as I, the editor of the journal Climatic Change, encourage my reviewers to do). The authors then rewrite their article in response to the reviewers and the editor serves as referee. The process usually goes back and forth several times with several revised drafts of the article until a suitable compromise is achieved among reviewers, authors and the editor.

Contrast this normal journal peer review process in which a few people are involved, with what happened in Asheville in 1995 at the IPCC's third workshop. Ben Santer from Lawrence Livermore National Lab, who had assembled the results of a number of modeling groups and was the first author of the submitted manuscript (Santer et al, 1996) on climate signal detection and the Convening Lead Author of Chapter 8 of the IPCC report (the controversial IPCC chapter on signal detection and attribution), presented the results of his group's effort not to just the half dozen Lead Authors of Chapter 8, as is typical in IPCC meetings, but to the entire assembled scientific group at Asheville. Not only did Santer have to explain the work of him and his colleagues (many of whom were there) to his most knowledgeable peers, but also to scores of others from communities as diverse as stratospheric ozone experts like Susan Solomon and Dan Albritton, to satellite meteorologists like John Christy or biospheric dynamics experts such as Jerry Melillo. Climatologists such as Tom Karl or myself were also present, along with heads of weather services and other officials from several countries who served on the IPCC's assessment team as a member of the scientific delegations of the various nations. Not everybody was equally knowledgeable in the technical details of the debate, of course, but even these less familiar participants served an essential role: of witnesses to the process of honest, open debate. Perhaps only twenty-five percent of those assembled had truly in-depth knowledge of the full range of details being discussed. However, all understood the basic scientific issues and most know how to recognize slipshod work -- to say nothing of a fraud or a "scientific cleansing" -- when they see it. This remarkable session lasted for hours, was occasionally intense, always was cordial, and never turned polemical. As a result, words for Chapter 8 were changed, ideas and concepts altered somewhat, but by and large basic conclusions were unchanged because the vast bulk of those assembled (and no one proclaimed to the contrary) were convinced that the carefully hedged statements the lead authors proposed were, in fact, an accurate reflection of the state of the science based upon all available knowledge -- including the new results. This was not only peer review, but this was peer review ten times normal! As the editor of a peer review journal it would be inconceivable for me to duplicate this process, as I have to hope that a few referees and myself can serve the peer reviewing role half as well as this remarkable, open process at Asheville. Moreover, after the Asheville meeting there were two more IPCC drafts written and reviewed by hundreds of additional scientists industrialists, policy makers, and NGOs from all over the globe.

Contrast this open IPCC process then, to the harsh critics of the IPCC, alleging "scientific cleansing", "herd mentality", and first presenting their detailed technical counter arguments in such "refereed scientific literature" as the editorial pages of the Wall Street Journal (Singer 1996, Seitz 1996,). Some had the temerity, although I do not understand how they could do it with a straight face, to allege that Chapter 8 conclusions were all based upon non peer reviewed work, despite the fact that the Asheville process was ten times normal peer review, to say nothing of the hundreds of scientific reviewers of the next draft of the IPCC report that followed. In the wake of all these reviews, textual alterations needed to be made, and these were minor, but were done over the course of time. The last round of changes were made by the Convening Lead, Ben Santer. Some interests subsequently alleged that these minor changes dramatically altered the report and, with no evidence, asserted they were politically motivated ("scientific cleansing" one charged -- and launched a vicious personal attack on one of the least political, most cautious scientists, Ben Santer). Any honest evaluation will reveal that this irresponsible charge -- published in the unrefereed opinion pages of a business daily -- is utterly absurd. In fact, the most famous line in the IPCC report (that there is a "discernible" human effect on climate) appeared as one sentence in a short paragraph that was 80% caveats! The IPCC report essentially "drips" with caveats.

Moreover, the "discernible" line is not a radical statement, as it reflects a lowest common denominator consensus view of the vast bulk of people exposed to the evidence. It does not assert climate signal detection to be proven beyond any doubt, nor do I or any other responsible scientists I know of make such assertions. Nor can such evidence of human effects be dismissed as wholly random at a very high probability by responsible scientists -- except perhaps in the opinions section of some newspapers. To ignore such contrarian critics would be inappropriate, I agree. However, to give them in news stories comparable weight to a hundred-scientists, thousand-reviewer document, as if somehow a small minority of scientists who are skeptical deserve equal weight, without informing the readership or viewership that the contrarians represent a tiny minority, is to mislead a public who cannot be expected to look up for themselves the relative weights of conflicting opinions. And to publish character-assassinating charges of "scientific cleansing" without checking the facts is simply unethical -- at least in any system of ethics I respect.

VI. Concluding Remarks

A condensed summary of the principal conclusions I would like to draw is as follows, beginning with the more narrowly technical issues and proceeding to broader generalizations about impacts, uncertainties and policy choices:

Hierarchy of models. A hierarchy of models, ranging from simple zero or one- dimensional, highly parameterized models up to coupled three-dimensional models that simulate the dynamics and thermodynamics of connected physical and biological sub- systems of the earth-system are needed for climatic effects assessment. The simpler models are more transparent -- allowing cause-and-effect processes to be more easily traced -- and are much more tractable to construct, run and diagnose, whereas multi- dimensional, dynamical models can provide geographic and temporal resolution needed for regional impact assessments and -- hopefully -- provide more realistic and detailed simulations, even if at much higher costs for construction, computation, diagnosis and interpretability. Since the real climate system is undergoing a transient response to regionally heterogeneous (patchy) forcings (e.g., aerosols and greenhouse gasses combined, which both vary over time and space), eventually it will be necessary to run fully-coupled three-dimensional earth systems models in order to "hand off" their results to a variety of regional impact assessment models. In the interim, lower resolution "simple" climate models can be hybridized into more comprehensive models to produce hybrid estimates of time-evolving regional patterns of climatic changes from a variety of emissions and land use change scenarios. Such estimates may be instructive to policy makers interested in the differential climatic impacts of various climate forcing scenarios and/or various assumptions about the internal dynamics of both climate and impact models.

Sensitivity studies are essential. It is unlikely that all important uncertainties in either climatic or impact models will be resolved to the satisfaction of the bulk of the scientific community in the near future. However, this does not imply that model results are uninformative. On the contrary, sensitivity analyses in which various policy-driven alternative radiative forcing assumptions are made can offer insights into the potential effectiveness of such policies in terms of their differential climatic effects and impacts. Even though absolute accuracy is not likely to be assured for the foreseeable future, considerable precision concerning the sensitivity of the physical and biological sub- systems of the earth can be studied via carefully planned and executed sensitivity studies across a hierarchy of models.

Validation and testing are required. Although it may be impractical, if not theoretically impossible, to validate the precise future course of climate given the uncertainties that remain in forcings, internal dynamics and unpredictable surprise events, many of the basic features of the coupled physical and biological sub-systems of the earth can already be simulated to a considerable degree. Testing models against each other when driven by the same sets of forcing scenarios, testing the overall simulation skill of models against empirical observations, testing model parameterizations against high resolution process models or data sets, testing models against proxy data of paleoclimatic changes and testing the sensitivity of models to radiative forcings of anthropogenic origin by computing their sensitivity to natural radiative forcings (e.g., season radiative forcing, volcanic dust forcing, orbital element variation forcings etc.) comprise a necessary set of validation-oriented exercises that all modelers should agree to perform. Similarly, impacts models should also be subjected to an analogous set of validation protocols if their insights are to gain a high degree of credibility.

Subjective probability assessment. In addition to standard simulation modeling exercises in which various parameters are specified or varied over an uncertainty range, formal decision-analytic techniques can be used to provide a more consistent set of values for uncertain model parameters or functional relationships. The embedding of subjective probability distributions into climatic models is just beginning (e.g., Titus and Narayanan, 1996), but may become an important element of integrated assessment modeling in future generations of model building (e.g., see the discussion of the hierarchy of integrated assessment models in Schneider, 1997b).

"Rolling reassessment." It is obvious that the projection of climatic effects and related impacts will continue to change as the state-of-the-art in both kinds of models improves over the next few decades. Therefore, the most flexible management possible of a global commons like the Earth's climate seems a virtual necessity, since the potential seriousness of the problem -- or even the perception of that seriousness -- is virtually certain to change with new discoveries and actual climatic and other environmental or social events. Therefore, a series of assessments of climatic effects, related impacts, and policy options to prevent potentially dangerous impacts will be needed periodically -- perhaps every five years as IPCC has chosen for the repeat period of its major Assessment Reports that treat climatic effects, impacts and policy issues as separable assessments. It seems important that whatever policy instruments are employed (to either mitigate anthropogenic forcings or help reduce damage from projected climatic effects) be flexible enough to respond quickly and cost-effectively to the evolving science that will emerge from this rolling reassessment process.

Consider surprises and irreversibility. Given the many uncertainties that still attend most aspects of the climatic change and impacts debate, priority should be considered for those aspects which could exhibit irreversible damages (e.g., extinction of species whose already-shrinking habitat is further stressed by rapid climatic changes) or for which imaginable "surprises" have been identified (e.g., alterations to oceanic currents from rapid increases in greenhouse gasses). For these reasons, management of climatic risks needs to be considered well in advance of more certain knowledge of climatic effects and impacts.

"Win-win" strategies. Economically efficient, cost-effective and environmentally sustainable policies have been identified and others can be found to help induce the kinds of technological innovations needed to reduce atmospheric emissions in the decades ahead. Some mix of emissions "cap and trade" , carbon taxes with revenue recycling, or technology development incentives can provide "win-win" solutions if all parties to the environment-development debate would lower the intensity of their ideological preconceptions and work together for cost-effective and equitable measures to protect the global commons.


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Copyright 2011, Stephen H. Schneider, Stanford University