Reality, Science and Climate

Mark Pottenger

(Posted in March & April 2009 on a no-longer-available message board)

Except for a few reflexes like a baby's sucking reflex or the classic knee-jerk, people do not react directly to sense impressions. People have to learn to interpret sense impressions, and then react based on their learned interpretations. This learning process essentially builds an internal map or model of the external world that is unique to each person. Some parts of the internal model of the world are easier to form than others. For example, people seem to be born with special brain circuitry to recognize faces, making the whole process of interacting with other people easier to learn (for most people in which the circuits are in working order).

If you think you respond directly to what your senses "tell" you with no interpretation required, test yourself with a few simple examples.

Listen to a sample of speech in a language you don't speak or know. You can probably (though not guaranteed) tell that it is speech, but you certainly can't get any linguistic meaning out of the sounds. Depending on the nature of the speech sample and the similarity of the sample language to languages you do speak, you might get emotional content from the sample, detecting anger or joy or other strong feelings.

Now look at unknown or unfamiliar pictures, especially of unfamiliar objects or involving unusual compositions. You will probably be able to identify what objects are depicted quickly in most cases, but if you look at enough pictures, you will also almost certainly encounter some that are just incomprehensible shapes and/or colors at first glance. Some might even take several long looks before you can spot an edge or a face or a head or a limb or something that gives you a clue to separate the image into recognizable objects. Once you achieve that recognition, it will be very difficult to see the picture again as incomprehensible.

Also in the area of pictures, there are multiple techniques for letting people see images that look three-dimensional. One very common technique involves a single image (an anaglyph) with overlapping components in red and blue. If you look at this with standard vision it is just a not-very-good picture. If you look at this through special glasses with one red side and one blue side, you see an apparently 3D picture. There is another technique (stereogram?) that looks like a jumble of colors. I have to take on faith that those can be viewed as 3D pictures because I have never been able to get my eyes & brain to see anything but a jumble of colors in the examples I've looked at.

For a final example, look at a few classic optical illusions or paradoxical figures. The face-vase is a classic, as are impossible triangles, perspective drawings of cubes that visually flip depending on how you view them, or some of the art of M. C. Escher. Many such illustrations change as you focus on different parts or as you mentally change what you think you are seeing.

I believe the fact that we respond to our mental model of the world rather than responding to the world directly is at the heart of the reference to the world as an illusion in several religions and philosophies. This is often misunderstood as a denial that a real world exists. I think it is a reminder that while the real world exists, that isn't what most people "see" in normal mental states. (That also suggests the thought that at least some mental illnesses could be described as bad models of reality.)

I mentioned the importance of expectations in my essay on genre labels. This ties in fairly closely to the point of personal mental models. Expectations are predictions from personal mental models. Inaccurate mental models can cause trouble by creating unrealistic expectations. Gambling can be an example when the gambler expects to win despite actual statistical odds for the house. I don't know the exact nature of the false expectations involved (prices will rise forever, nobody will notice bad assets hidden in complicated portfolios, perpetrators will be rich & retired before houses of cards collapse, etc.), but the current mess in the world's financial systems is a serious reality check of whatever false expectations guided so many people in so many companies for several years. The freezing of so much credit is another affect of models and expectations--many banks are afraid to make loans now that they can no longer shuffle bad debts off to some other sucker. The bankers, along with many other people, now fear an even worse economy, creating a spiral of inaction and loss. (Fear is a negative expectation based on a mental model.) Expectations based on mental models can create self-fulfilling prophecies through reinforcing feedback loops.

Just as every person has to build a personal model of the real world to be able to function in it, science is a collective process of building models of the world. Scientists have been engaged for centuries in the process of building better models of the world.

All modern technology depends on the models of reality established by science. The Internet, the servers hosting these message boards, my connection to the Internet, the computer I'm typing on, the electrical power grid letting me run my computer, and the power plants supplying electricity to that grid all work because they are built using good enough models of reality.

I do not make any claim that the models of reality already established by science are finished or complete. Part of the scientific method is the process of testing hypotheses. A theory or model of reality is only considered useful if it lets people (or programmed computers) make predictions and/or retrodictions (also called hindcasts) that can be tested. (A retrodiction is a prediction about the past--a statement made based on a hypothesis or model or theory that can be checked against past data.) A working scientist might assess the discipline as a whole differently, but my personal view is that modern science is doing very well in the physical and biological sciences, that it has a long way to go in the social and mental sciences, and that it is severely lacking in the spiritual sciences. (In fact, I almost never see anything about spiritual matters in the general science reporting I read.)

Laws governing planetary motion provide an example of scientific models of reality. Newton's laws provide a set of equations that are a good enough model of reality to correctly describe most of the motions of most of the bodies in the solar system most of the time. Einstein gave us the added refinements of relativity theory, adding equations that handle a few conditions that Newton's laws don't get right. There are a few situations in the solar system where chaos theory is involved. Each addition since the fundamental work of Newton has been a refinement of or supplement to his equations, not invalidating them in any way.

It is always possible for a model builder to misapply scientific knowledge. In a project years ago where I wanted to work with planetary positions over more than a 26,000-year precession cycle I got some really strange planetary positions out of one iteration of the programming. I finally traced the weirdness to limitations of the precession equation I had been using, but it was a good illustration of the need for a reality-check with any model.

Climate is an incredibly complicated field of study, so nothing short on the topic can be anything more than superficial. (The Teaching Company course Earth's Changing Climate is 12 lectures, and that is just on the narrow topic of climate change.) Completely modeling the climate of just one planet (Earth) requires understanding the Sun (total energy output, output in each frequency of the electromagnetic spectrum, particle emissions, storms, sunspots, magnetic fields), the Moon (mostly tidal effects and a little reflected light), cosmic rays from outside the solar system, and meteors (mostly dust and a little energy) as well as the Earth itself. On the Earth, it requires understanding physics (gravity, orbital and rotational motions & their changes over time, radiation belts above the atmosphere, radiation balance [reflection & absorption by every solid, liquid & gas; how changing albedo affects everything], pressure effects in solids & liquids & gases, convection, phase changes of water [evaporation, condensation, freezing, thawing, sublimating], flows of gases & liquids & solids & plasmas & particulates in gases, how the shapes of surface features affect all flows, magnetic fields, dynamics of storms, electrical or plasma effects in the ionosphere & auroras & lightning & sprites, heat and radiation effects from radioactive elements in all layers of Earth), chemistry (components & interactions of the atmosphere, oceans, continents, mantle & core), geology (contributions to atmosphere by volcanoes & geothermal sites, absorption & release of gases by rocks, effects of continental drift on existence of ice caps), biology (absorption & release of gases by all microscopic & macroscopic life, both while living and after death), technology (effects of human mechanisms and actions on all the preceding), meteorology (weather, cloud cover, storms, fogs, etc.), and probably several more things I haven't thought to list. Beyond all the factors involved in climate, there are issues with the science of chaos. The "butterfly effect" nickname for chaos comes from the observation that exact weather predictions will almost certainly never be achievable because some necessary calculations display sensitive dependence on initial conditions. You can give a range of expected results or a confidence rating with phenomena behaving in that way, but a single unambiguous answer is almost impossible. The same limitations would apply to any attempt to make exact detailed statements about future climate rather than statements with ranges of expected values.

Modern understanding of climate has developed tremendously since the development of computers with enough power to let scientists program computer models of all the factors involved (global circulation or climate models). I'm probably grossly oversimplifying, but my understanding is that the models set up as many data points (cells) as the computer's capacity will allow, plug in data for each point, then run simulations applying the equations & rules needed to describe as many of the factors mentioned above as the model can handle. The earliest models could use very few data points or equations at first, with more points allowing more detail with each generational increase in computer capacity. Each generation of model can improve in two (or more) ways. More data points allow each cell to describe a smaller portion of the Earth, which permits the model to include more details (topography, composition, life, etc.) and allows the many equations to work better. More computer capacity allows the model builders to incorporate more equations describing more contributing factors. The many factors involved do not contribute equally to climate. Some factors are much more important than others, and many factors interact in complex ways with reinforcing feedback or negating feedback or threshold triggers. Modeling started with the most obvious contributing factors and each generation of model can add weaker factors that refine the results, but the models are already beyond the level of refinement where an addition will make a big change in the development phase of working with past data. Modern climate models will probably approach within not too many more years as good a map of reality for climate as was achieved for celestial mechanics during Newton's lifetime. They also show how much more complexity science has learned to handle in a few centuries. I can run calculations of a Newtonian model of the dozen or so largest bodies in the solar system with a few constants and equations on a home computer. A climate model requires incredibly complex programming and masses of data on a supercomputer (a site listed below does have a cut-down subset for home computers). All climate models are tested & validated by running them for past times to be sure they make good retrodictions before running them for future times to make projections or predictions. Even 20 years ago the model Hansen used was good enough to make projections close to the actual measurements taken in this decade. The only valid basis for challenging the good fit to data (reality) achieved by GCMs [General Circulation Models] is some other model with an even better fit to the data (reality)--anyone who can ignore all that work or dismiss it because of religion, ideology or self-interest is living in a cave (Paleolithic or Platonic, take your pick).

Greenhouse gases are so labeled because adding more of them to the atmosphere acts on the Earth just like putting up glass to build a greenhouse. More greenhouse gases in the atmosphere cause more incoming energy to stay, causing overall warming. Carbon dioxide, methane, and several other more complicated molecules all act as greenhouse gases. They are a major focus of attention both because past human activity has released them into the atmosphere and because they are one of the few factors affecting climate that deliberate human action CAN change in the near future. The opportunity for people to act is a classic illustration of the phrase "an ounce of prevention is worth a pound of cure". The longer action is delayed, the more costly action becomes. Hurricane Katrina's disastrous flooding of New Orleans could have been prevented by better engineering of levees before the storm. Since the better engineering didn't happen, we have a devastated city that is still a mess over four years after the storm. Acting on climate is like rebuilding levees in New Orleans on a larger scale--act in time and you save a lot of lives and property, fail to act and you face massive loss of life and a huge repair bill.

Some uncertainty in the projections from climate models comes from factors I listed (or others I missed) above that are not yet incorporated into all models. Another uncertainty relates to the very conservative assumptions used in most projections, especially those from the ipcc. If the assumption that no component will drastically or suddenly shift turns out wrong, the situation could get much worse much faster. Most of the variations in the projections come from the use of different assumptions about future human actions. Optimistic projections assume people will wake up and take drastic action, leading to slowing increases in CO2 and temperature. (Worth repeating: the most optimistic outcome is a slowing of global warming, not an end or reversal any time within many years.) Less optimistic projections based on people continuing to act unthinkingly lead to scenarios rather hostile to human civilization as we know it.

The term "global warming" is used as shorthand for a very complicated process. The overall average temperature of Earth's atmosphere is increasing, so the term is accurate to an extent, but the whole process might better be called global climate destabilization. More overall energy in the atmosphere leads to more extreme weather of all kinds (hot, cold, hurricanes, droughts, floods, etc.), not just a gentle general warming. For a visual analogy, think of bringing a pot of water to a boil (by adding heat, just as is happening to our atmosphere)--at room temperature, there is little visible motion, but at a full boil there is a huge amount of bubbling and other motion.

Beyond the destabilization of weather, the warming aspect of the climate changes predicted by climate models has a couple already measured effects. It is melting both Arctic and Antarctic ice caps at rates unprecedented in recorded human history, which will lead to rises in sea level. The exact amount that sea levels will rise and the speed at which it will happen is still being argued, but the increased polar melting is already happening. In the rest of the world, climate change has already affected many habitats, causing plants to bloom and animals to breed at different dates, causing other animals to move their ranges when they can, and squeezing other plants and animals out completely when their ecological zones move and they can't move or adapt fast enough. Crop plants are not exempt from these problem, so problems with future food supplies can be expected.

Earlier, I posted a link to a Science News article about projected sea levels and the Maldives and Kiribati. Someone else posted a link to an article about Maldives local conditions. The local conditions article essentially says that since the Maldives experienced sea levels about 1/2 meter higher than now only about a millennium ago, a sea level rise of 1/2 meter as projected by the ipcc in 2001 is nothing to worry about.

That article does not change any conclusions of the Science News article. The 2001 ipcc sea level values are extremely conservative. The Science News article is discussing more recent and less conservative projections with possible sea level rises up to several meters. (Projecting to 2100 gives a convenient benchmark used in many projections, but nobody thinks changes will magically stop on that date. All projections without assumptions of major greenhouse gas abatement lead to even grimmer futures beyond that benchmark.) The local 1/2 meter dip would not save the Maldives if any of the higher projections are right. Since I've never seen the innards of a GCM, I don't know if the extra Indian Ocean evaporation mentioned in the article is already incorporated in the current generation (since the article is several years old, it might be), but this is exactly the kind of greater detail I said above improves each new GCM.

The Science News article also mentions that Kiribati is already dealing with increased flooding & other effects. Now. Real observations. Not projections.

Since I'm in my 50s and have no known children, nieces or nephews, most of the worst impacts of climate change are not expected soon enough to strongly affect anyone I know well. I still urge strong action because I don't find the thought of humanity regressing to a new age of "nasty, brutish and short" lives appealing.

On a side note, I don't understand why some people talk as if the concept of global warming is a conspiracy invented by Al Gore. I could understand castigating Gore for running such a poor campaign in 2000 as to allow W to occupy the White House, but AFAIK Gore's contribution to the climate debate is simply popularizing. He made a movie a few years ago that brought it to the attention of a lot of people who had previously ignored it, but the science has been around for years for anyone who pays attention. Just as one example, James Hansen testified to Congress in 1988 about global warming. The Kyoto Protocol is an international agreement about limit greenhouse gases that was adopted in 1997, and it was partially a follow-up of a big 1992 international meeting. Politicians in the U.S. and other countries have blocked action on the Kyoto Protocol for a decade now, making any solution more difficult and expensive.

Returning from the collective reality models of science to the individual reality models I started with, the personal nature of each model of reality has a major impact on communication and learning. New knowledge must build on or be acceptable to a person's model of reality or it stands almost no chance of being accepted. As Plato's allegory of the cave reminds us, trying to teach anyone something contrary to their current beliefs is more likely to achieve hostility than learning. If someone is raised in a culture that devalues science, citing the realities of science will never convince them of anything. Kuhn's material on scientific revolutions makes a similar point, arguing that many advances in knowledge require the old guard who think otherwise to die off.

At the level of the individual, the limiting case of bad modeling of reality can be death. Long ago the proximate cause would have been starvation, disease, losing a competition with some large animal, or some other basic survival problem. In the modern world fatal accidents are much more prevalent. ("I'm strong / fast / sober / alert / etc. enough to handle this situation / these driving conditions / this job.") Unfortunately, we now live in a world where one person's bad modeling of reality can lead to many deaths beyond their own (like the many traffic accidents that kill multiple drivers). The climate situation is an extreme case of this phenomenon. If enough people continue business as usual long enough, all people will suffer. This is a case where natural selection will operate at the species level rather than the individual level--if our species collectively isn't smart enough to deal with reality, we will join the dinosaurs as fossils (though dinosaurs lasted much longer than humans have so far).

Despite the difficulties, learning does still happen. Sometimes the 10th or 100th rewording of a topic finds a match in a person's model of reality and they are finally able to learn about the topic. The faint hope of that is why I was willing to spend hours working on this post.

Figures and suggested reading (there is lots more data on most of the host sites than just the pages linked here):

Here is a graph of CO2 concentrations for a few recent centuries (trend: rising).

Here is a graph of over 150 years of global temperatures (trend: rising):

[page no longer available]

Here is a graph of 30 years of arctic sea ice (trend: falling).

Here is a graph of changes to glaciers (trend: more retreating than advancing):

[page no longer available]

Here is a UK site with lots of weather & climate change info for anyone claiming to distrust US sources.

Here is a site with lots of experts & comments.

This is just one page of many within the above site that gives some idea of how complex some climate questions are (in this case, possible sea level rise).

Here is a site for anyone with idle computer time who wants to actually make a constructive contribution to climate science:

[page no longer available]

UK Treasury Review Report on the Economics of Climate Change.

(The short version: doing nothing about climate will cost 5% to 20% of global GDP per year while acting will cost 1%.)

Here is a site that goes beyond science to get into policy issues.

Lots of statistics about energy use.

If you want official US EPA greenhouse gas data:

[page no longer available]

Here is a lot about energy alternatives: [European Commission] [National Renewable Energy Laboratory].

A greenhouse stabilization proposal.

This describes a very recent meeting, one theme of which is that the situation is getting worse even faster than most people expected even a few years ago:

[page no longer available]

A recent show I happened to hear about melting glaciers.

James Hansen June 23, 2008 to Congress (20 years after 1988 testimony):

[page no longer available]

The Nature of Science

This is how I see science. Science collectively builds models of the world. These models are TESTED and refined or discarded based on how well their retrodictions and predictions match real measurements of whatever aspect of the world the models are trying to describe. Fields of science grow and mature just as people do. An immature science can explore many varying models. A more mature science coalesces around one model or a small number of models that consistently provide the best match for the most data. An immature science can make radical changes in models. A more mature science generally only refines one primary model by filling in details and expanding coverage at any edges. An immature science is more open for useful contributions from dabblers and non-specialists. A more mature science is largely a field for specialists or large teams, though sometimes outsiders can still make useful contributions. An immature science can involve a small enough sum of knowledge that a newcomer can learn the whole field in a relatively short time. A mature science will usually include so much specialized knowledge that it takes many years of study to master the field, and sometimes includes so much knowledge that it has to be broken into more narrow specialties to be within the grasp of individuals. Wildly different models can be on almost equal footings in an immature science, giving mavericks and pioneers a chance to contribute. With a mature science, models radically different from the mainstream or consensus have a huge burden of proof to overcome--they have to give retrodictions and predictions as good as the consensus model for all data used to validate the consensus model AND give BETTER retrodictions and predictions of data the consensus model hasn't handled.

Perhaps an analogy can make the concept of a developing science clearer. Think of producing an image of a library or school globe as the model of reality you are trying to construct. Early attempts might focus on a reflection of the globe in a mirror or on a shadow of the globe, but eventually the focus will be on the globe itself. Early images might have only a few black-and-white pixels of detail, then a few colors, then more pixels, and so on, with each generation of image adding more pixels or more gradations of colors or both. Eventually the best single image might become a hologram or some other 3-D technology. Finally, multiple images will be used to show the globe from all sides or angles or to show a time sequence as the globe rotates. After the first few false starts looking at reflections and shadows, every image is recognizably of the same object and no image invalidates any previous image, but the clarity of each image has grown step-by-step by showing more details.

The science of modeling the Earth's climate was quite immature several decades ago, but in the past several decades the science has matured tremendously. There is a huge amount of detail to be filled in, but the broad framework is established. There is now a mainstream or consensus model (or set of models [GCM]), and that consensus is the source of warnings of global warming. People talking about global warming decades ago turned out to be pioneers. Now they are the mainstream of a much more mature science.

Copyright © 2009 Mark Pottenger

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