Steve 41oo wrote:The position of the sceptics really puzzles me.
No-one[/b] denies that CO2 is a greenhouse gas. It's transparent to high frequency radiation from the sun, but absorbs the lower freqency radiation reflected from the earth's surface. Furthermore no one denies that there is considerably more CO2 in the atmosphere than before industrialisation. (When we started releasing billions of tonnes of CO2 in a geological blink of the eye, which had hitherto been trapped for eons).
The standard position is that warming is thus anthropogenic, i.e. is a result of man's activities.
But lets take the sceptical argument that warming has caused increased CO2 concentration, and that the Sun is the fundamental culprit. If[/b] that is the case, is that really justification for the continued and unregulated spewing out of carbon dioxide which we all agree is a greenhouse gas? If there is nothing we can do to turn the sun down a bit, dont we have just the same obligation not to make the situation worse by pumping out vast quantities of a known greenhouse gas?
The sceptics position seems to be one of despair. "There is nothing we can do about warming, so turn up the air conditioning while we still have enough fuel".
Steve, There are some important omissions and flaws in your argument above, as well as some undeniable truths. We agree on the effect of the industrial age and rising human population on the CO2 content of the atmosphere, and that this contributes to observed warming.
However, given that the earth's geological and climatilogical history is so continuously variable, we don't agree on the notion that what is observed is, or will continue to be, the only or even the dominant effect on climate change.
Science has learned a great deal about the dynamic behavior of coupled, highly non-linear systems, and the practical limits on mathematically modelling them, during the last several decades. The most fundamental new understanding comes in what is popularly called chaos theory. It, itself, arose from an early attempt to use modern computing power to model and accurately forecast weather patterns locally and across large areas. The attempt failed - and it stil fails - because of what was called "sensitive dependence on initial conditions". That means that such mathematical models quickly yield vastly different results when even the most infinitesmal change is made to the starting conditions. The models happily chug along, producing distributions that look like weather, but bear only a random connection with what actually unfolds in the real world. Moreover the underlying problem is mathematically intractable: there is no level of initial precision able to eliminate the large discrepancies.
The various numerical models used to forecast the shifts in ocean currents and climatological pattern that get so much public attention all have that characteristic and fundamental limitation. You may ask, "Why, knowing all that, do they publish these results?" I don't really know the answer. Perhaps it is because they have nothing better to go on; the result is, at least possible; and the publication gets them lots of attention, prominence, and further research grants. You may also ask, "Why does the public so blithely accept these forecasts, when they know, from their own experience, that meteroroligists (scientists) cannot even forecast the occurrence of a major storm a few weeks from the present?" I don't know the answer to that one either. Perhaps I should put the question to you.
There are other interesting properties of chaotic dynamic systems. They are somewhat self-regulating and, though their variations and continuing excursions are inherently unpredictable, their average behavior tends to repeat itself. They tend, in the long term, to damp out the effects of external changes. This is why the almanac and other empirical predictions of average climatology are practically useful. What implications this may have for the case of human generated increases in CO2 deposits in the atmosphere are hard to tell, but they do suggest that nature tends to resist unbounded excursions due to single variables. This is also a well-known principle of empirical science.
