To bad they want to predict the noise 20 years from now.”

What are you talking about? In this case noise means “A disturbance, especially a random and persistent disturbance, that obscures or reduces the clarity of a signal.” By the metaphor I employed, ’signal’ is the overall long-term temperature trend, and ‘noise’ is the year-to-year variation about that trend.

Also I’m not clear as to how the question of whether moore’s law is a self-fulfilling prophecy is consequential to my point that it can be more effectively used to predict processing power changes over 20 years than over shorter timescales (for example, it would break down if you were trying to compare the pentium 3 to the pentium 4, according to the graph). If anything the observation you make strengthens my point, because the phenomenon you are reporting would tend to make the model comparatively more effective over the shorter timeframes between generations of processors - in other words, it would reduce noise dramatically while only having a moderate effect on signal.

I think that the more extreme global warming advocates are making premature summary judgments, which is potentially problematic. I’m surprised at the thought of you taking such a position, however. And don’t try to say that your summary judgments wouldn’t have implications that have impacts on lots of people, because invading Iran certainly would, as would prohibiting safe injection centers or any of a number of other positions you have argued. Moreover, your rationales often amount to summary judgments, just like those the more extreme form of global warming relies upon.

Most of the

observational data have been presented by the scientists arguing for global warming

Is likely true. I stated this is the post found in points 1 and 2.

Can you read?

Why not? Long-term trends are often easier to predict than short-term trends simply because the effect of noise is reduced.

To bad they want to predict the noise 20 years from now.

From the same entry:

Although Moore’s Law was initially made in the form of an observation and forecast, the more widely it became accepted, the more it served as a goal for an entire industry. This drove both marketing and engineering departments of semiconductor manufacturers to focus enormous energy aiming for the specified increase in processing power that it was presumed one or more of their competitors would soon actually attain. In this regard, it can be viewed as a self-fulfilling prophecy. For example, the SEMATECH roadmap follows a 24 month cycle.

Its hard to see how wanting global warming will make us create catastrophic environmental conditions which is something we should actively regulate now, but whatever.

If I found the evidence compelling (and was reasonably confident that I wasn’t under the influence of some mind-altering substance or otherwise compromised when I made that determination), and someone could explain to me how I could even accomplish such a feat, yes. So again, we go back to my original suggestion - that you need to evaluate the evidence on a case-by-case basis rather than making such broad, un-nuanced statements.

“Are you an idiot?”

No, but just to help you not put your foot in your mouth again in this regard…

http://en.wikipedia.org/wiki/Appeal_to_consequences

I was attempting to warn you away from the argument of “if global warming is true, severe economic policies might be implicated. Therefore, global warming is false”.

To be charitable to you, perhaps you are merely confusing appeal to consequence with the opposite fallacy - appeal to the stick. If that’s really what you are arguing against, I see this as a bit of a strawman position, because both a mechanism and observational data have been presented by the scientists arguing for global warming: ultimately the question at issue is whether global warming advocates are making a summary judgment prematurely and/or drawing inductions that are too broad, given the data they have access to.

Even if they are, this puts you in the rather awkward position of trying to explain why it is good for you to make summary judgments with policy implications and bad for people who actually have training and background in the field to do so.

“Computer models that predict further than two decades are not convincing no matter who makes the argument.”

Why not? Long-term trends are often easier to predict than short-term trends simply because the effect of noise is reduced.

http://upload.wikimedia.org/wikipedia/commons/0/06/Moore_Law_diagram_%282004%29.png

From a year-to-year basis, there is a fairly erratic pattern that is based on extremely complicated and nearly unforeseeable factors. However, over time scales greater than 20 years, predictions of exponential increase made as early as 1965 have proven to be remarkably robust.

But even in that example its much easier for me to grant that scientist are much more capable of predicting the simple movements of a chunk of rock in space then the massive amount of calculations needed to predict the impact of climate change fifty years from now.

Furthermore, lets say that the scientist concerned about this rock ally themselves with a group of people interested in regulating capitalism because of the so-called damage it does to the environment. Seeing that scientists are proposing massive economic regulation they jump on board over stating the probability the rock will hit and what kind of damage the impact will have. Upon hearing this I have no doubt you will eagerly jump on board for massive economic regulation.

Out of curiosity, If scientists offered evidence suggesting that having sex with trees would in 543 years magically transform the world into heaven would you fuck a tree?

Finally:

Also, try to avoid making an appeal to consequences. That’s just poor argumentation.

Are you an idiot? My whole post was about others making this mistake.

Moreover, by your argument, if astronomers determined tomorrow that a minor planet were on a collision course with earth, there must be no basis for taking potentially expensive action to redirect its course, because science has no business determining policy based on things that haven’t been experimentally observed, -especially- if they are making extremely dire predictions. Honestly, I think you should stick to arguing that the science behind global warming is bad science, rather than that scientists shouldn’t ever be trusted with this sort of thing. The former is a much more defensible position.

Also, try to avoid making an appeal to consequences. That’s just poor argumentation.

As I already stated, in terms of global warming, a climatologists that is making claims twenty years from now, but I know to be impartial I’m likely to trust. Anything past that point that is not sufficiently broad enough I will distrust. My distrust grows when such predictions associated with a group of people whose world view I do not share.

This holds true for all things including epidemiological and economic forecasting. As already stated, when these kinds of forecasts are explicitly attached to political views I don’t hold, and to certain extent one’s that I do hold, I will always regard their future claims as dubious. An epidemiologist’s proclamations that most of mankind will be wiped out by some kind of disease 76 years from now is not compelling. It’s impossible for him to know what things could happen in the intervening years. For all we know an alien race could provide the antidote.

Countless prophets have declared the end of the world. Some are no doubt experts with the sacred texts from which they divine their dooms day predictions. Some of these expert doom day sayers are likely to agree with each other about when the end of times will come. Now we have knowledgeable experts all in a consensus with when the end of the world begins. How compelling would you find these predictions?

Again, you make an argument that scientific attempts to predict future climate conditions are less compelling the further they try to predict. What leads you to believe in this? What would you consider to be an accurate time-table for prediction? Is economic forecasting similarly flawed? Why? What about epidimiological forecasting? Scrap it? Meaningless?