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To add to your point that there is no comparison, the claims of evolutionists can be easily checked (DNA analysis, fossil morphology, speciation in the wild etc
by zeteo 16y ago
To add to your point that there is no comparison, the claims of evolutionists can be easily checked (DNA analysis, fossil morphology, speciation in the wild etc.). The _historical_ claims of climate scientists can also be verified (pollen analysis, study of ice cores etc.), although it is much more difficult to do so (what with people throwing away the original data sets and so forth).
However, the _predictive_ claims of climate scientists only follow from the historical facts through the means of statistical, computerized models that are, AFAIK, essentially unproven. In fact, exact quantitative predictions have consistently failed for the last two decades. There is no more science in _predictive_ climatology, I believe, than there is in forecasting the stock market (where the same kind of computer models are also used extensively).
- lutorm 16y agoI completely disagree with you. While there are certainly uncertainties in global circulation models, they are based on the laws of physics. Stock market modeling is not, it's entirely based on unproved/ad-hoc statistical models that likely have no relevance to the real world.
- zeteo 16y agoYes, but stock market modeling is also based on the law of supply and demand, which is pretty well proven. The trouble is that, in both cases, the base is far removed from the superstructure, and there's a chaotic system in between.
- lutorm 16y agoThe "law" in law of supply and demand is a very different thing than the law in the laws of physics... I agree with you about the chaotic thing, though.
- zeteo 16y agoIt's not that different from the laws of gases, really. Increase pressure, temperature increases (can't tell what individual molecules do). Increase demand, price increases. (Of course, this only works predictably for very, very atomized markets.)
- say_ 16y agoI disagree. Quantifying the energy balance of the planet is easier than quantifying the aggregate behavior of individual, semi-rational actors in the marketplace. What happens within the climate system of the Earth is chaotic, but the energy balance itself is measurable. If you'd like to see a chart summarizing the various climate forcings, then look at page 4 of this link: http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm.pdf http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm... I'm not going to track down all the literature behind those numbers here, but there are published, falsifiable arguments supporting them. Climate models aren't similar to Wall Street voodoo.
- zeteo 16y agoLooking at the Summary for Policymakers that you linked to, we are given measurements of [+0.6 to +2.4] W/ sq m at 90% confidence. Notice the huge interval: the interval length is three times the least value. If we'd re-scale it for 95%, or even 99% (the FDA will require that much for some drugs!), the warming disappears completely. And this is simply the measurement part. _Predicting_ what will happen is a thousand times more difficult. If you want predictive science based on the laws of physics, look at astronomy. 4000 years ago, the Babylonians could predict astronomical events with much more precision than anything today's climatologists can predict about average temperatures.
- yummyfajitas 16y agoNo they aren't. They are based on the laws of physics with all sorts of wild assumptions tacked on to make them tractable. For instance, water is typically modeled as having the consistency of molasses in the x-y directions, and some even more viscous material in the z-direction. Many important components of climate modelling are simply not derivable from simple physics (e.g., biological effects, cloud formation), and these are just made up to fit historical records, if not ignored. Scale separation and statistical pseudoequilibrium (forget the exact term) are just assumed in order to "get results". I.e., if you didn't make those assumptions, simulations would require so many data points that they would be impossible. Nonphysical energy damping is added, since without it, most simulations blow up. Lots of important parameters are just picked roughly at random, just to calibrate the model to historical data. Stock market predictions also tend to have one major advantage over GCM models - their proponents admit their limits.