I’m thinking of this in the barest, simplest of terms, and I need the help of the SDMB to flesh this out.
To determine how much human activity is affecting climate, “models” are made. My question is: on what are the models based? There is no parallel humanless Earth with which our own Earth can be compared … and I’m thinking the lack of such a “control” Earth would be a huge hindrance to really knowing what the climate would be like without human interference.
(Crossing my fingers that this thread can stay out of GD.)
Well there’s things like ice cores, and geological records, as well as tree growth rings, and the like to tell us about climate change, CO2 levels ect, before humans came around and built cars.
There’s computer models too.
There are tons of things that we use in daily life that is based on computer modeling - weather forecasts, economics, many kinds of engineering, epidemeology, architecture, etc. How did we know that the Empire State Building or the Petronus Towers were not going to crush under their own weight? You don’t have to build them 1:1 scale in a desert somewhere before you build them in a city.
A lot of the global warming skeptics are older guys who were around when computer/mathematical modelling first came around. Due to the newness of the technology and the lack of comprehensive data, they got a lot of crap results. The difference is that now the quality of the data is orders of magnitude better, and the models much more complex.
Modeling is just prediction based on the best available data. It isn’t perfect - Hurricane Dean was supposed to hit the Texas/Mexico border based on models last Friday. The thing you look for is when the various models start to converge around the same conclusion.
Lamar, I understand where you’re going. It just seems like with things like engineering of (relatively) static strutures, there’s not much chaos to account for. But I was always under the impression that the world’s weather was highly chaotic, and that things could just happen without obvious precursors.
As beowulff suggests, even if individual events behave somewhat chaotically, it may be possible to make statistical predictions about the behavior of many such events. While it may be impossible to predict the exact course of a hurricane more than a few hours in advance, one can predict, for example, the number of hurricanes that will occur in a given region in a particular year based on initial conditions, of course with some margin for error.
While we can’t actually do controlled experiments on the Earth as a whole, that’s not a unique situation in the sciences. There are also very few experiments possible in astronomy, but nobody disputes astronomy’s status as a science. One can, however, construct experiments which represent small aspects of the whole. In astronomy, for instance, one can put various gasses in a tube and excite them, to observe the spectra produced, and hence try to reconstruct the composition of astronomical objects whose spectra we observe. And in climatology, one can experimentally measure things like the infrared opacity of carbon dioxide, or the thermal expansion coefficient of seawater, which are among the many imputs to the climate models.
I think the short answer is that the Earth before the industrial revolution is the control.
If there was no evidence of past climates, we would not be able to say nearly as much about anthropogenic climate change. But there are many kinds of such evidence. If you look at the 10,000 centuries in the last million years, and only one of those centuries had either a sudden climate shift or a rise in CO2 that we remembered spitting out, and that century had both, then you have a pretty strong case. You can do this with the last million centuries, if you want - that’s still only 1.5% of the Earth’s history.
Aren’t the “severity of hurricane season” predictions notoriously bad, well outside of a reasonable margin of error (whatever “reasonable” is )?
There also seems to be some kind of bias going on – for instance, for the 2006 season, recent memories of Katrina and Rita seemed to lead to the prediction of a busy season for U.S. landfalls. Yet nothing happened … and AFAIK, it’s not at all exceptional for the predictions to be that far off.
Current conditions are considered to constitute a “sudden climate shift”? Or are you referring to volcanic activity or something similar in years past?
>Current conditions are considered to constitute a “sudden climate shift”?
Yes. I hope I remember correctly, but I don’t think there’s evidence of measureable shift in this short a time period in the record, except perhaps for big meteor inpacts.
Seeing a 10,000 year old glacier mostly disappear in decades is certainly an example of this. It obviously hadn’t happened in any of the other two hundred 50-year periods in this time, because the glacier wouldn’t be there if it had. I heard a while ago there wouldn’t be glaciers to look at in Glacier National Park soon (I think that was the name of the park).
Sorry I didn’t come back to this sooner … tough several days at work.
Cite for the bias? I don’t have that … that’s why I took care to note that there seemed (to me) to be bias. To be clear, I didn’t mean disingenuous, agenda-driven bias – I meant an overcorrection due to the record-setting 2005 season.
Cite for the inaccuracy of the 2006 hurricane predictions? See the two below:
I think you’re confusing modeling with experimentation.
Models don’t have controls, experiments do. Models (among other things) help to interpret the results of experiments. You are correct that there is no control in global warming models, but we are not really running an experiment. We are not injecting carbon gases into one earth and not doing it on another. That is, as you point out, nonsensical. The same issues applies to many other fields. Astronomy & Cosmology for instance. There is no second universe to control big bang theory against.
Modeling does not require a control. A model is judged to be strong/weak accurate/inaccurate based on many factors, one of which could be that it has shown success in identifying differences is controlled experiments.