Here in no particular order are some of the issues that skeptics of anthropogenic global warming theory are raising:
1. Global climate models have never been proven to have predictive power and are unlikely to ever be accurate in their current form. These models can be tweaked to reproduce known climate data but when tested prospectively, on their ability to predict what will happen, they fail rather badly.
To the extent that the trend up to 15 years ago was a straight line extension of the previous trend they models did OK for a time, but 15 years ago the temperature trend swerved and the models all missed it.
If one looks at the models then it's no mystery why they can't cut the mustard. They are remarkably crude. For example, the GISS model that produced their 2001 predictions models the continental US as a grid with 64 cells. The model can't see any difference in the climate between Baltimore and New York. It can't model clouds or rain. It relies in re-iterative approximations. Forecasting experts tell us such re-iterative models are only accurate for 5 or so iterations into the future. Climate modelers run them for hundreds of iterations.
Boiling the models down, though, much of the spacial information can be stripped out. What is left can be used to approximate the one thing people are most interested in, which is average global temperature from one year to the next. This can be modeled as a summation of all the climate forcings, which, if done, shows that the biggest source of variability in the model is atmospheric turbidity from aerosols, a variable that can't be predicted and is very difficult to measure globally.
2. The feedback from water vapor can't be as high as modelers say it is. Or, to be more specific, it can't be as high in nature or in practice as they say it is. It can be that high only in certain special circumstances, which is in atmosphere without cloud formation or rain. Study atmosphere with clouds and rain eliminated and you see this high feedback. But in nature such conditions are hardly ever seen. Instead the high water vapor content of the air is converted into clouds and then into precipitation, and there is never as much feedback from the water vapor as they calculate from clear skies. This is the reason for the absence of the trophospheric hot spot in the tropics. Before the hot spot develops clouds and rain intervenes.
The other line of evidence that goes against a high feedback is to consider what that ought to look like. Systems with high positive feedbacks tend to be driven rapidly to an extreme and stick there. In the tropics this would be a hot spot that grows and continues to heat up to some maximum. It would be runaway warming that spreads beyond the tropical regions. No such phenomenon has ever been observed. Clearly there is something limiting how much warming their is despite water vapor feedback.
3. Temperature proxies are never as good at estimating temperature as direct measurements of temperature. Proxies, such as tree ring thickness, are used where reference to a thermometer isn't possible, but often we see examples of proxies used to demonstrate warming when direct measurements are available and contradict the proxies. One example would be the snow cover of Mt. Kilimanjaro. As the snows thinned out in the 90s people claimed that this war the result of warming. But we had temperature measurements from the peak of the mountain, and they didn't show warming. As is often the case with proxies, there were other things that might explain the loss of snow. In this case it was a multi year drought. Once the drought was over the snows started coming back.
Similar contradictions are found with many other proxies whether we are talking about the distribution of wild life, the coming and going of mosquitoes, numbers of hurricanes and other storms, and so on.
In short, if you want to know what the temperature is doing then check the thermometer.
4. We can't cut carbon emissions enough to have any detectable effect on the climate even if you go by calculations supplied by the climate scientists who back AGW. Even cutting emissions by 80%, which would be tantamount to total destruction of the economy of the Western world, would have no detectable effect. It follows then that efforts in that direction, as expensive as they are, are a total waste.
5. Almost none of the predictions of the global doom and gloom climate crowd have proven accurate. Whether we are talking about population, global cooling, acid rain, ozone depletion and global warming. Most recently there was the prediction that this year we'd see millions of climate refugees. This also proved false. Next up will be a new crisis of some sort, perhaps ocean acidification.
6. Perhaps most difficult of all to predict is the direction that energy generation will take in the future. In the past 100 years we saw the development of atomic energy. In the next 100 years we might see even greater innovation and discovery. Such a thing could throw all the predictions, as inaccurate as they are already likely to be, into a cocked hat.
7. Cost analysis shows that it will be far more effective and economical to adapt to climate change, whatever it may be, than it would be to try to affect it with programs costing multiple trillions of dollars that the US and the rest of the developed world can ill afford.
1. Global climate models have never been proven to have predictive power and are unlikely to ever be accurate in their current form. These models can be tweaked to reproduce known climate data but when tested prospectively, on their ability to predict what will happen, they fail rather badly.
To the extent that the trend up to 15 years ago was a straight line extension of the previous trend they models did OK for a time, but 15 years ago the temperature trend swerved and the models all missed it.
If one looks at the models then it's no mystery why they can't cut the mustard. They are remarkably crude. For example, the GISS model that produced their 2001 predictions models the continental US as a grid with 64 cells. The model can't see any difference in the climate between Baltimore and New York. It can't model clouds or rain. It relies in re-iterative approximations. Forecasting experts tell us such re-iterative models are only accurate for 5 or so iterations into the future. Climate modelers run them for hundreds of iterations.
Boiling the models down, though, much of the spacial information can be stripped out. What is left can be used to approximate the one thing people are most interested in, which is average global temperature from one year to the next. This can be modeled as a summation of all the climate forcings, which, if done, shows that the biggest source of variability in the model is atmospheric turbidity from aerosols, a variable that can't be predicted and is very difficult to measure globally.
2. The feedback from water vapor can't be as high as modelers say it is. Or, to be more specific, it can't be as high in nature or in practice as they say it is. It can be that high only in certain special circumstances, which is in atmosphere without cloud formation or rain. Study atmosphere with clouds and rain eliminated and you see this high feedback. But in nature such conditions are hardly ever seen. Instead the high water vapor content of the air is converted into clouds and then into precipitation, and there is never as much feedback from the water vapor as they calculate from clear skies. This is the reason for the absence of the trophospheric hot spot in the tropics. Before the hot spot develops clouds and rain intervenes.
The other line of evidence that goes against a high feedback is to consider what that ought to look like. Systems with high positive feedbacks tend to be driven rapidly to an extreme and stick there. In the tropics this would be a hot spot that grows and continues to heat up to some maximum. It would be runaway warming that spreads beyond the tropical regions. No such phenomenon has ever been observed. Clearly there is something limiting how much warming their is despite water vapor feedback.
3. Temperature proxies are never as good at estimating temperature as direct measurements of temperature. Proxies, such as tree ring thickness, are used where reference to a thermometer isn't possible, but often we see examples of proxies used to demonstrate warming when direct measurements are available and contradict the proxies. One example would be the snow cover of Mt. Kilimanjaro. As the snows thinned out in the 90s people claimed that this war the result of warming. But we had temperature measurements from the peak of the mountain, and they didn't show warming. As is often the case with proxies, there were other things that might explain the loss of snow. In this case it was a multi year drought. Once the drought was over the snows started coming back.
Similar contradictions are found with many other proxies whether we are talking about the distribution of wild life, the coming and going of mosquitoes, numbers of hurricanes and other storms, and so on.
In short, if you want to know what the temperature is doing then check the thermometer.
4. We can't cut carbon emissions enough to have any detectable effect on the climate even if you go by calculations supplied by the climate scientists who back AGW. Even cutting emissions by 80%, which would be tantamount to total destruction of the economy of the Western world, would have no detectable effect. It follows then that efforts in that direction, as expensive as they are, are a total waste.
5. Almost none of the predictions of the global doom and gloom climate crowd have proven accurate. Whether we are talking about population, global cooling, acid rain, ozone depletion and global warming. Most recently there was the prediction that this year we'd see millions of climate refugees. This also proved false. Next up will be a new crisis of some sort, perhaps ocean acidification.
6. Perhaps most difficult of all to predict is the direction that energy generation will take in the future. In the past 100 years we saw the development of atomic energy. In the next 100 years we might see even greater innovation and discovery. Such a thing could throw all the predictions, as inaccurate as they are already likely to be, into a cocked hat.
7. Cost analysis shows that it will be far more effective and economical to adapt to climate change, whatever it may be, than it would be to try to affect it with programs costing multiple trillions of dollars that the US and the rest of the developed world can ill afford.
