Skip to comments.How Scientific Is Climate Science? What is arguably the most important reason to doubt global...
Posted on 04/13/2011 11:35:53 AM PDT by neverdem
What is arguably the most important reason to doubt global warming can be explained in plain English.
For years, some researchers have argued that the evidence for global warming is not nearly as strong as has been officially claimed. The details of the arguments are often technical. As a result, policy makers and other people outside the debate have relied on the pronouncements of a group of climate scientists. I think that is unnecessary. I believe that what is arguably the most important reason to doubt global warming can be explained in terms that most people can understand.
Consider the graph of global temperatures in Figure 1, which uses data from NASA. At first, it might seem...
We have already seen that the authors of the IPCC report have made one fundamental mistake in how they analyze their data, drawing conclusions based on an insupportable basic assumption. But they commit another error as wellthe same one, in fact, that hindered the scientists working to verify Milankovitch's hypothesis. Nowhere in the IPCC report is any testing done on the changes in global temperatures; only the temperatures themselves are considered. The alternative assumption I tested does make use of the changes in global temperatures and obtains a better fit with the data.
To be sure, there have been other studies that consider other alternative starting points and thereby reach different conclusions about the temperature data. The IPCC report nods toward such work, but without really acknowledging how crucially the soundness of its conclusions rests upon its choice of assumptions. Making the right choice, the one that best corresponds to physical reality, requires further, difficult research, and accepting conclusions based on shaky premises risks foreclosing upon such work. That would be gross negligence for a field claiming to be scientific to commit.
(Excerpt) Read more at informath.org ...
Just move those temperature monitors closer to air conditioner exhaust fans. That will get rid of any “controversy”.
As a mathematician myself, I can confirm this would be a major flaw. Time Series Analysis 101 would tell you the importance of checking the order of integration of your data. For data following an additive random walk (i.e. tomorrow = today + some change), you have to difference the data.
Dinosaurs would not have survived even one single WINTER, so the world has been cooling drastically for, uh, 65 million years or so...
Some noteworthy articles about politics, foreign or military affairs, IMHO, FReepmail me if you want on or off my list.
Always follow the money/power trail. That will lead you to the true motivation.
As a mathematician myself, I can confirm that following your advice would be a major flaw.
If the sky isn't falling, then we don't need to pay as much money for climate research, and the climate "scientists" may see their pay drop. They seem to have chosen profits over integrity, which could be a terrible error if they're actually right despite their sloppiness [I'd put in a "boy who cried wolf" picture, but I have a one fairy tale per post limit].
Thanks for the ping.
Good point. I guess it depends on what your objective function. If your plan is to maximize the amount of tax dollars you receive, then bad math is better than good.
Perhaps that’s the concern. After all, if the earth starts to warm, then these dinosaurs might come back to kill and eat us all!
'How Scientific Is Climate Science?'
How Scientific? Easy -- less than 0, that's 'how Scientific' it is.
'Climate Science' is to Science as ... Tarot Card Reading is to Auto Repair.
Outstanding article and great analysis.
Very clear examples for non-mathematicians.
This kind of analysis is missing from the debate.
That is a startling omission, one with consequences for how the IPCC's recommendations should be interpreted. A fairly elementary alternative assumption that some researchers and I have tested fits the actual temperature data better than the IPCC's AR1 assumptionso much better that we can conclude that the IPCC's assumption has no support. Under the alternative assumption, the data do not show a significant increase in global temperatures. We don't know whether the alternative assumption itself is reasonableother assumptions might be even betterbut the improved fit does tell us that until more research is done on the best assumptions to apply to global average temperature series, the IPCC's conclusions about the significance of the temperature changes are unfounded.
None of this is opinion. This is factual and indisputable. It applies to any warmingwhether attributable to humans or to nature. This assumption problem is not unique to the IPCC, either. The U.S. Climate Change Science Program, which advises Congress, published its report on temperature increases in 2006, and relied on the same insupportable assumption.
The hypothesis must fit the data, not the other way around.
When the anthropogenic warmists can explain why, a mere 125K years ago (well before significant human civilization, much less SUVs) during the last interglacial period, the Earth warmed sufficiently to raise sea levels 15-18 FEET (as compared to the 2-3 inches the warmists are decrying as the end of civilization), then they can talk to me about any warming trend in this particular interglacial period.
Based on geologic data, we are actually overdue for the next glacial period. Maybe CO2 is keeping us out of the cold!!
If global warming exists, it is demonstrated by extremely subtle changes to very large data sets that are handled by a very large number of people. These people, by and large, accept the premise of global warming and have a stake in having the data support their premise.
If even one in a hundred of the people who gather this data intentionally shades his reporting to support the conclusion, that would be enough to create a discernable trend and provide "proof" of global warming. Even more sinister, if a larger number of people unintentionally over-reported because they observe things in a biased way, this would also support the preconceived conclusion.
A lot of environmentalists who collect this data see this as a fight to save the planet. They see it as a battle between good (themselves) and evil (the energy companies, the deniers, the the polluters, etc). To conclude that this large number of people will observe and report data without introducing bias is simply not credible.
I remember, back in the '80s, sitting around with a bunch of lefty environmentalists back in Berkeley, California. We all knew, down in our bones, that the US consumed too much energy and was responsible for global pollution. We all knew that consumption in the US had to be curtailed and that the US would have to be made to pay for their over-consumption of global resources. What we did not know was the mechanism by which we would bring this about.
Then the concept of global warming came along. It fit our template exactly. It achieved everything we wanted to achieve and provided the lever we would need to move the World.
I can simply not believe that, in that situation, everybody at every level was reporting and analysing accurately. It was a contest to see which side could introduce bias more effectively, IMHO. Since the environmentalists provided most of the boots on the ground, they prevailed.
As a mathematician myself, I can confirm this would be a major flaw. Time Series Analysis 101 would tell you the importance of checking the order of integration of your data. For data following an additive random walk (i.e. tomorrow = today + some change), you have to difference the data.Nowhere in the IPCC report is any testing done on the changes in global temperatures; only the temperatures themselves are considered.
Although not a mathematician but an engineer, I have been accused of being a mathematician by engineers. And I have to say, from my experience of random data from tests, that just from the waveforms of the sunlight intensity and the ice quantity you can see that taking the derivative of the ice quantity will phase shift the data toward alignment with the inverse light intensity data. Seeing the actual result of the "derivative" operation is a great big DUH! Of course.
And when you think about it, why assume that the quantity of ice is what is determined by the intensity level, when we know that they vary with time? That is the assumption that the ice has no thermal inertia. It is the rate of change of the ice quantity which is driven by the intensity. Makes perfect sense.