A longtime reader of this blog sent me a blog post from Forbes entitled, “New NASA Data Blow Gaping Hole In Global Warming Alarmism.” With such a provocative title, of course, I had to read it.
The blog post makes some amazing claims. It says that the data, published in the Journal Remote Sensing, demonstrate that global climate models do not agree with what happens in the real world when it comes to how much heat the earth is radiating into space. It then says:
The new findings are extremely important and should dramatically alter the global warming debate.
Now this bothered me a bit, because we’ve known for a while that the global climate models don’t work very well. Back in 2009, for example, Richard Lindzen showed that global climate models don’t conform to the data when it comes to how the earth reacts to rising sea surface temperatures. Why should a paper that reaches essentially the same conclusion suddenly change the global warming debate?
The blog post concludes with this statement:
When objective NASA satellite data, reported in a peer-reviewed scientific journal, show a “huge discrepancy” between alarmist climate models and real-world facts, climate scientists, the media and our elected officials would be wise to take notice. Whether or not they do so will tell us a great deal about how honest the purveyors of global warming alarmism truly are.
The way the author of the blog post, James Taylor, wrote about these data made me want to read the scientific paper that contained them. When I read it, however, I found that the “data” were significantly less dramatic than what Mr. Taylor indicates.
The paper is in an open-access, peer-reviewed journal, so it is available to everyone. The journal itself is quite reputable, and its editorial board contains several scientists who are well-respected in their fields. It even contains a climate scientist (Dr. Toby N. Carlson). It is certainly not one of the premier journals in climate science, but it is a reasonable venue for a paper about climate-related data.
If you know much about climate change and read the paper, you see that Mr. Taylor is way, way off in his analysis. Essentially, the study looked at satellite data on cloud cover and surface temperatures from 2000 to 2010. The authors proposed a simple equation that tries to explain how the earth’s energy budget works, and then they modified a parameter in that equation until it fit those two data sets. The resulting parameter gives us an idea of how much energy the earth radiated into space for a given change in earth’s temperature. It then compared that parameter to the predictions of six global climate models used by the Intergovernmental Panel on Climate Change (IPCC), which is the United Nations organization that is promoting global warming as a serious problem. The study showed that based on the value of that parameter, the IPCC models were underestimating the amount of energy the earth radiates into space, which would make them predict global temperatures that were too warm.
So the key here is that the IPCC models were not compared directly to the data. They were compared to the results of the data being fit to a simple equation. That’s a big difference that leads to a very important question. How good is the fit? In other words, what’s the error associated with the parameter that they end up with? There is no indication of that in the paper. Since we don’t know the errors associated with the parameter, we don’t really know how well we should expect the models to compare to it.
Now if you look at the part of the paper that compares the parameter to the model calculations, you see that the calculations are consistently under the value of the parameter. Thus, there is definitely a discrepancy between the parameter and the models. However, we have no idea how bad that discrepancy is, because we have no idea how error-filled the parameter is.
Another shortcoming of the paper, which is common to many papers on climate science, is the short time frame of the data being studied. A ten-year period is a very small sample compared to earth’s history, and the smaller the sample, the more sensitive it is to random fluctuations. In addition, earth’s climate has short-term feedback mechanisms and long-term feedback mechanisms. At best, this paper indicates that the IPCC climate models are not doing well with the short-term feedback mechanisms. It says nothing about how they are doing with long-term feeback mechanisms.
Now don’t get me wrong. I think this is a very worthwhile paper. It not only tries to evaluate the IPCC climate models in a new way (which is always valuable), but it also tells us that the models aren’t doing as well as they could. Theoretically, this could lead to better models, which is what everyone should want. After all, if the current models are bad, we should not be making policy decisions based on them. If we get good climate models, good policy decisions could be based on them. Thus, any study that could lead to better climate models is worthwhile and should be published.
At the same time, however, this paper does not “blow a gaping hole in global warming alarmism,” as Taylor’s blog post implies. Instead, it simply shows what we have known all along – the global climate models used by the IPCC do not perform well when compared to the data. As a result, we need better models. Perhaps this paper (and many other papers along the way) may help us develop them.