I just watched Peter Sinclair’s petty little video on Anthony Watt’s effort to survey and provide some level of quality control on the nation’s surface temperature network. Having participated in the survey, I was going to do a rebuttal video from my own experience, but I just don’t have the time, but I want to offer a couple of quick thoughts.
- Will we ever see an alarmist be able to address any skeptics critique of AGW science without resorting to ad hominem attacks? I guess the whole “oil industry funding” thing is a base requirement for any alarmist article, but this guy really gets extra credit for the tobacco industry comparison. Seriously, do you guys really think this addresses the issue?
- I am fairly sure that Mr. Watt would not deny that the world has warmed over the last 100 years, though he might argue that warming has been exaggerated somewhat. Certainly satellites are immune to the biases and problems Mr. Watt’s group is identifying, and they still show warming (though less than the surface temperature networks is showing).
- The video tries to make Watt’s volunteers sound like silly children at camp, but in fact weather measurement and data collection in this country have a long history of involvement and leadership by volunteers and amateurs.
- The core point that really goes unaddressed is that the government, despite spending billions of dollars on AGW-related projects, is investing about zero in quality control of the single most critical data set to the current public policy decisions. Many of the sites are absolutely inexcusable, EVEN against the old goals of reporting weather rather than measuring climate change. I surveyed the Tucson site – it is a joke.
- Mr. Sinclair argues that the absolute value of the temperatures does not matter as much as their changes over time. Fine, I would agree. But again, he demonstrates his ignorance. This is an issue Anthony and most of his readers discuss all the time. When, for example, we talk about the really biased site at Tucson, it is always in the context of the fact that 100 years ago Tucson was a one horse town, and so all the urban heat biases we might find in a badly sited urban location have been introduced during the 20th century measurement period. These growing biases show up in the measurements as increasing temperatures. And the urban heat island effects are huge. My son and I personally measured about 10F in the evening. Even if this was only at Tmin, and was 0 effect at Tmax (daily average temps are the average of Tmin and Tmax) then this would still introduce a bias of 5F today that was surely close to zero a hundred years ago.
- Mr. Sinclair’s knowledge about these issues is less than one of our readers might have had 3 years ago. He says we should be satisfied with the data quality because the government promises that it has adjusted for these biases. But these very adjustments, and the inadequacy of the process, is one reason for Mr. Watt’s efforts. If Mr. Sinclair had bothered to educate himself, he would know that many folks have criticized these adjustments because they are done blind, without any reference to actual station quality or details, by statistical processes. But without the knowledge of which stations have better installations, the statistical processes tend to spread the bias around like peanut butter, rather than really correct for it, as demonstrated here for Tucson and the Grand Canyon (both of these stations I have personally visited).
- The other issue one runs into in trying to correct for a bad site through adjustments is the signal to noise problem. The world global warming signal over the last 100 years has been no more than 1 degree F. If urban heat biases are introducing a 5,8, or 10 degree bias, then the noise, and thus the correction factor, is 5-10 times larger than the signal. In practical terms, this means a 10-20% error in the correction factor can completely overwhelm the signal one is trying to detect. And since most of the correction factors are not much better than educated guesses, their errors are certainly higher than this.
- Overall Mr. Sinclair’s point seems to be that the quality of the stations does not matter. I find that incredible, and best illustrated with an example. The government makes decisions about the economy and interest rates and taxes and hundreds of other programs based on detailed economic data. Let’s say that instead of sampling all over Arizona, they just sampled in one location, say Paradise Valley zip code 85253. Paradise Valley happens to be (I think) the wealthiest zip code in the state. So, if by sampling only in Paradise Valley, the government decides that everyone is fine and no one needs any government aid, would Mr. Sinclair be happy? Would this be “good enough?” Or would we demand an investment in a better data gathering network that was not biased towards certain demographics to make better public policy decisions involving hundreds of billions of dollars?