And I suspect he’s done so willingly. Well, you know what they say about statistics and liars.
Here’s the story. The Wall Street Journal and the Daily Mail independently published highly misleading and blatantly idiotic pieces on climate change. We’ve covered this extensively already over the last few days. Phil Plait, of the Bad Astronomy Blog on Discovermagazine.com, was one of numerous scientists to respond to those flaming examples of horrific bottom feeding journalism with the post “While temperatures rise, denialists reach lower.” In that post, he presented a still-image from a moving GIF that has been going around, originally from Skeptical Science. I’ve used the GIF myself just recently, but I’ll re-post it here for your convenience:
The graph represents a bunch of data, from various sources, indicating global temperature over time. The data points are linked together with a “line” to show that they represent data over time, though you could leave the line out because the X axis is labeled as time and the data are basically a scatter of points showing the relational between two variables: Time and temperature. But lines like this are traditionally used in climate science and are technically known as “squiggles.” So the line belongs there.
The purpose of the data scatter on this graph is to demonstrate two conceptually distinct approaches to data analysis: Seeking large scale trends by scientists vs. denying the existence of large scale trends by science deniers.
The dynamic graph begins by displaying in sequence chunks of data, one chunk at a time, from left to right, and with each chunk a downward sloping blue line. This represents the denialist perspective … find a series of points that looks like a downward trend, and put a line on it; A downward facing line, of course. Then the graph shows all the data at once with a line representing the trend shown by these data; There is a clear upward slope.
This graphic is a fun and informative way to demonstrate the difference between a series of attempts to lie bout the data vs. an overall simple straightforward presentation of the data. The upward tend line in the final image is actually unnecessary but it serves as a punch line. Personally, I would have preferred different color scheme with the lies in red and the truth in blue, but what the heck.
Phil presented this graph without much comment in his post, and he presented only the part of the image that shows the upward trend. The only context provide for the graph was the short paragraph before it, which read, in reference to the argument that the Earth is cooling and not warming:
The Skeptical Science website destroyed this argument in November 2011, in fact. The OpEd also ignores the fact that nine of the ten hottest years on record all occurred since the year 2000.
Note the link to Skeptical Science that I’ve included here in the block quote. That is a link to the blog post that this nice graph was initially lifted from by everybody else. In that post, Sketpical Science says:
Right now we’re in the midst of a period where most short-term effects are acting in the cooling direction, dampening global warming. Many climate “skeptics” are trying to capitalize on this dampening, trying to argue that this time global warming has stopped, even though it didn’t stop after the global warming “pauses” in 1973 to 1980, 1980 to 1988, 1988 to 1995, 1995 to 2001, or 1998 to 2005 (Figure 1).
And provides this caption for it:
Figure 1: BEST land-only surface temperature data (green) with linear trends applied to the timeframes 1973 to 1980, 1980 to 1988, 1988 to 1995, 1995 to 2001, 1998 to 2005, 2002 to 2010 (blue), and 1973 to 2010 (red). Hat-tip to Skeptical Science contributor Sphaerica for identifying all of these “cooling trends.”
So now you know what the graph is, where it is from, and what Phil said about it and how he used it.
And now, it’s time to play Whack a Mole, because that is what talking about Science Deniers is these days.
William Briggs claims on his blog at wmbriggs.com to be a qualified statistical expert, and he felt moved to criticize Phil’s use of the graph and what the graph shows, but he totally screws that up clearly demonstrating that he needs to rethink his qualifications. Or his honesty.
First, Briggs obnoxiously tells us that he has already blogged about how to cheat or fool yourself with time series, and that Phil had not read this blog post or done his home work, as though anyone on this planet was required to, or interested in, paying much attention to him.
He then tells us that the data “…are not–they most certainly are not–global temperatures.”
Please see the caption above. Thes are BEST land-only surface temperature data.
He then tells us “Each dot instead is an estimate of global temperature: worse, most dots are also different kinds of estimates from each other. That is, the first dot was estimated using data X and method A, and the second dot was estimated using data Y and method B, and so forth. Well, maybe the first and second dot were the same, but older dots are different than the newer ones.”
The data are from here. Yes, they are from a variety of sources, and have been combined systematically to make a useful source of analysis for climate studies. Here’s what Berkeley Earth says about them:
The Berkeley Earth Surface Temperature Study has created a preliminary merged data set by combining 1.6 billion temperature reports from 15 preexisting data archives. Whenever possible, we have used raw data rather than previously homogenized or edited data. After eliminating duplicate records, the current archive contains 39,390 unique stations. This is more than five times the 7,280 stations found in the Global Historical Climatology Network Monthly data set (GHCN-M) that has served as the focus of many climate studies. The GHCN-M is limited by strict requirements for record length, completeness, and the need for nearly complete reference intervals used to define baselines. We have developed new algorithms that reduce the need to impose these requirements (see methodology), and as such we have intentionally created a more expansive data set.
We performed a series of tests to identify dubious data and merge identical data coming from multiple archives. In general, our process was to flag dubious data rather than simply eliminating it. Flagged values were generally excluded from further analysis, but their content is preserved for future consideration.
There’s more, but that should give you an idea of what we see here. Briggs is trying to make you think that this is a horrid data set that can’t be trusted with huge internal error, but in fact, this is one of the best data sets ever put together for anything.
Then Briggs says:
All you have to remember is these dots are estimates, results from statistical models. The dots are not raw data. That means the dots are uncertain. At the least, Plait should have shown us some “error bars” around those dots; some kind of measure of uncertainty.
This is wrong at three levels. First, the graph was not used by Phil or Skeptical Science in a way that requires error bars. Second, Briggs is inappropriately emphasizing the degree to which the data are estimates or derived or otherwise iffy. Third, one thing we know about these data is that at the global scale (remember,we are measuring global temperature here) the variation is relatively low. Most large scale variation in temperatures is regional or inter-regional, not global. This is a case of Briggs making a huge mistake in his evaluation: He has lost control of the source and nature of variation. Variation must be understood on a situational basis. For example, if I said that I’ve measured the number of heads per person in a classroom of living humans, and I gave you the estimate of “1” you would not say “Hang on a sec.. variation in opinion polling data tends to be about 5% at two sigmas, so you really should say that the number of head per person ranges from .95 to 1.05” If you added error bars to the dots on that graph you would still have the same graph, and if you added error zones to the line itself the line would still be there. Briggs is trying to make you think there is huge error that simply is not there. (More about estimates below.)
He then blathers on further about confusing estimates and predictions which is totally irrelevant to the graph as well as to Phil’s point. In any event, we do have confidence limits for these data, from Berkeley, shown in this graph:
Another point Briggs makes is that the starting point for a line determines the overall position of the line. That is not true. If you determine the Y-intercept of a line as fixed then the rest of the line will be different than if you let the Y-intercept go where it ends up, but that is not what has happened here. He points out that the starting point for this graph is 1973, “a point which is lower than the years preceding this date.” That’s interesting because it indicates that he’s seen the original raw data, but all of his other comments suggest he does not really know where the data are from. In any event, note that the line is not fixed at any starting point on the left side of the graph. He’s just making this up. If we need to look to the left, to time periods earlier than 1973, to see if 1972 and earlier were warm and that the Sketpical Science graph is thus made up, there are plenty of sources of information and pretty pictures to examine the longer term trends. Like this one:
Which is from here.
The earth is warming, folks. And Briggs is not making it any easier by pulling wool hats over our eyes.
I’d like to make another point about Brigg’s blathering on about “estimates.” Everything is an estimate. Say you want to know the temperature outside before you head off for work. You can look outside and make an estimate. You see snow, but around the edges it is wet. Someone is walking down the street with a heavy coat, but it is unzipped, yet they are wearing a hat. Someone is jogging and not wearing shorts, and their breath is just a little steamy. Someone else is wearing a medium size coat and it is zipped up.
Obviously it is about 35 degrees F, minus 3 and plus 6. That is an estimae.
Or, you can look at the thermometer you nailed to your fence last year. It says 34 degrees. Hey, that’s close to our estimate! But the thermometer reading is still an estimate. The thermometer works on the physics of a bimetalic strip inside it. How carefully was it calibrated, and it is accurate a all ranges of temperature? The angle of viewing adds variation of about a half a degree. In any event, the temperature indicated by the dial is not a temperature, but rather, a response to the physics of two metals contracting and expanding deferentially in a spring, and how this positions a pointer on a big dial of numbers. That’s not temperature, it is an indirect effect of temperature. And what temperature are you measuring? You want to know the ambient temperature of the air you will be walking around in, but the air by thermometer is the air in your snow covered yard, not the cleared off sidewalk next to the road. And the thermometer is measuring the temperature of the fence it is attached to and it’s own corpus on which the sun is shining, along with the air.
And so on and so forth. Don’t let this “it’s an estimate” thing of Briggs fool you. All measurements are estimates, and one of the things scientists do is deal with that reality by understanding where the numbers come from, what the sources of variation are, and what the tolerances of the system are. Briggs does not seem to understand that.
There is a word on estimates and Brigg’s misunderstanding of the term (and his misunderstanding of what an “average” is) over at Open Mind as well.
And now we come to the final and most important point. Briggs appears to be critiquing the points Phil Plait is making in his post, but he is not. He does not really talk about the points Phil makes. He has created straw arguments and then attacked them. He is trying to distract from the central point that the Wall Street Journal and the Daily Mail totally botched their reporting and are essentially engaged in a disinformation campaign, in which Briggs is willfully engaged as well. Briggs is playing the Watch the Monkey strategy.
Pay no attention to the monkey. Pay attention to the Planet.
By the way, if you’ve gotten this far, you probably would like to know about Mike Mann’s brand new book: The Hockey Stick and the Climate Wars I’ve not read it yet, but after writing this blog post I feel like I’m in it!