Lesson 1,126½ in how to be a science disinformer, featuring Bob Tisdale

In this lesson about how to be a climate disinformer, I refer to a recent article by Bob Tisdale (archived here, cached here). In fact I refer to umpteen articles by Bob Tisdale, because his articles are often copies and pastes of his previous articles, with slight updates.

You can also watch a video with Tom Peterson, who gives The Story of Climate Data. This article is worth it for that alone. Dr Peterson is President of the World Meteorological Organization's Commission for Climatology, and recently retired from NOAA.

The purpose of the lesson, and hiding the closing of the gap

The purpose of the deception is to "prove" that all models are useless by hiding the closing of the gap.

Before you start, it's important to see what the observations actually show. Below is a chart of HadCRUT4, plotted with the multi-model mean of CMIP5. The 95% probability is for all uncertainties for HadCRUT observations - measurement and sampling, bias and coverage uncertainties. The uncertainties relating to the multi-model mean of CMIP5 are not plotted. As always, click on the chart to enlarge it.

Fig 1 | Global mean surface temperature observations and multi-model mean.
Data sources: UK Met Office Hadley Centre and KNMI Climate Explorer (CMIP5)

As you can see, with 2015 year to date (to September 2015), the observations are now approaching the CMIP5 multi-model mean. This closing of the gap must be hidden from WUWT deniers at all costs. And it's not hard to do so if you follow the steps in the lesson.

Lesson 1,126½ in How to be a Science Disinformer

Now for Lesson 1,126½. This lesson is quite simple. Here are the five main steps.

1. Provide an introduction to tell the deniers what to think.
2. Rationalise your presentation of the data.
3. Make sure you don't include any error bars.
4. Use 61 month smoothing to ensure that the latest observations are discounted.
5. Add more words so that the chart illiterate know what to think.

Bob Tisdale has given us a live example. For Step 1, Bob told his readers what to think:

There are a number of ways to present how poorly climate models simulate global surface temperatures.  

That's the first step. You want deniers to think that models are poor, so that's what you tell them.

For Step 2, Bob rationalised his presentation of the data this way (my emphasis):

Normally they are compared in a time-series graph.  See the example in Figure 10. In that example, the UKMO HadCRUT4 land+ocean surface temperature reconstruction is compared to the multi-model mean of the climate models stored in the CMIP5 archive, which was used by the IPCC for their 5th Assessment Report. The reconstruction and model outputs have been smoothed with 61-month filters to reduce the monthly variations. Also, the anomalies for the reconstruction and model outputs have been referenced to the period of 1880 to 2013 so not to bias the results.

Now Bob didn't need to use 61 month smoothing to reduce the monthly variation. He could have shown the data as annual averages. By using 61 month smoothing - more than five years - he biases the chart away from the most recent 2½ years of observations. As Tamino once wrote:

More important, a moving average filter of width T will cut off a time span equal to half of T from both the beginning and the end of the time series — you lose what just might be the most interesting parts, the beginning and the end. 

Bob Tisdale's T was 61 months, so by using this filter, he was able to chop off the "most interesting parts", in this case, 2½ years, which includes the recent uptick in surface temperature.


This can be illustrated in Bob's steps 3 and 4. Bob put up this chart (his Figure 10), which I've annotated:

Fig 2 | Bob Tisdale hiding the recent uptick in surface temperature. Source: WUWT

In step 5, Bob again told his readers what to think, just in case they missed it. He wrote:

It’s very hard to overlook the fact that, over the past decade, climate models are simulating way too much warming and are diverging rapidly from reality.

Points to note - HadCRUT4 is reality

Now there are a couple of things to note before we go any further.

1. Bob endorses HadCRUT4. He calls it "reality". This is in contrast to most of the articles at WUWT, in which deniers more typically allege fraud and fudging of observations.
2. Bob claims the climate models are "diverging rapidly from reality". He can only make this statement because he's biased his chart away from the observations of the past 2½ years. In fact models and observations are converging, not diverging.

Illustrating the deception

Point 2 is demonstrated in the animation below, which goes from annualised data to data with a 61 month moving average:

Fig 3 | Animation of the global mean surface temperature observations and multi-model mean. This chart illustrates how using five year plus smoothing creates a gap that isn't seen in annual data.
Data sources: UK Met Office Hadley Centre and KNMI Climate Explorer (CMIP5) 

The animation shows how using a 61 month moving average hides the fact that the gap is closing. It creates a false gap between the multi-model mean and observations. There is no reason to use a 61 month moving average. None at all, unless you want to deceive your readers, particularly the numerically-challenged.

Bonus lesson, the ½ - plot monthly differences (I'm not kidding!)

Now Bob gives his readers a bonus. He plots the monthly differences between CMIP5 and HadCRUT4. Monthly - I kid you not.

Models are not weather forecasts. If internal variability in a particular model run occurs at the same time as observations, that is purely coincidental. On top of that, using multi-model means for CMIP5 means that all the pluses and minuses of individual runs will be smoothed out.  If you look at the annual charts above, you can immediately see the effect of smoothing. The CMIP5 plot is much smoother than HadCRUT4. If you were to look at an individual model run, it would have a lot more variability, just as observations have year to year variability.

Models are of climate - so they are intended to show longer term projections. By plotting monthly differences, Bob was able to amplify the differences to reach a maximum and minimum at times exceeding 0.4 °C. This isn't a great difference when it comes to monthly data. If he'd plotted the difference between an individual model run and HadCRUT4, he could have got an even greater difference.

Instead of plotting monthly differences like Bob did, how about decadal differences.

Fig 4 | Decadal global mean surface temperature observations and multi-model mean, and difference.
Data sources: UK Met Office Hadley Centre and KNMI Climate Explorer (CMIP5) 

The blue bar is the difference. The white dotted line up top is the average actual year to date for this year (to September), from HadCRUT4.

As you can see, the biggest difference is the most recent decade, from 2006 to 2015 (with 2015 being average year to date to September). It is no secret that the most recent years have had temperatures in the lower end of those modeled. The difference for the decade to 2015 is 0.2 °C. Other than that, the largest difference in prior decades is 0.106 °C.

The reasons for the difference in recent years have been well-documented. The models include known forcings only to around 2005. After that, the forcings were estimates only. As it turned out:

• The PDO index was negative from 2005, which suppressed surface temperatures. This internal variability is not programmed into the models, it is an emergent feature. Internal variability in the models is not expected to coincide with the timing in the real world. If it does happen to be timed with observations in any model run, it's pure coincidence. When you use multi-model means, this sort of variability will be averaged so you won't see the highs and lows of individual runs.
• Volcanic forcing (which is negative) was greater than that applied to the CMIP5 models
• Solar forcing (which is positive) was less than that applied to the models.

As you can see, Bob didn't need to go to such lengths. There was a difference between the modeled projections and observations. The reason he did can only have been to hide the fact that the gap is closing between the multi-model mean and observations.

If you're familiar with the "work" of Bob Tisdale, you'll know that he is not the least bit interested in exploring the reasons for any differences between modeled temperature and observations. That would conflict with his purpose in life. (His purpose being to deceive as many people as possible.)

Well that about covers it. This is the end of Lesson 1,126½ in how to be a climate science disinformer. Don't leave just yet, however, or you'll miss the bonus video below.

Bonus Video - Tom Peterson with The Story of Climate Data

If you are sceptical of all the false allegations made by deniers at WUWT, you will be even more so after watching this video. Anyone who's interested in the history and practice of preparing global surface temperature records should really enjoy this video. Tom Peterson talks about the early days of observing surface temperature, all the effort that has gone into constructing a global surface temperature record, the hoops that must be jumped through to obtain data from different countries, how gaps in the data are filled, how scientists have shown that poor siting makes little to no difference when it comes to broad-based surface temperature anomalies, and much more. (Don't mind the quality at the beginning - the video is well worth watching.)

The scientists who have worked so hard over the years to construct Bob's reality of surface temperature observations, should put disinformers like Anthony Watts and Bob Tisdale to shame.

From the WUWT comments

You can see how successful Lesson 1,126½ can be by reading the comments at WUWT. Bear in mind that I've only written about the part of Bob's article where he writes about climate models. Elsewhere in his article, he discusses the current El Niño.

Ged buys into Bob's deception:

November 16, 2015 at 6:49 pm
There is some serious divergence between the databases going on again, it seems.

Someone needs to tell highflight56433 that the record is adjusted to allow for UHI effects. Thing is, because they are adjusted, deniers cry foul.

November 16, 2015 at 7:07 pm
Should temperatures measured in UHI be reduced; after all they are an island? Where I live, driving into town always shows a +4 F to +9 F increase from the surrounding area which is primarily covered in trees rather than airport concrete and asphalt. Airport temps are only useful to aircraft performance.

markstoval wouldn't be interested in Tom Peterson's video or Bob Tisdale's reality of observations. He is a hard core denier/disinformer/defamer at WUWT.

November 17, 2015 at 2:09 am
But the objective of climate “science” is to show the greatest possible (or even impossible) temperature increase. They need to “adjust” those rural temps to match those city temps. Pronto!

MattN needs to wait a bit. Provided the lower troposphere calculations are reasonably accurate, he'll see his big spike early next year:

November 16, 2015 at 7:18 pm
Amazing. I distinctly remember that one of the reasons GISS had 2005 hotter than 1998 is they claimed GISS didn’t see all the heat the satellites did in 1998 and therefore had it cooler. Now the NINO3.4 temps are similar, they show a huge spike in temp. They really are having their cake and eating it too.

Eliza is very disappointed with Bob showing charts of temperature observations. She would much rather they remained hidden. She's also deluded for thinking that "warmists" would flog anything at WUWT, except in the negative sense, like here.

November 17, 2015 at 3:17 am
The warmists will flog ie promote this posting to no end. its gives credibility to GISS ect