The BBC's Richard Black Engages in "Goldilocks-Picking"

Guest post by David Middleton

From the BBC…

Climate: Cherries are not the only fruit

Just about the most predictable event of the week was the tempest of opinion created by the analysis of global temperature changes published in the Proceedings of the National Academy of Sciences (PNAS) on Monday.

As we (and a number of other mainstream news outlets) reported, Robert Kaufmann and colleagues analysed the impact of growing coal use, particularly in China, and the cooling effect of the sulphate aerosol particles emitted into the atmosphere.

They concluded that with a bit of help from changes in solar output and natural climatic cycles such as the El Nino Southern Oscillation (ENSO), the growth in the volume of aerosols being pumped up power station chimneys was probably enough to block the warming effect of rising greenhouse gas emissions over the period 1998-2008.

For some commentators, such as the UK Daily Mail’s Christopher Brooker, this was further proof that the “climate scaremongers” had got it wrong…


Cherry in the pie

One thing that everyone in the climate blogosphere seems to agree on is that the best fruit in the world is the cherry, judging by the number that are picked.

And the Kaufmann paper has brought a few more down from the tree.

The Global Warming Policy Foundation (GPWF), the UK-based pressure group, said researchers “tweak an out-of-date computer model and cherry-pick the outcome to get their desired result”.

To which the opponents’ rejoinder is, and long had been: “well, choosing 1998 as the baseline is cherry-picking, to start with”.

To illustrate the point, I’ve been through a quick exercise using the approach that groups such as GPWF favour – and that Kaufmann’s research group adopted – of using annual temperatures rather than any kind of smoothed average, and looking for the temperature change over a decade.

I took the record of global temperatures maintained by Nasa’s Goddard Institute for Space Studies (GISS) which is one of the three main global datasets, and calculated the rate of change over each of the most recent 10 decades – ie, 1991-2001, 1992-2002, and so on up to 2000-2010.

I’ve summarised the results in a table on this page. What it basically shows is two things:

  • the numbers vary quite a bit from year to year; and
  • all but one give a temperature rise – the only one that shows a small drop being 1998-2008.

Seeing as it’s logically impossible that the world warmed between 1997 and 2007, cooled between 1998 and 2008, and warmed again from 1999 to 2009, one conclusion you might reach is that using annual temperatures is not a sensible thing to do as it gives you a set of answers that does not make sense.

… which is why most scientists use the running mean approach.



Mr. Black seems to be suggesting that Figure 3 from Kaufmann is a cherry being picked by climate realists…

While he thinks that GISTEMP is the “tree”…

Well, I say that Mr. Black is Goldilocks-picking. Mr. Black asserts that it is cherry-picking to use 1998 as a starting point and that the starting point must be 1880. What’s so special about 1880 (apart from it being the start of the instrumental record)?

First off, let’s have a look at a few “cherries.”

Here is the HadCRUT3 global temperature anomaly (GTA) for 1977-2010 plotted with the GTA for 1911-1944…

HadCRUT3 Global Temperature Anomaly 1911-1944 & 1977-2010

Here’s the HadCRUT3 Northern Hemisphere temperature anomaly for 1976-2010 plotted with a non-carbonated interval from the Medieval Warm Period (Moberg et al., 2005)…

HadCRUT3 Northern Hemisphere 1976-2010 & Moberg 863-897

In both examples, the slopes are statistically indistinguishable.

The 66-yr period from 1944-2010 is pretty well indistinguishable from the first 66 years of three different century-scale cool-warm-cool cycles from Moberg’s Medieval Warm Period reconstruction…

HadCRUT3 global 1944-2010 & Moberg NH 831-930, 961-1050, 1038-1138 (Yes, I know I should have used HadCRUT3 NH… I just don’t have a display handy).

The peak of the Modern Warming is, at most, 0.1 to 0.2°C warmer than the peaks of three comparable, non-carbonated, intervals of the Medieval Warm Period, consistent with a net climate sensitivity of ~0.5°C. However, that difference is probably not statistically meaningful.

  • The error bars of all of the data sets are greater than the differences between them.
  • The proxy data show the MWP to be warmer than the late 20th century.
  • The proxies invariably have a lower resolution than the instrumental data; thus the amplitude of the proxy time series is attenuated relative to the instrumental record.

This means that the late 20th century warming might have been slightly warmer than the peak of the MWP. Almost all of the potential error is in the direction of magnifying the warmth of the Modern Warming relative to the MWP, so the odds are that the modern warming is very comparable to the Medieval Warm Period.

Since Mr. Black would probably say that the Medieval Warm Period is another “cherry,” let’s go back another 1,000 years, or so.

Ljungqvist, 2009 and HadCRUT3 NH

What happens if I project the polynomial trend-line a few hundred years into the future?

It starts looking like a cyclical pattern doesn’t it?

One of the “problems” with the way climate data are handled is in the obsession with applying linear trend lines to non-linear data.

A Sine wave has no secular trend…

Sine Wave (From Wood For Trees)

But… What happens if my data represent only a portion of a Sine wave pattern?

A partial Sine wave apparently has a very significant secular trend.

The r-squared of a linear trend line of this partial Sine wave is 0.88… 88% of the data fit the trend line. This implies a very strong secular trend; yet, we know that in reality Sine waves do not have secular trends.

If we take the entire HadCRUT3 series and apply a linear trend line, we get an apparent secular trend…

HadCRUT3 Temperature Anomaly 1850-2009

The r-squared is 0.55… 55% of the data fit the secular trend. This implies that there is a real long-term warming trend.

What happens to that secular trend if we expand our time series like we did with the Sine wave?

The apparent secular trend vanishes in a puff of mathematics…

Moberg et al., 2005 Climate Reconstruction

How can such a clear secular trend vanish like that? The answer is easy. Each “up hill” and each “down hill” leg of a Sine wave has a very strong secular trend. Unless you have enough data to see several cycles, you don’t know if you are looking at a long-term trend or an incomplete cycle.

Using the GISP2 ice core data from central Greenland we can see that over the last 50,000 years, there have been statistically significant warming trends…

GISP2: 50 kya to 1855 AD

GISP2: 1540 AD to 1855 AD

GISP2: 1778 AD to 1855 AD

And there have been cooling trends of varying statistical significance…

GISP2: 10 kya to 1855 AD

GISP2: 3.3 kya to 1855 AD

What does all of this mean?

It means that the Earth’s climate is cyclical. It means that the climate changes we’ve experienced over the last 150 years are not anomalous in any way, shape, fashion or form. And it means that the Mr. Black and the other warmists must “Goldilocks-Pick” their data. Too short of a time series yields no warming trend and too long of a time series also yields no warming trend. The time series must be “just right” in order to show an anomalous warming trend.


newest oldest most voted
Notify of

> What happens if I project the polynomial trend-line a few hundred years into the future?
You torture the data until it tells you what you want. Polynomial fits are generally completely useless for foreward/hindward projections. I tend to look at the end points of the range they cover with a lot of skepticism.
How many years forward does the fit have to go before the temperature goes below 0 K? What happens if you increase the order of the polynomial by one? One end will show an upward trend – it shouldn’t take much of a projection to get to boiling.


So giving the rampant cherry-public often seen here – are you formally saying that cherry picking is inherently wrong?

John Marshall

Climate change cycles seem to average about 1000years peak to trough, ie. 2000 year cycle length. Taking a small section 150 years long does not provide any idea of what is going on only that you have a trend, of either direction, which you naturally call CAGW.
Considering the great variation that atmospheric CO2 has had from 1000’s of ppmv to 300 ish ppmv, with no parallel change in climate one wonders where Black et al get their mad ideas.


Black’s mind clouded is from spinning for too long.
I’d really love to know where these magic Chinese aerosols appeared from. Not long before Kaufmann’s data ended, NASA was saying we were losing our aerosol “sunscreen” and it was worse than we thought.

Excellent piece. This illustrates why the hockey stick graph was so much propaganda. There is no interpreting current climate trends without a correct context.
The predictable observation from the article is that the warmists are scrambling to explain the flattening. Expect this to get much worse if we are indeed entering another little ice age. And help us all when we return to our most ‘normal’ temps which is true ice age conditions.
Even when a true ice age reappears, the faith of the religion of man made global warming will require convolutions stating the warming is still continuing, it’s just being masked. Then like any chaotic system the emphasis will switch and the cooling will be man’s fault again.
Or maybe the religious faithful will look at this little article and realize we are along for the ride for the most part.

Alexander K

Mr Black’s understanding of science is about the same as my understanding of Mandarin Chinese – nil.

I did a similar take back in Dec 2009 on how alarmist cherry pick their ranges to over-emphasize the secular trends in sinusoidal curves. It is the clearest example of twisting the full results and falsely imply a politically preferred result. That is not the scientific method, but the method of political PR.

They concluded that with a bit of help from changes in solar output and natural climatic cycles such as the El Nino Southern Oscillation (ENSO),..
Since the ENSO and its atmospheric component Southern Oscillation indices are highly correlated ( ) and having found what appears to be a driver modulating the SOI index all major indices (PDO, AMO and ENSO) appear to have common type of modulation caused by natural sources as displayed here:

I my opinion this paper is another example of how easy it is for climate modelers to adjust their models to apparently fit the data. These models have huge uncertainties in the parameters and by adjusting them any outcome is possible.
These climate computer modelers do not realize that a valid model should be able to reconstruct the patterns of the climate at multiple scales and forecast them to be credible.
As extensively proven in my paper
N. Scafetta, “Empirical evidence for a celestial origin of the climate oscillations and its implications”. Journal of Atmospheric and Solar-Terrestrial Physics 72, 951–970 (2010), doi:10.1016/j.jastp.2010.04.015 PDF
The climate system is clearly characterized by a 60-year cycle. We have seen statistically compatible periods of cooling during 1880-1910, 1940-1970, 2000-(2030 ?) and warming during 1850-1880, 1910-1940, 1970-2000.
This 60-year cycle goes back for centuries and millennia as also found by Knudsen et al (“Tracking the Atlantic Multidecadal Oscillation through the last 8,000 years”, Nature Communications, 2011, []):
It is overwhelming that the climate system is characterized by a 60-year cycle. The cooling observed since 2000 is perfectly compatible with this cycle.
So, the issue would be where were the Chinese sulphate aerosol particles during the period 1880-1910 and 1940-1970?
Note that the Kaufmann’s paper is very careful in keeping this 60-year cycle out of consideration by starting the analysis of their forcings in 1950 and running the climate model only since 1999 up to 2008 (?), and adding huge errors bars up to +/- 0.2 C.
Moreover, years ago China changed its policy because of the bad ambient air quality and from 2005 on all new installation have a state of the art desulfurization treatment. Sulfur is very likely going down since five years.
Finally, what happened to the data from 2008 to 2011 where the divergence data and model would be more drastic?


If aerosols pumped out by the Chinese are sufficient to pull down the global temperatures such that they counter-act the warming caused by CO2 then presumably the point at which they are most concentrated is a frozen wasteland?
One thing I can say for certain: Richard Black is an aerosol (just be careful how you say it….)

John Silver

From the NASA Goddard site FergalR linked to above:
“Image above: Sun-blocking aerosols around the world steadily declined (red line) since the 1991 eruption of Mount Pinatubo, according to satellite estimates. The decline appears to have brought an end to the “global dimming” earlier in the century. Credit: Michael Mishchenko, NASA”
Increasing or decreasing aerosols? I wish they could make up their minds.


David & Anthony.
Selecting a start point is a fact of life. What matters is the basis and reason for selecting the start point and the consideration that you give to the results based on that choice.
Selecting 1998 as the start point because it’s the only possible way to to get the data to tell the story you want to tell when the greater mass of data paints an entirely different narrative and then declaring that the data does not support global warming (let alone asserting that there is statistically significant cooling) is at best incompetent, at worst deception.
Selecting a start date because of sound reason with a demonstrable basis in physics or because it is the totality of the data set is not – especially when the conclusions you draw give due consideration (which David fails to do throughout this piece, leading him to a conclusion that is arse about face) to the limits of the data set would represent good analysis.
Climate at the will, not of physics, but of sine waves? Only on WUWT. – Anthony, can I guest write a piece that demonstrates how the climate data in graph form looks like different mountain ranges?


In my opinion, anything that starts after 1700 is cherry picking…………..
The LIA taught everyone that we needed heat, a better way to produce food, better ways to cook, harvest……..everything we developed and invented.
And almost everything that was invented was a direct result of how to take care of ourselves in case it gets cold again………………….

John Brookes

Agree entirely with Ric Werme – never extrapolate from a polynomial fit!
Anyway, it is always too easy to see patterns in things, and you are better off trying to understand the underlying processes, rather than indulging in curve fitting.

Grizzled Bear

This is my problem with the use of “anomalies”. The definition of an anomaly is “Something that deviates from what is standard, normal, or expected” ( Who is the authoritative voice to say what NORMAL is? NASA? Hardly! How about these outfits promote what the ACTUAL temperatures are / were / predicted? I know there are some benefits to calculating anomalies, but as soon as a statistician starts to calculate what is vs. what was expected (starting at point X), then the inevitable argument of cherry picking / Goldilocks picking is guaranteed to ensue. If they want to massage the cr*p out of the numbers to show their (expected) results, then that’s what Steve M and William B have the knowledge and experience to debunk. I just wish that Anomalies weren’t the go-to stat that journalists (hahahahaha I slay me!) like Black could so easily point to, as he screams “Ahhhhhh!!!” like a B-movie actress in a slasher film. Here’s a message for you Blackie: A shill is as a shill does.


FairPlay did you even read the article, didn’t you notice that your AGW belief have lets say some “minor” problems.

this might be nothing, im a computer scientist and did no statistics, but I was using excel…
I took the GISS data, calculated the mean anomoly for each year (average of each months anomoly), then subtracted each years mean from the previous to get a list of year on year change between each years mean value.
I didnt do an ABS at any point, I just wanted the change year on year between the means, interested in the magnitutde of change, not the direction.
I then did a min and a max on it to find the fastest changes between any two years in the data set. I got the same number for min and max 28.58333333 for 1976 to 1977 and -28.58333333.for 1963 to 1964.
What are the chances of this occuring in a real dataset?


Jay says:
July 11, 2011 at 6:48 am

But, the only people who selected starting points are Kaufmann et al and Richard Black.

Bob Barker

Ok then the AGW folks have their answer to controlling the climate and it is already pretty much in place. Crank up the coal-fired power plants with high-sulphur coal and turn the scrubbers on and off as needed to regulate the temperature. The bonus is that we get more CO2 which is needed to increase crop yields to feed the growing world population. Two problems solved at no cost to you. In addition you get lower cost electricity and less government involvement as a bonus. What’s wrong with that?

Dave Dardinger

Ok, let’s try this running average thingee on the data from some hypothetical world.
1 1 1 1 1 1 1 1 1 1 3 2 2 2 2 2 2 2 2 2 2 2 2. Assuming these are the readings from some annual temperature series with the 3 reading being 1998 what do we get? In 1997 we have 1 as our running average. In 1998 it jumps to about 1.2 and then rises gradually to 2.1 by 2007 and then drops to 2.0 an then stays the same. Anyone seeing this series would immediately say the temperature has remained constant for the past decade. Arguing that actually the temperature has risen is just playing mind games. This is essentially what this article is claiming.

Theo Goodwin

If Warmista Gaia Models are to be treated as scientific hypotheses then what we know about them is that since 1998 their predictions have been false. Rather than recognize that the models contain one or more false hypotheses, the Gaia Modelers introduced a new hypothesis, Chinese aerosols, to save their Gaia model from falsification. However, the tactic did not work because now the modelers must face the criticism that their Gaia models did not account for aerosols. The Gaia models were either false to experience or incomplete. In either case, the Gaia models are not up the standards of science.
If Gaia models are not to be treated as scientific hypotheses then they must be treated as statistical hypotheses about two sets of numbers, a temperature reading and a CO2 reading. Here we encounter all the problems of the famous Hockey Stick. As The Team learned when they decided to “hide the decline,” for the statistical comparison to be meaningful, you must know enough about the things compared to be able to explain why they are worthy of comparison. So, what do the Warmista do? They bring in aerosols to save their statistical hypotheses about CO2 and temperature. There can be no successful account of CO2, aerosols, and temperature until there is a scientific account of each, given in terms of physical hypotheses that describe natural processes, that enables the researchers to explain that the objects of their study, CO2 concentration, aerosol uptake, temperature records and such are not changing. They have no such accounts and are not seeking to create them. The Gaia Models are no more nor less than Hockey Sticks.


I think you give to much credit to Mr Black he’s more of a sycophant, “Yes emperor Gore your new kings cloths look amazing”.
While the sane people sit in the pub opposite pointing and laughing at a naked jester.

Don K

Ric Werme says:
July 11, 2011 at 5:42 am
> What happens if I project the polynomial trend-line a few hundred years into the future?
You torture the data until it tells you what you want. Polynomial fits are generally completely useless for foreward/hindward projections.
Exactly. The problem of dubious polynomial behavior at and outside the data boundaries seems to be fairly well known, but it lacks a name the one can feed into a search engine to find analyses of the problem. The problem can be exacerbated by fitting to too HIGH a degree of polynomial because each additional degree in the polynomial adds an inflection point to the curve. Inflection points near the boundaries are bad news as they allow a handful of data points to send the projected values outside the data to soar/crash toward plus or minus infinity at rates that aren’t remotely appropriate.
IMHO, If you are fond of correct answers, extrapolating linear fits can cause you more than enough grief. Polynomials are unlikely to be helpful.

David in Georiga

My biggest issue with the “Temperature anomaly” and cherry picking start and end dates is that, in order to prove CO2 is going to kill us all, some scientists picked a 30 year time period and called it “normal.” They then show any deviation from the average temperature at during that time period as an anomaly. If they are going to pick a normal temperature of the Earth, they should take the average temp from the last few million years, and express that temperature in Kelvin. Then, using the known deviations from that temperature as natural variability, plus or minus, the project out standard deviations. If we are not three standard deviations from the norm, we are still within the range of natural variation and there is no reason to look for any cause.
I could be wrong, but I believe our normal temperature is somewhere in the range of 283 degrees Kelvin, and the normal deviation is around 2.5 degrees. That would put 3 standard deviations at around 300 degrees Kelvin, right? So, unless we cross that line, we should be right where we are supposed to be, right? Isn’t that how it works?
Please correct my numbers if I’m wrong.

Bill Illis

Reflected short-wave solar radiation has not increased since 1984, it has probably gone down slightly (according to the Ceres and Erbe satellites)
So the Asian aerosol explanation does not work. We know the Asian aerosols have gone up, but for the Earth as a whole, there is very, very little change in the reflected solar radiation (just a blip from Mount Pinatubo in 1991-1993).


nicola scafetta says:
July 11, 2011 at 6:39 am
The climate system is clearly characterized by a 60-year cycle.
Climate is defined as weather averaged over 30 years. This greatly magnifies the calculated change in climate when there is a 60 year cycle.
As a result, the past fears over global cooling and now over global warming. Had science chosen 60 years average for climate, there would have been no alarm over global cooling of global warming, because the average would not have changed significantly.
The simple fact that the trend changes significance levels when you change the length of the moving average, this shows what you are dealing with is not real. It is a mathematical artifact. This has been formally recognized by Japanese researchers and is a large part of the reason they announced they would withdraw from Kyoto.
Climate change disappears when you change the definition of climate from weather averaged over 30 years to weather averaged over 60 years. It is an artifact of the definition, not of the climate system. When you change the definition of climate to 60 years of weather there is no significant warming post 1950 as compared to the warming since the end of the LIA.

Some European

All of this will be over by 2015, when the records of 2010 and 1998 will have been obliterated by increased solar activity, ENSO and decreased albedo as we go into virtually ice free arctic summers, oh and increased GHG concentrations of course. Then we can pick another year as the peak of the cycle start drawing lines to any next cooler year to prove the earth is not warming.
Anthony, if you are so opposed to cherry-picking, why don’t you mention all the other recent peer-reviewed reconstructions of past temperatures? I’m sure they all show the same nice cyclical pattern.

nicola scafetta says:
July 11, 2011 at 6:39 am
As extensively proven in my paper
N. Scafetta, “Empirical evidence for a celestial origin of the climate oscillations and its implications”.

I have strong reservations about your above claim. I have not found any evidence of the 60 year cycle within the climate indices. ‘Planetary connection’ is not obvious with its physical mechanism or its presence in the available data.
Solar correlation also appear to be very tenuous, at least as far as the longest temperature record is concerned
However there is a good correlation with the oceans’ currents distribution in both the North Atlantic
and the Pacific ocean.

Theo Goodwin

Grizzled Bear says:
July 11, 2011 at 6:58 am
“This is my problem with the use of “anomalies”. The definition of an anomaly is “Something that deviates from what is standard, normal, or expected” ( Who is the authoritative voice to say what NORMAL is? NASA? Hardly!”
As much as I hate to sound like a broken record, I must state my agreement with Grizzled Bear. The fact that anomalies are being used instead of actual empirical observations means that some assumptions have been made. Never have I seen these assumptions clearly explicated and defended. Other branches of physical science do not proceed in this manner.
The one defense of anomalies that sometimes gets stated is that the actual temperature readings are all over the map because they vary with altitude and many other factors. To my mind, there is no clearer case for not using anomalies. The fact that your science cannot do justice to your actual empirical observations should tell you that you are not doing science.

Seamus Dubh

Here’s a question. What happens to the charts and trends if we use the same sensitivity as when we first started recording temp data? ( i.e. we can now read to the thousandths of degree( 0.000))


Polynomial fits of degree n are useless if there is no underlying physics to make a polynomial of degree n relevant.
With enough terms you can fit any data, but without physical basis or insight. For example fitting a falling body accelerating with gravity with a quadratic fit makes sense. Fitting the earth’s temperate with a 5th order polynomial is fantasy.
A cyclic fit based on a sine wave of combinations of sine waves could make sense of there are cyclic phenomena going on( as is the fact, orbits etc).

Mr. Middleton
re: Ljungqvist temperature reconstruction graph.
You may be interested to know that both the Ljungqvist and Loehle correlate well with the change (as the first differential) of the geomagnetic field.


July 11, 2011 at 5:47 am
“So giving the rampant cherry-public often seen here – are you formally saying that cherry picking is inherently wrong?”
I can’t speak for David Middleton, but I can say that in my opinion, in the case of CAGW proponents, yes, it is. In the case of those that are skeptical of the CAGW hypothesis, no, it isn’t. In fact, it cannot really be defined as ‘cherry picking’, much as alarmists need to believe that in order to sleep at night.
To elaborate, I’m guessing you would make the same assertion as the IPCC – something along the lines of: ‘the rise in global average temperature since the start of the 20th century is overwhelmingly due to anthropogenic CO2 emissions, to a degree that eclipses natural variation’ or suchlike.
In order to have any credibility however, this assertion needs to be supported by evidence that:
(a) only CO2 + water vapour feedback effects can account for the majority of this rise (and that it can be separated from noise and natural processes like ENSO, PDO, cloud cover etc);
(b) this rise in global average temperature is unprecedented in history, in that nothing other than CO2 emissions can explain it;
(c) there is unanimous reliable evidence between corresponding data sets that temperatures have risen at the rate, and to the degree that would be required of the original assertion.
The problem for CAGW proponents is that this evidence is very thin on the ground, if not entirely missing. In order to ‘prove’ (a), evidence has to be fabricated – literally – in the sense of using computer simulations with a preordained bias towards the hypothesis (see Judith Curry’s series of articles: ‘Overconfidence in IPCC’s detection and attribution’, which discusses ‘bootstrapped plausibility’ of models). To date, no climate model has been shown to have any predictive ability, and they are all pretty weak in hind-casting too (and that’s the easy part – you can just rejig forcing parameters to fit the model to historical trends, and claim any correlation as victory).
The only way to prove (b) is to carefully ‘cherry pick’ start and end points of your analysis (usually different ones in different datasets, depending on how badly your argument fares), as outlined in David Middleton’s article above.
(c) cannot even be demonstrated at all by CAGW enthusiasts, so they tend to ignore it, or claim some deficiency in any record that doesn’t support their agenda. The paleo record does not agree with the instrumental record, satellite observations do not completely agree with the surface record, surface records do not completely agree with each other, and none of the records agree with the model projections.
So, cherry picking and fabrication is needed to demonstrate CAGW. When temperature records are seen in their historical context (as above), the CAGW hypothesis is unprovable. The fact that cherry picking is required at all to make a case makes this self-evident.
However, having the ability to find, select and present evidence that weakens or counters the CAGW hypothesis does not weaken the counter argument. For example, I can legitimately claim that the CAGW hypothesis is invalidated by the fact that none of the datasets since 1998 show significant warming. Even if you quibble about the meaning of the term ‘significant’, the fact that none of the datasets have risen to the levels predicted by past climate models – even in their ‘best case scenarios’ for CO2 emissions – still blows the hypothesis out of the water. There is no correlation between CO2 levels and temperature. Even one ‘cherry picked’ argument like this severely dents the CAGW hypothesis, and there are many more. The fact that there might have been a correlation between rising CO2 levels and temperatures between 1980 and 1995 has absolutely no bearing on my claim, and does not invalidate it in the slightest. It just leaves the door open for something other than CO2 being responsible for temperature rises in this period. So the cherry I have picked is valid.
As a CAGW proponent, the only avenue left to support your hypothesis beyond the illegitimate form of cherry picking I have highlighted is to attempt to reverse the burden of proof, and failing that engage in meaningless hand-waving, hoping nobody will call you out on it. For examples of the latter: ‘It must be particulate emissions from China countering global warming since 1998.’ Where are your measurements? What happened to all the Western industrial soot during the rest of the industrial era? ‘The Greenland ice cores only show regional, not global temperatures.’ Then why do you rely on GISS – where the only warming ‘signal’ comes from a small number of stations susceptible to large temperature variations due to changing coastal sea-ice, and is statistically extrapolated across vast swathes of the arctic – to demonstrate ‘global warming’ beyond that measured by satellites. My counter arguments are no less valid for having been cherry-picked.
Reversing the burden of proof, as suggested by Trenberth, as an alternative to AGW cherry picking, is just semantic nonsense used to wriggle out of having to provide justification for AGW assertions. However, even if sceptics do indulge AGW proponents and allow this, no problem. I hypothesise that natural variations can account for the vast majority of the warming seen within the bounds of certainty in the surface and sea temperature records in the industrial era. Just browse this blog for ample evidence of this: Bob Tisdale’s articles on ENSO, Mr Watts’ posts on Urban Heat Island effect on surface temperature sensors, posts such as the one above demonstrating distinct lack of ‘unprecedented’ in temperature rises, Willis Eschenbach’s posts on thunderstorms and tropical convection ignored by climate models, Svensmark and cloud cover, passing of energy over decadal cycles through changing ocean currents ruled by bounded chaos, observational evidence of feedback effects etc. Prove, beyond a doubt, any and all of these natural factors incapable of causing the warming we have seen and I will give you a huge cherry.

Don K

David Middleton says:
July 11, 2011 at 8:05 am
“I wasn’t making a “prediction” with the extrapolation of the polynomial function.”
I’m not trying to give you a hard time, but it’s hard to see how you aren’t making a prediction even if you aren’t framing it in the “usual” “climate science” sense of trying to demonstrate that we are all doomed unless we repent our sinning ways right now, today.
If you are trying to demonstrate cyclicity, wouldn’t Fourier analysis do that more cleanly? And no, before you ask, I don’t have the slightest idea how to do a rigorous Fourier analysis in Excel. Here’s a link that purports to explain how to do something along that line.

Grizzled Bear says: “This is my problem with the use of “anomalies”. The definition of an anomaly is “Something that deviates from what is standard, normal, or expected” ( Who is the authoritative voice to say what NORMAL is? NASA?…”
Grizzled Bear, the choice of the base years for anomalies makes no difference to the trend of the data or to the year-to-year variations. Changing the base years only shifts the entire dataset up or down. If you used 1880 to 1909 as the base years for a global temperature anomaly graph, most of the data would be above zero. Likewise, if you were to use 1980 to 2009 as the base years, most of the early data would be below zero, but the curves are the same.


The extreme AGW cherry picking is also to ignore the paleoclimatic data and the cosmogenic isotope changes that correlate with the paleoclimatic data,
The interglacial and the glacial planetary temperature data shows cycles of warming and cooling interrupted by very strong “RCEs” (Rickies) Rapid Climatic Change Events (For example the Younger Dryas abrupt cooling event and the termination of the last interglacial).
There is smoking gun evidence (cosmogenic isotope changes BE10 and C14) shows there are cyclic changes to the sun and abrupt changes to the sun and that the solar change occur at every climate change event. The question is not if but how the solar serial climate changer causes the cyclic gradual (mediavel warm period and the little ice age) and abrupt climate change (abrupt termination of the last 22 interglacial periods. There are clearly multiple mechanisms by which the sun changes the planet’s climate. (i.e. Abrupt and gradual climate changes are not caused by simple TSI changes. The sun does not get warmer or cooler to cause the observed climate change.)
The sun was at its highest activity state in 10,000 years during the later half of the 20th century. The solar magnetic cycle has been abruptly interrupted.
The AGW extremists are one trick ponies. The clear and present climate change danger is gradual and abrupt cooling.
I am curious what the AGW propaganda response will be a to cooling planet.


So the Chinese have fixed the global warming problem then …… without even really trying ??
That makes our lot look doubly stupid, eh ? Wind turbines destroying the environment etc.
Sulfur (sulphur) tax coming if it gets any colder ??


nicola scafetta says:
July 11, 2011 at 6:39 am
“The climate system is clearly characterized by a 60-year cycle. We have seen statistically compatible periods of cooling during 1880-1910, 1940-1970, 2000-(2030 ?) and warming during 1850-1880, 1910-1940, 1970-2000.”
Yep. We determined that in the course of the thread discussion here. I produced a PSD of HADCRUT data here which clearly shows a peak at ~65 years for the 20th century.
The physical basis for this cycle is that it is the result of excitation of a lightly damped mode in the Earth’s climate system driven by random inputs, not a steady state sinusoid. Over limited duration intervals, it can appear as a quasi-periodic, quasi-steady state sinusoid, but over longer intervals, the period appears to wander somewhat and the waverform appears to be amplitude modulated. This is a normal and completely ordinary phenomenology exhibited by systems governed by partial differential equations.
Engineers use finite element analysis to predict oscillatory modes in structures and fluid and electrical systems and so forth every hour of every day of the year, and use that knowledge to design buildings which will withstand gale force winds, or pumps which will deliver water to widespread communities, or substations which provide their electrical power. It’s old hat. Basic. Elementary. Cut and dried. Yet, the climate science community denies the existence of system modes. As I have related to many over the past decade or so, the climate scientists are trying to reinvent the wheel, and doing it very badly. Right now, their best model is a square.
Note, too, that the entire AGW imbroglio is founded on ~30 year trending, i.e., the interval you would need to either maximize or minimize the estimation of a trend. A ~30 year period is also roughly the rate of generational turnover, and loss of institutional memory, in human affairs. And so, we have had alternating Global Warming and Global Cooling scares like clockwork for the entire past century.
We have just reached the peak of the ~60 year cycle, which is why temperatures have stabilized. Soon, they will be trending down (superimposed on the long term rise from the last ice age), and all the sturm und drang of last couple of decades will be cast down the memory hole. Anyway, Nicola, good to see others are aware of what is really going on.

Matt G

I know the areosol cherry pickers are wrong and just goes to show how little they really know or really hide. Why wasn’t declining areosols over the decades by the same people mentioned to be part of warming? It wasn’t because these are the best cherry picking hockey stickers in science.
The pause in warming has not been accounted for by increases in SO2 emissions. The recent conjecture trying to expain this, shown no observed science to back this up, other than the fact emissions in the troposphere had increased recently in a few countries including India and especially China. Whereas especially the USA and Europe, SO2 levels have declined over the decades. The major problem here is that SO2 behaves differently when in the troposphere compared with the stratosphere. There is no observed evidence showing that human SO2 emissions reach the stratosphere. In the troposphere it has a very short life and interacts with water vapour creating acid rain. The SO2 that manages to briefly survive this has been demonstrated to show a warming. SO2 that reaches the stratosphere behaves differently and contributes to cooling. This is described in more detail via the link below.
There are numerous volcanic eruptions that release SO2 into the troposphere each year and have no noticeable affect on global temperatures, where cooling at least is concerned. Only the major volcanic eruptions that reach the stratosphere that affect global temperatures with cooling and how much depends on the lattitude of the planet. Pinatubo in 1991 emitted 15 times the amount then any maximum background stratopheric aerosol opitcal thickness during the recent decades. this contributed 0.35c in cooling over a few years. The background at any one time only contributed 0.02c and this value is far two small to explain the cooling between the 1940’s and 1970’s plus the pausing of recent decade global temperatures. The change in the ENSO, PDO and AMO explains this cooling much better.
The global stratospheric aerosol optical thickness shown above has declined over the recent decade. Thus it is not contributing to the recent pause because it requires to have increased for this to have any scientific weight.
If the CO2 had high sensitivity then any warming suppose to have occurred would have already happened by now. If CO2 has low sensitivity than it has contributed very little towards global warming because virtually all of the rise has occurred in just a few short steps. The observed planet shows it is currently the latter because the steps have only occurred exactly at the same time of a strongish El Nino.

Patrick Davis

The BBC, with so much “invested” in the scam, are we surprised? What really concerns me is the num ber of people who fall for this, hook line and sinker. No-one actually goes to a library anymore, just lap up the BS from the MSM. Monkey see, monkey do!

Steve Jones

The only statistics that matter are the concentration of CO2 in the atmosphere and average global temperatures. Remember, the Warmist argument that underpins their stance, and the reason they feel justified in proposing draconian measures to reduce CO2 output, is that the influence of CO2 over-rides all other factors in atmospheric thermodynamics. Lets not allow the AGW brigade to deflect the debate away from the fact that this magical correlation does not exist. It doesn’t matter what sophistry they come up with, the fact that the temp does not closely follow CO2 concentration (even allowing for time lag) blows their own argument out of the water.

Theo Goodwin

JJB MKI says:
July 11, 2011 at 9:12 am
You have written a brilliant essay, Sir. You have placed the ball squarely in the Warmista court. Your valuable time has not gone to waste; to the contrary, every critic of the Warmista position should print your post and tape it to the monitor.
About that ball in the Warmista court. They will have to fire up some Gaia Models and average them before they can respond.


These cyclic temperature trends give rise to an inevitable linkage to things we know for sure: Death and Taxes. As governments get sufficiently sophisticated, they will (or have) formulated ways of applying taxes to normal, cyclical climate fluctuations–they’ll tax us for making the temperature go up, and once that’s over, they’ll figure out how to tax us for making the temperature go down. Such governments are corrupt entities, of course, since they don’t deal with the truth–they just use natural phenomena to scam their citizens.

Theo Goodwin

Steve Jones says:
July 11, 2011 at 10:18 am
Absolutely! Keep the focus on the relationship between the CO2 concentration and the temperature because that relationship is the heart of the Warmista position.
If Gaia Models are hypotheses then they have been falsified. If they are statistical claims about correlations between two sets of numbers, CO2 concentration and temperature, then there is no correlation.
If they are statistical claims based on Bayesian Priors then they are fantasies just as the Priors are fantasies.

Old Goat

Richard Black IS Micahel Mann…..