By Christopher Monckton of Brenchley
A commenter on my post mentioning that according to the RSS satellite monthly global mean surface temperature dataset there has been no global warming at all for 200 months complains that I have cherry-picked my dataset. So let’s pick all the cherries. Here are graphs for all five global datasets since December 1996.
GISS:
HadCRUt4:
NCDC:
RSS:
UAH:
The mean of the three terrestrial datasets:
The mean of the two satellite datasets:
The mean of all five datasets:
Since a trend of less than 0.15 K is within the combined 2 σ data uncertainties arising from errors in measurement, bias, and coverage, global warming since December 1996 is only detectable on the UAH dataset, and then barely. On the RSS dataset, there has been no global warming at all. None of the datasets shows warming at a rate as high as 1 Cº/century. Their mean is just 0.5 Cº/century.
The bright blue lines are least-squares linear-regression trends. One might use other methods, such as order-n auto-regressive models, but in a vigorously stochastic dataset with no detectable seasonality the result will differ little from the least-squares trend, which even the IPCC uses for temperature trend analysis.
The central question is not how long there has been no warming, but how wide is the gap between what the models predict and what the real-world weather brings. The IPCC’s Fifth Assessment Report, to be published in Stockholm on September 27, combines the outputs of 34 climate models to generate a computer consensus to the effect that from 2005-2050 the world should warm at a rate equivalent to 2.33 Cº per century. Yeah, right. So, forget the Pause, and welcome to the Gap:
GISS:
HadCRUt4:
NCDC:
RSS:
UAH:
Mean of all three terrestrial datasets:
Mean of the two satellite datasets (monthly Global Warming Prediction Index):
Mean of all five datasets:
So let us have no more wriggling and squirming, squeaking and shrieking from the paid trolls. The world is not warming anything like as fast as the models and the IPCC have predicted. The predictions have failed. They are wrong. Get over it.
Does this growing gap between prediction and reality mean global warming will never resume? Not necessarily. But it is rightly leading many of those who had previously demanded obeisance to the models to think again.
Does the Great Gap prove the basic greenhouse-gas theory wrong? No. That has been demonstrated by oft-repeated experiments. Also, the fundamental equation of radiative transfer, though it was discovered empirically by Stefan (the only Slovene after whom an equation has been named), was demonstrated theoretically by his Austrian pupil Ludwig Boltzmann. It is a proven result.
The Gap is large and the models are wrong because in their obsession with radiative change they undervalue natural influences on the climate (which might have caused a little cooling recently if it had not been for greenhouse gases); they fancifully imagine that the harmless direct warming from a doubling of atmospheric CO2 concentration – just 1.16 Cº – ought to be tripled by imagined net-positive temperature feedbacks (not one of which can be measured, and which in combination may well be net-negative); they falsely triple the 1.16 Cº direct warming on the basis of a feedback-amplification equation that in its present form has no physical meaning in the real climate (though it nicely explains feedbacks in electronic circuits, for which it was originally devised); they do not model non-radiative transports such as evaporation and convection correctly (for instance, they underestimate the cooling effect of evaporation threefold); they do not take anything like enough account of the measured homeostasis of global temperatures over the past 420,000 years (variation of little more than ±3 Cº, or ±1%, in all that time); they daftly attempt to overcome the Lorentz unpredictability inherent in the mathematically-chaotic climate by using probability distributions (which, however, require more data than straightforward central estimates flanked by error-bars, and are thus even less predictable than simple estimates); they are aligned to one another by “inter-comparison” (which takes them further and further from reality); and they are run by people who fear, rightly, that politicians would lose interest and stop funding them unless they predict catastrophes (and fear that funding will dry up is scarcely a guarantee of high-minded, objective scientific inquiry).
That, in a single hefty paragraph, is why the models are doing such a spectacularly awful job of predicting global temperature – which is surely their key objective. They are not fit for their purpose. They are mere digital masturbation, and have made their operators blind to the truth. The modelers should be de-funded. Or perhaps paid in accordance with the accuracy of their predictions. Sum due to date: $0.00.
In the face of mounting evidence that global temperature is not responding at ordered, the paid trolls – one by one – are falling away from threads like this, and not before time. Their funding, too, is drying up. A few still quibble futilely about whether a zero trend is a negative trend or a statistically-insignificant trend, or even about whether I am a member of the House of Lords (I am – get over it). But their heart is not in it. Not any more.
Meanwhile, enjoy what warmth you can get. A math geek with a track-record of getting stuff right tells me we are in for 0.5 Cº of global cooling. It could happen in two years, but is very likely by 2020. His prediction is based on the behavior of the most obvious culprit in temperature change here on Earth – the Sun.
KNR says:
August 27, 2013 at 3:04 am
“To be fair , and as with both sides , ‘paid trolls ‘ is not really an issue like all religions the most fanatical are volunteers whose motivation is many fold but not finical . And we should be careful not to indulge in ‘conspiracy’ claims the alarmists are so fond off.”
So you dispute the claim of the EU’s transparency site, which details the amounts they give to green NGO’s, including Greenpeace.
http://www.climate-resistance.org/2011/06/fun-finding-the-eco-lobbys-funding.html
What evidence do you have that shows that the EU commission is lying?
JohnWho:
re your post at August 27, 2013 at 7:30 am
The troll posting as Village Idiot makes spurious points which need to be refuted for the benefit of onlookers who are seeking information about the subject of the thread.
Similarly, the troll posting as JohnWho needs to be answered and for the same reason.
Richard
I am confident that the voices of reason like Lord Monckton will eventually win out.
As to Village Idiot’s request for a better prediction; Steve McIntyre has found one.from 1938 that outperforms modern GCM’s.
http://climateaudit.org/2013/07/26/guy-callendar-vs-the-gcms/
Can I cherry pick too? I’m an amateur.
TSI is said to be 1.5%
Global mean temp is said to be 276 k.
We would be zero if it weren’t for the sun.
276X.015=4.14
A whopping 8.28k plus or minus differential due to the sun.
Simple really. 😉
Bruce Cobb says:
August 27, 2013 at 4:51 am
Not true–if we could stuff all the components of climate into a laboratory, we’d have an equivalent comparison–the lab experiment would just have to be a perfect replication.
However, that undertaking is proving to be just a bit difficult.
There’s a wealth of useful information in the text and graphics that Christopher Monckton of Brenchley has eloquently provided above, but I have a reservation about the graphics. There is a very interesting and potentially important missing piece of information in the plots. Indeed, this information has to my knowledge never appeared in any illustration of climate trend lines. In my own work on climate trends I *always* compute and plot this information. It is the confidence interval for the fitted regression line, at some arbitrary probability level (conventionally 95% in many branches of science). If presentation of this vital statistical information became the norm for those who publish on climate matters it would throw useful light on the arguments that surround interpretation linear fits to highly variable data.
In (climate) time series there is a problem involved in computing this interval that does not arise if the values in the underlying data set had been independent observations from the same distribution. They are not independent samples, and although the numerics of the linear fit are not affected, inferential statistics derived from these least squares calculations are. Steve McKintyre has frequently commented on this often ignored difficulty, and has referred to methods that have been proposed to allow for its effect. Overall, the modified interval is wider than the simple one, further degrading the predictive power of the regression.
The ultimate objective of those who work with climate data is usually to attempt to project into the future any wisdom that can be gained from studying the past. It is known as forecasting.
Anyone who has invested in the financial markets using professional advisers will have noticed their all-embracing caveats regarding future expectations. Exactly the same considerations apply to climate analyses.
Another interesting piece of information would be the confidence interval for a future (usually single) observation, for a datum coming from the same underlying distribution. This is normally a very disappointing statistic for most researchers, and in the case of highly autocorrelated data such as climate (often temperature) invariably are, might lead to despair.
All this leads to the point that R Squared, though a perfectly valid statisitic in itself, is a poor indicator of the practical (forecasting) value of the simple least squares fit. It would be an improvement to provide a probability level for the t value for computed coefficient (its magnitude divided by its standard error).
@ur momisugly Gail Combs
Thanks for the documentation re the warmists and their obsession about the time frame as to when the jig is up. It was most interesting.
I believe their new strategy is already revealed in that they are now concentrating on extreme weather events, of which, can always be found… somewhere.
I don’t know why TSI “variance” didn’t show up.
JimS says:
August 27, 2013 at 7:24 am
Yes, Gail, read further down from there….
>>>>>>>>>>>>
Sorry JimS, I comment as I read. I gave up trying to do it any other way such as trying to read all the comments first and then remembering what comments were which. Already there are 100 responses. Reading through once is bad enough. :>)
[Now, 157 comments. Mod]
“””””””………cd says:
August 27, 2013 at 3:37 am
Lord Monckton
I enjoyed reading your piece. There was a recent post which featured a talk given by Dr Essex on this very subject. Your post here affirms the points he was making.
I think you’re a bit hard on the poor modelers. Most of the people building and writing them are just doing a job. …….”””””””
I wish I had a $1 for every time I hear or read of the excuse; “I was just doing a job; AKA I was just following orders.”
I keep seeing different numbers for how many peer reviewed climate Temperature models there are.
13 ? 17 ? 19 ? 77 ? whatever?
And not one of them would let you postdict the mean global temperature in 1776, or 1066 , or 1492 , or 2011; let alone predict in 1988 (as Hansen did) what it would be in 2008; which it wasn’t.
So they are just doing a job Right ?
Hey that’s one job that the economy can well do without.
rgbatduke writes:
“One day I’m going to write an entire article on the “anomalous” sins of the climate community.”
Please do. Maybe your explication of these anomalous sins will cause some in the Alarmist camp to take the problems seriously. Once again, I thank you for your powerful contributions to our understanding of climate science as it is practiced today.
Lord Monckton is the “Celente” of climate. His classy indignation is welcomed and well received. He never comes off as ugly, calls names with the slickest of grace and provides entertainment with his meddle. He’s a pit bull with a pretty smile. Lord on, Lord Monckton! Me? A fanboy? Perhaps. I simply adore an coherent meddler.
“In general, we look for a new law by the following process: First we guess it; then we compute the consequences of the guess to see what would be implied if this law that we guessed is right; then we compare the result of the computation to nature, with experiment or experience, compare it directly with observation, to see if it works. If it disagrees with experiment, it is wrong. In that simple statement is the key to science. It does not make any difference how beautiful your guess is, it does not make any difference how smart you are, who made the guess, or what his name is — if it disagrees with experiment, it is wrong.”
― Richard P. Feynman
Thanks to Gail Combs and Richardscourtney for the info – really appreciated guys
Gail Combs says:
August 27, 2013 at 5:29 am
“Of the two satellite sets: UAH has the ‘Stigma’ from Dr. Roy Spencer (in the minds of the warmists) so that leave RSS as the only ‘neutral’ set.”
I agree, but why didn’t Monckton make that obvious point himself when going for the RSS data so as to shut up all the potential whiners that use the tiniest indication of prejudice to attack him.
Your Lordship, it is understandable that some might argue this point since the House of Lords itself does not list you among its membership, and indeed has asked you on more than one occaision to stop claming that you are a member of the house.
http://www.parliament.uk/business/news/2011/july/letter-to-viscount-monckton/
http://www.parliament.uk/mps-lords-and-offices/lords/
Robin Edwards says:
August 27, 2013 at 8:05 am
There’s a wealth of useful information in the text and graphics that Christopher Monckton of Brenchley has eloquently provided above, but I have a reservation about the graphics. …It is the confidence interval for the fitted regression line, at some arbitrary probability level (conventionally 95% in many branches of science).
It was not my intention to advertise my own article, http://wattsupwiththat.com/2013/08/25/rss-flat-for-200-months-now-includes-july-data/
however that article may have what you are looking for in Section 2:
As a result, we can now say the following: On six different data sets, there has been no statistically significant warming for between 18 and 23 years.
The details are below and are based on the SkS Temperature Trend Calculator:
For RSS the warming is not statistically significant for over 23 years.
For RSS: +0.120 +/-0.129 C/decade at the two sigma level from 1990
For UAH the warming is not statistically significant for over 19 years.
For UAH: 0.141 +/- 0.163 C/decade at the two sigma level from 1994
For Hadcrut3 the warming is not statistically significant for over 19 years.
For Hadcrut3: 0.091 +/- 0.110 C/decade at the two sigma level from 1994
For Hadcrut4 the warming is not statistically significant for over 18 years.
For Hadcrut4: 0.092 +/- 0.106 C/decade at the two sigma level from 1995
For GISS the warming is not statistically significant for over 18 years.
For GISS: 0.104 +/- 0.106 C/decade at the two sigma level from 1995
For NOAA the warming is not statistically significant for over 18 years.
For NOAA: 0.085 +/- 0.102 C/decade at the two sigma level from 1995
If you want to know the times to the nearest month that the warming is not statistically significant for each set to their latest update, they are as follows:
RSS since August 1989;
UAH since June 1993;
Hadcrut3 since August 1993;
Hadcrut4 since July 1994;
GISS since January 1995 and
NOAA since June 1994.
A truly EXCELLENT post. This should end, once and for all, the debate over “man-made warming.” But it won’t, because Big Money is involved in keeping the myth alive.
richardscourtney says:
August 27, 2013 at 7:53 am
Gail Combs says:
August 27, 2013 at 7:57 am
It is a strange situation that a scientific theory has to be dis-proven at the 95% level, but the models are already outside of that self-determined range. They don’t believe their own statistical ranges as set by their models, why would this one matter? If the modellers do not already acknowledge that the models are wrong, reaching some length of time that those models are wrong will not be convincing to them either: that time is just arbitrary and will be revised as egos require. It does not matter whether the models have diverged starting in 1997 or 1998 or some other time. The models and the data will continue to diverge, and they will eventually have to acquiesce, but they will only do it when they decide, not by hurrying the schedule.
The goal should be to get the science and analysis right, not score points in a contest.
It’s pretty funny stuff to see how alarmists tried to spin all things 7 years ago.
http://grist.org/series/skeptics/
Every click goes to a silly dance.
http://grist.org/climate-energy/climate-models-are-unproven/
…”models predict continuing and accelerating warming of the surface, and so far they are correct.”
Climate sensitivity (feedback) is a huge issue. Without it, increased CO2 would have only a modest effect on temperature and might even be beneficial given increased crop yields and longer growing seasons. IPCC and the models they use as the basis for their reports, assume a strongly positive feedback. If that is true, why did temperatures not run away when CO2 was 2,000ppm and higher in the not so distant past?
CG in BOS says:
August 27, 2013 at 7:01 am
The person you quote might not be a troll. However, the Washington Post sites are infected by paid trolls. Their technique is to post so quickly that interesting posts are scrolled off the first page before anyone has had a chance to read them. They also use other familiar troll techniques. How do I know? I have conversed with them online. But the clearer evidence is that they are not there on holidays or most weekends. Why did I care to learn this? Because Jennifer Rubin’s blog has had the comments section controlled by trolls since she started at WAPO. That is really sad because she is a first rate analyst of the news regardless of what you think of her political predispositions.
http://www.endofyourarm.com/2013/08/mann-versus-steyn-some-possibly-good.html
Looks like the judge on the Mann-Steyn case is being replaced.
“It is difficult to get a man to understand something, when his salary depends upon his not understanding it!” – Upton Sinclair To a large extent, the “scientists”, the green groups, the UN IPCC and the politicians; are all depending on not understanding it.