The 200 months of 'the pause'

The “3 degrees” is a strong element of every one of the Gap graphs (as in the oft-quoted 3 degrees of increase for a simple doubling of CO2 concentration). All the graphs are over/predicting by this same 3 degrees, with very minor variations.
This ought to lead to at least a question about the reliability of the sensitivity assumptions behind the models, I’d have thought …

So, now the ancient fear is graphically clarified…what “they” used to tell the boys, the caution: wanton digital manipulation leads to blindness. QED. Bravo, Lord Christopher!

They should surely have the message by now. Excellent post.

This is plain to see by everyone other than the unconvertible zealots. For them, a few other standard techniques might help: plotting the residuals as a histogram or probability plot, residuals versus predicted value, residuals versus time, and predicted values versus actual values.
But why bother? Anyone can see the model doesn’t fit the data. The residuals would all be positive and diverge over time. I guess the hope of those profiting from the public trough is that the real data will eventually catch up with the model.
If I tried to present a model describing drug stability this bad when filing a new drug with any agency, it would result in a nonapproval.

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. Trying perhaps do to the impossible, but I don’t think they should be de-funded for it. I think the real problem is that many of the scientists that use them don’t understand them and therefore attach to much confidence in their projections. Somewhere along the line there are scientists who are promoting what they know – at least now – to be inherently flawed methodologies. Perhaps they should be isolated and exposed for misrepresenting the models.

BTW….Lord Mocnkton
A friend of mine works for hedge fund company. He told me that they employ Oxford and Cambridge math graduates to build financial and economic models. He’s a physics graduate and helps run and maintain them. After years of building very complex models in order to predict the market, these incredibly bright people decided that extrapolating a running average a few days ahead was better at predicting the future than the highly complex models they had built.

Good post and nice, explanatory, charts. The linear regressions include very low “r-square” values, 0.000-0.035. If, in my work, I had data that gave r2’s like that, I’d re-examine the data set and experimental technique, because I would consider it to be no correlation. In climate science discussions, on the other hand, seem to ignore this lack of correlation and both sides of the issue divine significance of data that seem to be too noisy to have any good confidence level or much of a decent correlation.
I’m currently involved in an effort to optimize operations of a landfill gas to pipeline gas plant. We are collecting data and doing statistical analyses on the data. R2’s of 0.5 mean we can’t can’t attach much significance to the data. One of the things I don’t understand about climate science is making much of very poor correlations. Should you be using other curve-fitting, y=mx+b doesn’t seem to be overly convincing.

“predicting global temperature – which is surely their key objective”
I know some people who have been trying to use the same climate models for trying to predict rainfall.
One guy was telling me they were doing very well (tongue in cheek, I might add), because the model mean was tracking really well with reality.
Thing is, about half the models predict more rain, and half predict less rain. 😉

As good as this is, what we really need is some cooling that no one can deny/spin instead of non-warming.

Sheffield Chris asked:
“has anybody published a more realistic model output that matches reality?”
Yes, as long as one realises that the best we can do so far is determine the direction of trend rather than the rate of that trend. Internal system variation, especially from the oceans, currently confounds quantification of the rate of any underlying longer term trends.
The fact is that zonal jets with reducing cloudiness result in system warming and meridional jets with greater cloudiness result in system cooling by regulating the proportion of ToA insolation that gets into the oceans to drive the climate system.
That fits all the observations that I am aware of including LIA, MWP, Roman Warm Period et al.
http://www.newclimatemodel.com/new-climate-model/
So we need to start over from that point.

Quick, Mr. Obama, tweet it.

The climate models have clearly failed in the last 20 years.
Basically, since they were built. Most of them were developed less than 20 years ago.
If we go back to the first of them by Hansen and Manabe in the early 1980s, the predictions missed the last 20 years as well.
There is no global warming climate model that has a long pause in it because they are programmed to increase with rising CO2.
Why are we wasting so much resources on models which don’t work. Tens of millions of dollars per year and thousands of people are involved One might be tempted to say “why not reprogram them so they do a better job?” Well, whomever tried to do this would get blacklisted by the other climate scientists.
Hence, they go on and on looking for flimsy excuse after flimsy excuse when the obvious answer is right there staring them right in the face.

Additionally, the models all have subset characteristics which are testable, and failing. Tropical hotspots, water vapor content, sea level, etc.

If you had based your career and economic security on being a leader in your field and then came to find out, not only have you been wrong, but your methods that lead to your conclusions were also wrong, would you risk being sent away to the poor house with little more than a footnote in history? Most likely not so you would defend yourself to the bitter end, after all, what have you got to lose by hanging on as long as you can. (not a defense just an understanding of why)

A comment I’ve made before and will make again. It is pointless and misleading to superimpose the CO_2 curve, with an arbitrary y-axis scaling, on top of the temperature curve, with equally arbitrary y-axis scaling. This is screamingly obvious when one is plotting not absolute magnitudes (which have some meaning) but the cursed “anomalies” that climate scientists seem obsessed with, largely because of their belief that they can subtract away some sort of reliably known “time varying baseline” and focus only explaining deviations from this baseline, in a system described in even its simplest (almost trivial) forms by a nonlinear stochastic differential equation. Sadly, plotting anomalies is the subject of almost an entire chapter in the lovely book “How to Lie with Statistics”, (which could also be read as “How to make terrible errors using statistics naively” as an alternative title).
So please, please — remove the grey CO_2 curve. That isn’t science. It isn’t even good argumentation — since the two curves have completely different units you can easily scale the y-axis units for the CO_2 so that it falls nicely into the range of the temperature fluctuations and lines up with the temperature trends in perfect agreement with any positive temperature slope — and it still won’t mean anything.
If you want to see something really instructive, take a look at this:
http://www.woodfortrees.org/plot/hadcrut3gl/offset:287/plot/rss/plot/esrl-co2
This is what the actual global average temperature looks like in degrees Kelvin. Some “hockey stick”, huh? Only it doesn’t, because one cannot add a constant back — the Earth’s temperature varies seasonally just like the CO_2, and the anomaly was computed by subtracting something like a constant plus an annual sinusoid from the original data, and I cannot add back the annual sinusoid function because I don’t know it. I can’t even find it on the internet. I could probably figure it out if I looked deep in some computer code somewhere, and it probably is in the literature, but at the moment I don’t even know the purported range of monthly variation of the supposed mean global temperature relative to which the anomaly is computed (and it may be computed locally and subtracted before forming the anomaly mean!) So this entire figure could have monthly ripple that is as large or larger than the entire “anomaly” variation over the entire range. How would I know? How would anyone (but one of the deep climate cognoscenti) know?
It is also what the actual CO_2 concentration looks like in parts per million, which conveniently scales to fit on the same graph and (because pre-industrial baseline CO_2 was ballpark 287 ppm) by pure chance one can quite accurately extrapolate the near-exponential rise back to the left so that it appears to be rising from the temperature line. This does, actually, correctly illustrate the relative increase — CO_2 has increased by around a third of its original absolute pre-industrial concentration, and the bulk of that increase has occurred within the last 50 or 60 years.
Entertaining as it is to look at anomalies, sometimes it is very useful to look at the actual quantities involved. The skeptics who assert that a “trace gas” like CO_2 cannot provide much warming as it increases — well, look at these curves. It doesn’t, not in any absolute sense. Not much, of course, is not the same as zero.
A second sorry aspect of WFT is that it is (as far as I can tell, correct me if I’m wrong somebody) quite impossible to add simple little things like error bars to the curves, or to do a proper chisq fit USING the data uncertainties. In fact, there are a ton of things one cannot do within WFT, either because it is missing the functions needed to do it or because it is missing the DATA needed to do it. In particular any sort of reasonable error estimate. It would be infinitely more instructive to put all of the data into R (for example) where one could actually do statistics with it instead of thinking up fifty different ways to commit the sin of post hoc ergo propter hoc on the susceptibility of a quantity that cannot even be properly defined by the very people that compute it.
One day I’m going to write an entire article on the “anomalous” sins of the climate community. For example, GISS and HADCRUT and all of the rest of the datasets that purport to reach back to the mid-1800s are presented as anomalies across the entire range. At the same time, it is openly confessed that to transform the anomaly into an absolute temperature one has to add to the quantity an estimate of some baseline temperature, say, 14 C or 287 K. Only, there is no general agreement as to just what that baseline temperature ought to be — it might be as low as 286-something K or as high as 287-something K, where the range enabled by the “somethings” is order unity either way. What value you get depends — wait for it — on what model you use. Strangely enough, what value you get for the anomalies themselves also depends on what model you use! The error for the anomalies, surely, increases as one goes back in time. The error for the baseline similarly increases as one goes back in time! In fact, we have precisely zero thermometric measurements for entire continents — Antarctica, for example — from the mid-1800’s.
You can then see why it is essential not to present any sort of graphical treatment of the uncertainties in global temperature — this is never done even in the modern thermometric data. Each “anomaly” dataset is presented as a fait accompli, without the slightest hint of uncertainty, and (committing a sin that would cost them points on any physics exam!) to an absolutely absurd number of significant figures! The anomaly is never 0.1, it is 0.1327… (who knows how many digits of garbage they actually keep in their published computation — WFT is happy plotting at least 2. Thus we are presented with the illusion that we know the global temperature anomaly within an experimental resolution of at least 0.01 K, perhaps 0.001 K or even more! We are further led to believe that “smoothing” this data in some way leaves us with a real trend, and not just smoothed noise! Lying, lying, lying.
Let’s realistically assume that even in the modern era, it is most unlikely that we know the absolute global average temperature to an experimental resolution of 0.1 K. By this I mean that there is that much variation (easily) just between purported estimates of the anomaly alone, and since those estimates surely rely on substantially overlapping data, this variation almost certainly significantly underestimates the error. One could argue that in the modern era we probably don’t know the anomaly within 0.3 K, and of course this grows substantially as one goes into the past, and plotting the “anomaly” in the first place conceals the simple fact that we don’t know the baseline to which the anomaly is added to within more than about a degree.
One cannot assume that this error is unbiased normal error — pure statistical error resulting from some process with zero mean. For one thing, the datasets that compute anomalies have systematic differences — some are consistently higher than others (again, in spite of the fact that they have enormous data overlap and indeed are probably adjusted to remain IN approximate agreement). For another, the anomaly computations include systematic corrections to the raw data — which begs so very many questions it is difficult to count them — as well as perform black infilling and extrapolatory magic that literally cannot be validated outside of AT MOST a narrow window of time. Indeed, the strangest thing of all is that even the anomalies fluctuate by several tenths of a degree month to month, all or part of which could be pure statistical error. After all, what they are subtracting to form the anomaly isn’t even a constant average baseline temperature, it is an average baseline temperature plus an assumed known seasonal correction, which is a second order correction compared to the baseline.
With all that said, I do agree with you that the IPCC is getting ready to repeat the sins of AR4’s summary for policy makers and present the mean and standard deviation of many different model results as if it is a statistically meaningful quantity. Which is why your presentation above — especially when presented with the AR4 and/or AR5 predicted trend — is NOT cherrypicking, at least not when applied to the entire time after those (e.g. AR4) predictions were made. That is simply looking to see how the models did, which is terribly.
I’m not certain I agree that we are due for 0.5C of cooling — perhaps we are, perhaps not — because I don’t think uncertain science suddenly becomes certain for you, for me, for your friend who is sometimes right, for the IPCC, for the GCMs, or for your favorite psychic medium. Given the uncertainties in the data and the corrections, I’m not even sure we’ve had the claimed 1 C of global warming post the mid-1800s. I think we have actually had some warming, but it could be a half a degree, it could be a degree and a half. Who knows what Australia, Antarctica, the western half of the United States, most of South America, half of Canada, most of China, the bulk of the pacific, and the bulk of the Atlantic oceans were doing (temperature-wise) in the mid-1800s? Our thermometric data is spotty to sparse and inaccurate, and a lot of this was terra incognita to the point where we don’t even have good ANECDOTAL evidence of climate.
We are left trying to make sense of equally sparse proxies, where the proxy errors BEGIN with the residual errors of the modern era (which typically normalizes the proxy) and get strictly larger as one computes the proxy results further in the past, where the normalization period is almost certainly corrupted by the incorrect inclusion of UHI-contaminated data that is almost impossible to correct without doing a case by case study of EACH contributing station, if then.
I say “if then” because if one looks at the range of temperatures visible on the area weather stations just in the immediate vicinity of my house in Durham, while there are clearly visible UHI systematic errors in the local airports that contribute to e.g. GISS, it isn’t particularly easy to see how to correct them in a time-dependent way that allows for things like gradual urbanization of the area, the fact that it is piedmont (hilly, with significant vertical variation of temperature that is different at different times of the year), with a particular kind of soil that favors certain kids of convective updrafts and thunderstorm formation (at least in the nearby sandhills that influence our weather), with two large impoundments, both very near the airport, that have been built and filled over the last three decades, as the airport itself has gone from a single small terminal and a runway to three terminals and two large runways where they are on the THIRD REBUILD of two of those terminals, and where they relocated the airport weather station right next to the tarmac in the middle of nowhere, directly exposed to the sun, awash with jet exhaust, and right next to what amounts to solar heated rock, gravel and grass (no trees need apply, even though the entire region is heavily wooded EXCEPT for the cities proper and the airport). I shudder to think of doing this sort of thing, correctly, for every contributing weather station or pretending that a one-size fits all correction can be applied across the board on the basis of some simple functional form.
IMO we have at most 33 years of pretty good measurements of global average temperature(s) — by pretty good I mean arguably within a few tenths of a degree C combined systematic and statstical error. We have perhaps another 20-30 years of decent measurements (post-world-war-II, say) where our knowledge probably is within order of a half a degree. Before that, I suspect that it quickly broadens out to a degree or more of error, with an unknown fraction that could be systematic and not zero-trend statistical. It is a daunting proposition to try to measure the Earth’s temperature now with anything like real precision. It isn’t even possible to measure the temperature within a tenth of a degree in my own back yard. Yet we purport to know what the temperature in my own back yard was in the year 1870 to well within a degree? I don’t think so.
rgb

Will people start calling this the Mann-o-pause?

Bruce Cobb —
Maybe it was mentioned for people like me. The only explanation I have for how a “greenhouse gas” could possibly cause warming works equally well for preventing warming, i.e., for moderating temperature, damping both warming and cooling for a net change of zero. I am willing to be made wrong, because then I’d understand the matter better, but it remains that I honestly don’t see it. I’d welcome a direction to a high-school-level explanation (one not written by believers in AGW). Hopefully it will include why Venus, when pressure is accounted for, is no hotter than it “should” be just from closer proximity to the sun. ?

Chris Schoneveld says: @ August 27, 2013 at 3:57 am
…..It is a pity that he chose RSS, since it gave his opponents ammunition to attack his credibility.
>>>>>>>>>>>>>>>>>
I would also pick RSS because it is the ‘CLEANEST’ of the data sets. The three terrestrial datasets: GISS, HadCRUt4, NCDC, have been sliced diced and mutilated as has been shown repeatedly here at WUWT. An example from Jo Nova’s site.
The satellite sets also have better more uniform coverage without all the problems of very spotty coverage, siting, multiple instruments, calibrations and observers that give you a much larger possible error.
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.

Someone please send this to CNN, NYT, ABC, NBC, CBS, AND The President.
Please.
And add in every local college and highschool.
JimB

All models are going to shop – show

Another well-written piece that even a non-scientist like myself can at least appreciate. Christopher Monckton writes very eloquently for the ordinary reader – it’s a tragedy the msm are too cowardly to ever print his informed analysis.

RGB, your points are well-founded, but it is quite relevant for Monckton to mention–in some manner–the behavior of CO2 in a period in which Earth’s temperature, represented in the main available data sets, has been nearly unchanged. The best temperature information we now have invites skepticism about AGW; it would be ironic is the warmists were to seize upon the unreliability of their own data as a defense against Monckton’s criticism.

James Strom says–
Typo: “ironic if the warmists”. Darn! And I used preview.

Steve Jones says: @ August 27, 2013 at 4:44 am
….. Sadly, amateur has come to mean second rate.…
>>>>>>>>>>>>>>>>>>>>
That is very unfortunate since I know a lot of ‘amateurs’ who are a lot better than ‘professionals’ in many different callings. As far as I can see the only difference between the two is as you mentioned an amateur does it for love and a professional for money. There is nothing in those definitions that says who is actually better. In some instances, like horse training, the amateur, who has no reason to force the horse to be ridable in a month, does a much better and more thorough job of it. In science, whether in academia or industry, again the professional is playing to someone else’s tune and if he doesn’t ‘produce’ what is wanted within time constraints he is penalized. All the science fraud in many different fields that is now coming to light is cause by this problem with ‘professionals’
His Lordship, as you say “is definitely an amateur in the original sense of the word.”

Ric Werme says:
August 27, 2013 at 6:11 am
I don’t think the Old Farmer’s Almanac is out yet, you are referring to the Farmers’ Almanac from Maine, a pretender to the throne.
================================
The Farmers’ Almanac is using words like “piercing cold,” “bitterly cold” and “biting cold” to describe the upcoming winter. And if its predictions are right, the first outdoor Super Bowl in years will be a messy “Storm Bowl.”
The 197-year-old publication that hits newsstands Monday predicts a winter storm will hit the Northeast around the time the Super Bowl is played at MetLife Stadium in the Meadowlands in New Jersey. It also predicts a colder-than-normal winter for two-thirds of the country and heavy snowfall in the Midwest, Great Lakes and New England.
http://www.cbsnews.com/8301-201_162-57600023/farmers-almanac-predicts-a-bitterly-cold-winter/

Monckton
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.

KNR
For some it is that which as to be defended to the death, for they know that once the academic ‘trend’ slips away from them, they have nothing but to go back to but obscurity, defunding and lack of jobs.

LOL. Where is Nick Stokes? He seems to think that the IPCC has never made a prediction. ROFLMAO.

The error in the models is largely a result of the assumption that post LIA warming stopped 150 years ago. This warm biases the models because they assume that natural warming must be due to human activity.
Occam tells us to pick the simplest explanation. The simplest explanation is that post LIA warming did not suddenly stop 150 years ago, that it continues to this day. Thus the climate models are running hot because they do not account for long term natural variability.

Dear Lord Monckton,
In the first sentence of the second to the last paragraph, my Minnesota ear for American English wonders if the phrase at ordered is a small typographical error and should read as ordered?
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.

richardscourtney says:
August 27, 2013 at 4:27 am
“Lord Monckton….as a scientist”
Nope…Google him and I don’t think he is. Jounalist, yes. Knight of Honour and Devotion of the Sovereign Military Order of Malta, yep. He is obviously, as you so rightly say, an amateur, doing what he loves best…Christopher Walter Monckton, 3rd Viscount Monckton of Brenchley (born 14 February 1952) is a British public speaker.
http://en.wikipedia.org/wiki/Christopher_Monckton,_3rd_Viscount_Monckton_of_Brenchley
So will the Honorable Knight pick up the gauntlet? Methinks not. He may be many things, but he’s not stupid enough to put his money where his mouth – he’d crash and burn. He’d rather keep his powder dry and “predict by proxy”: “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.”
What a clever Champion we have!

Village Idiot says:
August 27, 2013 at 6:49 am
=====
What an odd request….
Asking someone to make a prediction….when the argument is we don’t know enough to make those predictions

Excellent article! One would like to point out notes from Sankhya research little long .sorry if there is any inconvenience.
The Suns (hence Earth’s too) distance from the galactic centre keeps changing which causes polar glacial meltdown every 26000 yrs. It is moving towards cooling!
In Sankhya the Triguna theory of simultaneous and self similar interactions derives the standard oscillatory cycle of components in space through axiomatic theorems and equals 2.965759669e+8 interactions per cycle,. It is approximately equal to the frequency of modern velocity of light at a wavelength of a meter in 1.010845 seconds, which is due the earth’s distance from the Sun. The solar gravity field flux density varies as the log of distance. The Meter to yard conversion factor of 1.30795 for cubic space and a time correction of 2.99792458e+8/1.486e+11 shown below which is an indicator of their scientific knowledge. It yields the value of 3.5312861 x 1025 cubic yards per second exact to the 7th decimal place of the value from the Rigvedic theorem. Statistically this equivalence cannot be an accident. An important factor is that time correction for Galactic and Earth velocities were included which means the Vedic forefathers knew of the Doppler shift in frequency due to relative movement
“Sanskrit” means a refined code. “Sama” means equalised and “krit” means cut, clipped, divided, pulsed or in other words a code. The language was developed scientifically and logically as the only possible code human beings could create naturally with the equipment they had, the human body.
Any cyclic vibration has a typical characteristic of reversal of action, like up and down, forward and backward or left and right and this variation can be described as creation and destruction or acceleration and deceleration or sinusoidal oscillation. If the opposing effects are equal they cancel out or the nett algebraic effect is zero which does not contribute to detectable or measurable signal. The period the pulse is on can be considered a ‘mark’ and the silence a ‘space’ and a combination of mark and space makes a cycle.
(Rapid Rise of Sea Level 19,000 Years Ago and Its Global Implications
Peter U. Clark,1* A. Marshall McCabe,3 Alan C. Mix,2 Andrew J. Weaver4
Evidence from the Irish Sea basin supports the existence of an abrupt rise in sea level (meltwater pulse) at 19,000 years before the present (B.P.). Climate records indicate a large reduction in the strength of North Atlantic Deep Water formation and attendant cooling of the North Atlantic at this time, indicating a source of the meltwater pulse from one or more Northern Hemisphere ice sheets. Warming of the tropical Atlantic and Pacific oceans and the Southern Hemisphere also began at 19,000 years B.P. These responses identify mechanisms responsible for the propagation of deglacial climate signals to the Southern Hemisphere and tropics while maintaining a cold climate in the Northern Hemisphere.)
The stellar divisions based on 28 Nakshatras- the angular width = 12.857 (With 27 the angular divisions are 13.333 deg.)
Calculations show that the current starting position or the 0 degree position on the ecliptic to date is in the Nakshatra( Na = ‘not’ Aksha = ‘terrestrial latitude’ Atra = ‘in this case’ meaning not a terrestrial latitude in this case) is a label to identify a numerical angular position or celestial latitude or longitude Aswini or Aries constellation between 0 and 13 degrees. As a rough guide the total ayanamsa period of 25739 years divided by 28 yields 919 years per Nakshatra passage.
The Vedic scholars, following the Sankhya principle of self-similarity that governed the dynamic state of the Substratum, took the ecliptic coincidence as a clock time benchmark that can at least be relied on in a cycle of approximately 25739 years. This drift or Ayanamsa(Ayan = motion or movement and Amsha degree or division) was used by astronomers and astrologers to fix the moving zodiac (ecliptic) so that accurate comparisons of events could be made in a locality where everything is moving relative to everything else. If the number of Ayanamsa cycles are known between events in multiple units of 25739 years, then it could be compared meaningfully.
The earth’s equator spins at a mean surface velocity of approximately 462 m/s and the earth itself moves around the sun at an algebraic mean speed of approx. 29845.4 m/s. But the earth’s axis is tilted by 23.5 deg. to the plane of revolution around the sun, called the ecliptic. As a result of this tilt, the earth’s maximum spin velocity vector at the equator works out to : 462 x .91706 (cos 23.5) = 423.52 m/s. The drift of the starting point of the ecliptic is at the rate of 423.52 / 29845.4 = 1 / 70.47 of a cycle and the drift due to the sidereal effect is 1/365.25 thereby giving a total drift of 1 / (70.47 x 365.25) = 1/ 25739 of a cycle. It means that an identical ecliptic coincidence of the sun and earth at a particular position will be repeated only after 25739 cycles or years in this case. This calculation has been shown in a simplified form to make it understandable but a very accurate calculation supported by many years of practical observation gives a drift rate of 50.35 seconds of arc per solar year and is only used in Vedic astrological calculations as a normal course . The precession of the equinox calculated by applying modern principles of celestial mechanics is 26000 years or (49.85 sec of arc per year.).The precession of the equinox provides the correct algorithm to predict global weather trends.. The glacial melt about 10000 years ago is now driving the world towards a colder regime in another 3000 years or the mid cycle of 26000 years to another glacial melt But extremely accurate calculations give varying precessional rates at different periods and relative positions, but the 25739 rate is an average of over 30000 years.
Finally, The numerical proof for this fact comes from the enigmatic 2.7 degree Kelvin background temperature in space that Peebles et al recorded. The 10e+17 modes of change in entropy in a micro blackhole in space logarithmically equals the natural log value of e = 2.718 or the total sum of self-similar change in volume per cycle. Mathematically it could never exceed 2.718. Hawking et al exposed the entropy value but as a macro blackhole phenomenon on a solar scale, for science was apparently unaware of the concept of scale invariance and reflection symmetry in a frozen hologram. So a tiny blackhole is no different from a massive blackhole except for its self- similar time cycle.
The earth spins on its own axis in 24 hours or 1/365.25 of its annual orbit around the sun. This sets the actual time of a daily revolution to less than 24 hours of clock time, if the starting point of each daily revolution is referred to a location in the sky; that is ( (24 x 3600)/365.25) = 236.55 sec or 3 min and 56.55 sec less than 24 hours. It means that if we use a particular stellar constellation or star at the zenith or the horizon, identifying the starting point for the daily revolution of the earth, one would see this mark arrive 3 min and 56.55 sec earlier every day and will again coincide with the same stellar location and clock time only after 365.25 days or a year. It is the natural shift in timing of an object that is both spinning and orbiting in space. The time of 23 hrs 56 min 3.45 sec is called sidereal time. Hence we can locate the star accurately at any future time by applying the sidereal time from a known date within an annual cycle. Similarly if the location of this star is recorded at a particular time, it is possible to work out the location of the observer and the date of such observation, all within the cycle of one year. This example has been quoted to show that location and date of events can be ascertained with the required degree of accuracy based on the sidereal shift in stellar positions. Added to the sidereal shift that moves along the solar ecliptic, there is another movement due to the shift in the angle of earth’s axis to the ecliptic that creates a relative change in the angle of inclination of the ecliptic. This movement is called precession of the equinox and is treated in current physics as a problem connected with spinning bodies like a gyroscope and in relativistic physics it is due to the curvature of the field. But Sankhya proves that all phenomenon is due to the synchronisation of vibrations or it is of a holographic nature and treats space like any other matter field comprising gas or fluid etc. that causes delay by superpositioning of vibrations and therefore a shift in the static or synchronised state and both these shifts are combined and defined as Ayanamsa (Ayan = motion or movement and Amsha degree or division- in Sanskrit explained below). The fundamental reason that precession exists is that the oscillating or vibrating parameters along the two axis in the plane of motion is not synchronous or the synchronous nodes along the two axis have marginally different rates of oscillations. Two sets of axial vibrations can be in resonance or have a standing wave relationship if the two axis (say x and y ) have a ratio of one to two. That is the tangent of an angle of 26.565 is exactly ½ and at this value the resonant state at the 2nd harmonic is maintained. This is perhaps just the tip of iceberg !!! Pls explore http://www.kapillavastu.com

JimS says:
August 27, 2013 at 6:00 am
The Old Farmers Almanac does it better than the climate models. It is predicting 2014 to be a very cold year….
>>>>>>>>>>>>>>>>>
Sorry Jim, that is the pretender The Farmers Almanac not the Old Farmers Almanac because the 2014 issue is due out September 10, 2013!

@Gail Combs
Yes, Gail, read further down from there – correction noted, made, and walked off with tail between my legs already.

Gail Combs says:
August 27, 2013 at 7:17 am
Sorry Jim, that is the pretender The Farmers Almanac not the Old Farmers Almanac because the 2014 issue is due out September 10, 2013!
=====
Gail, it is the Old Farmers Almanac….it’s in their press release
http://www.almanac.com/sites/new.almanac.com/files/2014_ofa_usa_press_release_web_rev.pdf

It is perfectly obvious that the IPCC models are not fit for purpose because they are structured incorrectly ab initio.They are based on three irrational and false assumptions. First that CO2 is the main climate driver ,second that in calculating climate sensitivity the GHE due to water vapour should be added to that of CO2 as a feed back effect and third that the GHE of water vapour is always positive.As to the last point the feedbacks cannot be positive otherwise we wouldn’t be here to talk about it .
Temperature drives both CO2 and water vapour independently,. The whole CAGW – GHG scare is based on the obvious fallacy of putting the effect before the cause.As a simple (not exact) analogy controlling CO2 levels to control temperature is like trying to lower the temperature of an electric hot plate under a boiling pan of water by capturing and sequestering the steam coming off the top.A corollory to this idea is that the whole idea of a simple climate sensitivity to CO2 is nonsense and the sensitivity equation has no physical meaning unless you already know what the natural controls on energy inputs are already ie the extent of the natural variability.
A simple empirical approach based on the forward projection of quasi cyclic quasi repetitive patterns is much more useful.Here are the conclusions of a Thirty Year Forecaste update posted on my blog at
http://climatesense-norpag.blogspot.com
To summarise- Using the 60 and 100 year quasi repetitive patterns in conjunction with the solar data leads straightforwardly to the following reasonable predictions for Global SSTs
1 Continued modest cooling until a more significant temperature drop at about 2016-17
2 Possible unusual cold snap 2021-22
3 Built in cooling trend until at least 2024
4 Temperature Hadsst3 moving average anomaly 2035 – 0.15
5Temperature Hadsst3 moving average anomaly 2100 – 0.5
6 General Conclusion – by 2100 all the 20th century temperature rise will have been reversed,
7 By 2650 earth could possibly be back to the depths of the little ice age.
8 The effect of increasing CO2 emissions will be minor but beneficial – they may slightly ameliorate the forecast cooling and more CO2 would help maintain crop yields .
9 Warning !!
The Solar Cycles 2,3,4 correlation with cycles 21,22,23 would suggest that a Dalton minimum could be imminent. The Livingston and Penn Solar data indicate that a faster drop to the Maunder Minimum Little Ice Age temperatures might even be on the horizon.If either of these actually occur there would be a much more rapid and economically disruptive cooling than that forecast above which may turn out to be a best case scenario”
Note – I believe that the SSTs are the best metric for climate change because we should really be measuring enthalpy and the SSTs are a reasonable guide to the changing enthalpy of the oceans and the thermal inertia of the oceans smooths out short term noise.Perhaps Monckton could add the HadSST3 and the NOAA SST data to his comparisons.

Paid trolls are mythical creatures. Just like the few hundred regular WUWT posters, they do it for free.

Chris4692 says: @ August 27, 2013 at 6:57 am
Determining when the trend change is a bit puzzling….
>>>>>>>>>>>>>>>>>>>
It is all about the statements made by Warmists:
1. Prof. Phil Jones saying in the Climategate emails – “Bottom line: the “no upward trend” has to continue for a total of 15 years before we get worried.” Also see: interview with Judith Curry and Phil Jones
2. Ben Santer in a 2011 paper “Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature.” link
3. The NOAA falsification criterion is on page S23 of its 2008 report titled The State Of The Climate

ENSO-adjusted warming in the three surface temperature datasets over the last 2–25 yr continually lies within the 90% range of all similar-length ENSO-adjusted temperature changes in these simulations (Fig. 2.8b). Near-zero and even negative trends are common for intervals of a decade or less in the simulations, due to the model’s internal climate variability. The simulations rule out (at the 95% level) zero trends for intervals of 15 yr or more, [Maybe THAT is the 95% the IPCC is now talking about.] suggesting that an observed absence of warming of this duration is needed to create a discrepancy with the expected present-day warming rate.

So the falsification criteria is 15 years to 17 years. That is why we start at the present and count backwards. Once we hit 17 years The Goose is Cooked. Unfortunately the Goose seems to be a zombie and keeps rising from the dead.
Anyone have silver bullets, garlic and a wooden stake?

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/

Bruce Cobb says:
August 27, 2013 at 4:51 am

I’m not sure why ghg theory not being proved wrong is mentioned, as it’s a straw man. The real argument is over what the climate sensitivity to man’s CO2 actually is. The “human fingerprint” has not been shown. That doesn’t mean there is none; it just means that it is very small. It appears that climate just doesn’t respond like a laboratory. Fancy that.

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.

@ 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.

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]

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.

“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

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.

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.

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?

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.

Hoya Skeptic says:
August 27, 2013 at 8:25 am
There you have it, in basic form, from the last great scientist who often expressed awareness of his social and political roles as scientist. He constantly taught scientific method and the duty of each scientist to follow scientific method in detail.
The problem that Alarmists face is that none of them have produced even one new well confirmed physical hypothesis. As regards CO2, they are dependent on Arrhenius. As regards the “forcings and feedbacks,” they have produced nothing.

Steven Mosher says:
August 27, 2013 at 8:57 am
He did not present it as a prediction, at least not as one he accepts. He presented it as one among a list of possibilities that cannot be excluded at this time.

Neil,
Take your Meds.

Chris Schoneveld says….
>>>>>>>>>>>>>
Lord Monckton has been known to take suggestions from the peanut gallery (us)

Chris4692 says: @ August 27, 2013 at 8:38 am
….The goal should be to get the science and analysis right, not score points in a contest.
>>>>>>>>>>>>>>>>>>
On that we agree, however when we try to bring up the science and discuss it we are shouted down as D*ni*rs and worse. So it is very nice to be able to refute those claims using their OWN WORDS and their OWN DATA. Not that we don’t still get the Zombie Effect.

Monckton I see you referenced an anonymous cooling forecast..Would you care to comment on the cooling forecast and the method used made in an earlier comment above(7:45) and supported in full at
http://climatesense.norpag.blogspot.com

Just Steve says: @ August 27, 2013 at 8:41 am….
Fredrick Weisberg as a decent reputation link Definitely a turn for the better.

sometimes, your Lordship, I really wish you would get off the fence and tell us what you really think 😉

cd says: @ August 27, 2013 at 9:36 am
just following orders.”
For God’s sake they’re typically math graduates that write computer code. They aren’t carrying out execution orders….
>>>>>>>>>>>>>>>>>>>>
Please tell that to the families of the thousands who died from the effect of hypothermia in the UK. Please tell that to the old people having to chose between eating and staying warm. Please tell that to the one in four families living in fuel poverty. Please tell that to the 22% unemployed in the USA who will never see their jobs come back while increasing costs of energy (and regulations) makes darn sure no new industry will chose the USA.
As long as these cowards continue to ‘defend’ their jobs they are contributors to the misery of others. I speak as someone who refused to ‘Go along to Get along’ with falsifying lab data and was fired and blackballed as a result. But at least I am not a ‘Lady MacBeth.’ However these people don’t even have her amount of conscience. They tell themselves any amount of lying is fine because it is ‘For the Cause’ so who cares about the thousands to millions who die as a result of the lies.

JimS says: August 27, 2013 at 9:54 am
@MattN
I think the only thing that will shut some of the CAGWers up is to have the Laurentide Glacier to start building up again over North America. Even then, warmists like Jim Hansen will blame CO2 for the glacier’s return.
________________
But, according to Hansen, burning more coal equals more soot, which in turn absorbs heat and MELTS glaciers, 🙂

“Yeah, right. So, forget the Pause, and welcome to the Gap:”
_______________
Love it. The Great Gap.

cd says:
August 27, 2013 at 9:36 am
“BTW the models, while rubbish at predicting the climate, have actually played an important part in moving scientific programming and numerical methods along.”
In what way? Granted they look awesome; you can create animations that look similar to a real planet. Otherwise? Chaos theory has moved maths forward (and explains why GCM’s fail so hard). But Chaos theory delivered its crushing verdict early in the 80ies. That would have been a good time to stop wasting billions with supercomputers; and instead think down and think. This time has been wasted – or; maybe the climate scientists would have found a way to cause even more harm, had we not payed them to play with their useless models.

JohnWho says:
August 27, 2013 at 6:33 am

“…most obvious culprit in temperature change here on Earth – the Sun.”

Yeah, right, as if the Sun was the primary source of heat for the planet or something.
Oh, wait…never mind.
Didn’t Willis once point out that even the reflected off the Moon heat from the Sun is noticeable? If such a small amount can be detected, what a great effect would be even a small change in the Sun?

Thanks, John. Actually, what I talked about was the “moon wind”, the wind that blow across the moon’s terminator line on earth. It is perceivable, but only in certain circumstance. In my opinion, the net effect on the climate, however, is far below the level of detectability.
w.

Richard M says:
August 27, 2013 at 5:51 am

Mr. Idiot, since the IPCC does not do any future predictions (according to Trenberth) why is it you expect Monckton to do something different? Maybe you should direct your energies to the IPCC or Trenberth.
The CO2 GHE was quoted about as 1.16C/doubling. I’ve seen many references to different numbers. If I use the following site to compute the increase of 3.7 w/m2 I get less that .8C (start at TOA/4 and add 3.7 to the power) . Does anyone have a reference to why these various numbers are different.
http://mc-computing.com/Science_Facts/Temperature_Conversions.html
Also, the CERES data that Willis referenced in his “spot” article shows that feedbacks are negative for most of the planet. This means whatever the impact of the CO2 GHE, the result will not be as high as the computed value.

Thanks, Richard. I showed that the relationship between albedo and temperature is positive for some of the earth, in particular many regions in the tropics … but not for most of the earth.
All the best,
w.

Wouldn’t it be good to get say ‘rgbatduke’ and ‘LordM’ perhaps one or two other ‘heavy hitters’ to spend a few days together to hammer out an agreed stance, then post the results here.
If we could get agreement amongst the logical, well spoken people, we may start to move the argument much further forwards….

Chris Schoneveld says:
August 27, 2013 at 8:32 am
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.

The catastrophic AGW wiggle watchers would always base their hysteria on RSS; that is until it also showed slower rises then stopped showing warming. Now when one of the ‘opposite camp’ uses RSS the wiggle watchers shout cherry picking?
This is yet another case of ‘projection’.