Guest Post by Dr. Nicola Scafetta
Herein, I would like to briefly present my latest publication that continues my research about the meaning of natural climatic cycles and their implication for climate changes:
Nicola Scafetta, “Testing an astronomically based decadal-scale empirical harmonic climate model versus the IPCC (2007) general circulation climate models” Journal of Atmospheric and Solar-Terrestrial Physics (2011).
http://www.sciencedirect.com/science/article/pii/S1364682611003385
Also, a booklet version (PDF) with this comment is here
The main results of this new paper are summarized in the paper’s highlights:
1) The IPCC (CMIP3) climate models fail in reproducing observed decadal and multidecadal limate cycles. 2) Equivalent cycles are found among the major oscillations of the solar system.
3) A correction for the projected anthropogenic warming for the 21st century is proposed.
4) A full empirical model is developed for forecasting climate change for a few decades since 2000.
5) The climate will likely stay steady until 2030/2040 and may warm by about 0.3-1.2 °C by 2100.
About our climate, is the science really settled, as nobody really believes but too many have said, and already implemented in computer climate models, the so-called general circulation models (GCMs)? Can we really trust the GCM projections for the 21st century?
These projections, summarized, by the IPCC in 2007, predict a significant warming of the planet unless drastic decisions about greenhouse gases emissions are taken, and perhaps it is already too late to fix the problem, people have being also told.
However, the scientific method requires that a physical model fulfills two simple conditions: it has to reconstruct and predict (or forecast) physical observations. Thus, it is perfectly legitimate in science to check whether the computer GCMs adopted by the IPCC fulfill the required scientific tests, that is whether these models reconstruct sufficiently well the 20th century global surface temperature and, consequently, whether these models can be truly trusted in their 21st century projections. If the answer is negative, it is perfectly legitimate to look for the missing mechanisms and/or for alternative methodologies.
One of the greatest difficulties in climate science, as I see it, is in the fact that we cannot test the reliability of a climate theory or computer model by controlled lab experiments, nor we can study other planets’ climate for comparison. How it could be easy to quantify the anthropogenic effect on climate if we could simply observe the climate on another planet identical to the Earth in everything by without humans! But we do not have this luxury.
Unfortunately, we can only test a climate theory or computer model against the available data, and when these data refer to a complex system, it is well known that an even apparently minor discrepancy between a model outcome and the data may reveal major physical problems.
In some of my previous papers, for example,
Scafetta (2011): http://www.sciencedirect.com/science/article/pii/S1364682611002872
Scafetta (2010): http://www.sciencedirect.com/science/article/pii/S1364682610001495
Loehle & Scafetta (2011): http://www.benthamscience.com/open/toascj/articles/V005/74TOASCJ.htm Mazzarella & Scafetta (2011): http://www.springerlink.com/content/f637064p57n45023/
we have argued that the global instrumental surface temperature records, which are available since 1850 with some confidence, suggest that the climate system is resonating and/or synchronized to numerous astronomical oscillations found in the solar activity, in the heliospheric oscillations due to planetary movements and in the lunar cycles.
The most prominent cycles that can be detected in the global surface temperature records have periods of about 9.1 year, 10-11 years, about 20 year and about 60 years. The 9.1 year cycle appears to be linked to a Soli/Lunar tidal cycles, as I also show in the paper, while the other three cycles appear to be solar/planetary cycles ultimately related to the orbits of Jupiter and Saturn. Other cycles, at all time scales, are present but ignored in the present paper.
The above four major periodicities can be easily detected in the temperature records with alternative power spectrum analysis methodologies, as the figure below shows:
figure 1
Similar decadal and multidecadal cycles have being observed in numerous climatic proxy models for centuries and millennia, as documented in the references of my papers, although the proxy models need to be studied with great care because of the large divergence from the temperature they may present.
The bottom figure highlights the existence of a 60-year cycle in the temperature (red) which becomes clearly visible once the warming trend is detrended from the data and the fast fluctuations are filtered out. The black curves are obtained with harmonic models at the decadal and multidecadal scale calibrated on two non-overlapping periods: 1850-1950 and 1950-2010, so that they can validate each other.
Although the chain of the actual physical mechanisms generating these cycles is still obscure, (I have argued in my previous papers that the available climatic data would suggest an astronomical modulation of the cloud cover that would induce small oscillations in the albedo that, consequently, would cause oscillations in the surface temperature also by modulating ocean oscillations), the detected cycles can surely be considered from a purely geometrical point of view as a description of the dynamical evolution of the climate system.
Evidently, the harmonic components of the climate dynamics can be empirically modeled without any detailed knowledge of the underlying physics in the same way as the ocean tides are currently reconstructed and predicted by means of simple harmonic constituents, as Lord Kelvin realized in the 19th century. Readers should realize that Kelvin’s tidal harmonic model is likely the only geophysical model that has been proven to have good predicting capabilities and has being implemented in tidal-predicting machines: for details see
http://en.wikipedia.org/wiki/Theory_of_tides#Harmonic_analysis
In my paper I implement the same Kelvin’s philosophical approach in two ways:
- by checking whether the GCMs adopted by the IPCC geometrically reproduce the detected global surface temperature cycles;
- and by checking whether a harmonic model may be proposed to forecast climate changes. A comparison between the two methodologies is also added in the paper.
I studied all available climate model simulations for the 20th century collected by the Program for Climate
Model Diagnosis and Intercomparison (PCMDI) mostly during the years 2005 and 2006, and this archived data constitutes phase 3 of the Coupled Model Intercomparison Project (CMIP3). That can be downloaded from http://climexp.knmi.nl/selectfield_co2.cgi?
The paper contains a large supplement file with pictures of all GCM runs and their comparison with the global surface temperature for example given by the Climatic Research Unit (HadCRUT3). I strongly invite people to give a look at the numerous figures in the supplement file to have a feeling about the real performance of these models in reconstructing the observed climate, which in my opinion is quite poor at all time scales.
In the figure below I just present the HadCRUT3 record against, for example, the average simulation of the GISS ModelE for the global surface temperature from 1880 to 2003 by using all forcings, which can be downloaded from http://data.giss.nasa.gov/modelE/transient/Rc_jt.1.11.html
figure 2
The comparison clearly emphasizes the strong discrepancy between the model simulation and the temperature data. Qualitatively similar discrepancies are found and are typical for all GCMs adopted by the IPCC.
In fact, despite a certain warming trend is reproduced in the model, which appears to agree with the observations, the model simulation clearly fail in reproducing the cyclical dynamics of the climate that presents an evident quasi 60-year cycle with peaks around 1880, 1940 and 2000. This pattern is further stressed by the synchronized 20-year temperature cycle.
The GISS ModelE model also presents huge volcano spikes that are quite difficult to observe in the temperature record. Indeed, in the supplement file I plot the GISS ModelE signature of the volcano forcing alone against the same signature obtained with two proposed empirical models that extract the volcano signature directly from the temperature data themselves.
figure 3
The figure clearly shows that the GISS ModelE computer model greatly overestimates the volcano cooling signature. The same is true for the other GCMs, as shown in the supplement file of the paper. This issue is quite important, as I will explain later. In fact, thee exists an attempt to reconstruct climate variations by stressing the climatic effect of the volcano aerosol, but the lack of strong volcano spikes in the temperature record suggest that the volcano effect is already overestimated.
In any case, the paper focuses on whether the GCMs adopted by the IPCC in 2007 reproduce the cyclical modulations observed in the temperature records. With a simple regression model based on the four cycles (about 9.1, 10, 20 and 60 year period) plus an upward trend, that can be geometrically captured by a quadratic fit of the temperature, in the paper I have proved that all GCMs adopted by the IPCC fail to geometrically reproduce the detected temperature cycles at both decadal and multidecadal scale.
figure 4
For example, the above figure depicts the regression model coefficients “a” (for the 60-year cycle) and “b” (for the 20 year cycle) as estimated for all IPCC GCMs runs which are simply numbered in the abscissa of the figure. Values of “a” and “b” close to 1 would indicate that the model simulation well reproduces the correspondent temperature cycle. As it is evident in the figure (and in the tables reported in the paper) all models fail the test quite macroscopically.
The conclusion is evident, simple and straightforward: all GCMs adopted by the IPCC fail in correctly reproducing the decadal and multidecadal dynamical modulation observed in the global surface temperature record, thus they do not reproduce the observed dynamics of the climate. Evidently, the “science is settled” claim is false. Indeed, the models are missing important physical mechanisms driving climate changes, which may also be still quite mysterious and which I believe to ultimately be astronomical induced, as better explained in my other papers.
But now, what can we do with this physical information?
It is important to realize that the “science is settled” claim is a necessary prerequisite for efficiently engineering any physical system with an analytical computer model, as the GCMs want to do for the climate system. If the science is not settled, however, such an engineering task is not efficient and theoretically impossible. For example, an engineer can not build a functional electric devise (a phone or a radio or a TV or a computer), or a bridge or an airplane if some of the necessary physical mechanisms were unknown. Engineering does not really work with a partial science, usually. In medicine, for example, nobody claims to cure people by using some kind of physiological GCM! And GCM computer modelers are essentially climate computer engineers more than climate scientists.
In theoretical science, however, people can attempt to overcome the above problem by using a different kind of models, the empirical/phenomenological ones., which have their own limits, but also numerous advantages. There is just the need to appropriately extracting and using the information contained in the data themselves to model the observed dynamics.
Well, in the paper I used the geometrical information deduced from the temperature data to do two things:
- I propose a correction of the proposed net anthropogenic warming effect on the climate
- I implement the above net anthropogenic warming effect in the harmonic model to produce an approximate forecast for the 21st century global surface temperature by assuming the same IPCC emission projections.
To solve the first point we need to adopt a subtle reasoning. In fact, it is not possible to directly solving the natural versus the anthropogenic component of the upward warming trend observed in the climate since 1850 (about 0.8 °C) by using the harmonic model calibrated on the same data because with 161 years of data at most a 60-year cycle can be well detected, but not longer cycles.
Indeed, what numerous papers have shown, including some of mine, for example
http://www.sciencedirect.com/science/article/pii/S1364682609002089 , is that this 1850-2010 upward warming trend can be part of a multi-secular/millenarian natural cycle, which was also responsible for the Roman warming period, the Dark Ages, the Medieval Warm Period and the Little Ica Age.
The following figure from Hulum et al. (2011), http://www.sciencedirect.com/science/article/pii/S0921818111001457 ,
figure 5
gives an idea of how these multi-secular/millenarian natural cycles may appear by attempting a reconstruction of a pluri-millennial record proxy model for the temperature in central Greenland.
However, an accurate modeling of the multi-secular/millenarian natural cycles is not currently possible. The frequencies, amplitudes and phases are not known with great precision because the proxy models of the temperature look quite different from each other. Essentially, for our study, we want only to use the real temperature data and these data start in 1850, which evidently is a too short record for extracting multi-secular/millenarian natural cycles.
To proceed I have adopted a strategy based on the 60-year cycle, which has been estimate to have amplitude of about 0.3 °C, as the first figure above shows.
To understand the reasoning a good start is the IPCC’s figures 9.5a and 9.5b which are particularly popular among the anthropogenic global warming (AGW) advocates: http://www.ipcc.ch/publications_and_data/ar4/wg1/en/figure-9-5.html
These two figures are reproduced below:
figure 6
The above figure b shows that without anthropogenic forcing, according to the IPCC, the climate had to cool from 1970 to 2000 by about 0.0-0.2 °C because of volcano activity. Only the addition of anthropogenic forcings (see figure a) could have produced the 0.5 °C warming observed from 1970 to 2000. Thus, from 1970 to 2000 anthropogenic forcings are claimed to have produced a warming of about 0.5-0.7 °C in 30 years. This warming is then extended in the IPCC GCMs’ projections for the 21st century with an anthropogenic warming trend of about 2.3 °C/century, as evident in the IPCC’s figure SPM5 shown below
figure 7
But our trust about this IPCC’s estimate of the anthropogenic warming effect is directly challenged by the failure of these GCMs in reproducing the 60-year natural modulation which is responsible for at least about 0.3 °C of warming from 1970 to 2000. Consequently, by taking into account this natural variability the net anthropogenic warming effect should not be above 0.2-0.4 °C from 1970 to 2000, instead of the IPCC claimed 0.5-0.7 °C.
This implies that the net anthropogenic warming effect must be reduced to a maximum within a range of 0.5-1.3 °C/century since 1970 to about 2050 by taking into account the same IPCC emission projections, as argued in the paper. In the paper this result is reached by taking also into account several possibilities including the fact that the volcano cooling is evidently overestimated in the GCMs, as we have seen above, and that part of the leftover warming from 1970 to 2000 could have still be due to other factors such as urban heat island and land use change.
At this point it is possible to attempt a full forecast of the climate since 2000 that is made of the four detected decadal and multidecadal cycles plus the corrected anthropogenic warming effect trending. The results are depicted in the figures below
figure 8
The figure shows a full climate forecast of my proposed empirical model, against the IPCC projections since 2000. It is evident that my proposed model agrees with the data much better than the IPCC projections, as also other tests present in the paper show.
My proposed model shows two curves: one is calibrated during the period 1850-1950 and the other is calibrated during the period 1950-2010. It is evident that the two curves equally well reconstruct the climate variability from 1850 to 2011 at the decadal /multidecadal scales, as the gray temperature smooth curve highlights, with an average error of just 0.05 °C.
The propose empirical model would suggest that the same IPCC projected anthropogenic emissions would imply a global warming by about 0.3–1.2 °C by 2100, in opposition to the IPCC 1.0–3.6 °C projected warming. My proposed estimate also excludes an additional possible cooling that may derived from the multi-secular/millennial cycle.
Some implicit evident consequences of this finding is that, for example, the ocean may rise quite less, let us say a third (about 5 inches/12.5 cm) by 2100, than what projected by the IPCC, and that we probably do not need to destroy our economy for attempting to reduce CO2 emissions.
Will my forecast curve work, hopefully, for at least a few decades? Well, my model is not a “oracle crystal ball”. As it happens for the ocean tides, numerous other natural cycles may be present in the climate system at all time scales and may produce interesting interference patterns and a complex dynamics. Other nonlinear factors may be present as well, and sudden events such as volcano eruptions can always disrupt the dynamical pattern for a while. So, the model can be surely improved.
Perhaps, the model I proposed in just another illusion, we do not know yet for sure. What can be done is to continue and improve our research and possibly add month after month new temperature dots to the graph to see how the proposed forecast performs, as depicted in the figure below:
figure 9
The above figure shows an updated graph than what published in the paper, where the temperature record in red stops in Oct/2011. The figure adds the Nov/2011 temperature value in blue color. The monthly temperature data are from http://www.cru.uea.ac.uk/cru/data/temperature/hadcrut3gl.txt
The empirical curve forecast (black curve made of the harmonic component plus the proposed corrected anthropogenic warming trend) looks in good agreement with the data up to now. Ok, it is just one month somebody may say, but indeed the depicted forecasting model started in Jan/2000!
By comparison, the figure shows in yellow the harmonic component alone made of the four cycles, which may be interpreted as a lower boundary for the natural variability, based on the same four cycles.
figure 10
In conclusion the empirical model proposed in the current paper is surely a simplified model that probably can be improved, but it already appears to greatly outperform all current GCMs adopted by the IPCC, such as the GISS ModelE. All of them fail in reconstructing the decadal and multidecadal cycles observed in the temperature records and have failed to properly forecast the steady global surface temperature observed since 2001.
It is evident that a climate model would be useful for any civil strategic purpose only if it is proved capable of predicting the climate evolution at least at a decadal/multidecadal scale. The traditional GCMs have failed up to now this goal, as shown in the paper.
The attempts of some of current climate modelers to explain and solve the failure of their GCMs in properly forecasting the approximate steady climate of the last 10 years are very unsatisfactory for any practical and theoretical purpose. In fact, some of the proposed solutions are: 1) a presumed underestimation of small volcano eruption cooling effects [Solomon et al., Science 2011] (while the GCM volcano effect is already evidently overestimated!), or 2) a hypothetical Chinese aerosol emission [Kaufmann et al., PNAS 2011](which, however, was likely decreasing since 2005!), or 3) a 10-year “red noise” unpredictable fluctuation of the climate system driven by an ocean heat content fluctuation [Meehl et al, NCC 2011] (that, however, in the model simulations would occur in 2055 and 2075!).
Apparently, these GCMs can “forecast” climate change only “a posteriori”, that is, for example, if we want to know what may happen with these GCMs from 2012 to 2020 we need first to wait the 2020 and then adjust the GCM model with ad-hoc physical explanations including even an appeal to an unpredictable “red-noise” fluctuation of the ocean heat content and flux system (occurring in the model in 2055 and 2075!) to attempt to explain the data during surface temperature hiatus periods that contradict the projected anthropogenic GHG warming!
Indeed, if this is the situation it is really impossible to forecast climate change for at least a few decades and the practical usefulness of these kind of GCMs is quite limited and potentially very misleading because the model can project a 10-year warming while then the “red-noise” dynamics of the climate system changes completely the projected pattern!
The fact is that the above ad-hoc explanations appear to be in conflict with dynamics of the climate system as evident since 1850. Indeed, this dynamics suggests a major multiple harmonic influence component on the climate with a likely astronomical origin (sun + moon + planets) although not yet fully understood in its physical mechanisms, that, as shown in the above figures, can apparently explain also the post 2000 climate quite satisfactorily (even by using my model calibrated from 1850 to 1950, that is more than 50 years before the observed temperature hiatus period since 2000!).
Perhaps, a new kind of climate models based, at least in part, on empirical reconstruction of the climate constructed on empirically detected natural cycles may indeed perform better, may have better predicting capabilities and, consequently, may be found to be more beneficial to the society than the current GCMs adopted by the IPCC.
So, is a kind of Copernican Revolution needed in climate change research, as Alan Carlin has also suggested? http://www.carlineconomics.com/archives/1456
I personally believe that there is an urgent necessity of investing more funding in scientific methodologies alternative to the traditional GCM approach and, in general, to invest more in pure climate science research than just in climate GCM engineering research as done until now on the false claim that there is no need in investing in pure science because the “science is already settled”.
About the other common AGW slogan according to which the current mainstream AGW climate science cannot be challenged because it has been based on the so-called “scientific consensus,” I would strongly suggest the reading of this post by Kevin Rice at the blog Catholibertarian entitled “On the dangerous naivety of uncritical acceptance of the scientific consensus”
It is a very educational and open-mind reading, in my opinion.
Nicola Scafetta, “Testing an astronomically based decadal-scale empirical harmonic climate model versus the IPCC (2007) general circulation climate models” Journal of Atmospheric and Solar-Terrestrial Physics (2011).
http://www.sciencedirect.com/science/article/pii/S1364682611003385
http://scienceandpublicpolicy.org/reprint/astronomical_harmonics_testing.html
Abstract:
We compare the performance of a recently proposed empirical climate model based on astronomical harmonics against all CMIP3 available general circulation climate models (GCM) used by the IPCC (2007) to interpret the 20th century global surface temperature. The proposed astronomical empirical climate model assumes that the climate is resonating with, or synchronized to a set of natural harmonics that, in previous works (Scafetta, 2010b, 2011b), have been associated to the solar system planetary motion, which is mostly determined by Jupiter and Saturn. We show that the GCMs fail to reproduce the major decadal and multidecadal oscillations found in the global surface temperature record from 1850 to 2011. On the contrary, the proposed harmonic model (which herein uses cycles with 9.1, 10–10.5, 20–21, 60–62 year periods) is found to well reconstruct the observed climate oscillations from 1850 to 2011, and it is shown to be able to forecast the climate oscillations from 1950 to 2011 using the data covering the period 1850–1950, and vice versa. The 9.1-year cycle is shown to be likely related to a decadal Soli/Lunar tidal oscillation, while the 10–10.5, 20–21 and 60–62 year cycles are synchronous to solar and heliospheric planetary oscillations. We show that the IPCC GCM’s claim that all warming observed from 1970 to 2000 has been anthropogenically induced is erroneous because of the GCM failure in reconstructing the quasi 20-year and 60-year climatic cycles. Finally, we show how the presence of these large natural cycles can be used to correct the IPCC projected anthropogenic warming trend for the 21st century. By combining this corrected trend with the natural cycles, we show that the temperature may not significantly increase during the next 30 years mostly because of the negative phase of the 60-year cycle. If multisecular natural cycles (which according to some authors have significantly contributed to the observed 1700–2010 warming and may contribute to an additional natural cooling by 2100) are ignored, the same IPCC projected anthropogenic emissions would imply a global warming by about 0.3–1.2 °C by 2100, contrary to the IPCC 1.0–3.6 °C projected warming. The results of this paper reinforce previous claims that the relevant physical mechanisms that explain the detected climatic cycles are still missing in the current GCMs and that climate variations at the multidecadal scales are astronomically induced and, in first approximation, can be forecast.
“I personally believe that there is an urgent necessity of investing more funding in scientific methodologies alternative to the traditional GCM approach and, in general, to invest more in pure climate science research than just in climate GCM engineering research as done until now on the false claim that there is no need in investing in pure science because the “science is already settled”.”
Bravo Nicola!
Start by funding these two guys
http://tallbloke.wordpress.com/2012/01/09/two-more-theories-relevant-to-the-unified-theory-of-climate-by-nikolov-and-zeller/
Excellent!
I never liked the GHG theory for many reasons not least the violations of the laws of thermodynamics but also the failure to follow observations which alarmists claim are a problem with the observations not the theory!
If all else fails then you need another theory and one that follows observed facts and physical laws.
Thank you Dr. Scafetta. I can only agree with your take on ignoring the inherent cyclic nature of climate as the IPCC and the CO2 hysterics do.
I don’t see why models that assume from the start that variation is due to internal oscillations are any more valid than models that assume from the start that CO2 is the primary driver.
It will take 500 years to add a longer cycle to this sequence but that’s ok – we have the time.
Personally, I’d add one more line to your Fig 9 – a dashed black line to show the “center” of the IPCC 2007 projection range. Makes it easier to see just how far off-center the observed temps are compared to their projection.
This thread is going to generate some good Connors/McEnroe ‘Correlation is not causation’ back-and-forths.
‘………….The 9.1-year cycle is shown to be likely related to a decadal Soli/Lunar tidal oscillation, while the 10–10.5, 20–21 and 60–62 year cycles are synchronous to solar and heliospheric planetary oscillations……..’
Talk about putting your cards on the table:
‘……..5) The climate will likely stay steady until 2030/2040 and may warm by about 0.3-1.2 °C by 2100……..’
Interesting stuff!!!!
Actually if you included the RSS and UAH latest data (0.03 and .12C for past 2 months) and R Spencer i now saying that there is a warm bias in his data. the above graphs would look awful to the AGW crowd. I peronally do not trust ANYTHING coming out of EAU.
Exceptionally well communicated by your numerous graphs.
What will it take to have your harmonic climate model and comparisons with temperature added to the Coupled Model Intercomparison Project (CMIP3)? http://climexp.knmi.nl/selectfield_co2.cgi
Most interesting article.
One of the ways of checking for periodic, or almost periodic signal is to do a spectral (Fourier) analysis. If used properly, it gives a great perspective to find underlying signals. Similar to the way 2-D multi-spectral imaging does for ancient documents.
Here are a couple of graphs using data from 14 of the longest temperature records available. Included in each is the spectral power (energy) density, All records start prior to 1800. They a averaged anomaly, that include Central England (1659), Debilt, Upsalla, Berlin, Prague, Paris, etc., most were from:
http://www.rimfrost.no/
The 1st is a 20 yr. low pass, while the 2nd has a 50 yr cut off:
http://www.4shared.com/photo/I04JY2jI/Ave14_2010_FF_20yr.html
http://www.4shared.com/photo/4FKXcwnw/Ave14_2010_FF_50yr.html
Here the periodic nature of the signals seem to be more present, then are shown in pure statistical methods, One of the better features is that it shows the end points better, then the MOV and some other techniques.
You might note the apparent plateau in more recent years.
The next figure:
http://www.4shared.com/photo/2foIw4k7/CRU-Fig-6a.html
is a comparison check, between the Fourier & EMD, using the CRU data, & how well the two different methods correlate.. ,
I have been using statistical curve fitting techniques on available “climate data” to identify the frequency and magnitude of these natural cycles. These cycles are the earths harmonic responses to external forces such as the radiation energy received from the sun. http://www.kidswincom.net/climate.pdf
Pattern recognition. Humanity would have died out long ago if we didn’t have the ability to recognize patterns in nature. To date, computers are way behind humans in this ability.
With the advent of Newton and computers, we have developed numerical prediction methods, which are basically a summation of countless small predictions that, by their nature, are MOSTLY correct. While the numerical prediction method has proven itself very valuable in some areas, it is useless in others, particularly complex, coupled, non-linear systems. In such systems, the tiny errors inherent in numerical prediction grow exponentially and soon render the solutions meaningless. In order to prevent this from happening in the climate models, the modelers must employ all kinds of governing assumptions that ultimately make any conclusion predetermined. There is no reason to waste the electricity to run the models. The assumptions allow only one answer. (And the modelers know this! They must. They can not be that ignorant.)
Over the last 50 years, atmospheric scientists have fallen so much in love with numerical prediction, they seem to have lost the ability to recognize its inherent limitations. They have also ignored pattern recognition, and how much more valuable it is than numerical prediction in complex, coupled, non-linear systems, like global climate.
Nicola Scafetta has employed a valuable method for predicting future climate. The IPCC has not. Is everyone at the IPCC ignorant, fooling themselves, or simply ignoring what they know to be true to fulfill their agenda? Once again…I can not believe that they are that ignorant.
What is the theory behind Saturn and Jupiter affecting our climate? This seems like a bit of a stretch in my, admittedly, uneducated mind.
Solar output, obviously, has a huge impact on our climate, but other than that, my suspicion is it’s just really a chaotic, variable, system. I suspect ocean currents are the biggest driver of major climate shifts.
Dr. Scafetta
Just looked through pdf booklet, it is an excellent presentation. I have just glanced through, so will need to read it. I found only one general reference to the AMO, which I happen to think is the most important oscillating factor in the temperature integral compilations, be it the global or the N. Hemisphere’s, leaving its cause aside.
I would make two technical points:
a) Any spectral analysis (periodogram) result which produces periods longer than 1/3 of the data-set’s time line, I would consider unreliable (this can be easily proved by analysing various lengths of the CET 350 year long record).
b) Spectral analysis I’ve done on the same climate data produced ‘similar’ results, but with different emphasis on the constituent frequencies. In addition if you superimposed the solar cycles’ spectrum (and the AMO’s) on the spectrum of the global temperatures, you might have found cause for some concern. I did search for such graph and couldn’t find one. I shall assume the omission is accidental not a deliberate one.
For benefit of the other blog readers, what I found is shown here:
http://www.vukcevic.talktalk.net/Spc.htm
I used hadcrut3 & crutem3 data, but there isn’t much difference to the GISS data, as far as the spectrum is concerned
I like the analogy of the Kelvin tide charts being useful for predicting tides despite the exact orbital
equations not being determined. This concept is a counter to the correlation is not causation crowd.
Only when IPCC scientists finally recognize natural forcings and associated harmonics will the AGW cult be stopped.
To those of us keeping an eye on natural indexes as opposed to aerosols from coal and co2 the big story now is not only the recent (post 1998) decline in global temps but the declining solar wind, the possibility of a triple La Nina, negative NAO and declining sea level rise. Declining sea level rise is a particular problem for the cult because it squeezes contributions from ice melt vs thermal expansion. The SOI index has recently spiked pointing to a stronger La Nina to come.
Great work for predicting the future which I think will follow the harmonic only yellow line if Climate sensitivity is as low as I believe.
Re
UnfrozenCavemanMD says:
January 9, 2012 at 6:38 am
I don’t see why models that assume from the start that variation is due to internal oscillations are any more valid than models that assume from the start that CO2 is the primary driver.
So you can’t see that the CO2 correlation doesn’t work at all then?
This is spot on. Nicola has done a great job !
A fit to HadCrut data using a 6o year, 11 and 9 year harmonics plus a logarithmic dependency on CO2 concentrations (using Mauna Loa data) gives the result
DT=-0.34+2.5ln(CO2(x)/290)+0.14sin(0.105(x-1860))-0.003sin(0.57(x-1867))-0.2sin(0.68(x-1879))
Then using the CEiSIN CO2 emission scenarios we can extrapolate forward Temperatures are unlikely to rise until 2025 before rising again by about 0.6 degrees for scenario B1 and 1.2 degrees for “business as usual” scenario A1B. These are less than half the IPCC predictions.
All this should be placed in context of the other new paper regarding offsetting cooling to a new Ice Age due to start in 1500 years time ! “Global warming caused by greenhouse gases delays natural patterns of glaciation, researchers say” .
more about the fit here : http://clivebest.com/blog/?p=2353
Dr. Scafetta: excellent work and very clear. The graphs really help. The point about different frequency components (9.1 years, 10-11, 20, 60 and longer) is central, of course. Lower frequency “beats” take longer to detect and characterize, since we need to (a) use standardized measuring tools and methods and (b) measure several cycles (the more, the better) to know what we’re looking at. So those long-running cycles will take a while to “see.” But even the shorter ones tell us a great deal. Thanks.
[Reply: snip-barycentric effect theories are a prohibited topic on this site. No whining or complaining of holdin’ down the oppressed. We are not going down this road. I’m back for a guest appearance only. Relish it. ~ctm]
@M.A.Vukcevic
Why is the spectrum analysis cut off at 16 years? Just curious as the 60-ish year signal is very strong, too.
[Reply: barycentric effect theories are a prohibited topic on this site. See above. Enjoy the ride. ~ctm]
Holy cow! I know enough about physics to expect the sun to have some wobble from the planets, but had no idea the giants could affect it so much from such a great distance!
“What is the theory behind Saturn and Jupiter affecting our climate? This seems like a bit of a stretch in my, admittedly, uneducated mind.”
A couple possible mechanisms: tidal effects on the sun, tidal effects on the interplanetary gasses.
As for the validity of the approach: isn’t this process what we used to simply refer to as “science”? He’s looking for a pattern in the data, and looking for a mathematical fit for that pattern. It would be nice to also have the underlying mechanism explained, but it’s not necessary — what matters is that it could be shown to be false, and that it have predictive ability. We had good models for acceleration, inertia, friction, and gravity long before we’ve had the complete processes worked out.
@Matt:
Matt says:
January 9, 2012 at 8:00 am
What is the theory behind Saturn and Jupiter affecting our climate? This seems like a bit of a stretch in my, admittedly, uneducated mind.
Solar output, obviously, has a huge impact on our climate, but other than that, my suspicion is it’s just really a chaotic, variable, system. I suspect ocean currents are the biggest driver of major climate shifts.
[Reply: snip–barycentric effect theories are a prohibited topic on this site. ~ctm]
“… and that part of the leftover warming from 1970 to 2000 could have still be due to other factors such as urban heat island and land use change.”
Yep!
This post is only a reply to George, since don’t whish to offend anyone’s sensitivity.
George says: January 9, 2012 at 8:58 am
@M.A.Vukcevic
Why is the spectrum analysis cut off at 16 years? Just curious as the 60-ish year signal is very strong, too.
It would not be ‘polite’ to rain on the Dr. Scafetta’s parade (I’ll leave it to our resident ‘60 year cycle sceptic maximums’, fortunately he is on his way to Japan), but since you ask, my results are here:
http://www.vukcevic.talktalk.net/Spectra.htm
You can draw your own conclusion (~70 looks as the dominant number).If you look at this article
http://berkeleyearth.org/pdf/berkeley-earth-santa-fe.pdf
(you may not whish to take it seriously, but it is your choice) at page 1/24 is a list of prominent scientists and on page 10/24 is their result (using totally different method), which appears to concur with my findings.
If you are going to model something then you need to start from someplace. It is always a guess based on limited empirical information. Numeric models seem to have an inherent ± error over time. Cycles are important in all this. Much of our local universe has a cyclical nature to it. Cycles are not however the answer. That is because nature tends not to have any “the answers” in it. When it comes to cycles any geologist is knowledgeable. Were it not for cycles most of what us seismologists would be out of business. We just need to keep in focus the objective, purpose and limitations of what we do or wish to do.
„The proposed astronomical empirical climate model assumes that the
climate is resonating with, or synchronized to a set of natural harmonics that, in previous works have been associated to the solar system planetary motion, which is mostly determined by Jupiter and Saturn. We show that the GCMs fail to reproduce the major decadal and multidecadal oscillations found in the global surface temperature record from 1850 to 2011. On the contrary, the proposed harmonic model (which herein uses cycles with 9.1, 10–10.5, 20–21, 60–62 year periods) is found to well reconstruct the observed climate oscillations from 1850 to 2011, and it is shown to be able to forecast the climate oscillations from 1950 to 2011 using the data covering the period 1850–1950, and vice versa. The 9.1-year cycle is shown to be likely related to a decadal Soli/Lunar tidal oscillation, while the 10–10.5, 20–21 and 60–62 year cycles are synchronous to solar and heliospheric planetary oscillations.“
Astronomy is the science of the lawof the (moving) stars. J. Kepler has found some laws and from this it is well known that each heliocentric path of a moving star is elliptical. This means that the velocity of a moving star in respect to the Sun is not constant. This becomes important in synodic motions. The term ‘natural harmonics’ in the context with the given time periods suggest a physics of overtones of resonating modes. But because it is not correct to claim here an astronomical (synchronous) model, and because there is no resonance from the moving stars shown, it is a loud shot in the dark. I see no scientific worth in some empiric math gymnastic, claiming a better simulation then GCMs.
I have shown several times here that if one takes the real heliocentric (astronomical true) path of corresponding (11) couples from Mercury to Quaoar the sum of their synodic tide functions correlates well with the known temperature proxies in high time resolution (month) for two and more millennia back in time.
See graph 1, graph 2, graph 3, graph 4, graph 5, and graph 6. Graph 6 includes sea level oscillations for the last three years.
V.
However, the scientific method requires that a physical model fulfills two simple conditions: it has to reconstruct and predict (or forecast) physical observations.
When is “mainstream” Climate Science ever going to satisfy either condition? The answer is, “never”. Because mainstream Climate Science not only is not adhering to the principles and practices of real science, it is intentionally avoiding them as a necessary component of its own “method”. The empirical reality of real science is of absolutely no concern to mainstream Climate Science.
There could be influences from Jupiter and Saturn, but I think it is unlikely. Tidal forces from the great planets at the Earth are just tiny. More likely, IMHO, is that the correlation is coincidental.
Physical systems do not require cyclical forcing to get cyclical behavior. Every bounded system has some set of natural modes of oscillation, e.g., the natural frequency of a spring due to its stiffness and load. Such cyclical behavior can be induced by purely random forcing.
To predict future behavior optimally, one could formulate a Kalman filter, with an internal model of the oscillations driven by white noise, initialize the states by running it backwards and forwards over the measurements, and then propagate the model open loop forward in time. The Kalman filter equations would also simultaneously produce the error bars for the prediction.
BS alert. Saturn? Jupiter? Ha, ha, ha. That’s a good one.
What a wonderful prediction. Until 2035, the predicted temperature variations wiggle conveniently around 0 temperature difference from today. We won’t be able to tell whether this model is a load of crap until 2050. Except we can already tell. Cyclical effects probably do affect climate. Whether they come from Saturn or Jupiter or something else with the same or similar periodicity, a physical model needs to provide a mechanism of action. Tidal forces from Jupiter affecting the Earth or the Sun? Good luck selling that one. And as we all know, with enough parameters, you can fit any curve.
I vote for the Copernican Revolution, or is it Revelation?
Ape to Man
Speach to Language
Gods to God
Langauge to Writing
Mythology to Astronomy
Flat Earth to Round Earth
Earth Centric to Sun Centric
Astronomy to Physics
Writing to Printing
God to Evolution
Oligarchy to Democracy
Physics to Engineering
Poverty to Economy
Engineering to Science (You are here)
Science to Understanding
Understanding to Prosperity
Nicola,
I think the comparison of GISS with the measured trend after Pinatubo would provide more useful information if the effects of ENSO on short term temperature were first removed from the data. For example, the lagged (3-6 months?) Nino3.4 index correlates strongly with short term temperature changes. When this type of adjustment is applied tot eh temperature data, the Pinatubo effect in 1992, 1993, and 1994 should be somewhat stronger (especially in 1992), and a bit closer to the GISS model trend. Of course, that doesn’t prove the GISS model is correct, since the modeled trend seems due to a combination of overstated ocean heat uptake (known to be incorrect) and an almost certainly overstated sensitivity to forcing. A combination of lower sensitivity and lower ocean heat uptake fits the same data reasonably well.
Engineering is perfectly happy to construct something based solely on purely empirical models that happen to have solid, reproducible, accurate & precise predictive power.
Note, for instance, the complete lack of proof of a ‘graviton’ and the plentiful roller coasters. Engineers didn’t need more than F=ma and a couple of tests to see “Hey, what’s ‘a’ for gravity here?” The fact that later theoretical developments led to the universal gravitation constant G didn’t suddenly break the earlier roller coasters. The fact that there’s currently a swath of ‘plausible theories’ for why we even have gravity is is irrelevant – and will continue to be so even if we do nail one down.
If you study early physicists (Galileo, Newton, etc.) they’re often finding -empirical- models themselves. “Well, I rolled the ball down the incline, here’s a formula that fits the data, and I call this factor here …” Then later consolidating years of data into coherent theories. That is: theory doesn’t -always- lead experimentation.
There is certainly a 60 year cycle evident in the temperature record of the last 130 years – but isn’t this supposed to be due to ocean oscillations? I assume that the down arrows on figure 1 are supposed to indicate the 9.1 year cycle as well. One or two misses but not a bad match. As for the ‘black curves’ they seem to have changed colour to blue and green.
It is an interesting conjecture that this is due to the orbits of Jupiter and Saturn, but it.is not supported in any way by this post. It seems a very unlikely explanation but I might have been interested if some rationale had been presented, instead of just an unsubstantiated assertion.Since it wasn’t, I am inclined to dismiss this as another unsupported, wild hypothesis.
“[Figure 8] shows a full climate forecast of my proposed empirical model, against the IPCC projections since 2000. It is evident that my proposed model agrees with the data much better than the IPCC projections”
Yes, but the IPCC projection was made in 2000, your forecast was made in 2012 and so , unsurprisingly, it makes a better forecast from 2000 to 2011. I can also make very accurate ‘retrospective’ predictions. I just wish I could make all my gambling predictions with the benefit of hindsight.
So, lets see how the future prediction goes – and if by any chance it is close – then perhaps Dr, Nicola Scafetta can explain what this has to do with the orbit of Saturn. Until then, I won’t hold my breath.
Dr Scafetta – As you state clearly, you still have the problem that you are operating with cycles of up to ~60 years based on a timeframe of only ~150 years. It’s not enough for any reasonable degree of certainty – but as you are not claiming any, there is at least a good basis for discussion.
My feeling is that you have successfully demonstrated that the IPCC models are close to useless and that the best predictive models we have are cycle-based like yours, but I would argue that until we understand the mechanisms behind the cycles, including those longer than ~60 years, we cannot predict anything with any confidence.
Have you tested your method against the CET? That gives you an extra 200 years. I would suggest that the appropriate way to do that would be to start with the same periods 1850-1950 and 1950-2010, do the same curve-fitting, and then calculate the whole 1650-2011 period and see how it compares.
A potential problem for any prediction is that the sun appears to be undergoing a major change which is outside of any up-to-60-year cycles.
Those cycles and their good fit don’t matter because they’re off-message:
There is no urban heat island effect and solar variance is neglibible,
so the science remains settled: Doomsday is nigh,
CO2 is ultra-powerful, and only world dictatorship can save us.
If it’s not in Nature Climate Change it can’t be real.
Hoser says:
January 9, 2012 at 10:32 am
… a physical model needs to provide a mechanism of action.
There is a general 5:2 resonance between the main frequency of Jupiter of 2.672082 nHz and the main frequency of Saturn of 1.068498 nHz. It seems that this ‘mechanism’ is free of action for million of years, and it is called therefore Perpetuum mobile. As we know from the shift of angular momentum from the (system) Earth to the Moon, there is no loss in angular momentum.
From this a physical model is different to the perpetual motion of Jupiter and Saturn. A physical model has a cause and a effect. A perpetual motion not.
Tidal forces from Jupiter affecting the Earth or the Sun? >
Slowly. It is evident that a rough analysis of short global temperature spectra shows tide frequencies of the synodic couple Jupiter/Earth, superimposed by the couples Mercury/Earth, Venus/Earth and Mercury/Jupiter. Phase coherent to this pattern is the main oscillation of the sea level:
http://www.volker-doormann.org/images/sealevel_vs_abcd.gif .
The logic is to explain why the sea level oscillation and the global temperature oscillation is phase coherent to heliocentric functions of Jupiter, Earth, Venus and Mercury.
The logic is not to ignore this fact because physicians believe it is in contradiction to their handbooks about action.
V.
Mike Jonas says:
January 9, 2012 at 11:56 am
…………..
I did test with CET, it contradicts the above article not only on 60y but on the long term prediction. Results are here:
http://www.vukcevic.talktalk.net/Spectra.htm
http://www.vukcevic.talktalk.net/CET-NVa.htm
>>
For benefit of the other blog readers, what I found is shown here:
http://www.vukcevic.talktalk.net/Spc.htm
I used hadcrut3 & crutem3 data, but there isn’t much difference to the GISS data, as far as the spectrum is concerned
>>
I would suggest you look at the “adjustment” that is made between the original ICOADS data in producing hadSST3. The adjustment is that is taken out is effectively a very large 60y sinusoidal. It seems that they have removed this period as being an error. Try doing your frequency analysis with less fabricated datasets and see how things compare.
richcar 1225 says:
January 9, 2012 at 8:23 am
>>
I like the analogy of the Kelvin tide charts being useful for predicting tides despite the exact orbital
equations not being determined.
>>
Yes, the fact that we still rely totally on empirical cycle analysis to predict tides (and it works to an amazingly high degree of reliability) is something that I only discovered recently.
I think this is a very strong argument for adopting this kind of method in analysis of another chaotic system that we are totally failing to model from first principals: climate.
I would like to thank Antony for the post, and the interested readers of this blog.
I will try to respond some of the comments:
@ tallbloke. January 9, 2012 at 6:18 am
I hope that everything is going fine for you. Let us hope that there will be some funding around, if not, we will ask Antony to start a fundraising project too for us
@ David L. Hagen January 9, 2012 at 7:34 am
I do not know what can be done to add my model to the list of the Coupled Model Intercomparison Project. We can try to add one temperature dot every month and publish updates to see how the fings work out.
@ Jim Clarke January 9, 2012 at 7:58 am
I do agree with the importance of pattern recognition strategy. One should never forget to look at the data if we want to do science!
@ Vukcevic January 9, 2012 at 8:15 am
As I explained to you many times, you never listen apparently, the CET record is not easy to analyze. It is a very local record and local records may not have the same patterns than the global ones. Moreover, when you analyze longer local sequences such as CET other factors may influence the records beginning from volcano activity to instrumental failure. Power spectra technique are very sensitive to everything, so you need to be careful. For example, have you taken off the volcano signal from the CET before your spectral analysis?
You need to read my references in addition to my other papers.
Try this one, for example
http://dcm2.enr.state.nc.us/slr/Jevrejeva_et_al_2008.pdf
look at the 60-year oscillation in Figure 3b.
Or look here
http://www.vliz.be/imisdocs/publications/218039.pdf
figure 5.
The above two papers, together with numerous other references, also answer the doubts of the other readers about the fact that the instrumental temperature records I am studying cover only 160 years. A 60-year cycle is indeed seen in several proxy models for centuries and millennia (not on all possible proxy model one may think). People just need to read the references.
Another paper is
Mazzarella and N. Scafetta, “Evidences for a quasi 60-year North Atlantic Oscillation since 1700 and its meaning for global climate change,” Theor. Appl. Climatol., DOI 10.1007/s00704-011-0499-4 (2011).
http://www.fel.duke.edu/~scafetta/pdf/Mazzarella-%20Scafetta-60-yr.pdf
Moreover, when yo study longer records, other cycles start to appear. So the calculations must be done carefully.
Other peoples have doubts about my conjecture that the oscillations are astronomically induced. Their argument is that a clear mechanism is not proposed. Fine.
However, science does not start with the statement “we know already everything.” We discover something and something else remains unknown. The list is long.
In the ancient times almost everybody knew that the ocean tides were somehow linked to the moon, but people did not know about the gravitation theory of Newton.
I believe that on this topic, some of the fundamental mechanisms of climate change are still unknown, so what! I am try to show that empirical evidences exists to support the theory.
The purpose of the paper is to show that the climate appears much better reconstructed assuming the existence of planetary forcing regulated by known astronomical frequencies. In the future the issue may be further clarified.
The cycles will be there even if the astronomical theory is found wrong. In any case, at the moment, interested readers may give a look at my other two major publications on this issue for further evidences.
N. Scafetta, “A shared frequency set between the historical mid-latitude aurora records and the global surface temperature” Journal of Atmospheric and Solar-Terrestrial Physics 74, 145-163 (2011). DOI: 10.1016/j.jastp.2011.10.013.
http://www.fel.duke.edu/~scafetta/pdf/Scafetta_models_comparison_ATP.pdf
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
http://www.fel.duke.edu/~scafetta/pdf/scafetta-JSTP2.pdf
“One of the greatest difficulties in climate science, as I see it, is in the fact that we cannot test the reliability of a climate theory or computer model by controlled lab experiments, nor we can study other planets’ climate for comparison. How it could be easy to quantify the anthropogenic effect on climate if we could simply observe the climate on another planet identical to the Earth in everything by without humans! But we do not have this luxury.”
This is nonsense. We do not need to do lab experiments and we certainly do not need another Earth for experimental purposes. Even if we had another Earth we have nothing approaching a comprehensive theory of climate which is what we would be testing.
Earth’s climate changes are an ongoing experiment that require only observation. We will know what causes changes in cloud behavior and the effects of those changes as soon as we have the will to invest in the instruments necessary to give us reliable and detailed information about what is important for climate in those changes. Implicit in my last claim is that some brilliant climate scientists must come up with some physical hypotheses about cloud behavior that are worthy of empirical investigation; at this time, there are no such physical hypotheses. The beginning of knowledge is recognition of our ignorance. In the arena of science, failure to recognize our ignorance has never failed to lead to delusion.
“Although the chain of the actual physical mechanisms generating these cycles is still obscure, (I have argued in my previous papers that the available climatic data would suggest an astronomical modulation of the cloud cover that would induce small oscillations in the albedo that, consequently, would cause oscillations in the surface temperature also by modulating ocean oscillations), the detected cycles can surely be considered from a purely geometrical point of view as a description of the dynamical evolution of the climate system.”
“The detected cycles can surely be considered from a purely geometrical point of view…”
Yeah, they make pretty geometric patterns. That is as far as the geometrical point of view takes you. Put the pretty patterns on a graph of climate phenomena and they are still just pretty patterns.
“…as a description of…”
What does a circle describe? A point? A sine curve? None of them describe anything. To claim that they can describe the “dynamical evolution of the climate system” is totally without meaning.
More to come if I have time.
@ Theo Goodwin says: “…..”
If I will be able to understand what you are trying to say, I too will also try to give a response.
Dr. Scafetta
Thanks for your extensive answer. To the contrary, there is high correlation between the CET and global temperatures, spectrum and trend-wise:
http://www.vukcevic.talktalk.net/Spectra.htm
P. Solar
There are 3 data sets for globa l(Land & Ocean) temperature, there are hardly any perceptible differences in the anomaly trends between the three.
http://www.vukcevic.talktalk.net/L&O.gif
We have to accept data as available, unless you have a dataset which is substantially different to the above, I conclude that your comment is not valid.
@ Vukcevic
“Thanks for your extensive answer. To the contrary, there is high correlation between the CET and global temperatures, spectrum and trend-wise”
during which period?
On a recent thread here @WUWT, Leif made the following observation. Wondering if what he is saying collides with the conclusions presented here. The last sentence in particular.
‘………………………………………………
Leif Svalgaard says:
January 5, 2012 at 6:01 pm
meemoe_uk says:
January 5, 2012 at 5:34 pm
Leif : “What the proxies show is that there isn’t a link”
The exact opposite is true. The proxies evidence a direct link between SSN and Earth climate.
Then it is time to put the temperature on the plot as well. Now it should be clear that there is no correlation; e.g. look at the deepest minimum of all the past 200 years around 650AD: http://www.leif.org/research/Temperature-vs-10Be-14C.png
Most readers of this blog believe this and can see it in your charts.
Most readers suffer from confirmation bias: to see what they want to see and ignore what doesn’t fit. This is a normal human affliction. You should know it well.
Why do you think an anti-AGW blog is so focused on solar activity?
beats me. The AGW people NEED solar activity to explain LIA, MWP, and even the rise in the 20th century until ~1950, e.g. http://www.atmos.washington.edu/2009Q1/111/Readings/Lockwood2007_Recent_oppositely_directed_trends.pdf
“There are many interesting palaeoclimate studies that suggest that solar variability had an influence on pre-industrial climate. There are also some detection–attribution studies using global climate models that suggest there was a detectable influence of solar variability in the first half of the twentieth century and that the solar radiative forcing variations were amplified by some mechanism that is, as yet, unknown. However, these findings are not relevant to any debates about modern climate change. Our results show that the observed rapid rise in global mean temperatures seen after 1985 cannot be ascribed to solar variability, whichever of the mechanisms is invoked and no matter how much the solar variation is amplified”
They are the biggest fans of solar activity. If I may speculate, I might say that anti-AGW cult desperately need a mechanism, any mechanism [even astrology], to counter the AGW cult who has a mechanism……………………………………….’
Thank you.
V.
Well done Nicola, you’ve been doing some good work for some time now.
I wish you every success.
For those who doubt that Jupiter Saturn and Neptune (even Uranus) can have an effect on solar motions ought to try the Olympic sport of hammer throwing.
A mere 7.2kgs at the end of a 1.2mtr long chain swung around and around will really shift you off your feet.
Now thinking about the Sun swinging all these “heavy” planets at the end of a very very long chain and it’s not hard to see the profound effects on the suns motion around its centre.
I believe it’s called CENTRIPETAL Force
johnnythelowery says:
“Leif’s comments are no sense. Leif believes the solar activity is essentially flat with no backgroud variation. So, his comments derive from his own belief.”
The problem is that Leif is not able to explain anything with his opinions and he stresses only the opinions of the people that would support his prejudices without checking their validity.
For example he references Lockwood 2007 work claiming that there exists an opposite trend between temperatre and solaractivity by using PMOD total solar irradiance model, but Leif does not refences ACRIM works
http://www.acrim.com/
that shows on the contrary the existence of such common trend.
Nor Leif references my on works such as therecent
N. Scafetta, “Total Solar Irradiance Satellite Composites and their Phenomenological Effect on Climate,” chapter 12, pag 289-316. (In “Evidence-Based Climate Science, Elsevier) (2011).
http://www.fel.duke.edu/~scafetta/pdf/Scafetta-easterbrook.pdf
that shows some fatal problems of the PMOD solar model.
Leif, unfortunately, is only biased.
Nicola Scafetta says:
during which period?
Dr. Scafetta
I thought it was clear from the graphs I linked:
http://www.vukcevic.talktalk.net/Spectra.htm
– First graph: there is no obvious 60 year component in the Global, Northern Hemisphere, CET and LOD (2 CET periods show problems of a short data set, where apparently single component is dissolved into three distinct CET periods of 55, 70 and 90 years). Eye balling 60 years from a chart is not sufficient if the spectrum shows it as 70.
Also see: http://berkeleyearth.org/pdf/berkeley-earth-santa-fe.pdf page 10.
– Second graph (to the left) shows on visual inspection good agreement between the CET and the Global temps for period 1880-2010; the 2011 CET is now second highest on the record http://www.vukcevic.talktalk.net/CET2011.htm
– The visual inspection is not sufficient, thus correlation graph to the far right, with convincing R^2=0.7.
All the references to 60 year cycle are no good unless it shows in spectral analysis of one of the major data sets.
Dr Scafetta, no one would be happier than myself, if it can be shown that the climate oscillations are driven by the Jupiter-Saturn link, which appears to drive the sunspot cycles, since the extrapolation of equation (I formulated in 2003 using the Jupiter/Saturn orbital properties) for the SC24, has proven to be (up to date) the most accurate sunspot cycle prediction tool:
http://www.vukcevic.talktalk.net/NFC7a.htm
I am an engineer by profession, I did travel along the ‘60 year path’, but if I can’t find either 11 or 60 year cycle in the temperature numbers then unfortunately that is that, the end of my story, but you are welcome to continue your narrative, I whish you luck.
Dr. Scafetta, could you please provide a dowmload site/source to retrieve the data points from the output of your calculation? I and I’m sure others would like to look at the results in more detail.
@ M.A.Vukcevic says:
I am sorry, but I have a very strong impression that you never look at the references, nor you read my papers. You continuously simply repeat again and again your point referencing the CET record which is a complex records and it is not appropriate for the analysis without a deailed study.
Ok, let us try again,let us talk about only one case for simplicity. Look here
http://www.vliz.be/imisdocs/publications/218039.pdf
look figure 5.
Describe me exctly what that figure shows, so we know that you gave a look at it. Note that figure is made of multiple figures. I am asking you to describe with precision what each of those figures show.
If you give me the impression that you are looking at the figures, we can try to analyze another paper.
@ BarryW
Model Diagnosis and Intercomparison (PCMDI) mostly during the years 2005 and 2006, and this archived data constitutes phase 3 of the Coupled Model Intercomparison Project (CMIP3). That can be downloaded from
http://climexp.knmi.nl/selectfield_co2.cgi?
The monthly temperature data are from http://www.cru.uea.ac.uk/cru/data/temperature/hadcrut3gl.txt
Re. Fig 5.
It is not exactly clear what you whish to prove with it, there is a hotchpotch of periods there; proxy dating of any kind (excluding natural annual growth e.g. tree rings or coral) has large margins (for 2k years back could be as +- 25 or more years due to particle diffusion process).
On basis of Fig. 5, in the industry I spend some decades, you wouldn’t get a look in, not to mention a budget for evaluating, let alone construction of a project.
The blue circle denotes the spectral peak for the instrumental AMO record, false assertion; the AMO was discovered in 1990s and reconstructed back from incomplete sea surface temperatures back to 1950s. Only numbers after 1970 can be considered to be reliable. As for prior to 1950 I wouldn’t put my shirt on it, relevant papers:
Corrections to Pre-1941 SST Measurements for Studies of Long-Term Changes in SSTs, Jones et al
http://icoads.noaa.gov/Boulder/Boulder.Jones.pdf
Assessing bias corrections in historical sea surface temperature using a climate model, Folland
ftp://ftp.wmo.int/Documents/PublicWeb/amp/mmop/documents/JCOMM-TR/J-TR-13-Marine-Climatology/REV1/joc1171.pdf
Reassessing biases and other uncertainties in sea surface temperature observations, Kennedy et al
ftp://ftp.astr.ucl.ac.be/publi/2011_08_03-08h24-hugues.goosse-14.pdf
Nicola Scafetta says:
January 9, 2012 at 1:27 pm
“@ Theo Goodwin says: “…..”
If I will be able to understand what you are trying to say, I too will also try to give a response.”
You begin with the following:
“However, the scientific method requires that a physical model fulfills two simple conditions: it has to reconstruct and predict (or forecast) physical observations. Thus, it is perfectly legitimate in science to check whether the computer GCMs adopted by the IPCC fulfill the required scientific tests, that is whether these models reconstruct sufficiently well the 20th century global surface temperature and, consequently, whether these models can be truly trusted in their 21st century projections. If the answer is negative, it is perfectly legitimate to look for the missing mechanisms and/or for alternative methodologies.”
Models cannot be used to predict anything. You, like the vast majority of climate scientists today, show that you are ignorant of the differences between models and theories. Theories can be used for prediction but models serve only to reproduce (reconstruct, in your terms) reality. Now, how can you predict anything from a reconstruction of reality? To get right to the point without taking the time to be polite, and I beg your pardon, what you are doing is extrapolating lines on past graphs into lines on graphs about the future. That is not a recipe for science, though it is not without value.
My time is extremely limited so I have copied here some comments of mine from Andrew Montford’s website. I hope they clarify for you the differences between models and theories. Also, I hope that they make clear that the well confirmed physical hypotheses that make up theories are essential to science while models are really wonderful analytic tools but secondary to the scientific enterprise. I recommend that you read the entire post (not by me) and comments at Montford’s website.
http://bishophill.squarespace.com/blog/2012/1/4/conveying-truth.html?currentPage=3#comments
“Thanks for your question. A little terminology will clarify the matter. Newton’s theory is a physical theory and its several hypotheses are well confirmed as it applies to our solar system. Of course it does not provide the detail or reach of Einstein’s theory but it does just fine in our solar system.
Our solar system is a model of Newton’s equations. A model is a set of objects that renders true all the individual statements in a physical theory. One can construct computer models of Newton’s theory. Some company sells an “observatory” that will project our solar system on the semicircular ceiling that you have constructed just for this purpose and it will predict and postdict planetary movement and such. A model that does prediction and postdiction can exist because of Newton’s theory. In other words, the programmers actually used Newton’s equations to calculate where all the shiny little dots should appear on the ceiling in the future or past as you dial-up one time or another.
The climate scientists who are creating GCMs, models of Earth’s climate, have no set of physical hypotheses that play the role of Newton’s equations in our little observatory. All they have are Arrhenius’s equations and a lot of data about climate. Arrhenius’ equations have never been rigorously formulated for the actual Earth. So they are not well confirmed in Earth’s atmosphere. No less important, everyone knows, as Arrhenius knew, that Arrhenius’ equations are not enough to explain or predict Earth’s climate. In addition, you need the physical hypotheses that govern all the so-called “feedbacks” such as cloud behavior. These physical hypotheses do not exist in any form that could be considered well confirmed. Much empirical research must be done before they can exist.
As for the data, models contain wonderful differential equations that manipulate the data in wonderful ways; however, all of that data manipulation is nothing more than a sophisticated method of extrapolating the future from existing graphs. That is not science. That is a system of hunches.
I hope you now understand the difference between theories and models. Theories describe the natural regularities that make up nature while models reproduce the objects or events that are nature. It is not possible to make predictions from a model. If you had the perfect model of Earth’s climate all you would have is Earth’s climate. How can you make predictions from that?”
Jan 5, 2012 at 6:59 PM | Theo Goodwin
What follows contains a more complete description of physical hypotheses and their absolutely essential role at the heart of science and scientific method. It is also from Montford’s blog.
“You have failed to grasp the difference between physical hypotheses and models. Physical hypotheses describe natural regularities. The key word here is “describe.” Physical hypotheses are about some aspect of physical reality and the true or really well confirmed physical hypotheses (which make up mature theories, eventually) tell us what that reality is.The key word here is “about.” The physical hypotheses are creations of intellect that stand apart from reality and tell us about reality, tell us what reality is.
By contrast, models produce simulations that reproduce some salient features of reality. Simulations do not describe reality and are not about reality and, for those reasons, simulations are neither true nor false. Simulations are complete or not. They give an exact reproduction of reality or they fail as simulations to some degree. Simulations are not creations of intellect; rather, the computer code that generates them is a creation of intellect. However, the computer code does not describe reality and is not about reality. In sum, the value of a simulation depends entirely on whether and to what degree it reproduces reality. Why would you think that a reproduction of reality can be used to predict reality?
Physical hypotheses bear an important logical relationship to the reality that they describe. When combined with statements of initial conditions specifying observable fact, they logically imply observation sentences about future events. These observation sentences are what logicians call “instances” of the natural regularities described by the physical hypotheses. A record of predictions found true make physical hypotheses well confirmed and make for them a place in science. Note the centrality of “natural regularities.” The purpose of science is to discover the natural regularities that comprise nature.
By contrast, can you specify some logical relationship that exists between reality and a model and its simulations? You cannot because there is none. That is why the usefulness of models in science is limited to analytical work such as discovering hidden assumptions.
Models cannot substitute for well confirmed physical hypotheses. The point is not based on temporary or practical considerations but on the very logic of the two structures.”
Jan 6, 2012 at 4:40 AM | Theo Goodwin
Typo alert! “Guest Post by Dr, Nicola Scafetta” should have a period after the “Dr,” not a comma. One of the few useful contributions my liberal arts education permits me on this science heavy forum.
[Your education paid dividends. Typo fixed. ~dbs, mod.]
@Theo Goodwin,
Unfortunately I do not understand how your philosophical essay fits my study.
You say : “Models cannot be used to predict anything. ”
I do not agree. In science models are always used to try to predict something. If they succeed or not and at what degree it is another thing that can be tested with analysis of the data.
@ M.A.Vukcevic says:
“Re. Fig 5.
It is not exactly clear what you whish to prove with it, there is a hotchpotch of periods there; proxy dating of any kind (excluding natural annual growth e.g. tree rings or coral) has large margins (for 2k years back could be as +- 25 or more years due to particle diffusion process).”
You just proved me that when I ask you to look at some data you are not able to do it. So, there is no reason for me to try to explain you things.
@johnnythelowery says:
January 9, 2012 at 1:48 pm
What if the Loehle reconstruction is very poor through the 7th century:
http://wattsupwiththat.com/2012/01/04/solar-cycle-update-sunspots-down-ap-index-way-down/#comment-856954
Dr. Scafetta, Your modeling shows a continuous increasing trend to 2100.
I’m curious; If the model continues:
Does it ever reach a maximum?
Does it model the larger climate minima and maxima over a 2000 year time scale?
Can it make any predictions for the next ice age?
Ugh! This is exhausting.
[Reply: snip–yes it is, barycentric effect theories are a prohibited topic on this site. ~ctm]
@ Greg Cavanagh says: “…..”
the upward trend is based on the same emission scenarios of the IPCC. They stop in 2100 as the model. After 2100 the model scenario show a platoo. So also my model will stabilize.
However, my model may work for a few decads because on longer scales other longer cycles, not included in the model, will be important.
An excellent article. I would add that Prof Claes Johnson has now proved that there can be no warming of the surface by backradiation, so the greenhouse effect is a non-event which you don’t need to allow for.
I also wondered what you think of the inverted plot of the sum of the scalar angular momentum of the Sun and 9 planets as here: http://earth-climate.com/planetcycles.jpg
Nicola: Thank you for your response. Interesting posting.
Dr. Scafetta “However, my model may work for a few decades because on longer scales other longer cycles, not included in the model, will be important.”
My thinking exactly. The longer time scale “ups and downs” could make your 2100 estimate somewhat more inaccurate than is useful. Though your modelling shows obvious usefulness in the shorter timescales.
Personally; I like the empirical approaches to future estimates, much more than the first principle approach. I like your work.
Doug Cotton says: “….”
it is an interesting graph.
The longer cycles are the most difficult to determine.
But I am trying to develop an extended model
On the barycenter:
From various comments, here and in other threads, it appears that some believe that the position of the barycenter matters. It does not. No real physical effect can depend upon the position of the barycenter. The reason is simple. The barycenter is not real. It is a mathematical abstraction. There is no mass at the barycenter. It is not a source of gravitational attraction, torque , magnetic fields of anything else. It is simply the origin of a particular coordinate system designed to make solving for the motions of the planets easier. No physical property can ever depend upon the choice of coordinate system, as coordinate systems are mathematical inventions, not real objects.
To show that it can have no effect I will use a reductio ad absurdum. Imagine including the next nearest star system in your equations – the Centauri system, which has three components that we know about with a combined mass more than twice that of our sun. Although it would make the maths more difficult, you could solve the equations of motion for the positions of our star, the planets and the elements of the Centauri system. And guess what – you would get exactly the same answers for the relative motions of our star and planets, despite the fact that for the combined system the barycenter would be roughly 3 light-years away.
[Reply: thanks, but even dismissals will be limited as they spawn further replies ~ ctm]
…..so, I think it’s all going to kick off on this thread. Generally, when Leif issues a rebuff: It tends to leave it’s target………well,…………..in the Buff really. I think i’ll get the beers and pop corn in for this one!
UnfrozenCavemanMD says:
January 9, 2012 at 6:38 am
I don’t see why models that assume from the start that variation is due to internal oscillations are any more valid
Because linear relationships in Nature have long since been eliminated by time. Only cyclical relationships survive billions of years. Thus looking to model nature with as a linear functions is not going to be accurate.
Bart says:
January 9, 2012 at 10:23 am
There could be influences from Jupiter and Saturn, but I think it is unlikely. Tidal forces from the great planets at the Earth are just tiny. More likely, IMHO, is that the correlation is coincidental.
The solar system moves in near integer harmonics. The tidal forces are tiny yet the odds of this being due to chance are fantastic. We like to think we know the secrets of the universe. We have only scratched the surface.
The force of a child on a swing is tiny, yet the result is large. However, if you only watched the child when they first got on the swing, you would never guess what was going to happen. Without having seen a swing, you would guess the child might rock back and forth an inch or two, according to their puny motions.
The missing ingredient in our view of reality is time. We fail to see this because our lives are so short. Over time, a drop of water over time will cut a mountain in half.
Unless I misread this, the training period was from 1850 to 1950.
Results look pretty good from that.
Physical models as I recall are trained to present day.
Modelling from incomplete physics is always going to fail, empiricism rules.
This doesn’t change my view that there is no meaningful Global average temperature.
DaveE.
tallbloke says:
January 9, 2012 at 6:18 am
Start by funding these two guys
http://tallbloke.wordpress.com/2012/01/09/two-more-theories-relevant-to-the-unified-theory-of-climate-by-nikolov-and-zeller/
Gore made use of his time as VP to ensure only those folks on the AGW bandwagon would have a say in allocating research funds. Then he invested in AGW. A generation of science was lost as a result.
CTM re the snip: My bad. I didn’t know that topic was off-limits. Having done a little more reading, I think I see why it’s a dead end.
Dr. Scafetta, I take very little notice, don’t waste my time and don’t take for granted little ‘pretty pictures’ wherever they come from. I only take interest only if I can reproduce it from data myself, as many of visitors of this blog know via many graphs I originated and presented. Call it whatever you whish, many were and are happy with what Dr. Mann said about his ‘hockey stick’ graph without question.
Dr. Scafetta
here is something I just put up on another WUWT thread you should have a good look
http://www.vukcevic.talktalk.net/CET-SW.htm
Notice the common components at 22 years (solar magnetic -Hale cycle, btw not much if anything at 11 years) and around 70 years, but also the non-sync ones at 55 for summer and ~90 for winter, disappointingly there is nothing at 60 years. Disapproving of the longest and most accurate world temperature record (the CET) doesn’t do much for credibility.
Bart makes a good point when he says that you don’t need cyclic forcings to get cyclic behaviour. The 9, 10, 20 and 60 year cycles could just be natural frequencies of the complex system that is our climate and they’ll appear with any random forcing. So trying to correlate with orbits of far-away planets might actually not be relevant.
The problem is with forecasting on the basis of these 4 oscillations, is that these natural frequencies can shift and/or or change in magnitude. Figure 1 shows another cycle of approximately 14 year, which is not a lot smaller than the 10 year cycle. Maybe it was larger than the 10 year peak at some time?
It would be interesting to see how these peaks vary over time, e.g. with a wavelet transform.
Vukcevic,
you really seems a broken disk. You continuously refer to CET record ignoring all my explanation.
Did you take off the volcano signal first? Have you compared CET records with the other records we have? Have you adjusted the analysis by taking into account influences from other phenomena that could disrupt the record?
Do you want to understand that CET record is a local record referring to a square of a 200 hundred miles of length that is a microscopic percentage of the global surface?
Have you read my papers?
For example:
A. Mazzarella and N. Scafetta, “Evidences for a quasi 60-year North Atlantic Oscillation since 1700 and its meaning for global climate change,” Theor. Appl. Climatol., DOI 10.1007/s00704-011-0499-4 (2011).
N. Scafetta, “A shared frequency set between the historical mid-latitude aurora records and the global surface temperature” Journal of Atmospheric and Solar-Terrestrial Physics 74, 145-163 (2011). DOI: 10.1016/j.jastp.2011.10.013.
Did you look at the numerous references my paper contains? you were not even able to see just one reference I added above.
Ok, let us try again, let us talk about only one case for simplicity. Look here
http://www.vliz.be/imisdocs/publications/218039.pdf
look at figure 5.
Describe me exctly what that figure shows, so we know that you gave a look at it. Note that figure is made of multiple figures. I am asking you to describe with precision what each of those figures show.
If you give me the impression that you are looking at the figures, we can try to analyze another paper.
Dr. Scafetta
1. I think you may be missing an important point: for good long term temperature study you need good long term record, and the CET is the longest and the most reliable. Further more it is next door to the AMO which is the most influential factor, at least for the period or the reliable global temperatures instrumental records:
http://www.vukcevic.talktalk.net/GT-AMO.htm
Global temperature is just a bit more than a carbon copy of the North Atlantic SST (the AMO) and there are good reasons for that.
So my advice is get to know CET, get to know North Atlantic, the rest comes naturally.
2. Paleo “proxies” as tree rings, ice cores, sediments, coral reefs etc, are only direction pointers and not reliable numerical references, hence I do not waist to much time on that.
3. You should find some conciliation in a short note at the end of the web page:
http://www.vukcevic.talktalk.net/CET-SW.htm
stating: There is strong 22 year component, coinciding with the Solar magnetic (Hale) cycle, which is not used in the reconstruction. It can be noted that the substantial drop in temperatures (2020-2050) predicted by the extrapolation is in a good agreement with a similar drop in the solar magnetic activity as obtained by extrapolation of totally different and unrelated equation
http://www.vukcevic.talktalk.net/NFC7a.htm
I leave you to consider the numbers in the equation related to the Hale cycle graph of the sun’s polar magnetic field, which is an excellent precursor to the following SS cycle.
Analysing another paper? No thanks, I work to a different time table
Its time for me to move on.
Good luck.
@Vukcevic, “I think you may be missing an important point: for good long term temperature study you need good long term record, and the CET is the longest and the most reliable. ”
Actually, that is not true. You may be interested in this work (among my references that you refuse to read)
Camuffo, D., et al., 2010.
500-year temperature reconstruction in the Mediterranean Basin by means of documentary data and instrumental observations.
Climatic Change 101, 169–199.
http://www.springerlink.com/content/q36j5713138wt30p
Here there is a claim of a quasi 60-year cycle in the temperature records since 1650.
You may also be interested in reading this (free) book
http://lyubushin.hotbox.ru/Climate_Changes_and_Fish_Productivity.pdf
Theo Goodwin said @ January 9, 2012 at 3:32 pm
Models are used to predict things all the time. Planetariums are models of the solar system for example and are used to predict the future positions of the planets relative to each other.
Newton had no Theory of Gravitation and categorically refused to provide one. Newton showed that there was a mathematical equation linking the motions of the planets and every other body with mass. This is Newton’s Law of Gravity and is used to construct planetariums. Neither of the two competing theories of gravitation (quantum/relativity) have any relevance for building planetariums (models).
A hypothesis is a provisional theory. It must accord with known facts, and serves as a starting-point for further investigation by which a theory may be arrived at. A theory is a system of ideas or statements held as an explanation of a group of facts or phenomena. A Hypothesis that has been corroborated by observation or experiment, and is accepted as accounting for the known facts is a Theory. In current philosophy of science the latter distinction has little importance. While theories can be falsified, few believe they can be proved. Using Popper’s terminology, hypotheses and theories are both conjectures.
Nicola, your modelling looks interesting. The proof of the pudding will be in the eating 🙂
Nicola Scafetta said @ January 10, 2012 at 10:34 am
Nicola, I get a 404 on this.
It goes to show that chaos is not the observed disorder of things, it is the lack (disorder) of knowledge about the observed order of things. Facts do not confer wisdom, but it is wisdom that discovers the context of the facts.
Doctor Scafetta, there is also a millennial scale that needs to be added to your harmonic, that of Earth’s Obliquity. Observing the graphs for the Ice Ages and Obliquity, one thing stands out: The average length of an ice age event is 100k years, that average is composed of 80k and 120k events. While the earth does not exit an Ice Age every 41k years according to the obliquity cycle when it achieves it’s maximum angle of >24 degrees, over the 10 recorded Ice Age events, EVERY TIME WITHOUT FAIL as obliquity drops below 23.5% an Ice Age STARTS. We are now below 23.5 degrees of obliquity. Superimpose figure 5 with the Earth’s obliquity and then recalculate using this trend in your figure 9 for more accurate results.
Theo Goodwin says:
January 9, 2012 at 1:19 pm
“”What does a circle describe? A point? A sine curve? None of them describe anything. To claim that they can describe the “dynamical evolution of the climate system” is totally without meaning.””
For a look at how well the solar/lunar cycle repeats at the ~18 year period, click link below, scroll down to the forecast maps for the 31 of January of this year 2012. where the comparison between the composite forecast map and the four maps of the temperatures from the past periods can be checked for similarities between cycles over time.
http://tallbloke.wordpress.com/aerology-forecast-verfication/
Thank you very much Dr. Scafetta,
Very interesting article. The way I read it, your model does not foresee much of a global cooling continuing for much longer or going much more cooler from 2001.
I hope you are right!
@ thepompousgit says: “….”
do not click on the link (for some reason it does not work)
http://lyubushin.hotbox.ru/Climate_Changes_and_Fish_Productivity.pdf
you need to copy and past the link in the browser.
@ dscott says:
“It goes to show that chaos is not the observed disorder of things, it is the lack (disorder) of knowledge about the observed order of things.”
that is an interesting sentence 🙂
The linear trend plus sinusoids plus noise model is so simplistic that the success of any prediction based on it will be more a matter of luck than of scientific skill. Aside from the tides, geophysical variables are almost never strictly periodic; chaotic randomness is the general rule. What makes reliance on harmonic components highly precarious here is that even Scafetta’s analyses do not show the sharp spectral peaks characteristic of narrow-band processes, which might be usefully approximated over short prediction horizons by pure sinusoids. The situation calls for proper predictive filters rather than curve fitting.
Nicola Scafetta sayid @ January 10, 2012 at 6:51 pm
Thanks 🙂
Shannon — Information Theory. Very interesting…
Dr Scafetta,
I recently posted a highly relevant article on Lucia’s site here:
http://rankexploits.com/musings/2011/noisy-blue-ocean-blue-suede-shoes-and-agw-attribution/
It considers the inversion of the temperature series (Hadcrut3 used in the aericle) to the input flux forcings i.e. the flux required to give us the exact reproduction of the temperature series, using in this instance the same assumed sensitivity as the GISS-ER model.
Decomposition of the resulting flux data reveals the very low frequency component to be a smooth convex curve over the entire instrument series. This is not compatible with your assuming a quadratic fit for the very low frequency component (periodicity > 60 years) in the temperature series in history, since this translates into a straight line in the flux data. Nor is it compatible with your extrapolation of the very low frequency component using a linear extrapolation, since this translates into a constant value in the flux data.
In fact, it is readily shown that the statistics of temperature fit obtained using the abstracted flux curve are superior to your assumption of a quadratic in temperature/straight line in flux.
I really do urge you to read the article. It should not only improve your historical fit, but also potentially offers firmer ground on which to base your prognosis.
@ Paul_K says:
January 10, 2012 at 9:27 pm
Paul, the quadratic curve is just a geometrical way to captures the temperature trending from 1850 to 2000. There is nothing wrong in using it. It is just a first+second order approximation of the trending. As esplained in the paper many times, the quadratic trending is not part of the physical model. About the linear trending, that is what the IPCC does. So, I use the same approximation.
You need to read carefully my paper to understand the reasoning.
If other observables are used instead of the temperature the geometry may appear different, of course. It is always good to start using simple models, then it is possible to search for an improvement of the models.
Interesting article. One question. Why do the initial (1850) temperature anomolies differ so significantly from your initial temperature anomolies in the lower part of figure 1?
@Pterostyrax says:
the quality of the temperature data decreases as we go back in time. So, as you go back in time the record become more noisy.
This ca be see more easily in this my publication, figure 4
http://www.fel.duke.edu/~scafetta/pdf/PRE26303.pdf
There has been published another comment here, people may be interested to read:
http://www.forbes.com/sites/larrybell/2012/01/10/global-warming-no-natural-predictable-climate-change/
Dr. Scafetta,
I have published an article on my page “Climate Change (“Global Warming”?) – The cyclic nature of Earth’s climate” quoting the abstract of your paper “Testing an Astronomically Based Decadal-Scale Empirical Harmonic Climate Model vs. the IPCC (2007) General Circulation Climate Models” at http://www.oarval.org/ClimateChange.htm (Spanish at http://www.oarval.org/CambioClima.htm).
I hope you approve of it. If you have any comments, please let me know.
Andres, thank you
nice web-page with a lot of information!
Re: quadratic interpolation… one of the most interersting adaptive equalization methods I have seen is based on negentropy, approximated by squaring the kurtosis (fourth order), an eighth order equation. Interestingly, under proper conditions, the result collapses to a second order equation known as a “minimum output energy” solution. In general, the mechanism is referred to as independent component analysis, a stricter cousin of principal component analysis, i.e. the same PCA that mann the physics dropout made infamous.
Mark
For those interested, there will be a post on my blog soon which deals with part of the topic.
I understand why Anthony doesn’t want the subject discussed here, no matter well established it is in the scientific literature. To quote Ivanka Charvatova:
“I represent our institute in the Czech National Climate Programme. These people “research” only greenhouse effect vs temperatures. I call them “heaters”. Sometimes I feel like a lone Hussite warrior – myself against all. They deny the existence of solar influence on climate let alone the influence of the whole solar system. Most of them refuse to talk to me, most of them even do not say hello, when we meet. Even now when many world journals publish articles about the influence of the Sun on climate. Probably this requires more time. Many discoveries had to wait, some very long. I do not waste my time fighting windmills. God will sort it out when the right time comes.”
http://tallbloke.wordpress.com/2011/06/10/interview-with-ivanka-charvatova-is-climate-change-caused-by-solar-inertial-motion/
Dr. Scafetta, good work, good article abstract with resulting conclusions…..
It explains well the stepwise shape of GMT: Planetary (Jupiter and Saturn) oscillations as
physical 3-body-problem with Jup+Sat as 3.body gravitation force pulling/pushing the
real Earth’s trajectory further/closer to the Sun (less/more RF)……
……as you point out: “The actual physical mechanism…..of cycles is still obscure…”
But, analyzing the planetary (now its time for the planet Earth) oscillation (or Libration:
see Wikipedia: animated picture for the Moon), [other terms: perturbation, ligation, osculatio]
we will detect further RF (radiative forcing)…..and be on the bottom of this “Copernican approach…”
I hope I will have my paper ready by May/June on the subject and will send you then an authors
copy…..
JS
Nicola: I don’t know if you are there still or if you’ll see this. But I was wondering what your first thoughts, off the top of your head, are regarding this thought. I was impressed with Brian Cox’s ‘Wonders of the Solar Sytem’. What stuck in my head was his visit to the Iguazu (sp?) River. He stated that the river (level or flow rate??) tracks sunspots. He stated that there was no known connection. I discussed it here @ WUWT and asked Lief why this was not interesting. He said correlation is not causation. While the Iguazu does, many or nearly all rivers, including the Amazon don’t. Made sense to me…but……why does the Iguazu track Sunspots. I puzzled it but dropped it but often wondered about this. It would have to be an anomaly that only affected that particular feeder area of the Iguazu. What on earth could it be? So i’m sitting, minding my own business watching a youtube clip below. It seems that, the Hubble was having trouble with a couple of instruments….but only over Brazil/Argentina (..or in the ‘neck of the woods of the Iguazu). NASA gave this patch which affected their instruments a name: .the Sourth Atlantic Anomaly. To prevent this, Nasa switched off the instruments while Hubble flew through the South Atlantic Anomaly. So, perhaps, the phenomenon driving the Iguazu is as much to do with the Sun as it is the local oddities in earth’s magntic field. Here is the clip. The part relevant to the above is @ 00.43 and from then on. Thx..
I would like to read this paper carefully, but the impression I get if I understand the bits I read is that the author is just finding patterns of the oscillatory nature and then suggesting those patterns will hold and can be used to predict the future. The question here is, specifically for the 60 year cycle case, how many previous 60 year cycles has he analyzed since we have only had at most 3 such cycles of quasi decent temperature measurements. [I’m am only going back at most into the middle 1800s since such a cycle obviously is not very large in amplitude and would disappear in the error bars of the proxy reconstructions that go further back.] This study is interesting as a way to help zoom in on possible physics we might not yet be clearly aware of, but until you identify the physics, you won’t get far in any scientific community. .. Anyway, I haven’t read the posting or the paper yet.
…Another concern I have (prior to reading the material beyond a piece of the introduction.. and judging by a random comment I read) is that the IPCC models are perhaps being attacked for not meeting at every pixel, yet that is not necessary if you stay within error bounds. I am not saying the current climate computer models can stand no improvements. I’m saying that I can come up with “an infinite” number of curves (eg, by hand or using a computer if I want to get fancy) that come closer than any given model yet be absolutely incorrect about the future. I can draw a line right through the average of the current temps and then after 2012 do 5 loop the loops and end with a dive towards 0K before I even get to 2100. The possibilities are limitless! As for predictions based on cycle analysis. We can use the stock market as an example. Since when does cycle analysis predict the stock market? It doesn’t. [Of course, man has a much greater say over market prices than we do over earth surface temps.] Remember that we didn’t get to the moon or create modern technology via models that extent historical cyclic patterns blindly to the actual physics going on. We progress because of improved understanding of the physics. .. Anyway, despite what I just said, I can imagine how a paper on this topic might make a good contribution to climate science.
I have a lot of the paper to read, but I have skimmed enough to be critical of their methods and conclusions.
The predictably rising CO2 (greenhouse effect) contribution to temperature does not show up in a pure cyclical (harmonic) analysis. This paper does more than harmonic analysis, but the coefficients derived from the harmonic parts can get thrown off to the extent the superimposed trends don’t fit the data well. I haven’t done the math yet, but it’s possible this skewing effect cancels out some or all of what the authors’ believe the IPCC incorrectly included in their projections. Instead, this analysis can easily end up attributing to a cyclical pattern what is more appropriately a part of a growing non-cyclical trend that might have in fact been properly identified by the IPCC.
The full analysis in this paper also includes two “trend” components that are superimposed on the cycles, a linear and a quadratic trend. Without at least these functions, their analysis would not work since, as covered extensively in the literature, the temperatures from 1850 to 2000 have had an upwards, non-cyclical trend due to CO2 greenhouse effect. Essentially, the authors used a quadratic function to simulate the upward trend from 1850 to 2000, and then, convenient to their thesis, assume that from 2000 onward, the trend no longer has a quadratically increasing component but devine it will simply have a linear component.
In conclusion (for now), the authors recognized you needed a function that grows faster than linear in order to properly capture the trend from 1850 – 2000, but then decide the future temperatures of the planet will no longer have such a quadratic trend and instead merely have a linear trend. Why the authors change gears like this is a detail I hope to discover as I read the paper. If the authors don’t provide a solid physical explanation for why we should no longer expect to see the observed quadratic trend we have been seeing since 1850 and instead expect no more than a linear trend after 2000, the paper would appear to fall flat on its face (at least as concerns its conclusions that climate sensitivity should be about 1/3 what the IPCC predicts). For those who want to explore this, check out in particular the definition of q(t) as defined on page 10, eqns 9 and 10.
THe UPWARD going linear warming trend (1850-2000) cannot be explained with Scafetta, but the
cyclic shape of the upward trend…..
The upward going trend has to be added to Scafetta, see Literature on German Amazon.de
ISBN 978-3-86805-604-4, which starts at the bottom of the LIA (1650) and culminates
by year 2000 into the temp plateau of the 21. Cty…… BUT this NOT linearly, but in cycle steps,
(Scafetta achievement) which have an astronomical cause (3-body-gravitation-taking Saturn/Jupiter into account)….
In order to assess the full message/causes of global warming/climate change, you need
both literatures together….. which complement each other…
JS
Joachim Seifert>> THe UPWARD going linear warming trend (1850-2000)
In this paper, in contrast to a paper he co-authored published earlier last year (which I recently glanced at after downloading from a different website), Scafetta did not use a linear trend for the 1850-2000 period but used instead a quadratic trend. See this via eqn 10 on page 10 and eqn 4 on page 6 [the formal paper starts of page 19 of the pdf linked on the top blog posting].
Let me add:
Scafetta then switched to a linear trend for the 2000-2100 prediction period. This is shown in eqn 10 and eqn 9. [Note that p(2000) is a constant value not a quadratic function.]
Had the paper stayed with the same exact quadratic trend that fit the 1850-2000 period, the temperature value at 2100 would have been (.000049*(250)^2-.0035*250-.3)-(.000049*(150)^2-.0035*150-.3) = (1.89)-(.28) = 1.61 C higher. According to his chart, Fig 5 on page 11, this would put his 2100 projection mean, not at about 1.15 but at about 2.75.
I am not sure how this 2100 projection compares with 2xCO2 and climate sensitivity (which is defined as an ideal value representing 2xCO2 @ equilibrium.. which would be a number higher than the temp on the date 2xCO2 is first achieved), but I think those figures are in the ballpark.. putting climate sensitivity not too far from 3.
I think Scafetta’s reasoning for switching over abruptly to a linear trend from 2000 onward is: “Thus, the above estimated 1.30 C/century anthropogenic warming trending is likely an upper limit estimate. As a lower limit we can reasonably assume the 0.66 +/- 16 C/century, as estimated in Loehle and Scafetta (2011).”
If Scafetta is right that the warming trend will be linear in growth as he estimated from 2000 to 2100, then the 2100 temp projection is probably a decent one, at least if the assumption stated at the beginning of the paper holds, that the climate goes through natural cycles of fixed durations and amplitudes [note the constant C_1 and C_2 values of eqn 3, constant C_3 and C_4 values of eqn 7, and the constant periods of all of those cosines]. However, if the trends continue roughly as he modeled from the 1850-2000 period, then his projections for 2100 were about 1.6 C on the low side.
I think this sort of analysis is interesting and can provide insight and probably a first guess estimate, but it is not based on physics.
Jose X: Scafettas paper explains very well the influence of the astronomic 3-body-gravitation
cycles which result in a STEPWISE (flat-steep-flat-steep) form of the climate (60-20-40 year)
cycles also given in a recent paper of Akasofu, S.-I: “On the recovery from the LIttle Ice Age”
in Natural Science 2 p 1211-1224 …..where ” Earth’s recovery from the LIA proceeded with a
roughly 0.5 C/century recovery rate in a LINEAR manner…… the reason and the calculation for this recovery see my booklet, as pointed out before…..
Scafetta/s analysis does the following, quote Akasofu: Focusses on modulation of multidecadal
oscillations of 50-60 years superimposed on the recovery trend….and from which we can see
causation of halting of warming after 2000….
In short: Scafetta analyzes only the superimposed trend……
This occurs on top of the linearly mannered recovery trend- which he just takes as a fact without
cause analysis from 3 to 4 cycles since 1850……
Therefore, his superimposed trend and the recovery trend from me as joint analysis would
provide you the whole picture…..You cannot blame Scafetta, for not having integrated the full
recovery analysis……but do not worry, there are more months ahead and you will get it later
in the year…..
JS
>> Had the paper stayed with the same exact quadratic trend that fit the 1850-2000 period, the temperature value at 2100 would have been (.000049*(250)^2-.0035*250-.3)-(.000049*(150)^2-.0035*150-.3) = (1.89)-(.28) = 1.61 C higher. According to his chart, Fig 5 on page 11, this would put his 2100 projection mean, not at about 1.15 but at about 2.75.
Oops, that is wrong. I did part of the calculation in my head and forgot to consider it when I wrote the comment.
The projections would change by 1.61 – q(2100) = 1.61 – .9 = .71
So the overall projections would not be +1.15 C but instead be about +1.85 C. This would imply, I am guesstimating, that climate sensitivity probably is in the 2.xx range closer to 2.5 than to the IPCC 2xCO2 mean value of 3. However, I am not sure of this analysis.. which is rather rough and doesn’t correspond to a 2xCO2 analysis [the paper just tries to guess at year 2100 temp values not at climate sensitivity].
If the number of words and the number of posts won arguments, Jose_X would be the world champ.
But he’s not. The planet disagrees with Jose_X. Which one should we believe?
Joachim Seifert, finding patterns gives us clues to what we should be analyzing. I like that about this research from Scafetta and others.
I am assuming Scafetta has not analyzed the forces from Jupiter and Saturn to see what effect they might have on Earth low frequency (climate) ocean up/downwelling cycles or anything like that. I think any accurate patterns discovered offer very interesting clues that may help us improve climate physics in the future and give further insight into climate phenomenons (like ENSO). [I am ignorant of a lot of ocean/heat physics, so maybe someone with more knowledge would dismiss these patterns as pure correlation among many possible patterns.]
I would guess that the cycle periods (and eqns) calculated in this paper can probably be used by some GCMs (as short-cuts) to increase the resolution of their forecasting/projections to less than 30 years and with tighter error bounds.
Do you have a link to a paper or book I can download and read for free? I don’t think I will be buying ISBN 978-3-86805-604-4. I try to limit my research reading to free material only.
The booklet is only 15 US$, thus a fraction of paywalled papers…. It also contains
108 pages with 95 % original knowledge, not repeating other secondary sources; further,
over 30 graphs explain the content and context well…. I believe you could do without
German…. in case of questions email : weltklima (at) Gmail.com
I promise, the trail is good…..you will see….what we need are trails which lead
to rock solid climate analysis and reliable forecasts….
……which cannot be done based on AGW nonsense….the AGW-trails lead into nowhere land…
…clear by now, not only to skeptics….
Cheers
JS
Smokey, should I repeat again that you need to take a stand with math instead of jumping to any pattern you think you have found? What physics/math basis do you offer that in your eyes suggests that a small downward trend in temperature is inconsistent with rising CO2? We have had many several year trends that were flat or slightly negative in the past 40 year period, during which time the overall trend has been clearly positive (don’t cherry pick years, start at a nice round number like a multiple of 5 or 10). You may want to read again the examples I gave here …..????[*] of how CO2 is not the only driver of temperature (I think Scarfetta would agree soundly with this). When you have many drivers, the car sort of oscillates. The pictures you provided do not “disagree with Jose_X.”
BTW, I noticed a link I hadn’t seen (the second one). If you change the scale on either the CO2 or the temperature, you can get each of their trend lines to “visually” almost overlap. Next time provide math/physics relationship so we can test if the visual smoke actually comes with fire.
[*]I just noticed that my last comment from yesterday on the Monckton/potholer thread was not posted on WUWT. I’ll try reposting it.
Joachim Seifert>> Scafettas paper explains very well the influence of the astronomic 3-body-gravitation
Can you tell me on which page the physics analysis of Jupiter’s and Saturn’s effects on Earth begins?
For the astronomical part, his calculations are called the “Harmonic model” which indicates the
astronomical connection…..it has to do with gravitation of Jup/Sat as 3rd body (besides Erth and Sun) and with the Sun motion’s in its proper barycenter….too bad, you joined this post somehow late, because Scafetta now will not read is (I assume)…. he answered questions once the post
began….
Find out more on your own…
JS
Jose_X says:
“The pictures you provided do not ‘disagree with Jose_X.’ ”
Sorry, I mis-typed. Let me state it correctly: “The planet’s actions falsify Jose_X.”
There. Fixed it for you. Now everyone can see that CO2 is not worth worrying about.
And FYI, charts are more effective than math, which most readers skip over. That’s why I provide visual aids: people can see who is telling the truth, with a glance at a chart, and who is trying to deceive the public with the evidence-free fake CAGW scam [that would include “Jose_X”, among others.]
Joachim Seifert, I agree with your recent comment that this paper does better coverage of the cycles than of the trends.
Paper doesn’t appear to do physics analysis of cyclical trends:
I don’t think however that the cycles analysis and patterns found with the planets (the details of which I haven’t yet read) includes any significant physics analysis. The paper carried out curve-fitting and pattern correlation. This isn’t deriving an effect from physical principles.
Patterns we observe in the past fail to hold in the future all the time. This is why we need to find a physics explanation in order to create a solid foundation. Finding a pattern correlation with movement of major nearby planets is interesting of course, but it isn’t the same thing as adding a physics foundation. We’d have to analyze gravity effects from those planets on fluid/heat motions on the earth. If we can’t do this, we have little confidence that the patterns found with the planets are anything but a correlation that may not hold for long or be but a pure coincidence among the many patterns that exist in the sky.
60 yr might already be include in IPCC models:
The models used for the IPCC estimates do include numerous periodic influences. It’s possible that the 60 year cycle is an artifact of smaller cycles that line up every 60 years and which already might be accounted in some IPCC climate models. For example a 20 year cycle and a 30 year cycle will create a 60 year cycle automatically. If you understand the 20 and 30 year cycles individually, you will include all the 60 yr cycle effects in your results automatically. There would be no extra need to model a 60 year cycle specifically. [Note, I don’t know the cycles of the climate patterns. Is there a 20 yr cycle and a 30 yr cycle? Or a 15 yr cycle and a 20 yr cycle?]
Is the IPCC 2100 estimate really off by .7:
I also understand the claims made in the Abstract of this paper, where the IPCC range value is reduced by .7, but I would think the IPCC projections already include this effect since the climate models start their modelling way back before 2007. If the IPCC doesn’t include the offset of the cycles that existed in 2007, then the paper might be correct that the 2100 IPCC estimates should be shifted down by .7. I really expect the IPCC estimates already account for this, however.
Smokey, falsify what? What does “falsify Jose_X” mean? I am still around, so I haven’t been “falsified”. What comment did I make in this thread above that you found was falsified? Let’s start with specifics, so we can analyze the logic.
Honestly, I made no comments about graphs or disputed any specific temperatures or mathematical functions of temperatures (like a yearly trend) that would be falsified by either of those pictures you showed.
I have not claimed (and neither do or have mainstream climate scientists) that a rise in CO2 must correspond to a rise in global average temperature for that measurement period. That would make no sense to claim that. It’s easy to disprove. Climate scientist know there are numerous variables that affect temperature values. CO2 approximately contributes through particular mathematical relationships used in various models and analysis.
So I have no idea what you think I am saying, but those graphs don’t “falsify” me or anything I can remember having said. I keep records of my comments, so ask me about something if you can’t find it posted but remember reading it.
BTW, if you are interested in discussing accurate science, you have to be willing to look at math. If you aren’t willing, then you aren’t interested in discussing accurate science. I didn’t make up that rule. Ask this question to almost anyone who designs what runs modern society. And I can tell you from personal experience that I have seen claims made in papers fail once mathematical (or physics) errors were fixed. If we had ignored the math, we’d still be arguing about what is or isn’t and waving our arms wildly.
Jose, if you cannot understand that the planet is falsifying your belief system, that is because you believe things that are provably not true. As I have shown you: CO2 rises follow temperature rises. But you believe otherwise. You probably believe is astrology and Scientology, too. I can’t help that. But when the planet proves you are wrong – and it has, consistently – then for the benefit of readers who might be misled by your misguided belief system, I feel that I must correct the record.
And for the record, the UN/IPCC is not a scientific organization, it is a political body with an agenda. Nothing they say can be relied upon scientifically.
Thanks Joachim Seifert, but I don’t spend on research papers. I am a fan of open publishing and want to promote that. I have not paid for a paper in at least about 10 years and don’t plan on starting back up this year. I guess I will miss out on that original material you mentioned if it isn’t also posted for free online. I would pay for value-add that I appreciated (eg, if I wanted a physical book) but not simply to access information (although obviously I would make exceptions if I found it important enough to access that information). Thanks anyway.
>> if you cannot understand that the planet is falsifying your belief system, that is because you believe things that are provably not true.
Or because you are confused and keep making those inaccurate claims.
Anyway, Smokey, I came to this webpage to analyze an interesting paper. Do you see yourself as a guardian of the anti-AGW tone of this website and absolutely want to preserve that at the cost of driving polite and critical discussion off the site? I hope you don’t speak for Anthony, but de facto this is what is happening.
Note to moderators and/or Anthony Watts: My mostly favorable if very limited experiences commenting on this website got notched down a bit.. at least if my last and polite comment on that other thread continues to get moderated out of existence. I should be able to feel comfortable replying to individuals like Smokey when they make what I believe are inaccurate statements (more so if they pertain to me). Thinking that my replies will just get removed if I don’t yield to such verbal attacks is rather disappointing to say the least.
Smokey, almost any graph of measured CO2 atmosphere concentrations and average global temperatures which don’t smooth too much will show all of the following 4 possibilities:
a) CO2 rising “after” temp rises
b) temp rising “after” CO2 rises
c) CO2 falling “after” temp falls
d) temp falling “after” CO2 falls
In fact, you will observe this correlation in almost any two sets of time based graphs you pick.
Please convert to using math and physics modelling. With these tools, we can start to have a more meaningful conversation.
Jose,
You are quibbling. All the major temperature rises show CO2 following, by about 800 years, ±200 years. And quit changing the subject: numbers are used to construct graphs, which I post. Now you want me to reduce the graphs to numbers again? Do it yourself, I don’t take homework assignments.
.. and the other 4:
e) CO2 rising “after” temp falls
f) temp rising “after” CO2 falls
g) CO2 falling “after” temp rises
h) temp falling “after” CO2 rises
You will even notice all of those results on two graphs of “random” data points.
Please embrace math and physics modelling a little bit more so we can have a precise conversation.
[@Anthony Watts/moderators: can someone explain to me why the following comment I am now reposting was moderated out of existence? I hit “submit” because I intended to participate in this open forum. If I didn’t want it posted I would not have hit submit. I thought the polite public was welcomed to participate in discussions on this website.]
REPLY: SPAM filter flags keywords and phrases – automatic – Anthony
Smokey, I wasn’t “quibbling”. I was showing you how wrong you were in claiming that showing a graph with CO2 rising after temp rises disproves AGW.
Here I’ll use a graph you provided to show you in more detail.
http://members.shaw.ca/sch25/FOS/GlobalTroposphereTemperaturesAverage.jpg
Let’s start with a few events that are easy to see on the graph and happen almost at the same time:
e,h) [1979] CO2 is rising while temp is falling
f,g) [then mid-1979] CO2 is falling while temp is rising
a,b) [1984] CO2 is rising while temp is rising
c,d) [then mid-1984] CO2 is falling while temp is falling
Now, let’s look at different points in time.
e,h) [@1981 @1993] CO2 rose while temp fell
a,b) [@1985 @1995] CO2 rose while temp rose
[For the most part CO2 has not fallen except intra-year or across very near term years in out of sync months; thus, I’ll leave it as an exercise in squinting to find examples of f,g,c,d for different points in time scenario.]
Smokey, I just gave you examples of CO2 and temp going in the same direction as well as in the opposite direction.
If we look at longer term trends going back to 1850, we see that they both have risen. You can’t say if the chicken or the egg rose first unless you first provide a mathematical relationship that explicitly links the cause and effect in time. When you decide to embrace mathematics as clearly superior to ambiguous graphs, I’ll consider doing the next lesson with you.
Conclusion: CO2 can follow or lead temperature, and they can go in the same or opposite directions. The reason why is simply and I hope you will absorb it some day: basically, CO2 and temp are linked together in a complex way. We need math to really understand what is going on, but your statement that CO2 always rises after temp rises is as true (and useless) as saying temp always rises after CO2 rises. They both happen. You can’t use that silly statement to prove anything about greenhouse effect or AGW.