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.
>> 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.