Mike Jonas
My paper (“the paper”) on the “100,000-year problem” has been published. Many thanks to WUWT reader Burl Henry for recommending the WJARR journal – most journals are quite simply too expensive for unfunded authors like me (eg, 9,500 Euros to be open-access in Nature).
The paper: The inter-glacial cycle is not a 100,000-year cycle, it is a shorter cycle with missing beats
The main point of the paper is that the 100,000-year and 41,000-year inter-glacial cycles that are the subject of the “100,000-year problem” never existed.
I won’t repeat the abstract here – you can access it, and the whole paper which is open-access, at the above link. I find it difficult to believe that any rational person could still believe that climate models can work, given the IPCC’s statement that “long-term prediction of future climate states is not possible“. The paper provides empirical evidence supporting that IPCC statement. Even though the paper refers only to multi-thousand-year cycles, it seems reasonable to suppose that similar non-linear chaotic features apply at both longer and shorter time-scales too. There still seem to be plenty of irrational people in climate science, though.
This supposed “100,000-year problem” has an interesting history:
– – –
- Wikipedia states : “The 100,000-year-problem refers to the lack of an obvious explanation for the periodicity of ice ages at roughly 100,000 years for the past million years, but not before, when the dominant periodicity corresponded to 41,000 years.“.
- The “problem” has been written up in Wikipedia since at least 2007 (possibly much earlier?), when the article ended with “Alternatively, the 21,000 year Precession cycles may be responsible.“.
- Once there was an established perception that the inter-glacial cycles changed dramatically from a 41,000-year cycle to a 100,000-year cycle about a million years ago, that idea got “stuck” and couldn’t be removed. When Liesecki and Rahmo put together their temperature chart for the Quaternary ice age, for example, they “tuned” the data to make it come more into line with the 41,000-year obliquity cycle: “In our second tuning we loosen the LSR constraint in order to keep the δ18O signal approximately in phase with the obliquity component of the ice model.“.
- Back in 2006, Ralph Ellis and Michael Palmer published a paper which identified the much shorter Precession cycle as the main driver, but with missing cycles. ie, the cycle sometimes failed to start an inter-glacial period, with very low versus not-so-low concentrations of CO2 being a significant factor. The whole Ellis and Palmer paper is really worth reading!
- For a long time, the Wikipedia article on the 100,000-year problem had no indication that the Precession cycle played a role in the inter-glacial cycle, with the 2007 “Precession” statement having been removed[*] . In particular, there was no mention of Ellis and Palmer.
- It is difficult to believe that the Wikipedia authors were unaware of the Ellis and Palmer paper, because there was a “Ralph Ellis” page in Wikipedia, which explicitly referred to the Ellis and Palmer paper under the heading “Ice ages, precession and dust-albedo feedbacks“.
- Even worse than that, and looking suspiciously like an attempt to remove Ralph Ellis’s ideas completely, in 2017 the “Ralph Ellis” page was deleted from Wikipedia. See Deletionpedia.
- A recent addition[*] to the Wikipedia “100,000-year problem” page now mentions Precession again, but still with no mention of Ellis and Palmer.
[*] I say this from memory, because I cannot remember seeing in the last year or two any Wikipedia suggestion that Precession plays a significant role. I may be mistaken. The Wikipedia page has been edited 5 times in March 2022 alone, so unravelling its history would be rather time-consuming.
– – –
The paper should be indexed in Google Scholar in due course. Journal editing placed the “Discussion” section before “Conclusion”, although I thought the other way round was more natural because “Discussion” discusses issues arising from the Conclusion.
I hope that the paper will go at least some way towards resurrecting the ideas put forward by Ralph Ellis and Michael Palmer, and that the climate modellers will start to take seriously the IPCC statement that “The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible.“.
Journal editing placed the “Discussion” section before “Conclusion”, although I thought the other way round was more natural because “Discussion” discusses issues arising from the Conclusion.
That’s a strange concept and one I’ve never seen espoused before.
There’s a reason it is called “Conclusion” 🙂
It’s the outcome of the “Discussion”, not the other way round and logically follows the Discussion. The Conclusion should be a summary of the discussion and should not introduce any concepts not already discussed!
The author of the article should indicate what he/she/it considers conclusion and discussion. There is already far too much assumed discipline in our conversations. Get rid of high horses.
http://jrtdd.com/wp-content/uploads/2018/05/How-to-Write-a-Paper-in-Scientific-Journal-Style-and-Format.pdf puts ‘Discussion’ after ‘Results’. I think content is more important than headings, but the journal obviously had its own view. They switched ‘Conclusion’ and ‘Discussion’ sections, but I’m OK with that – the content is all correct, just IMHO that the sequence doesn’t work quite as well as maybe it could.
When I have been allowed to, Results and Discussion were one section, followed by Conclusions. Conclusions and Abstract were for the senior managers who did not want to read the report, just get the points it was making.
IPCC withdrew their statement “The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible.“ because it caused much grief to their conjecture that human CO2 emissions alone have governed global warming/climate change since they began to appear in the atmosphere. Thus they see a simple linear relationship that is easy to predict. However it surely doesn’t mean that a pattern will not emerge, even though it is impossible to predict??
“IPCC withdrew their statement”
Evidence? I know of none. It is a simple statement of fact, which is well understood by most, and causes no grief. It is universally true in fluid mechanics too, at least above very low Reynolds numbers. It says that you can construct a system which will generate weather and which which obeys conservation laws. The statistics of the weather will be correct, from conservation, but the timing of individual events will not correspond to what is eventually observed. This is analogous to turbulence in fluid mechanics, which has been successfully treated for a long time. The full statement, still on their site here says:
“The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible. Rather the focus must be upon the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions. Addressing adequately the statistical nature of climate is computationally intensive and requires the application of new methods of model diagnosis, but such statistical information is essential. “
No-one with any understanding of non-linear processes has any trouble with that statement. The difficulties that the present author has with it does not encourage me to read his paper, if he can’t get past that. But I probably will.
”The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible”
[”It is a simple statement of fact, which is well understood by most, and causes no grief.”
The full statement says….]
”Rather the focus must be upon the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions.”
I’m so glad you clarified that point. All good now.
I wonder if you can use the probability distribution function to predict 10 swings in of this….?
Just for fun, lets say the red ball is a decade and the blue ball a year..
“I wonder if you can use the probability distribution function to predict 10 swings in of this….?”
You seem to be totally missing the point. It is very difficult to predict the state. But there is a lot you can say about it. I’m sure you could predict total momentum, kinetic energy, say a lot about the average potential energy, and the general shape of the trajectories.
CO2 is a control knob 😉
That is the only driver of long term climate prediction in the models. Take out that parameter and bingo no global warming
. . . except for the (ahem!) inconvenient fact that the best paleoclimatology data available shows that there has been no—I repeat, NO—good correlation of atmospheric CO2 concentration with “global temperatures” over the last 600 million years or so.
And, there is no correlation between net atmospheric CO2 flux, at the monthly or annual temporal resolution, and the anthropogenic CO2 flux.
That is probably best explained by the CO2 flux being caused by, and lagging, temperature changes, as reflected in the Law Dome ice cores.
It is good that China, India, Indonesia, the developing countries, etc., are ignoring calls from the woke socialist countries to remain in poverty for the sake of the environment – if emissions continue growing and temperatures continue not growing (as per Dr. Spencer) then it should be obvious to everyone that the climate emergency is a cult or a scam or both.
You would do well to actually read the two references you cite in your diagram. They do not agree with your statement.
So, Dan, you are basically asserting that the plotted data given in the graph that I presented in my previous post—the temperature line ascribed to Dr. Christopher R. Scotese, currently Research Associate at the Field Museum of Natural History and an Adjunct Professor in the Department of Earth and Environmental Sciences at Northwestern University, and creator of the Paleomap Project, and the CO2 line ascribed to Dr. Robert A. Berner, past Professor Emeritus at Yale University—are not accurate individually.
The data exists regardless of what the professors assembling that data may have thought about connecting “global temperature” levels with atmospheric CO2 levels.
Therefore, I invite you, for the benefit of all WUWT readers, to prove your assertion with some hard paleoclimatology data.
I am not aware that any other scientist had made an assertion such as yours related to this graph, which I believe dates back 10 years or more.
Waiting . . .
Both papers state there is a correlation between CO₂ concentration and temperature. An unsurprising conclusion given WUWT also agree that CO₂ is a climate forcing.
So why did the two graphs put together by a coal mining engineer suggest there was no correlation?
Let’s dig deeper and look at the actual science:
Dan, your reply to me is more telling than I think you realize.
1) I combine your posted question “So why did the two graphs put together by a coal mining engineer suggest there was no correlation?” with the snide comments of unnamed narrator of the video you elected to post in attempted support of your assertions, and come away concluding that you both favor the ad hominem method of engaging in “discussion”. Well, that’s your choice but it’s not convincing . . . after all Albert Einstein was “only” a low level patent office clerk when he alone developed the Special Theory of Relativity.
2) I had to laugh with how easily the unnamed narrator in the video cherry picks a few published articles discussing CO2 versus temperature correlations to outright dismiss—his words to the effect that we can “cross out”—Moore’s (along with other scientists’) statement that the climate has always changed . . . with the accompany graphic showing such at 5:15 into the YouTube video clip. Now, this is a not-so-clever strawman argument: asserting that because Moore did not address the issue of global CO2 levels versus global atmospheric temperatures, his statement that climate has always changed must therefore be wrong.
3) Related to Item #2, the unnamed narrator makes an assertion at 3:30 into the video that is simply not supported by paleoclimatology science: that declining atmospheric CO2 level caused the decline in global temperatures at that time. The fact is that recent studies show that temperature trends always lead atmospheric CO2 trends; that is, it is much more credible that declining global temperatures (due to Milankovitch cycles or other presently unknown factors) caused declining atmospheric CO2 levels, rather than the other way around. This is entirely consistent with the simple fact that cold ocean waters can absorb and dissolve more CO2 (from the atmosphere) than can warm ocean waters. AFAIK, there is no credible scientist today that asserts reductions in atmospheric CO2 levels are the cause of Ice Ages (nor, for that matter, the initiator of glacial intervals). In fact, this same unnamed narrator, at 6:12 into the video, clearly states that Milankovitch cycles are the triggers for glacial and interglacial cycles . . . as if he just forgot his previous claims that atmospheric CO2 levels are the cause of climate variations (his argued reason the climate is always changing). Very interesting, and laughable!
4) The video only begins to address the Scotese vs Berner graph overlay (the data in the graph I included in my OP above) at 7:44 in. Of course, there is the initial ad hominem comment that is was a coal mining engineer that put the two data sets together to compare them, as if that had any relevance at all to the scientific accuracy of either data set. Next, and once more, notice the sleight-of-hand trick played here by the narrator. His does not address the data assembled by Scotese nor that assembled by Berner, but instead immediately states what is wrong with the graph is that Patrick Moore (who had nothing to do with the graph construction not data it references “. . . completely omitted the warming effect of the Sun”. WTF?
5) Following Item 4, the video starting at 9:29 shows an apparently alarmingly increasing graph labeled “Change in solar luminosity” with attendant narration of “Sorry if you’ve heard this before, but the Sun has been growing steadily hotter over time.” Yeah, right, no quantification stated for that “hotter over time” remark, so I took the opportunity to look it up and here are the facts (ref https://usm.maine.edu/planet/sun-getting-hotter-if-so-why-will-earth-eventually-become-too-hot-life )
“The Sun is becoming increasingly hotter (or more luminous) with time. However, the rate of change is so slight we won’t notice anything even over many millennia, let alone a single human lifetime. . . . Astronomers estimate that the Sun’s luminosity will increase by about 6% every billion years.”
So, in the last million years (which encompasses the total span of the graph of the combined Scotese and Berner data), the Sun’s luminosity has increased by about 6%/1000 = 0.006%, horror of horrors! For reference the Sun’s luminosity varies by about 0.1% over a typical 11-year sunspot cycle, or about 17 times as much as the overall luminosity increase occurring over that one million years.
I could not bear to go on further with the charade of the video just refusing to address whether or not the data attributed to Scotese and to Berner was valid or not, so I’ll leave the rest of the intentionally misleading, sophomoric video unaddressed.
But this bears repeating, the data exists regardless of what the professors assembling that data (or how many other scientists) may have thought about connecting “global temperature” levels with atmospheric CO2 levels.
If you can look at the graph in question and see a positive correlation between the temperature data attributed to Scotese (no matter where or from who he may have obtained that data) and the atmospheric CO2 concentration data attributed to Berner (even if he obtained it using GEOCARB III), good luck to you. I do not see ANY positive correlation between the two data curves.
In summary, what you posted immediately above is a big FAIL as regards my request that you show the data ascribed to Scotese and to Berner is not accurate. Outside of the ad hominem attacks by you and your linked video, nothing has been shown to invalidate this data.
Finally, your throw-out comment “. . . given WUWT also agree that CO₂ is a climate forcing” seems to assert that this is a (ahem) consensus opinion of the WUWT community of contributing authors and commentors; IMHO nothing could be further from the truth.
But there seems to be pretty strong evidense of a 246 million year cycle…
Oddgeir
Reference for that?
”the general shape of the trajectories.”
Not the general shape you need to predict but which side it would be on at a given time. And by the way, this is simple. Try adding another 15 pendulums and you might start getting close to all the interacting climate influences. If you are out by a tiny fraction, then the model is worse than useless. No better than a coin toss.
Climate modeling is for entertainment only and it’s about time all you climate modelers out there admit it and stop jerking around the gullible masses.
You are trying to deflect from the point. You can not predict what will be occurring and why. Can you write a function describing the motions of each ball throughout time? Average potential energy and average general shape tell you nothing about the paths of the balls.
Add several more balls and try to develop a time based function that describes the motion of even one of the balls. LOL.
If the models had the physics correct, you should be able to let them run continuously, just like the earth does, and just like these balls do. Having to run them iteratively says they are not correct. Evidence, because the earth doesn’t go off the rails.
“Can you write a function describing the motions of each ball throughout time?”
No. This is a very common situation in science. Think of he air in your tyre. Can you write an equation to describe the motion of each molecule? Of course not. But you can predict the pressure, temperature, density etc. And that is what you want to know.
But see, the issue isn’t to determine that basic information. It’s to predict if the trajectory will hit the observer. That’s what matters – knowing the odds of specific events happening.
With climate, it could go from snowball Earth to Venusian Earth. But we want to know specifics of each, not that it could do either of those – or nothing.
CliSciFi bullshit. How does one get a “… prediction of a probability distribution of the system’s possible future states by the generation of ensembles of model solutions.” with models that fundamentally disagree with each other, are not modeling the Earth’s climate system as it exists and consistently fail to reflect past and present climate metrics? It is all computer game speculation designed to give a pre-determined answer.
Nick – if by ‘present author’ you mean me, then I would like to point out that, far from having difficulties with it, I express the hope that the climate modellers will start to take it seriously.
Of course they understand it, and I suppose you could say take it seriously. It is an unremarkable remark. Less informed people get excited because the technical term “climate state” sounds like climate. But it actually means the instantaneous state that you would find in a climate model – ie including weather. And the proposition that we can’t predict the weather on 1/1/2101 is a commonplace. But we can say a lot about the climate.
We can also say that the climate has a “tipping point” and that “The sky is falling”. But you can’t say when. So just repeat saying that over and over and hope it sticks.
Such as the tropical sea temperature will reach 34C in the land of model only.
This in of itself relegates most to the bin.
History matching without the aid of parameters to fix the past should be the first test, if they fail without they are gone.
Worked in the area of oil field models history matching sinks 99% of models they don’t get a “fix” to make them work because the company will go broke within the work cycle of the modellers and be themselves relegated to the bin.
I have a problem with the whole statement, and particularly this part of it. Model accuracy will only be true:
Note that the current spaghetti curves from the models are woefully inadequate for meeting any of these conditions, much less all of them. Additionally, models don’t include a large number of well discussed important variables. These include ocean currents, Thunderstorms, cloud coverage, humidity, air mass momentum, solar variation, cosmic rays, Milankovitch Cycles, etc., etc.
Logically, there can only be one best prediction. Averaging that single best prediction with all the other less skilled members of the ensemble will degrade the quality. However, that is important because it reinforces the claim “… the long-term prediction of future climate states is not possible.“
Were it not for clamping of unreasonable intermediate calculations, the ensemble envelope would probably grow unbounded.
“Additionally, models don’t include a large number of well discussed important variables. These include ocean currents…”
Of course they do. You don’t know much about models. Here they are:
This is certainly an impressive display of SST reacting to ocean currents. It seems to me though that ENSO trends are inaccurate beyond a year or so, and longer-term items such as AMO and PDO are even worse.
Current models are indeed useless, but a statistical approach is the only viable one.
https://www.math.uh.edu/analysis/Theses/2010-Chinmaya-Gupta.pdf
Exactly. I tried to capture that with point 3. Therein lies the dilemma. Climate models not only lack important factors (I won’t call them ‘forcings”), but they also require so much computational power that large numbers of repeat runs using statistically varying parameters cannot be made using current technology. In a chaotic system, a single run using a single value for each variable doesn’t result in the calculation of an accurate future state.
I have run simple Monti Carlo simulations of simple systems with only a couple of non-linear variables, and it takes hundreds of repetitions to converge on a useful solution.
IMO the most important cycle is axial tilt or obliquity, ie the angle of Earth’s axis of rotation as it travels around the Sun .
Obliquity is why Earth has seasons. Over the last million years, it has varied between 22.1 and 24.5 degrees with respect to Earth’s orbital plane. The greater Earth’s axial tilt angle, the more extreme our seasons are, as each hemisphere receives more solar radiation during its summer, when the hemisphere is tilted toward the Sun, and less during winter, when it is tilted away.
Larger tilt angles favor periods of deglaciation (the melting and retreat of glaciers and ice sheets). These effects aren’t uniform globally. Higher latitudes receive a larger change in total solar radiation than areas closer to the equator.
Earth’s axis is currently tilted 23.4 degrees, or about half way between its extremes. This angle is very slowly decreasing in a cycle that spans about 41,000 years. It was last at its maximum tilt about 10,700 years ago, and will reach its minimum tilt about 9,800 years from now.
As obliquity decreases, it gradually makes our seasons milder, resulting in increasingly warmer winters, and cooler summers that gradually, over time, allow snow and ice at high latitudes to build up into large ice sheets. As ice cover increases, it reflects more of the Sun’s energy back into space, promoting even further cooling.
https://climate.nasa.gov/news/2948/milankovitch-orbital-cycles-and-their-role-in-earths-climate/
Early in the Pleistocene Epoch, when continental Northern Hemisphere ice sheets began forming some 2.6 million years ago (Ma), glacial cycles matched this 41,000-year period. Between about 1.2 Ma and 800 Ka, glaciations apparently switched to a 100,000-year cycle.
But in fact, the 41,000-year tilt cycle still rules. The seeming 100,000-year cycle is an average of two and three obliquity cycles, ie 82,000 and 123,000 years. The stillborn cycles are stadials and interstadials, the colder and less cold intervals within glaciations. The warmer periods between glacials, in which the ice sheets melt, are called interglacials. They vary in length, depending largely upon the other Milankovitch cycles.
Our present Holocene interglacial has so far been shorter and cooler than the preceding Eemian.
Precession is much more significant in changing global climate trends than obliquity. Obliquity certainly drives the seasons but humans have learnt to survive under the extremes. Climate trends that create glaciation and much lower sea level will require much greater changes to adapt. For example, there is probably no exiting sea port that will be useful. Canada and Northern Europe will look like Greenland. These are millennial scale changes primarily driven by precession. Four cycles of glaciation back, orbital eccentricity was similar to now, near the minimum, but the variation was enough to start glaciation.
Oceans and atmosphere above absorb 71% of the incoming sunlight while land absorbs only 52%. In the present era the sun has a very good view of ocean during perihelion. That is when Earth takes in a good portion of its energy. In December alone, ALL the atmospheric water is cycled from ocean to land more than once. When the sun views the northern land masses during aphelion, the Earth loses energy despite the temperature reaching a maximum.
As the precession cycle moves on such that the sun views the water during aphelion, the boreal winters will be colder and a greater proportion of the precipitation will fall as snow. That will be well into the next glaciation.
For the first 1.4 million years of the Pleistocene, the tilt cycle clearly rules. Nothing changed that after the apparent Mid-Pleistocene Transition. The world just got progressively colder, so some obliquity cycles were stillborn. It depends upon the other cycles and possibly extraneous factors such as geomagnetic shifts.
Take a look at Figure 1 in the paper. I don’t think you will find 82,000 or 123,000 years. The 65N, however, is spot on for all 17 cycles (Figures 1 and 2).
I do find the 41 K cycle in stadials.
Note the pronounced difference in duration of both glacial and interglacial intervals.
John, the graph you posted has the sentence underneath that states:
“Note the pronounced difference in duration of both glacial and interglacial intervals.”
I don’t know if that comes directly from you or from the source of the graph, but I observe the following . . . the difference in durations between glacial and interglacial intervals is a direct consequence of where one sets the y-axis line of demarcation between those two states. Instead of 230 ppm CO2, set the line of demarcation at 220 ppm (or even 240 ppm) and you’ll get markedly different interval durations.
I don’t know of any reason to think that setting the demarcation at 230 ppm CO2 has a valid basis.
I agree with your assessment and sentiment.
The climate modelers have no interest in bringing back the old statement from the IPCC because there’s more money to be had feeding the green blob.
The statement is simple and accurate. It never went away. It is here.
Nick, you misdirect readers by not fully informing people. The whole section was a plea for better data and much better models. The relevant passage for this discussion is:
“Improve methods to quantify uncertainties of climate projections and scenarios, including development and exploration of long-term ensemble simulations using complex models. The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible. Rather the focus must be upon the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions. Addressing adequately the statistical nature of climate is computationally intensive and requires the application of new methods of model diagnosis, but such statistical information is essential.”
In no way does that passage say that current model ensembles can predict the probability distribution of the Earth’s future possible states. This is eyewash to keep the narrative flowing. You should have stopped when you were ahead, Nick. Leftists, of course, always push too hard.
How does it improve information to tell people that the IPCC has withdrawn the statement when they clearly haven’t?
“current model ensembles”
The statement dates from 2003.
They may not have withdrawn the statement, but have surrounded it with more verbage that can be used to defend the calculations which are otherwise not fit for purpose, using soft, yet scary words.
Engineers use this sort of calculation methodology, but they NEVER average together individual runs, because that just produces junk to the nth power. Instead, engineers use the uncertainty to draw a boundary around the calculations, and then design the equipment to be able to handle the worst case situations. It is called “adding margin” to the design, so that you can be sure that you won’t run into a phenomenon or boundary condition that you did not explicitly consider.
The whole approach by the IPCC with these projections is a mis-appropriation and corruption of a technique that was invented for engineering applications. Just like Hansen’s mis-appropriation and corruption of control system theory to predict the effect of CO2.
Nick, your comment in no way addresses my assertion that UN IPCC CliSciFi models cannot predict the “probability distribution” of Earth’s future climate states. They are unfit for the purpose of fundamentally altering our society, economy and energy systems.
Nick, UN IPCC CliSciFi CMIP3 models are fundamentally the same and just as uncertain as the current CMIP6 models. Over time the models are getting worse at duplicating some past and present climate metrics. Again, they are unfit for fundamentally altering our society, economy and energy systems: Socialism never works; the UN IPCC is just a stalking horse for the neo-Marxists and one-world government types.
My thanks to Mr. Stokes for providing the link.
I had been too lazy to bother to read the latest IPCC assessment but, now that I have read the chapter that he provided, I cannot understand how anyone could give credence to long term predictions based on climate models as they exist today. It seems clear to me that such predictions are based on faith rather than on facts.
Why waste billions of dollars on curbing CO2 emissions based on such predictions/guesses. Particularly when there is so much global poverty still to be alleviated.
Will there be a Marshall Plan to help re-build Ukraine after the damage done by Russia? Or will all surplus monies be spent on anthropogenic ‘climate change’ boondoggles?
“Why waste billions of dollars on curbing CO2 emissions based on such predictions/guesses. Particularly when there is so much global poverty still to be alleviated.”
Especially since, after 40 or so years of alarmism, there is still no evidence of a climate crisis/catastrophe/emergency/whatever.
“to read the latest IPCC assessment but, now that I have read the chapter that he provided”
The quote I provided is from the TAR, written in 2003.
This statement was not included in the Summary Report for Policymakers given to the press and public.
The term “lies of omission” comes to mind.
Of course not. It is a trivial and obvious statement. The IPCC report is long, the SPM is short.
It is not trivial. In fact it is quite significant.
I agree with you that it is obvious.
You could throw out the long IPCC report and state “The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible.“
That would have saved a few trillion dollars and many lives instead of using 14th century solutions to a nonexistent problem.
This will be an interesting reference to follow. I can hindcast sea level associated with glaciation reasonably well by considering insolation variation in the North Atlantic. I agree precession dominates glaciation.
https://1drv.ms/b/s!Aq1iAj8Yo7jNhEUPzdLmLlSCh3_I
So far I have not been able to get recovery from glaciation using variation in insolation. I need some sort of trigger that causes rapid melting. The idea of dust is a possibility.
Svenmark trigger there also.
Several variables not always cyclic but mixed in.
The paper was published in 2016, not 2006.
It is interesting to read on WUWT a theory of glaciations based on CO2. I can’t see that this new paper adds much to that of Ralph Ellis, which sets it out fairly completely. Lots of people, as described there, have thought that there is some frequency divider process going on, and precession seems a reasonable candidate.
Nick, “a theory of glaciations based on CO2.” Funny, it has been shown temperatures lead CO2. Does the future drive the past?
Take that up with Ellis and co (or Mike Jonas).
Dave – The Ellis and Palmer paper is well worth reading. Their basic finding is that very LOW CO2 concentrations caused deserts to expand and hence more dust to be blown around. The dust then helped the ice sheets to melt, which led to higher temperatures. So LOW CO2 caused higher temperatures. Not the CO2 control knob being promoted by the climate crowd.
Mike
What you describe is a self correcting mechanism?
Stasis maintenance?
When CO2 during glaciation gets so low that plants die back and desert/dead areas expand, to the point that enough dust is generated to trigger glacial melting.
Seems like Russian roulette to me, will melting always occur soon enough to prevent CO2 falling below 150 where we all die?
See how close to the edge we can get before it’s all too late?
Volcanic activity has gradually decreased enough that now we teeter on CO2 starvation at times. As you say, CO2 starvation could be the next and last great extinction event.
Nick – I agree that Ellis and Palmer set it out fairly completely. The main point in my paper in this respect is (as it states) that it tests their hypothesis over a longer timeframe.
Image thanks to Javier
Where my paper does things differently is that it looks at glacial terminations not inter-glacial peaks, and it does so over a significantly longer time-scale which includes the earlier period with shorter intervals between inter-glacials. The significant finding is that the pattern is similar over the whole extended period.
I don’t claim that what I highlight is the only thing going on or the only thing worth looking at. In fact it is pretty clear that many things are going on and we know little about most of them. Javier’s analysis is a useful part of the total.
“In fact it is pretty clear that many things are going on and we know little about most of them”
In my 10 years of research, that is the take home quote. By many orders of magnitude.
Mike
Your analysis of this topic is useful and timely.
It may be best not to separate the three cycles but consider their integrated effect together. I don’t think it’s like clockwork. If its a weakly periodically forced nonlinear oscillator, then there won’t necessarily be a strict and precise relationship between the forcing and the emergent pattern. My guess is that at the MPR it transitioned between strong (mainly obliquity) and weak periodic forcing.
I take your point however about 65N insolation being very influential.
If seen over millions of years, [deep] oceans are cooling. The colder the upwelling deep ocean waters, the more difficult it is to reach surface temperatures that cause enough melt of ice and snow and result in enough of our main greenhouse gas: water vapor.
For that extra warming needed in a deep Ice House State like ours, the extra warming by precession is needed. Precession is also causing the Sahara to green: adding more water vapor to the atmosphere and diminishing nighttime/wintertime cooling. Precession produces just enough extra energy at the right place(s) to cause enough warming to further melt large surfaces of ice and snow, diminishing reflection and causing more surface warming resulting in still more water vapor in the air over large surface areas.
Water is by far the most important greenhouse gas. Besides, more water vapor causes all weather systems to change, and in their turn, the changing weather systems change the behavior of the oceans: changing wind direction and changing wind strength directly influence oceanic behavior.
The average of 30 years of weather is by definition: climate. Water vapor is the main greenhouse gas and the gas that changes the weather, an essential part of the system causing smaller and larger variations in climate.
Wim
Yes a long term secular cooling is the reason for the transition (MPR) from 41,000 year to a about 100,000 year interglacial spacing, about a million years ago. It’s getting harder to kick-start interglacials. They may stop altogether in the future.
Thanks, Phil. Knowing your background in oceanography makes me take your comment(s) very seriously.
There is a possibility that adding CO2 to the atmosphere has a very positive side effect: deserts and colder areas plus most other areas are greening. Greening of the landscape enhances the quantity of water available in soil and vegetation and the result is more water vapor in the air, especially at places where the local atmosphere was relatively void of water vapor. Dry and cold places exhibit a large loss of surface energy directly to space because they relatively lack the main greenhouse gas water vapor. The Earth’s oceans have been cooling since the ending of the Green Sahara, some 5000-6000 years ago.
The greening of large landmasses could [partly?] compensate for the loss of water vapor when Milankovitch cycles bring the Earth to a less optimal position to the Sun which is causing colder and so drier land surfaces at the higher latitudes of the Northern Hemisphere. The greening of the Earth could diminish, stabilize or even reverse the long-term cooling trend that is already bringing the larger temperature variability we experienced during the Little Ice Age and in our present Modern Warming. That higher variability historically accompanies cooling oceans and a cooling surface.
Warmer periods (having more water vapor in the air) are more stable than colder periods with less water vapor in the air. Historical graphics show. The colder the oceans, the higher the variability: see figure b for the most recent 5 million years.
Global deep ocean temperature in the Cenozoic Era, with the Pliocene and Pleistocene expanded in (b)
James E. Hansen and Makiko Sato 2011
Many years OK, in a series of articles on the ice-ages, I not only said the ice-age cycle was not a constant 100ka, but also provided a potential mechanism to explain it.
I couldn’t entirely explain the cycle, but I’m hoping that if I see the next ice-age start soon, I will be able to complete the theory, just in time to see our entire civilisation collapse.
If you’re in Scotland rather than an ex-pat you should be one of the first to notice the returning year round snow.
It already snows year round in calgary.
Should I be worried
Mike
Thanks for the paper.
Although orbital motion is the dominant player, there are clearly many other known and unknown butterflies that impact climate.
One such butterfly might be continental drift and the slow closure of the isthmus of PAnama. This would have slowly changed ocean circulation.
I have no ideal of the quantitative impact of this closure or The impacts of hundreds of other phenomena that play their minor part in tweaking the climate
I am curious about the affiliation that Mike Jonas lists. It states “Department of Mathematics, Oxford University” but he claims to be an unfunded author and the University’s website does not list him as a member of the department. Curiously enough in 2015 he claimed here to have retired after 40 years of working in IT which again suggests that he is not a member of the Department of Mathematics at Oxford.
I submitted the paper with “Affiliation: None”, but the editor insisted on there being an affiliation. The only possible affiliation was the university where I got my maths degree over 50 years ago. The Cambridge Dictionary defines affiliation only as a connection, not membership. So I reckon it’s OK. If Oxford objects, I’ll have to do something different for my next paper. If there is one.
“If Oxford objects”
You may be rusticated.
You have been rusticated on this site many times for your obfuscation.
CO2 as a control knob indeed.
I’m not sure that I would notice.
Affiliation: The Human Race
I’m a Native American by all possible definitions, but I don’t get to fish without a license as I’m not THAT kind of Native American.
I suppose you are curious if he is funded by big oil 😉
You are a piece of work.
Couldn’t find anything wrong with the paper (nor could Nick Stokes apart from a missing IPCC statement) so attack the background of the author and his qualifications instead. Not an uncommon tactic.
I’ve met many people in IT who didn’t start their careers there. Even a few Mathematicians. Some of the best started in a manufacturing environment where Murphy’s Law operates in all it’s variants. This to the question “Does it work?” being answered by “It seems to so far”. So it’s obvious very few, if any Climate Scientists are familiar with Murphy and his law.
Acknowledging all of the ramifications of Murphy’s Law would interfere with their grant-gathering from the policy makers. [BTW, Murphy didn’t write Murphy’s Law.]
Besides, Murphy’s law is inconvenient for them. Murph’s 3rd law is “Models never work. “
Izaak Following the Griff pattern of attack the author first, then try to slander their name.
I am curious that you didn’t address his paper at all, but we know why.
There is nothing in the paper to address. It is nothing more than a collection of figures taken from other papers with no analysis or additional insight. The conclusion states that:
“what the data shows is that glacial terminations align with the 65N insolation cycle, as driven by precession and modulated by both obliquity and eccentricity, but with missing cycles.”
Now what Mr. Jonas calls “missing cycles” others call a 100k cycle (or a 41k cycle). The only difference between Mr. Jonas’ paper and previous ones like Ellis and Palmer is that previous studies have tried to find a causal reason for the missing cycles while Mr. Jonas just blandly asserts
“This finding underlines the chaotic non-linear nature of Earth’s climate.”
but fails to state how or why this is the case.
It is also worth noting that others have address this transition in more detail using nonlinear coupled equations with delayed feedback and fine a transition between 41k oscillations and 100k oscillations. See
https://epubs.siam.org/doi/10.1137/18M1203079
for more details. Which means that unlike Mr. Jonas’ assertion that the climate has a chaotic nonlinear nature it only needs to have a nonlinear nature and might not be chaotic at all.
might not be chaotic at all
Why are you afraid of climate being chaotic?
You still haven’t addressed his paper but thanks for the reply which helps me remain unconvinced with you.
As usual, you are more concerned with the credentials of the author than with the facts and logic of his argument. I’m just curious if all you can offer are ad hominem attacks?
Um, Wikipedia and “Climate change”?
I don’t think so.
Pass. Life is too short
If you read this article, you will see some rather dubious actions from Wikipedia being given exposure. However, Wikipedia also gives a nice clear definition of the ‘100,000-year problem’. Best to take everything on its merits.
I remember once taking a tour of Taliesin West (Phoenix), where Frank Lloyd Wright would winter. The tour guide remarked that some local architects objected to him practicing when he wasn’t licensed to practice architecture in Arizona. When I heard that, I thought to myself it was not unlike some Christian clergy complaining that Christ had not been baptized.
Some, like Izaak, get too hung up on pedigrees and ignore the performance.
Mike Jonas,
Congratulations.
May this encourage more and more authors to promote their studies and where appropriate, to criticise others with weaknesses.
Geoff S
Thank you Mike Jonas. I will read your paper today.
“Even though the paper refers only to multi-thousand-year cycles, it seems reasonable to suppose that similar non-linear chaotic features apply at both longer and shorter time-scales too.“
For “shorter”, I refer to my recent post on an open thread here at WUWT. 365 plots, by date, from the USHCN daily data, for the period 1895-2021, of the 5-year centered mean of Tmax for the contiguous U.S. Timed influences, combining irregularly, could produce this effect – that the cycles and trends differ so much from each other by date. I invite you to take a look, clicking through the series of plot images and just watching the result.
https://wattsupwiththat.com/2022/03/13/open-thread-22/#comment-3476060
It’s never gonna happen is it.
The realisation of what drives climate and thus climate cycles
(Ice age) cycles as seen for the last million years but not before then.
Some pretty epic (one-off) calamities maybe but the big space rocks are now all fallen into either Jupiter or the sun. Apart from the one that triggered the Carrington Event notsolongago.
Water controls climate.
Over the ocean, water supply is not an issue
Over the land, (climate-driving) water supply/availability is determined by how much is stored on that land.
Either in lakes or most especially within the soil
But pure natural ‘bare soil’ is simply crunched up rock & stones with virtually zero water retention properties. = Desert
Enter plants.
They feed off the nutrients released from the bare rock by the action of Carbonic Acid (rain)
So the plants grow but, somewhere along the line (evolution) – they were/are programmed to die.
And when they do, gravity pulls their remains into the crushed rock.
And cellulose/lignin/starch/sugar have mahoooosive water retaining properties
Thus, what is generally called ‘Dry Land’ is in fact anything but.
A 12 inch depth of high organic soil will capture/retain 2 inches of rainfall before it even ‘feels’ wet. The depth of the organic layer depends on how far Oxygen can get down – else it goes rotten and becomes coal and or oil
Lets say 4 feet depth
Thus ‘Dry Land’ is typically an extension of the ocean – except maybe ‘only’ (at 4ft depth) and ocean that has a water depth of 8 inches
Plants have an evolved wisdom and they work to conserve that water as best they can – hence the default Earth Vegetation is forest.
i.e. Trees that put up a solid continuous canopy to prevent sunlight (energy) getting near the water in the soil and also, the canopy keeps the wind out.
Trees moderate the ground/soil temperature by releasing water vapour as required to make clouds.
This is a very lovely and extremely robust, mechanism but with 2 particular weak points (3 actually ##)
Controlled by epic amounts of negative feedback. That feedback is = epic because the feedback loop has very high open-loop gain – that gain effected by the immense heat capacities of the working fluid.
i.e. Water. Got to be the most misunderstood and taken-for-granted substance known to man.
There is nothing else in this entire universe comes close to what water does. Nothing
But there is a repair mechanism, one that returns CO2 from under the water and also supplies fresh nutrients to the top layer of soil
Basically what we call Plate Tectonics, mountain building and volcanoes. That is all new fresh rock and the volcanoes work as cement kilns – acting on subducted limestone to create slaked lime and importantly, Carbon Dioxide
But then The Real Killer enters the fray…
The thing that powers Plate Tectonics and all its wonders is itself dying.
The radioactive elements with Earth will now be at very least 5, 6 or 7 billion years old – there can not be much of them left so their rock melting effect will be fading rapidly.
Thus the supply of fresh rock and CO2 will be dwindling
Q: How low was CO2 in 1850?
A: Not very far away from the level at which plants, effectively, suffocate through lack of same.
This now where clear thinking folks lose the will to live because when the trees/plants die, either through malnutrition, disease, pests or wildfire – what is left behind is what was there to start with.
i.e. Bare rock, sand and stones
aka Desert
And deserts, despite having ‘high temperatures’ are in fact cold places.
Because there is no longer any water there. Its that simple.
But cold places, as long as there is still an ocean somewhere, will become buried in ice.
The ice works very similarly to how Plate Tectonics create and uncover fresh new rock for plants to use. The ice sheets and glaciers are very effective ploughs – they sweep away the top layers of old soil to revels fresh rock from underneath.
And they mash it up a bit to get the ball rolling
But that new rock will suffer the same fate as the old rock, any rock in fact and so that ice age ‘cycle’ will be duty-bound to repeat.
Which it will, until, the ice ever gets to the Equator.
Then it really is curtains for Life on Earth
Strangely enough, we us ourselves humans could so very easily replicate what the ice sheets do.
We already do in fact – do we still dig up and re-bury 58 Gigatonnes of rock every year
(that is quite an old number)
Makes you wonder, is there method in the renewable madness = how many times do we hear about the amount of mining & quarrying needed to find the materials required?
## In case you wondered, weak point number 3 is us.
How we started with flint axes, fire-sticks, digging stick and goats.
Technology has moved on a bit…
Yo Gaia. All hail Mama!
=======
I think the real problem is that there is no regularity to these cycles – NONE at all. It’s something that doesn’t jive with the needs of the grants seekers to have regularity where there is NONE. ZERO. NADA. RIEN. There’s no clockwork mechanism ticking along, getting ready to Burp The Big One, no matter how much they desperately want it to be there.
If there were any regularity to it, then why would the Atlantic ridge start waking up now, first up in Iceland’s volcanic fields, and then down south to Tenerife? I know they have control issues – that’s pretty clear – but you can’t average irregularity. Trying to do that is silly, and ignores reality that there is no control of the planet by Hoomans.
I was in grade school when Surtsy erupted out of the seabed. Surtsy’s still there, and Iceland’s newest volcano has gone quiet, although there are tremors being monitored by the Icelanders. It ain’t over ’til the planet says so.
Now, I know that offends their delicate sensibilities, but they’ll have to accept some day that they have no control over anything at all, including their digestive systems and a ridiculous need for buttered popcorn at 2AM.
“I think the real problem is that there is no regularity to these cycles – NONE at all.”
Ummmm . . . I beg to disagree. Look at the attached graph (courtesy of https://serc.carleton.edu/eslabs/cryosphere/4a.html ) and tell me if you detect any regularity—any regularity at all—in the graph of glacial/interglacial cycles over the last million years.
With all due respect, Gordon, not really. What I found in periods of time over the last BUT600,000 years was this:
NAME
W 0 – PRESENT 0-18 18,000 years in length (Holocene)
C WISCONSIN 18-67 49,000 started 67KY ago and ended 18KY ago
W SANGAMON 75-128 61,000
C ILLINOISAN** 128-180 52,000
W YARMOUTH**180-230 50,000
C KANSAN** 230-300 70,000
W AFTONIAN 300-330 30,000
C NEBRASKAN 330-470 140,000
W WAALIAN 470-540 70,000
C DONAU II 540-550 10,000
W TIGLIAN 550-585 35,000
C DONAU I 585-600 15,000
LENGTH OF TIME (MILLENIA/YEARS)
That is rough, yes, but this is why I said there is no real regularity to the length of time of warm and cold periods, or when they start and stop. If there were a regularity to it, each of those time periods would look more like clockwork than anything else, but they don’t. The Nebraskan cold period was the longest, and you’d have to ask why. However, the WARM periods appear to be consistently shorter than the cold periods, with the exception of the Donau I and Donau II being split by the Tiglian warm period. And even then, there is no regularity.
Sorry that’s such a rough presentation.
Thank you for your response, but with all due respect, Sarah, your original statement was: “I think the real problem is that there is no regularity to these cycles – NONE at all.”
You did not originally specify “regularity” only with respect to time, but just raised that definition limitation in your response to me.
In my response to your OP, I just wanted to point out there is clearly the regularity of cyclic behavior (hence my bold emphasis of the term: cycle) . . . cool periods are regularly followed by warm periods.
Also, if you examine the prior three full cycles of glacial-interglacial climates (aka stadials-interstadials), you will see that they averaged about 100,000 years duration. Furthermore, using the average mid-point between warmest temperature and coolest temperature of a full cycle interval as line of demarcation between “warm” (interglacial) and “cool” (glacial), one finds there is a consistent average of about 22% of each full cycle period being on the warm side of the midpoint of max/min temperatures for those cycles.
Lastly, for comparison, many scientists refer to the regularity of the 11-year (aka Schwabe) sunspot cycle occurring on Sol. “However, the length of this cycle does vary. Between 1700 and the present, the sunspot cycle (from one solar min to the next solar min) has varied in length from as short as nine years to as long as fourteen years. Note, however, that of the 26 solar cycles during that three-century span, 21 had a length between ten and twelve years.” —source: https://scied.ucar.edu/learning-zone/sun-space-weather/sunspot-cycle
A range of 9 to 14 years is a variation of +/- 22% . . . does this mean the Schwabe cycle has no regularity?
Okay, i understand your point of view. I do. But I do believe that using averaging is not a good idea because it does not allow for small things like solar cycles with zero sunspots, or weather cycles like the 1930s Dust Bowl. That’s my point. I’m not even sure that it allows room for the very real effects of the chaos factor, which (in my view) is more important than averaging.
Averaging doesn’t explain why a thriving forest growing hundreds of millennia ago is now a place where the petrified remains of those trees and other plants are all that is left.
Why, for example, should the middle of the African continent be everything from grassy fields to dense jungle, while the north end of it is mostly desert, bordering the Mediterranean and the landscape on the north side of the Mediterranean is lush and green?
I understand what you’re saying, but averaging doesn’t (in my view) really allow for such things. Not arguing that averaging cycles isn’t valid, not at all. Just saying it doesn’t really address the hard-copy stuff like what caused the end of the Bronze Age (volcanic activity outside the straits of Gibraltar, most likely, sending people west into the Med to escape it). Averaging glosses over those things, which are very pertinent to what allowed humans to develop civilization.
Averaging doesn’t address things like why civilization began some 15,000 to 18,000 years ago, with the Syrian towers being built and the building of a small town in Jordan, and the city of Ur being constructed, and all of that area is now mostly desert. This is around the time the last ice sheets were melting back and what is now Iran/Iraq had the benefit of lush green acreages and plenty of water resources form the Tigris and Euphrates rivers. Since it is now desert, it’s logical to ask why anyone would build a civilization there, but that was done when the ice sheets in Europe were receding. Now it’s all desert on that side of the Med and on the north shores of the Med, southern Europe is still green and lush by comparison. Where’s the explanation for those differences?
It’s valid to average if you don’t want to bother with the details, but I think doing so sets aside the effects that come out of those cycle changes, and the details are in the changes that occur in those cycles. Averaging does not, in my view, address these things adequately. It also doesn’t explain why the warm periods are almost consistently shorter than the cold periods.
Sara, thank you for your thoughtful, well-argued reply.
We agree that nature has complexities (e.g. stochastic processes) that rule out exact regularity in nearly all physical processes. It then becomes a matter of individual interpretation when there is enough dispersion in repeated cyclical process to call them irregular or even, as you point out, not having any temporal or spatial regularity at all.
I also agree in general with your comment about “averaging” data without consideration of what might be lost in the process, although I’ll also assert that “averaging”-with-understanding-of-the-process provides very useful insights into both statistical and physical processes. Humans have benefited enormously from using this mathematical technique.
Finally, I do believe it is correct to say that “averaging” was never meant to provide understanding of the underlying reasons for variations within a given data set.
Thanks, Gordon. I think we see more eye-to-eye on this than I had realized. Maybe I’m too detail oriented, but sometimes, the details aren’t the things that should be set aside. Might miss something really important.
Thanks again, and have a nice weekend.!
The second link (“IPCC’s statement”) returns a page not found error.
Apologies. The IPCC website says: For any links that you cannot find on the new website, follow the path archive.ipcc.ch/… instead of http://www.ipcc.ch/... including the rest of the path. Hopefully that will work.
Variations in the Earth’s Orbit: Pacemaker of the Ice Ages:
J. D. HAYSJOHN IMBRIEAND N. J. SHACKLETON
SCIENCE • 10 Dec 1976 • Vol 194, Issue 4270 • pp. 1121-1132
In that paper they identified numerous variances of 23,000 42,000 and 100,000 years with some 19,000 and 82,000 occasional variances in it too.
Thanks for that link. I will read that. I’ve come across other such articles occasionally. They are worth the time it takes to read them.
it seems reasonable to suppose that similar non-linear chaotic features apply at both longer and shorter time-scales too.
======
A fractal distribution.
I thought an inter-glacial is the warm interlude between the glacial expansions? Therefore the Eemian and the Holocene are inter-glacials?
There are three Milankovich cycles. At any given time, they are all additive and subtractive. At some point in the long-distant future, they will all peak at the same time. Regardless of when that is, earth’s climate will reflect that situation. And if that affects climate, they all affect climate in their own way, but the other cycles will be subtractive from the biggest one.
As a long-time electronics engineer, and using lock-in amplifiers, I have seen how sine waves interact with each other. If those M. cycles were in microseconds instead of thousands of years, you would be able to see how they interact. It is a simple experiment to set up – three sine wave generators, set at the appropriate frequency, and displayed on an oscilloscope would display the resultant wave appearance. None of them would be visible by itself – it would be a complex wave, which is exactly what is happening in our long-term climate cycles.
If some researcher would set this experiment up properly, it could be determined what our climate future looks like long-term. It could also identify exactly where we are today, in that complex waveform, and thus look at exactly what is coming.
Note that the longest term cycle will dominate the screen. the others will be sqiggles on the largest. The longest has the most ‘power’. The shortest will appear as sqiggles on the longest. It could be determined when the three peak together with enough computer power and an understanding of where we are right now.
No CO2 was harmed in this message.
John
An interesting insight, thanks.
I agree that it may be best to consider the three orbital cycles, precession obliquity and eccentricity, as a combined single entity. Precession and eccentricity are linked by their nature. Post the mid-Pleistocene revolution (MPR) about one million years ago the variable approximately 100,000 year period is well explained by interglacials happening when the combined warming of all 3 cycles together reaches a maximum.
Another clear observation that is rarely commented on (except by me) is that when obliquity peaks are equidistant before and after a combined eccentricity-precession peak, then you get a double-headed, not single, interglacial peak. This supports the overall picture of all 3 cycles working together while obliquity is dominant. These double headed interglacials occurred at 200 and 600 kya, and will happen again 200 k years from now.
Overall the system is understandable as a bistable weakly periodically forced nonlinear oscillator.
That’s exactly what I found when I set up my cold v. warm period bar chart: the Nebraskan cold period is so lengthy that in a bar chart, it makes the entire thing look like a gigantic sine wave for the cold periods, and I found that the same thing applied to the warm periods in between the cold periods. Thanks!!!
HI MIKE,
I have not yet perused your whole paper yet and look forward to doing so. I agree there is no 100,000 year cycle I agree the longer cycles or due to missed beats of shorter forcings. I see Dansgaard Oeschger events as representing short term forcing attempts to remove insulating sea ice and ventilate the heat that would terminate a glaciation, but that dynamic needs orbital help.
I fall into the obliquity-41,000 year cycle as that main orbital helper.
A paper by Huyber and Wunsch supported that hypothesis so I am curious what your take was on their analyses. I did not see it referenced in your paper.
from Obliquity pacing of the late Pleistocene
glacial terminations (2004) Huybers & Wunsch
“The null hypothesis that glacial terminations are independent of obliquity is rejected at
the 5% significance level. In contrast, for eccentricity and precession, the corresponding
null-hypotheses are not rejected.”
Yes, obliquity plays a part in it all, and the paper (by quoting Ellis and Palmer on it) says so. But 65N hits every glacial termination spot on. I’ll take a look at Huyber and Wunsch, but from what you say it looks like they only show that obliquity plays a part.
Is there any way to account for why the ice periods never really hit the southern hemisphere and most of it was in the north? It seems to have mostly been in the northern hemisphere.
Just asking, because except for Antarctica and Tierra del Fuego, and southern mountain ranges, there isn’t much down there.
Sara,
I think you have answered your own question. With so little land in the SH, any ice that isn’t frozen solidly to land can just float away and melt as it gets closer to the Equator. Another thing is that land can and does get colder because it takes less energy to warm (and conversely, cool) rocks, soil, and vegetation. Thus, during glacial summers, there is less melting where there is a lot of land, i.e. NH.
I’ve read the H&W abstract (couldn’t access the whole paper). They only go back 700,000 years, and they only claim that obliquity plays a role. If you look at my figure 2 which goes back a lot further, obliquity is not a good fit. I don’t claim that obliquity plays no part, but the 17 glacial terminations in my analysis display a pretty stunning fit.
I like that this paper dovetails nicely with the Ellis and Palmer hypothesis, which I find quite compelling. Their model is especially galling to alarmists because it postulates that the rise in temperature at the end of a glacial period and the beginning of an inter-glacial is not caused by a rise in CO2, but is instead caused by extremely low CO2. The low CO2 results in widespread dust storms that in turn changes the albedo of the polar ice sheets. It is interesting to speculate that upcoming glacial periods could well have increasing numbers of “missing beats”. Further research could look into plausible controls on the number of expected missing beats within glacial periods (e.g., plate tectonics, orbital, volcanism, etc.).
If the Ellis and Palmer hypothesis were ever to become widely accepted, it could point to viable geoengineering solutions if we ever start to slip into a glacial at the end of the Holocene. Anthropogenic control of ice sheet albedo might just be the way to go. Unless, of course, we decide that having all this nice real estate in the Northern Hemisphere really should be under a mile of ice.
How much influence might have been involved during the Industrial Revolution, when smog and fog and (in some places) leaking gases from sewers? London was notorious for its smog back then, and Chicago and New York City weren’t much better.
Might any of that explain that it influenced the drought that became a weather phenomenon like the Dust Bowl, which was influenced by the loss of humidity that normally came out of the Gulf of Mexico?
I think one should be careful to distinguish between the absence of a 100,000 year cycle and the possibility that there may be a forcing mechanism (one of many) with 100,000 year period. Personally, I think that the work of Muller and MacDonald does not get enough attention.
https://muller.lbl.gov/pages/glacialmain.htm
I’ve read M&M’s quick summary. I like that they suggest a way that their hypothesis can be tested. It is surely possible that orbital inclination plays a role, as they hypothesise, but I seriously doubt that it is as important as they suggest. They only go back 600,000 years, so they only cover the period for which the 100,000-year cycle is thought to operate. I suggest that their hypothesis would not successfully extend back over the whole period that I cover.
Jonas ==> re: Wikipedia Always check the TALK page for any article on controversial subjects like climate. ALL controversies on the Wiki are tightly controlled by a self-appointed cadre of contributors — and it is their opinions that create the page — contrary views, no matter how well documented, are expunged.
The Wiki is a good staring place for basic knowledge points, but COMPLETELY undependable on any topic that has the slightest modern controversy.
Nicely done, Mike. The time-domain evidence for the thesis of skipped beats of a 21kyr Milankovich cycle is quite intriguing. Would love to see, however, buttressing of thesis in the frequency domain, such as provided by cross-spectral analysis of observed climate data against the full gamut of M-cycles.
I like my maths to be simple. If it isn’t, I try to make it simple. The last thing I need to do with this data is to hit it with cross-spectral analysis. I’ve got 17 out of 17 glacial terminations hitting the 65N cycle absolutely on the button. That’s simple, and to my mind it’s deadly. Even better, all of them were identified by two independent sets of others and mapped to 65N by those same others. Better again, one of those sets of others wasn’t even looking for what I found in their data, so there is no possibility of them having done anything to the data to make it fit. All that a cross-spectral analysis would do is open up a can of worms that others could use to obfuscate. If you want, you are welcome to do a cross-spectral analysis. Me, I’ll keep it simple thanks.
Alas, the “simple math” that you present is largely a visual comparison of two time series. Cross-spectral analysis provides quantitative measures not only of the power levels of various frequency bands, but also the coherence (spectral correlation) of corresponding signals in those narrow bands. It is the latter measure that is critical in establishing systematic relationships between between component signals. Without significant coherence, one cannot cannot convincingly claim any causal relationship between the two series.
The frequency bands you speak of are regular frequency bands. My point is that Earth’s climate is chaotic and non-linear, and the main cycle I looked at is irregular. But the glacial terminations hit that irregular cycle absolutely spot on in all 17 of the 17 identified events. That matters.
I’m trying to get some non-linear thinking into the way that climate is analysed. Regular frequency bands fit too easily with linear thinking, and their relevance needs to be considered.
The frequency bands in cross-spectrum analysis are NOT the discrete lines characteristic of regular sinusoidal cycles; they are of finite width characteristic of irregular stochastic variations, such as encountered in most geophysical signals. System non-linearity introduces various phase-bound harmonics in response to excitation. Thus bi-spectral techniques are required to distinguish signal components that are produced by known excitation from those that are unrelated. That issue lies at the very heart of rigorous causal attribution in chaotic dynamic systems and cannot be resolved in the time domain alone.
Mike
How are they to have any fun if they aren’t allowed to make scary predictions?
All they have is terrifying children and the gullible, why prevent the most fulfilling aspect of their lives?
Everything is a pendulum. Waves on water, rabbits go up and rabbits go down, and hawks/coyotes follow. Day/night, seasons, temperatures, birds/bees wings go up and down. EM waves, sound waves, and so on. Orbits, precessions, convections, and comets all are cyclical. ENSO, PDO, AMO all are cycles. Nature is cyclical. The trick is to find the frequencies, phases, and interactions.
Forecasting a coupled, non-linear system with simple averages and linear regressions is a losing proposition. Models driven by simple linear increases in concentration of CO2 are not going to take all the interactions into account properly. Models that don’t use variable periods in cycles for various variables that interact won’t generate proper probabilities.
This is just one reason I am skeptical of models that turn into linear projections. That just can’t be science.
The underlined italicized text is a small mistake in Ellis and Palmer: “The IPCC data gives a similar figure of 2.8 W/m² for all greenhouse gases, but neither of these values include water vapour feedbacks … But since interglacial warming events average about 5000 years this represents just 0.006 W/m² per decade of additional feedbacks and warming, which is about a third of the energy required to power a honey bee in flight (Roberts and Elekonich, 2005).”
The 0.006 W/m² bee analogy seemed like a way to illustrate the tiny perturbation represented by the average annual 0.0035 W/m² perturbation from forcing by CO₂ emissions.
So I looked up Roberts and Elekonich, and they report the aerodynamic power of the honey bee as 0.2 Wg¯¹ — that is, per gram not per meter-squared.
Ellis and Palmer mistakenly equated Wm¯² to Wg¯¹.
The mean weight of adult honey bees is 120 mg. The thorax where power is generated is about 4×4×4 mm. Energy flux in W/m^2 per bee is then 0.2 W/gm × 0.12 gm ÷ 16×10¯⁶ m² = 2000 W/m². For four radiating surfaces front and rear neglected), that’s 500 W/m² per surface.
If emission is over the whole body of a honey bee (12.5 mm × 4 mm× 4 mm), the emission works out to 120 W/m² per surface (for four surfaces).
Hot stuff, the honey bee. The analogy with the annual average 0.0035 W/m² of CO₂ emissions becomes even more interesting.
It can now be said that climate modelers claim to detect a perturbation to Earth’s climate that’s 2000/0.035 = 57,143 times smaller than the energy required to power a honey bee in flight. Bonus! 🙂
There’s a mistake above, which it’s too late to edit out. So, here’s the corrected comment — same result slightly different numbers. If the moderator could remove the older one.
The underlined italicized text is a small mistake in Ellis and Palmer: “The IPCC data gives a similar figure of 2.8 W/m² for all greenhouse gases, but neither of these values include water vapour feedbacks … But since interglacial warming events average about 5000 years this represents just 0.006 W/m² per decade of additional feedbacks and warming, which is about a third of the energy required to power a honey bee in flight (Roberts and Elekonich, 2005).”
The 0.006 W/m² bee analogy seemed like a way to illustrate the tiny perturbation represented by the average annual 0.035 W/m² perturbation from forcing by CO₂ emissions.
So I looked up Roberts and Elekonich, and they report the aerodynamic power of the honey bee as 0.2 Wg¯¹ — that is, per gram not per meter-squared.
Ellis and Palmer mistakenly equated Wm¯² to Wg¯¹. And 3×0.006 = 0.018, not 0.18.
Carrying on, the mean weight of adult honey bees is 120 mg. The thorax where power is generated is about 4×4×4 mm. Energy flux in W/m² per bee in flight is then 0.2 W/gm × 0.12 gm ÷ 16×10¯⁶ m² = 1500 W/m². For four radiating surfaces (front and rear neglected), that’s 375 W/m² per surface.
If emission is over the whole body of a flying honey bee (four 12.5 mm × 4 mm surfaces), the emission works out to 120 W/m² per surface.
Hot stuff, the honey bee. The analogy with the annual average 0.035 W/m² forcing of CO₂ emissions becomes even more interesting.
It can now be said that climate modelers claim to detect an annual perturbation to Earth’s climate that’s 1500/0.035 = 42,857 times smaller than the energy required to power a honey bee in flight. Bonus! 🙂
That seems to be about in the ball park for a large butterfly flapping its wings! 🙂
If you count Ellis and Palmer’s honey bees, you will see that there are about 8 bees to the square metre.
I jest. I think what Ellis and Palmer were saying was that the bee’s efforts per gram, if applied to a square metre, ………..
So, the Earth needs a good cardiologist!
We aren’t having too much luck with all the proctologists
Mike, an interesting paper. You say:
I’m sorry to be the bearer of bad tidings. I just did a CEEMD analysis of the EPICA data. Here are the results.
As you can see, both the 41,000 year and the 100,000-year cycles are very real.
And what’s not real is the 21,000-year cycle. I don’t mean that the 21,000-year precession isn’t real. I mean that there’s no sign of it in the EPICA temperature records.
The oddity of this to me is the 71,000-year cycle … especially since the beat frequency of a 71,000-year cycle and a 41,000-year cycle is a 97,000-year cycle … which is the accurate measurement of the “100,000-year cycle”
I do love a world full of mysteries.
My best to you,
w.
Full of mysteries indeed. The problems with using CEEMD to look for the 21,000-year cycle are that (a) it’s not a constant 21,000-year cycle, as the paper says it’s influenced by other cycles, and (b) thanks to the non-linear nature of Earth’s climate, the cycle misses beats which will create havoc with cycle-seeking software. Note that although precession plays the major role in the 65N cycle, it is not the only influence so 65N doesn’t fit it precisely, and the specific cycle I was matching was the 65N cycle not precession.
The crucial factor is that every single one of the 17 glacial terminations as identified by the authors I cite hits a 65N minimum exactly on the button. I consider that to be very difficult to argue against successfully. Note that since I played no part in identifying either the glacial termination dates or the 65N dates, I could not possibly have influenced them in any way and I could not have cherry-picked anything, etc.
We are dealing with a chaotic non-linear system, and it is very reasonable to suppose that cycle-seeking software is quite simply not going to be able to see some of the cycles. But 17 out of 17 dates absolutely smack on is surely enough for humans, if not software, to understand as being very significant.
I would have liked to look even further back in time, but the most accepted ice age temperature data appears to be by Liesecki and Rahmo, and they state in their paper that they adjusted the dates to give a better match to the 41,000-year cycle. I emailed Lorraine Liesecki to see if she could provide the unadjusted data, but I got no reply (maybe I’m in a spam filter?).
PS. My paper refers to 100,000-year and 41,000-year inter-glacial cycles, not to 100,000-year and 41,000-year temperature cycles. Yes, there are 100,000-year and 41,000-year cycles visible in the temperature data, but I was looking specifically at the dates of glacial terminations.
There are no 71kyr or 97kyr intervals between interglacials of the last 800kyrs, but curiously their sum is twice 84kyrs, and 84kyrs is a common interglacial interval.
Ellis & Palmer, 2016 is open access at Elsevier (ScienceDirect). But only in html; their PDF download is broke. I had to go to researchgate to get the PDF.
Re: Wikipedia – For years the Quantized Inertia (QI) hypothesis lingered at Wikipedia; read by few. Recently the idea got some funding to validate it – with very promising results too. But Wikipedia removed QI because it’s ‘not official physics‘!
String Theory – of course – has a massive article at Wikipedia. But there are tens of thousands of PhDs awarded studying it. It’s official physics – although nothing in it will ever be validated because it can’t be and it’s really just playing with maths – not physics at all!
Modern Science is owned by intellectual Stalinists.
Planetary cycles creating Earth’s orbital variations would be also ordering longer term changes in solar activity, in different combinations, giving rise to interference patterns.
There is a mirror image symmetry centered at interglacial 11C, including minor peaks, which has broken down since the Eemian. The red lines in the image are at 369kyrs, or 9 x 41kyrs.
The most common interval between the peaks measures at about 84,000 years.
Using the 1726.62 year cycle of grand solar minima as a unit;
49 x 1726.62 = 84,604.
And the smaller intervals like between 15a and 15c:
18 x 1726.62 = 31,079.
Adding them together is 67 x 1726.62 = 115,683 years, which coincides very closely with 25 x the 4627.33 year cycle of the four gas giants. That 115.6kyr interval exists between several of the larger and the smaller peaks, like before and after 11c, as well as between 17c and 15a, and between 15e and 13a.
The graph is from figure 2 here, zoom it out and make an 84-85kyr marked paper gauge from the time scale to measure between the interglacial peaks.
https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2015RG000482