Guest Post by Willis Eschenbach
Normal carbon has six neutrons and six protons, for an atomic weight of twelve. However, there is a slightly different form of carbon which has two extra neutrons. That form of carbon, called carbon-14 or “14C”, has an atomic weight of fourteen. It is known to be formed by the interaction of high-energy cosmic rays with the atmosphere.
Therefore, the production of the carbon isotope 14C goes up and down with the number of cosmic rays.
Thus, other things being equal, the production of 14C could be a proxy for how many cosmic rays are passing through the atmosphere. And the number of cosmic rays striking the earth is regulated by a combination of the magnetic fields of the earth and the sun. When the combined magnetic field is strong, it deflects the cosmic rays away from the earth. When it is weak, more cosmic rays strike the earth.
So let me start, as I prefer to do, with the largest, longest view of the underlying raw data. In this case it is something called the “INTCAL13 Calibration Curve”. It is a record of historical variations in the levels of the carbon isotope 14C.
Figure 1. INTCAL13 calibration curve. The interval between values is five years in the recent part of the record (since 11950 BC). In the middle part of the record, from 23050 BC to 11950 BC values are ten years apart. And in the earliest part, from the beginning to 23050 BC, values are 20 years apart.
The large variations in the curve are said to be from slow changes in the earth’s own geomagnetic field over the millennia. However, our knowledge of geomagnetism millennia ago is not of the finest … given that, it does seem like a possible explanation.
Keep that INTCAL13 calibration curve in mind for a moment, and let me move on to discuss a guest post over at Judith Curry’s often-excellent website, by someone named “Javier”. The post is all about solar cycles. And there’s a new post on WUWT discussing Javier’s solar cycles. These are solar cycles that are two thousand four hundred years long, to be exact. How do they know that? Well, here’s Javier’s money graph.
Figure 2. Javier’s graph showing a claimed 2400-year cycle in the 14C record, which in turn is claimed to be a solar cycle.
So the obvious question is … how on earth did they get from the curve shown in Figure 1 to the curve shown in Figure 2? Javier says it is done by “removal of the long-term trend” … but how was that done? I went to the cited work of Clilverd et al. to find out the answer.
First, because the sun and the cosmic rays are negatively correlated, they flip the 14C record over as shown in Figure 3. In this orientation, warmer is at the top of the chart and cooler is at the bottom. That’s just a graphic convenience, no problem.
Figure 3. Inverted INTCAL13 calibration curve.
Then they throw away more than three-quarters of the data, leaving only the chunk since 9600 BC as shown in Figure 4.
Figure 4. Inverted INTCAL13 calibration curve since 9,600 BC.
Following that, they fit a linear trend to the data, and detrend it. Then they subtract out a purported 7,000 year signal of unknown origin. Figure 5 below from Clilverd et al. illustrates the procedure. Note that the upper panel of Figure 5 matches my Figure 4.
Figure 5. Figure 1 of Clilverd et al.
I note in passing that although Javier asserts a “correct” cycle length of 2400 years, Clilverd shows a 2300 year cycle. I guess that’s why Javier’s version is “adapted from” … but I digress.
Let me recapitulate the bidding. To get from the inverted 14C record shown in Figure 3 to the record used by Clilverd et al, they have
- thrown away three-quarters of the data,
- removed a purported linear trend of unknown origin from the remainder,
- subtracted a 7000-year cycle of unknown origin , and
- ASSERTED that the remainder represents solar variations with an underlying 2,300 year period …
I suspect that y’all can see the problems in each and every step of that process. First and foremost, why throw away three-quarters of the data? That alone disqualifies the study in my mind. But let us continue listing the difficulties:
Where did the claimed linear trend come from? What justifies removing it? Why use an exactly 7,000 year cycle, and where did it come from? How does one diagnose a 7.000 year cycle when you only have about 12,000 years of data, not even two full cycles? How do they know that the 7,000 year cycle is NOT solar-related and the 2,400 year cycle IS solar-related?
And finally, what evidence do we have that the remainder has anything to do with the sun?
But wait, as they say on the TV ads, there’s more. Let’s set the work of Javier aside entirely and return to the question of cosmic rays, which Javier does not discuss. Remember that the relationship between cosmic rays and the climate is supposed to work as follows:
In times when there are more cosmic rays, the rays cause more cloud nuclei to form. As a result more clouds form (and in addition, more 14C forms) and the world is colder. But in times when there are less cosmic rays (indicated by less 14C), there are less clouds, and thus the world ends up warmer.
And according to that theory, people claim that the final dip in the 2400-year cycle seen in Figures 2 & 5 is the cause of the cold times around the Little Ice Age. Back then it was a couple of degrees cooler than at present. If that theory is correct, this means that a change in ∆14C of about 10 per mil reflects a change in cosmic rays that is enough to cause a global temperature change of 2°C.
Now that all sounds good until you take another look at Figure 3. Let me replot it, and this time I’ll include the 10 per mil change in ∆14C, and hence in cosmic rays, rumored to be responsible for the Little Ice Age.
Figure 6. Inverted INTCAL13 calibration curve. Gray lines show the variation in ∆14C of 10 per mil claimed to be from cosmic rays and said to be responsible for the 2° cooling during Little Ice Age. The large swings are said to be due to changes in the strength of the geomagnetic field.
I reckon you folks can see the difficulty … according to this, about twenty thousand years ago it should have been about 100°C colder than today …
Now, about the only way out of this dilemma is to say that the peak-to-peak swing of about 500 per mil in ∆14C is from some kind of non-cosmic ray variations. You know, like the claimed 7,000 year cycle that was removed in Figure 5 that was ascribed to … hang on, I want to get this right … OK, they said it was from “changes within the carbon system itself”.
(Let me say that I like that particular bit of bafflegab a lot, “changes within the system itself”. Seems like that would cover a host of unpleasant variations in any dataset you might find … but again I digress.)
So to recap: IF the claims are true that the changes in ∆14C shown in Figure 6 reflect changes in cosmic rays and that the changes in cosmic rays result in the claimed changes in temperature, then twenty thousand years ago the earth should have been 100°C cooler. Even if I’m wrong by 100%, it is still saying that it was 50°C cooler back then … didn’t happen.
Since that is not possible, then it seems we must assume that “changes within the system itself” are causing the huge swings in ∆14C.
But if that is the case, then it is more than possible that these unknown changes within the system are also responsible for the smaller swings currently ascribed to variations in cosmic rays.
Anyhow, that’s my cosmic problem with rays. Here I have no problems. It’s two AM, I’m a night owl. There’s been rain for three days, wonderful rain. And there’s still rain in the area, a small cell passing north of us. But the wind has shifted. It was blowing strongly from the south or southwest for the last three days. Now the wind is just a mild breeze, and from the west. There are big gaps in the clouds, and the moon, aah, for the first time in a while the moon is finally showing its face. I can hear the distant hungry grumbling of the surf as it nibbles on the ribs of the coastline some six miles (ten km) away … a good night to be alive here in the redwood forest, with the giant trees standing stark and clear in the pale wash of moonlight, and silvered cumulus drifting across the sky.
Best to everyone,
w.
My Usual Request: Misunderstandings are the bane of the web. Please further understanding by quoting the exact words that you disagree with. That is the only way that we can all be clear about the exact nature of what you object to.
My Other Request: Bald statements that someone doesn’t know what they are doing, even if true, are of little use to anyone. If you think someone is using a wrong method or a wrong dataset, please further everyone’s understanding by demonstrating the right method or by linking to the right dataset.
Even with the statistical manipulations, there are major oopsies in tracking trends at ~9000 and ~3000 years.
So what is the origin of that 14C curve that goes back 50,000 years. It seems to me that 50.000 years is about the limit of the ability to radiocarbon date anything.
But how do they get back beyond around 5-6,000 years which is the limit for the bristlecone pine tree ring calibration capability.
You can radiocarbon date individually each ring of a tree, and obtain believable data on 14 C over time for about 5,000-5500 years.
So where does that other 45,000 years of older data come from.
Now I have some pieces of Kauri wood that are 45,000 years old. But they have been dead for probably 42-43 of those millennia.
But I tend to agree with what I think Willis is saying.
Basically baloney on these 2300 and 2400 year solar cycles. And yes it even looks like a lousy fit to me.
G
I don’t think you can just look at one thing when it comes to describing climate. Cosmic rays are part of the equation, not the entire statement. Further, our understanding of the role of cosmic rays is far from complete.
I think they may have misunderstood what the “INTCAL13 Calibration Curve” is for.
It appears from my (brief) research that this is the curve used to change from an apparent age from carbon dating assuming linear values to the actual age. I don’t see how this can be used for the purposes given here.
Good question. The calibration curve shows the difference in time between carbon age and actual age for specimens of known antiquity.
The connection is that the difference between carbon age and actual age is said to be from different levels of ∆14C at various times in the past. Thus the difference in time can be used to calculate the varying levels of 14C in the past.
w.
Good work Willis, I was sure you’d be onto this one.
Yes it seems that the curve is not applicable in the way it was used. Each carbon age is based on an exponential decay from the presumed integration by the living system ( thee, plant, whatever ). The correction curve reflects the non constant amount of C14 generation over time.
This curve is questionable in itself and more so the further back.
So the curve at any point exp decay of 14C at that time, plus the integral of decay of any 14C created since. Working this backwards starts to sound at a lot like working out a temperature history from borehole temperature data drilled today. The result depends more upon your favourite assumptions and the model you use than anything else.
How you reconvert that to get 14C production as a time series needs a bit of thought but I’m fairly sure that detrending is not the answer. I’m not sure what the answer is but I’m fairly sure it’s not Sam Sausage.
It’s a while since I read up on this but my recollection was that there’s a point about half way up that curve , circa 15ka BP where it all gets very fluffy and speculative.
Recent record is pretty good since it can be corroborated by dendrochronology, which actually means the study of time by trees , not the study of temperature. 😉
dendrochronology is pretty exact. That goes back about 11ka and is largely based on our favourite thermometer: the bristle-cone pine.
http://www.radiocarbon.com/tree-ring-calibration.htm
PS a lot of that linear slope is probably due to not using the correct half-life : for historical reasons.
The interesting thing about that curve is that if you have a d14C measurement of 400 per mil you can choose between 14ka and 43ka !
If you are between 400 and 550 per mil , you can chose between about 5 different dating results.
I’m starting to recall why I don’t believe carbon dates beyond 15ka.
… and if you look at the detailed “calibration” curves (http://www.radiocarbon.org/IntCal13%20files/intcal13.pdf ) you see that the data quality beyond 10’000 years is getting quite poor.
“Warmer” and “cooler”? The graph has nothing to do with temperature.
Same comment. I’ll also note that it was colder 20,000 years ago, we were just coming out of the last glaciation. Compare the graph here with the 110k and 120k graphs on the paleoclimate page. There seems to be some correlation.
But HOW do they get the TRUE age of those carbon samples back earlier than 5500 YA from BCP trees.
G
‘could be a proxy’….
The first part of winter 2008-2009 has been characterized
by a stable and cold polar vortex which allowed
the persistent formation of PSC particles. In
mid-January of 2009, however, the most intense sudden
stratospheric warming (SSW) ever observed occurred
[Manney et al. 2009, Di Biagio et al. 2010].
Lidar and GBMS measurements at Thule observed
the occurrence of the major SSW, sampling air inside
the polar vortex at first and following the propagation
of the SSW down to the lower stratosphere afterwards.
The contour plots in Figures 14, 15, and 16 show the
changes of the atmospheric chemical composition over
Thule and temperature associated with the SSW. Figure
14 shows a sudden increase in N2O mixing ratio
(mr) which occurred on January 24 at around 35 km altitude
and over the whole stratosphere between days
26 and 28. At higher levels, the vortex splitting and the
vortex edge transit over Thule was marked by a rapid
decrease in CO mr. CO data (not shown) indicate that
in the upper stratosphere (45-50 km) the vortex broke
up over Thule on January 19-20.
Concurrently, as warm, O3-rich air from outside
the vortex moved over Thule during the SSW, the GBMS
measured an increase in O3 mr in the upper stratosphere
which reached a peak of ~8 ppmv at 35 km (Figure
15). The O3 concentration in the lower stratosphere
shows a clear sign of the passage of the vortex edge
over Thule on January 26, in agreement with the N2O
concentration displayed in Figure 14, but there are signs
of out-vortex air intrusions also a few days earlier. In
Figure 16 lidar temperatures show a sudden increase on
late January 22. However, the warming in the upper
stratosphere started a few days earlier, as shown by the
superimposed Aura MLS temperatures, and lidar measurements
missed the onset of the SSW due to instrumental
upgrades between January 16 and 22. The
maximum physical temperature of 289 K was recorded
by lidar near 40 km on January 22. In the following
days, the warming progressed downward reaching
about 15 km altitude on January 29, when the temperature
profile became nearly isothermal, particularly in
the altitude layer between 15 and 45 km.
http://www.earth-prints.org/bitstream/2122/9123/1/2014ann_geoph_muscari.pdf
The level of neutrons in Oulu in January 2009.
http://cosmicrays.oulu.fi/webform/query.cgi?startday=01&startmonth=01&startyear=2009&starttime=00%3A00&endday=01&endmonth=02&endyear=2009&endtime=00%3A00&resolution=Automatic+choice&picture=on
GCR breaks O2 in the upper atmosphere. This gives rise to N2O, which (as O3) radiates in the infrared.
This article is a moral warning about time series analysis.
Robert, I think it is more a moral lesson about cherry picking data. Why throw away most of the “data”?
Thanks Willis and Anthony. A very interesting read.
I think that you would get similar results using a high pass filter. The object is to expose coherence between cosmic rays and C14. This wouldn’t give the entire relationship.
We need a T.A.R.D.I.S. to get the proper history. Grant time!
(In a mood. Sorry)
Willis, as to your 100 degrees colder comment, wouldn’t the fact there is a finite area that clouds can cover limit the amount that the temperature can drop ? I agree with the rest of the post though..thanx
Another reason why the cosmic ray hypothesis of climate change seems unlikely.
Hence my preference for the idea that solar effects act upon the ozone creation / destruction process in the stratosphere differently above equator and poles.
The consequence is a change in the gradient of tropopause height between equator and poles so as to allow changes in jet stream behaviour which leads to cloudiness / albedo changes.
Willis, I would like to use this as an example of how to deconstruct research and apply critical thinking skills in th high school chemistry and physics I teach. Would you give permission to reprint and share?
Your students aren’t going to learn much from such awful example. Why don’t you read what is being criticized to see if anything is being deconstructed? Is that how you teach your students, to accept one side without reading the other?
I read your stuff.
Like I said.
Junk.
Start with the basics.
Do a simple post.
Show (ATTACH) all your data
show ( ATTACH) all your code.
Demonstrate how you find the cycle you claim.
you cant
you wont
Why should you show us your data when all we want to do is find mistakes.
Sound familair..?
Sorry bud, Willis has been really really consistent in the application of his skepticism.
One chart.. just produce Figure 2 from above ( citing your figure 1 )
Produce that ONE CHART from scratch.. Dont cut and paste shit… Just produce ONE CHART from
scratch.
FROM SCRATCH.
That means.
1. get the raw data. POST IT
2. Document Via CODE how you get from the raw data to the plotted data
ONE CHART
you cant
you wont.
Willis wins.
Steven,
Everything I said in that article has been published in the scientific literature and was adequately cited. If you have a problem finding the source for anything, just ask.
That you consider it junk is actually encouraging as you seem to be so wrong about what you believe in climate science. I would be very worried and checking everything again if you were endorsing it. Same with Willis regarding anything solar. He is terribly biased. But it seems from his comments that Willis didn’t bother to read my article. That’s a winner for you, you see?
darrowfarms October 17, 2016 at 4:12 am
darrowfarms, you are most welcome to use any of it.
Javier October 17, 2016 at 5:22 am
Javier, your objection to my work is totally unclear. Please note the part of the head post that says:
Once you make it clear just what you think is wrong about my post, we can discuss it. Until then I have no idea what you object to.
w.
As you are not darrowfarms, that comment wasn’t directed to you. For you I have a question, Willis. Did you read my article in its entirety before writing yours? I think people here have the right to know that.
Looks like total BS to me. Believable to those who desperately want to believe.
What was the variation of the target gas, CO2, over the time period in question?
That is the primary natural source. It’s nitrogen atoms ( also weight 14 ) getting blasted by high energy neutrons caused by cosmic rays.
Non natural sources are post WWII atmospheric test which roughly doubles 14C before 1963.
Differences doses of ionizing radiation in winter and summer, during the solar minimum (1996).
http://pics.tinypic.pl/i/00830/ylq4i6nd49v3.jpg
They might indeed exceed the annual dose. However the risk they run is a reduced risk of cancer and other effects of radiation. Please see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2477708/.
As requested, the words I disagree with:
“Then they subtract out a purported 7,000 year signal of unknown origin.”
I disagree because it is not of unknown origin, it is referenced to Beer 2000, Long-term indirect indices of solar variability Space Science Reviews, vol 94.
The abstract contains the following
“Comparison of different nuclides (e.g. 10Be and 14C) that are produced in a very similar way but exhibit a completely different geochemical behaviour, allows us to separate production effects from system effects.
The presently available data show cyclic variability ranging from 11-year to millennial time scale periodicities ”
I presume the 7000 year cycle is one of the millennial time scale cycles described in this article, as indicated by the reference.
So what is its origin? We know there’s a trend – we can see it.
“We know there’s a trend” should be “We know there’s a “cycle” (and a trend)”
“So what is its origin?”
You must go to the original paper to see. That is how science works. Clilverd et al are telling the reader that the source of the 7000 year cycle can be found in Beer 2000. You must go and check to see if you think it reasonable or not. That is why we have references in papers. It is wrong to say it is of unknown origin when the origin is given very clearly in the paper.
Ok – but when you wrote that you disagreed with the statement that the 7k year signal was of “unknown origin” I assumed it might have been because you knew the origin. That’s also often the way things work.
Yes, John Finn, a slight mix-up between origin for this paper and proper origin. The reason the origin is unknown to Willis is because he didn’t look it up. I don’t think that counts as “unknown”. It is, alas, also unknown to me because I have not looked it up 🙂
seaice1 October 17, 2016 at 5:01 am
Thanks for the comment, seaice1. However, Clilverd et al. say in the caption to Figure 5 that the 7000-year variation is:
So I fear that yes, according to Clilverd that 7000-year signal IS of unknown origin.
Now according to Beer 2000 it may not be of unknown origin … but that is exactly the problem—there is little agreement on the matter.
Regards,
w.
Clilverd et al said they got it from Beer 2000. There are two possible interpretations for “origin of the cycle” 1) the physical basis for the cycle and 2) where Clilvert et al got it from. We can recognise tides without knowing the theory of gravity. Yet if someone in ancient history published tide tables we would not dismiss them because of the unknown physical basis for the tides. They are observed to exist. So you could possibly mean that the cycle is real and has justifiable data to support it, but that the physical basis is not known.
Some more specific words “How does one diagnose a 7.000 year cycle when you only have about 12,000 years of data, not even two full cycles? How do they know that the 7,000 year cycle is NOT solar-related and the 2,400 year cycle IS solar-related?”
The answer is that we do not know what data was used to diagnose the 7000 year cycle without reading Beer 2000. You imply that the cycle was diagnosed by Clilvert et al, when it was not. They used a cycle that had been identified by Beer. This suggests to me that you did not intend to convey the idea that the cycle may be real but the physical basis was unknown.
Your use of the words “unknown origin” are either wrong or misleading. From the words I quote in this post I think they are wrong, but hey, maybe you prefer misleading.
blockquote> Clilverd et al said they got it from Beer 2000.
Quite. Chilverd et al also say “possibly caused by changes within the carbon system itself” so, having referenced Beer 2000, they have no more knowledge on the “physical basis” for the cycle than the postman. They, have clearly failed to glean anything concrete from Beer.so we must assume that the 7000 year “cycle” is of unknown origin.
blockquote> The answer is that we do not know what data was used to diagnose the 7000 year cycle without reading Beer 2000.
Well – we do have a bit of a clue from the Beer Abstract.
Cosmic radiation depending on the geomagnetic field.
http://pics.tinypic.pl/i/00830/uekext55etmo.jpg
Thanks, ren, but that doesn’t rescue the theory. It claims that the cosmic rays vary so much because of the geomagnetic field … but if that’s the case, then the world should have been much, much, much colder ten thousand years ago.
w.
Just an idiot-level question here: cosmic rays consist of electrons, protons, a range of other nuclei, small amounts of antimatter, gamma rays, and dear knows what. Do all these things vary in exactly the same way? That is, is “cosmic ray intensity” really one thing that can be represented well by a single number? And another idiot-level question: the error range on the cosmic ray intensity line in ren’s graph is awfully narrow much of the time; do we *really* know it that well?
If I recall properly, some years back (when I was a nuclear engineer) I took an interest in Carbon -14. I stumbled on a calibration curve, but I am not sure of the source. It had to do with dating of organic matter. The basis of C-14 dating makes a pretty big assumption in relation to the concentration of C-14 in the atmosphere.
If you have a decaying radioactive sample and you want to know it’s inception date, you must determine the present concentration of C-14, (know the half-life of C-14) and know the concentration of the C-14 when the sample was created. Then the age is a simple calculation.
Variations in the C-14 atmospheric concentration perturb the accuracy of the C-14 dating method so proxy calibration methods must be used to establish the basis of C-14 concentration in time. So the accuracy of C-14 is reliant on less reliable data which constitutes the calibration.
I don’t believe there is yet a remedy for this conundrum. It has been a while since I looked into it but I don’t believe the C-14 calibration curve is all that reliable. Correct me if I am wrong if you please.
I think up to 11ka is fairly good because of dendro cross-ref after that it gets speculative.
There are alternative radio datings but they are just as loose or worse.
Javier may have been right to chuck out older data in fact but I don’t recall him giving a reason. Also the detrend may be merited is the slope is to correct for the historical , incorrect half-life. Also in that case it should be direct calculation not a “detrend” over some arbitrary bit of the data.
Right for the wrong reason?
The circa 7ka “cycle” seems like it may run further back if the data can be trusted. That is the most obvious signal which needs explaining , not chucking out.
What you do is find a sample with a well known age, and measure the ratio of C-14 in it, and work backwards from there.
No, you calibrate with wood from tree-rings which have an exactly known age. That goes back to about 10,000 BC. Beyond that the calibration curve is based on speleothems and sediments and is decidedly shaky. Which is probably the reason they “discarded three quarters of the data”.
tty, That is my understanding. Going back farther is slightly better than speculation.
But how good are the dendrochronologies? I recall that there are significant problems with autocorrelation mistie potentials? I am under the impression that any particular 100 year tree-ring interval can usually be matched to a half dozen episodes in the span of 1000 years. It is a non-unique result with significant probabilities for more than one possible match. So it helps to have corroborating evidence to choose the right period. How good is the corroborating evidence?
The way I was told the story of C14 calibration (some 40 years ago), when C14-dating in its infancy, the researchers went to Egyptologists, as them for samples of wood with a known date. The first results were hundreds of years off the Chronologies. Hence the need for a calibration curve to adjust for changes in atmospheric C14 in the past. But it all hinged on the Egyptologists having the correct dates in the first place. Even today there is disagreement in absolute ages by as much as 10% (400 years in 4000). https://en.wikipedia.org/wiki/Egyptian_chronology
Without doubt, Egyptian Chronologies are aided by C14 dating today. But are we dealing with floating benchmarks? Science A calibrating off of Science B and Science B checking themselves with Science A?
It reminds me of the old story of the clock shop in a town with a factory. The Clock Shop had all it’s clocks on the wall running and showing the same time. A fellow comes into the shop admiring the different clocks and appreciating they all chimed the hour at the same time. The fellow asked the owner how it was he was able to set all his clocks to the correct time. The owner say, “I listen to the factory whistle for the end of shift.” The fellow paused and said, “I am the one who blows the whistle… And I set my watch from your store.”
tty: How exactly does you comment differ from what I wrote?
C-14 calibration is mostly done using dendrochronogical “direct” meaasures. InterCal13 also uses other proxies including speleothems. Standard radiocarbon dates deliberately do not use the correct halflife. The original estimate was 5,568 years, while the current accepted estimate is about 5,730 years (there are also estimated errors for each estimate). So, the “first” calibration is actually converting from the old half life to the current accepted one. The retention of the older half life is permit simple comparisons between older data and modern data. The second calibration is derived from direct measurements of carbon isotopes in tree rings (the standard set are Bristlecone pine data from the White Mountains). That set reveals that C-14 production and accumulation was never a “neat” process. Currently a continuous series of tree-ring assays including the Bristlecone data, bog oaks and other sources extends over 14,000 years, Corrections from uncalibrated age estimates can have pretty significant effects in interpretations. In fact the initial use of dendro-calibrated data turned Neolithic and Bronze Age European prehistory into a huge problem for theorists. Quite suddenly the oldest stone structures in Europe and the Middle East migrated northward and westward, roosting in Malta and the Orkney Islands. Pretty theories of how societies develop crumbled like wet paper.
Dendro-calibrated ages are actually more accurate. BUT, there are also fractionation and reservoir effects and those are really problems. Various types of plants tend to separate carbon isotopes: C3 (Calivin), C4 (Hatch-Slack), CAMS (Crassulacean acid metabolism) plants, and that can create problems when both C3 and C4 or CAMS plants occur together. Wood is always C3, but many grasses (e.g. maize) and shrubs are either C4 or CAMS and give radically different “ages” for material from precisely the same point in time. Because of this C-13/C-12 ratios are measured to further calibrate an age estimate. Reservoir effects were noted when living aquatic organisms from lakes with limestone basins were found to be apparently over a thousand years old based on the C-14 levels – apparently dead as well.
And, just for grins, there are hemispheric “effects” between the northern and southern hemispheres.
Yes, that someone would be me. Javier is my Christian name. I am a PhD and scientist known by full name to Judith and Anthony. If my desire of privacy bothers you then don’t write about me and don’t even read me.
Did you bother to read the article? The Bray cycle, also known as the Hallstatt cycle was discovered in 1968 from a consilience of evidence and has been studied since to this day by many authors. It does not rest on a graph from an article. That is a huge misrepresentation. With a completely different analysis others authors arrive to the same result. As the article cites, Usoskin et al., 2007 did a thorough statistic analysis and found the periodicity to be significant.
You haven’t done enough reading on the issue. 14C levels are affected by changes in carbon mass budget. Prior to 11,000 BP there were big changes in sea levels and oceanic CO2 release. As the corrections are not to be trusted prior to that date, most analysis stop at 9000-11700 BP.
Again you need more reading before writing your critics. There is a 400 year period of overlapping between 14C data and solar observations where the changes agree with the theory.
Even Leif Svalgaard recognizes that:
https://wattsupwiththat.com/2016/09/12/chinese-sunspots/#comment-2301158
So I guess you are alone in the world defending the opposite.
Again a misrepresentation. You did not read that in my article. That’s an hypothesis that I do not share so everything that you say based on that is irrelevant regarding my article and should not be a part of your critic.
Which authors? I am the sole author of the post you are criticizing and my claim is that the solar grand minima were the main cause of the LIA, but not the only one. Volcanic activity also contributed. Did you read my article?
This is completely bogus and crazy. You are building your own strawman before deconstructing it. Please leave me out of that mental exercise of yours.
You are the only one making those claims and then attacking them. It is solar activity, not cosmic rays, what is proposed to have a relationship with climate. Something very basic explained in great detail in the article that you are criticizing without even bothering reading (or understanding)
You seem to be criticizing something that you haven’t read, on a scientific matter on which you appear to not have even basic knowledge and without having read the necessary bibliography to discuss it. Your amateurish approach to science appears to be sufficient to convince the average reader at WUWT that you know what you are talking about. You do not. Read more, write less.
Javier,
You cannot hide behind anonymity and attack others (Mosh for example) and then cry foul when someone criticizes your work.
You can’t have it both ways amigo.
yes he can. Judith and Anthony allowed Him to Snipe from the Shadows.
Seems to me that if Anthony is going to allow anonymous Posters that They be held to HIGHER standard of propriety. that is the anonymous should never be allowed to single out those of us who do take the risk of having our comments and opinions live forever on the internet.
In the end Javier will slink away and when nature proves him wrong.. none of us will know.
When the warming continues and ice disappears.. will Willis show up to eat crow? Perhaps.. At least I know that I can challenge him and he will be around.
When it the cooling comes and the ice grows, will I show up to eat crow? you bet and Willis knows how to find me. You know he will call me out.
So here we are Willis and Mosh at 10 paces..
And Javier hides up in one the buildings as is allowed to shoot at the honorable duelers.
Frickin disgraceful.
were this my blog, he’d have to post data and code AT THE VERY LEAST or be banned for life.
[snip – saving you from yourself -mod]
I asked Javier to provide the code and data you seek, here is his reply:
On another article Javier wrote, I asked him for the data and code and he provided it, and the post has been updated with it.
https://wattsupwiththat.com/2016/10/07/evidence-that-multidecadal-arctic-sea-ice-has-turned-the-corner/
Yet somehow, I don’t think this will appease Mr. Mosher, who seems more interested in personal bashing lately. I doubt he’ll even come back to reply.
Ha ha,
Javier, made it clear WHY he does that,that Anthony and Dr. Curry know who he is,but agrees to omit his last name.
“Yes, that someone would be me. Javier is my Christian name. I am a PhD and scientist known by full name to Judith and Anthony. If my desire of privacy bothers you then don’t write about me and don’t even read me.”
meanwhile you hide your last name…….
What do YOU have to hide from,Rob?
Says who?
“yes he can. Judith and Anthony allowed Him to Snipe from the Shadows.”
Would you like some cheese to go with that whine, Mosher?
Welcome to WUWT
I have posted on this site for years as RobRicket….first and last name. Of course, I’m not the one hiding behind an academic title and belittling someone else’s work.
RobR
“Your amateurish approach to science appears to be sufficient to convince the average reader at WUWT that you know what you are talking about.”
“I am a PhD and scientist known by full name to Judith and Anthony. If my desire of privacy bothers you then don’t write about me and don’t even read me.”
A number of years ago I as working at a nuclear power station as a fire protection engineer. We had an issue with fire exposure to a cable chase room located above an office area. Both the regulator (NRC Inspector) and I had a concern about a fire damaging important cables. We commissioned a “state of the art” fire modeling study to better understand the exposure and to help determine the appropriate changes to better protect the cables. The model used was a generally accepted physics based model. In general you “built” a simulated environment and then lit various fires to see what might happen. The model usage is constrained by real world fire experiments to determine the usable “envelope” of the model. We hired a very respected, very expensive firm, complete with a PhD in the required area. The resultant report concluded that the cable chase tray sprinklers (water supplied heat actuated fire suppression sprinklers) would not adequately protect the cables from a fire in the office below. I (no PhD) questioned the result. I basically approached the problem much like Willis…ie a big picture simplistic viewpoint. The first item I noticed was that the model was failing the cables due to unacceptably high heat flux (what you feel when standing near a fire). I then asked the question…why were the cables damaged, yet the sprinklers located right next to them not actuated? I applied my simple, armature approach and did a gross calculation of the resultant temperature increase of the sprinkler head (it works by melting or bursting a temperature sensitive element holding back the water). My simple calculation on a blackboard in front of my supervisor and a few other engineers clearly showed that the same heat flux the was supposed to damage the cables would definitely cause the sprinklers to actuate long before the cables could be damaged. I/we were left with the question of why? I spoke at length to the PhD about my questions…who initially dismissed my “amateurish approach”. He was completely unimpressed with my back of the envelope heat calculation showing the sprinklers should actuate. After all, he was using a state of the art computer model, had a PhD is fire dynamics, and the government (NRC) had accepted the use of the model. I was obviously incorrect in my conclusion. Undeterred, I starting studying the underlying model. It took very little effort to determine that the model was using different heat transfer calculations for the cables than for the sprinkler heads. Basically, the cables were being exposed to the simulated heat flux, but the sprinklers were only exposed to the simulated gross area air temperature. This “feature” resulted in a report which concluded that the cables would be damaged, because the sprinklers did not actuate. The PhD was relatively unimpressed…but did allow that the sprinklers would likely actuate, protecting the cables. Oh well, what’s a few hundred thousand dollars for a lovely looking report with nonsense results. Unfortunately , I have found over 40 years of engineering experience that this kind of situation is all to common. Another story, in a nutshell, involved a steel plate and failure under differential pressure. Bottom line…a very simplistic approach involving standing and jumping on a plate, following by a test stand with me supplied the air pressure (ie blowing into a test volume with a tube) showed that the plate would not fail. My point here, is that anytime anyone has an issue with a critique that relies on a simplistic big picture approach immediately makes me suspicious. Couple that with an unwillingness to provide your name..well, these obviously don’t in and of themselves negate their work…but they sure set off some alarm bells.
Willis may be completely off base here, but based on my experience through many years of similar analysis, I certainly won’t dismiss his observations based on Dr. Javier’s objections.
Regards,
Ethan Brand
@Javier: interaction of solar particle wind with atmosphere is
a) producing 14C from 12N
and
b) alleged to be changing the nucleation of water droplets, and thus, possibly, precipitation patterns. The CLOUD project at the CERN is not yet conclusive.
These interactions being influenced by two parameters, solar activity and orientation of the Earth’s magnetic field, its is quite risky to separate these variables and to pick one for a causality analysis.
Is there data about declination angle of the Earth Magnetic field over the sane time period?
oOops : from 14 N, sorry
Michel.
“alleged to be changing the nucleation of water droplets, and thus, possibly, precipitation patterns.”
That is a hypothesis that I do not share, because the changes to cosmic rays are a factor of ten due to the changes in the geomagnetic field of the Earth over the changes in solar magnetic field due to solar variability. As I do not believe that the climate of the Earth depends primarily on its geomagnetic field, I cannot believe that hypothesis.
Javier
October 17, 2016 at 5:16 am
You haven’t done enough reading on the issue. 14C levels are affected by changes in carbon mass budget. Prior to 11,000 BP there were big changes in sea levels and oceanic CO2 release. As the corrections are not to be trusted prior to that date, most analysis stop at 9000-11700 BP.
————–
Javier, I could be wrong but, your statement above to me seems very wrong.
Meaning that the data after 11 000bp to present could be wrong too.
You see, the changes in the carbon mass budget while do effect the overall CO2 concentration in the atmosphere, actually that change and variation does not really effect the 14C concentration in atmosphere, as it, is effected only by the sink not the emissions, as it, is not a “product” of the overall CO2 emissions.
And sinks variation is very insignificant really in comparison with emissions, meaning the residence time of CO2 (including 14C) varies very little and it is not very significant in effecting or affecting the C14 to have an extra variation over time in the top of what causes it and its variation in the first place in the atmosphere, the cosmic rays+ etc. etc., whatever.
But the samples used for estimation of the C14 concentration in the atmosphere will be effected by the overall CO2 emission and what you call the carbon mass budget because is the CO2 emission and its variation over the time causing the actual CO2 concentration amount and its variation (including 14C) in the samples. (and in the atmosphere too, apart from effecting 14C levels there).
So a very flawed method to rely at for estimations of the 14C levels in the atmosphere, as also
the samples budged CO2 intake is not limitless.
As there is no any actual quantifying of the CO2 emissions variation over that long time period there realistically can not be even a pretense of quantifying of 14C concentration variation in the samples, let alone in the atmosphere actually.
Lack of such a quantifying does not allow a “translation” of actual amounts of CO2 emissions in actual amounts of CO2 concentration in atmosphere.
Without a correct residence time for CO2 in atmosphere it will never be possible,,,,, even then it will be a hard task…..with lots of headaches
Remember overall CO2 emission and its variation over time does not effect or affect the 14C in atmosphere, when in same time it may very well much so effect or affect the C14 concentration in the samples used for the estimating of the C14 concentration in the atmosphere.
cheers.
Whiten,
This is the reason why no solar reconstruction from 14C extends past 12000 BP:
http://i1039.photobucket.com/albums/a475/Knownuthing/Radiocarbon%20Reconstruction_zps3qtxsigo.png
(b) is the 1 sigma.
Source:
http://www.clim-past.net/9/1879/2013/cp-9-1879-2013.pdf
Roth, R., & Joos, F. (2013). A reconstruction of radiocarbon production and total solar irradiance from the Holocene 14 C and CO 2 records: implications of data and model uncertainties. Climate of the Past, 9(4), 1879-1909.
It appears that neither Mosh and RobR,have anything to complain about Javier’s, reply to Willis. They cry about a missing last name, as if that was of critical importance, to what he writes.
Grow up,Fellas!
I think you may have totally misunderstood the Intcal curve to start with.
That’s one point.
The second is that its SO much easier if you have the data, and have interpolated enough sample points to make a decent set, to throw it a a fast Fourier algorithm and see what the spectral density is without all this bodg9ng and effective high pass filtering.
That’s a criticism of both the article being criticised in this post, and the post.
I dont have time to verify the first assertion, so urge people to peer review this against what a C14 calibration curve actually is…
One of the primary conditions for doing F analysis is that the data be stationary.
One way to do this would be to take the first difference which effectively detrends it. A spectral analysis is the first thing I would have done ( after first diff ).
Actually as I noted above I think the trend is due to a maths correction and could be removed quite precisely.
I find the first graph absolutely unbelievable on the face of it. How can we prove that conditions were so very different, and got more different, as we look further back into the past? The error bars for each preceding year must grow ever wider, to the point where no confidence can be placed in the “data”. I suspect the point of no believable return is around the -7000 mark.
Furthermore, the half-life of C-14 is around 5700 years. Can anyone seriously tell me they can extrapolate out to nine or ten half-lives?
Nobody is making claims based on 14C prior to 11,700 BP, i.e. the start of the Holocene. Prior claims are based on 10Be in ice cores.
So why is the graph labeled delta_C14? Are two different data sets being spliced, a la Mann?
Oh, I think you will lots of geologists doing just that.
Because they do measure changes in 14C. It is used for carbon dating, and prior to 11,700 the dates are less and less reliable, but nobody reconstructs solar activity from 14C prior to 11,700 BP.
“They do measure changes in 14C”…I think you’re saying that C14 changes are deduced from 10Be? Sounds extremely Mannish to me.
“I think you’re saying that C14 changes are deduced from 10Be?”
No. That’s not what I mean. 14C is measured from organic remains, mostly wood, that have been dated by geological, archeological, and dendrochronological means. That’s how IntCal is built and updated. IntCal serves the purpose of carbon dating. Libby got a Nobel prize for that. Carbon dating can be used up to 50,000 yr BP.
14C is also a proxy for solar activity, but AFAIK nobody has tried to reconstruct solar activity from 14C for earlier than 11,700 BP.
10Be is completely independent from 14C in everything except that its production is also increased by cosmic rays.
“archeological and dendrochronological” I can believe for a few thousands of years (maybe 20,000 for the latter), but geological evidence must be based on equally (if not more suspect) assumptions about the initial state and subsequent interactions of samples. Not trying to be argumentative, I find the first graph frankly incredible just from its shape alone.
As I’ve pointed out a couple of times, there is an incorrect half-life for 14C which needs correcting for.
You need to check that out before jumping to conclusions.
Greg Goodman October 17, 2016 at 7:11 am
As I’ve pointed out a couple of times, there is an incorrect half-life for 14C which needs correcting for.
Yes the INTCAL13 graph includes the correction from the value determined by Libby (5568) and the presently determined value (5730).
I dunno if the recent replies are meant for me. The 14C half-life is an x-axis unit wrt graph 1, so only drastic difference from 5700 approx. would make the graph look much different. Just the “things were 20x different (y-axis) in the past” doesn’t pass the smell test. If they were all that different, how many of the necessary assumptions still apply? None, it would seem to me.
The term normal is not used in isotopes stable isotopes of carbon are C12 (98.9%) and C13 (1.1%). Naturally occurring isotopes of Carbon also includes C14.
I suppose somewhere there is a paper explaining C14 abundance over time. In addition to solar, there is geomagnetic and I suppose galactic variations (10My+ cycle). I would guess that the earth came out of a glacial period 12Ka factors into this.
Note that the interval between values for Fig 1 is 5 years from 11950BC, but coarser before then. So I have no problems with looking at the data set for just the last 12,000 years which corresponds to both the fine granularity data and the interglacial.
The purpose of the Clilverd paper is too project solar activity in the next century, and does so by looking at a proxy for solar activity over a 10,000 year period. In the paper, it is stated that the 7000-year cycle is mainly attributed to geomagnetic, so this is not entirely unknown. I did not find an attribution for the linear term, but this could be a long cycle characteristic.
If the assertion is that C14 variations due to solar activity have lower periodicity, then it is perfectly reasonable to filter out long cycle variation. Given that the 2300-year cycle is probably not geomagnetic, then it is likely to be solar.
The supposition is that solar variations might be correlated to climate. This does not mean C14 variation is correlated to climate, only the solar portion.
That is a very good assessment of Clilverd et al. Their projection to the future is very controversial and I do not agree with it, but their analysis of past solar activity is absolutely non-controversial and in agreement with the field.
I cannot accept that C14 fluctuations are not driven by geomagnetic fluctuations at 100 year and longer time frames. I don’t think we have the data to rule it out. Plus the Leschamp event (~41ka) adequately shows two paleomagnetic reversals in the span of a few hundred years. If a reversal can happen that quickly, then a reduction or increase in geomagnetic field strength by a factor of 2 in a few hundred years must be a plausible event. If so, the geomagnetic field fluctuations probably swamp any solar signal.
You don’t, unless you know you’re dealing with a continuous (ie. unchanging) waveform. That’s not the case here.
Or is the issue rather about a change in a variable perturbs the climate system balance? Does it really matter at what absolute value you make one variable change? Any time you change a variable, the system re-balances itself to the new dynamic. Are you conflating a cumulative value with an instantaneous trend in an apples versus oranges comparison?
Why does not the INTCAL13 Calibration Curve show a spike circa1960? If Greg Goodman’s chart (above) is correct, there was a huge spike of about 1500 per mil sometime around then. Perhaps the 20-year sampling period just happened to miss it or perhaps it was “corrected” away.
Because the INTCAL13 data stops in 1950 (0BP).
Seems logical to me. C14 will change due to cosmic rays, but it is also dependent on available carbon. That first graph looks amazingly similar to the curve coming out of the last ice age, thus outgassing of CO2 increases available carbon. …. natural increase in C14 that is independent of cosmic rays.
Dr Deanster October 17, 2016 at 6:19 am
No, it doesn’t. It starts changing about 20,000 years ago and changes in roughly a straight line from there to the present. The curve of temperatures for the last glacial termination, on the other hand, warms from ~ 15000 to ~10,000 years ago, and then is level or cools slightly since then. Not even similar.
w.
Willis, I think your analysis is a good example of critical thinking, but this one objection to their methodology is probably a bit hasty.
Look again at the INTCAL13 graph. After 9600 BC, the data is spiky on a short timescale that varies from a bit less than a century at the beginning to about a decade in the most recent past (eyeball estimates). Obviously, there’s a wealth of data there and it comes, mainly from overlapping tree-ring data [probably useless as palaeotemperature proxies, tree rings are an invaluable way of reconstructing the past]. But before 9600 BC, the curve becomes very smooth, and this reflects a much sparser data set.
Think about it. How does one get a “true” age (it’s called a calendar age) for the carbon in fossil remains or limestone? You can google it and read it yourself. Basically, it’s plant debris in varved sediments from a single lake in Japan, U-Th dating of annually-banded speleothems (stalactites and stalagmites to you n me) and fossils from well bedded marine sediments. These “older” dates require adjustment where their ∆14C dates overlap with the tree-ring set, and where they overlap with each other, and this undoubtedly reduces the accuracy of the pre-9600 BC dates considerably.
So the answer is: they threw out three-quarters of the data because it didn’t have the accuracy or the temporal resolution to support the kind of analysis that they did. An extremely reasonable step IMO.
The rest of it is, as you eloquently point out, very shaky. They have basically found three components in the 11,600-year record: a 2300- or 2400-year cycle, a possible 7,000-year cycle, and a “trend”, which if you look at the long-term graph, is almost certainly part of a cycle of 50,000 years or more. So they found that the 2300-year cycle correlates with a solar cycle. Quel surprise! They found what they were looking for!
It would have been more interesting if they had searched for natural phenomena that correlate with their other cycles and/or trend. I suspect that if they did, and if they found something, they are going to publish something on those lines in another paper. After all, why put all the work that you did in a week or so in a single paper when you can get 4 or 5 papers out of it? Publish or perish and that cobblers. More likely, they looked and couldn’t find any obvious correlations.
They did not find the 7000 year cycle, they used the cycle that was identified by Beer 2000.
According to Wikipedia, another beer cycle of 7000 years (so far) has been identified by chemical tests of ancient pottery jars, revealing that beer was produced as far back as about 7,000 years ago in what is today Iran.
Three cheers to the ancient Iranians!
Smart Rock October 17, 2016 at 6:31 am
In the head post I gave the dates of the changes between samples every twenty years, samples every ten years, and samples every five years.
None of them changes in 9600 BC …
w.
You are clearly not aware of the issues in this field.
http://www.clim-past.net/9/1879/2013/cp-9-1879-2013.pdf
Roth, R., & Joos, F. (2013). A reconstruction of radiocarbon production and total solar irradiance from the Holocene 14 C and CO 2 records: implications of data and model uncertainties. Climate of the Past, 9(4), 1879-1909.
“according to this, about twenty thousand years ago it should have been about 100°C colder than today”
You assume a linear relationship.
Nope. The people who believe that CO2 is related to 14C claim that it is linear, not me.
w.
You are the one who claimed that since the smaller change resulted in a 2C temp change, then the larger one should have resulted in a 100C change.
That’s linear thinking, IE, each change in C14 should result in the same amount of temperature change.
changes in C14?
Sorry, very distracted. Can changes in C14 against the background pattern be used to indicate large combustion events in the atmosphere – would several huge forest fires plume enough up to create spikes in total C14 or would they be drowned out by volcano events… and my big question… would the C14 be retained in *petrified wood*?
(limited it seems to 250,000 years due to 5730 year halflife)
No. combustion events would release both C13 and C14 into the atmosphere. Unless you had some sort of combustion event that only burned 1,000+ year old trees, they would not effect the atmospheric concentration in the least in my opinion.
Petrified wood is wood that has had silica (in the general case) replace the wood along the structure of the wood. Carbon is not retained.
@ShrNfr
Burning peat or burning coal seams would allow dilution in the C14/C12 ratio, but I cannot envision a scenario where enough could burn that wouldn’t already be well known to geologists.
A major Methane Hydrate release would dilute C14 in a larger pool of C12 as well. But it too would leave behind evidence that I don’t think we see. It could be mixed up with submarine canyons and basin floor deposits, but it would be awful recent deposits. That much methane would cause a temperature spike, too. So unless it was the event that ended the last ice age, where would we see it?
What is 14C?
Carbon is one of the elements which all living things are composed of. The most common form of carbon is carbon-12 which has 6 protons and 6 neutrons. 99 percent of all the carbon in the world is carbon-12 but some carbon atoms (isotopes) have additional 1 or 2 neutrons. These isotopes are called carbon-13 and carbon-14 respectively.
Where does 14C come from?
Carbon-14, the isotc14ope with 8 neutrons, is created in the atmosphere. Cosmic rays enter the atmosphere from space and create energetic neutrons. When one of these energetic neutrons collides with a nitrogen atom (7 protons and 7 neutrons), it forces out one of the protons, creating a Carbon-14 atom (6 protons and 8 neutrons).
http://web.whoi.edu/coastal-group/about/how-we-work/lab-methods/c14-dating-techniques/
http://neutronm.bartol.udel.edu/realtime/southpole.html
It’s not really clear to me what the vertical axis means. The “delta” must mean some kind of change, since the graphs go below zero at the end. Does the “(per mil)” mean atoms per million, atoms per millennium or something else?
“The conversion of the radiocarbon proxy record (McCormac et al., 2004; Reimer et al., 2009) to TSI involves several steps. First a carbon cycle model is applied to infer radiocarbon production by deconvolving the atmospheric radiocarbon budget. Radiocarbon production is equal to the prescribed changes in the atmospheric radiocarbon inventory and decay in the atmosphere plus the modelled net air-to-sea and net air-to-land 14C fluxes. The radiocarbon signature of a flux or a reservoir is commonly reported in the ∆14C notation, i.e. as the fractionation-corrected per mil deviation of 14 R = 14 C/12 C from a given standard defined as 14 Rstd = 1.176 × 10(−12) (Stuiver and Polach, 1977).”
http://www.clim-past.net/9/1879/2013/cp-9-1879-2013.pdf
Most of the data in these curves older than about 15,000 years is highly speculative and inaccurate. Consider how delta-14C is determined. You need to know the measured 14C age of wood and the calendar age–the difference allows you to calculate delta-14C. You can measure the 14C age in a mass spec, and the calendar age can be measured by counting tree rings. That works well for living trees (up to a couple thousand years) and that can be extended to somewhere around 8,000 years or so by matching tree rings in dead trees. Beyond that, you have to use some other way to determine calendar ages, generally various cyclic deposits but they are quite inaccurate.
A second problem is that the older a sample, the less accurate the dating becomes. For example, the usual +/- for a 10k sample is about +/- 50 years, but for a 30-40k it is generally a few thousand years. Thus, although the accuracy of older samples is OK for most purposes, it is not accurate enough for detailed delta-14C calculations.
An even greater problem is determining the calendar age of a 14C-dated sample. How can you do that with sufficient accuracy to calculate delta-14C? The answer is that you really can’t.
The bottom line here is that, aside from Willis’s reservations, I wouldn’t bet a nickel on the accuracy of any of the delta-14C data beyond about 20k in the paper.
Clilverd et al., 2003 doesn’t go beyond 11,700 yr BP.
The wavelet spectrum of solar activity (Fig. 4B) shows that the amplitudes of these periodicities have varied in time, that is, the de Vries cycle amplitude has varied with a period of about 2,200 y, called the Hallstatt cycle (29). The largest amplitudes of the de Vries cycle are found during Hallstatt cycle minima centered at approximately 8,200; 5,500; 2,500; and 500 BP. Comparison of the time series of solar activity and its wavelet spectrum (Fig. 4 A and B) show that grand solar minima occur preferentially at minima of the de Vries cycles (note that solar activity is plotted on a reversed scale in Fig. 4A). Comparison of the time series of solar activity and climate (Fig. 4A) and their wavelet coherence (Fig. 4C) shows that in general during the Hallstatt cycle minima of solar activity (again characterized by large de Vries cycle amplitudes and a frequent occurrence of grand solar minima) the AM is weaker. However, there is some discrepancy during the Hallstatt cycle minima between 5,000 and 6,000 BP and in the past 1,500 y. During these periods the wavelet coherence for the periodicity of the de Vries cycle (around 210 y) is low, although several grand solar minima are visible. A similar pattern is visible at the Eddy periodicity (around 1,000 y), which has high power in the wavelet coherence, except in the period 3,000 to 5,000 BP. Such temporal differences are expected because the Sun is not the only driver of the climate system. Other forcing factors such as volcanic aerosols and greenhouse gases have changed in time, obscuring temporally the solar fingerprint.
Fig. 4.
Comparison of solar activity (total solar irradiance [TSI]) in blue and δ18O from Dongge cave, China, in green representing changes of the Asian climate. possibly the Asian monsoon (AM) (low δ18O corresponds to strong AM monsoon and vice versa). TSI has been reconstructed from the cosmic ray intensity reconstruction (SI Appendix, Section S10). Both records have been normalized (subtraction of mean value and division by the standard deviation), linearly detrended and high-pass filtered with 2,000 y. (A) Time series of solar activity (TSI) and δ18O. Solar activity (TSI) is plotted on a reversed scale. (B) Wavelet of solar activity (TSI). De Vries cycle at approximately 210 y and Eddy cycle at approximately 1,000 y are marked with horizontal, gray dashed lines. Black boundaries mark 95% significance level. (C) Wavelet coherence of solar activity (TSI) and δ18O. De Vries cycle at approximately 210 y and Eddy cycle at approximately 1,000 y are marked with horizontal, gray dashed lines. Arrows pointing to the right indicate that the records are in phase. Black boundaries mark the 95% significance level.
http://m.pnas.org/content/109/16/5967/F4.large.jpg
http://m.pnas.org/content/109/16/5967.full
TSI weighted reconstruction since approximately 9500 BC. In order to provide a better visualization, the evolution since 1000 BC is displayed in panel b). The filled gray band represents region limited by the KN08-VADM and KC05-VDM reconstructions. For reference, the red lines represent the 10-year averaged reconstruction by Krivova et al. (2010a).
http://www.aanda.org/articles/aa/full_html/2011/07/aa15843-10/aa15843-10-fig11.jpg
http://www.aanda.org/articles/aa/full_html/2011/07/aa15843-10/aa15843-10.html
On the half-life question:
http://www.radiocarbon.com/tree-ring-calibration.htm
http://www.radiocarbon.org/IntCal13%20files/intcal13.14c
0-50000 years calBP
http://www.radiocarbon.com/tree-ring-calibration.htm
Carbon dating results must be clear, hence they should not be reported simply as BC, AD, or BP.
oops , messed the quotes:
http://www.radiocarbon.com/tree-ring-calibration.htm
The data Willis plotted was col 1 and 4 which he appears to have adjusted from year “Before Present” ( ie 1950 ) in the file to AD dates. So the X axis should have been labelled ” calAD” not Year ( AD/BC ).
Otherwise this is showing true estimation in calender years for each d14C value. My earlier impression this was affected by the Libby half-life was incorrect, they are already adjusted. Col 2 is the uncorrected radiocarbon years.
My university professors that taught me signal processing techniques would weep if they saw the original article(s) as well as Willis’ critique. Not sure what this says about modern PhD programs…
I plan on running a proper frequency analysis later (probably too late as this post will pass in to history), but for now here’s some brief critique of critique:
(changed bullets to numbers)
For (1) there’s a good explanation above about the noise issues with dates older than 11k. I won’t repeat that.
(2) standard frequency analysis assumes a periodic signal so endpoints are thrown away using e.g a Hamming window. this has a similar (but not the same) effect as de-trending. This detrending has zero effect on data whose periods of 2,300 years when the entire data sample is ~> 4x as long (which it is). So the critique is not valid.
(3) subtraction in the time domain is equivalent to subtraction in the frequency domain. So again no effect on any 2,300 year periods present in the signal when you subtract a 7000 year signal. BTW a Hamming window would have removed signals with periods > 5,000 years anyways.
(4) Willis is correct in questioning whether the remaining signal has 2,300 periods, but for the wrong reasons. To my eyes, the signal-noise ratio looks so bad it could just be noise. A proper frequency analysis would tell us that. Overlaying signals in the time domain is not proper signal analysis.
It would appear to me that in the last 25 years anyone with decent signal processing knowledge has left the University to pursue more lucrative careers in industry. This is Mann-level silliness.
Peter
In quick look, I find a peak at 2461 and another at 87y .
Even using diff to detrend which attenuates long periods hard. The 2461 peak is clearly above noise.
actually this data looks like it’s been through a low-pass filter, there’s very little below 40y.
Like I said at the top, I don’t believe this data in this state is a measure of solar activity.
The 14C trapped in any biological sample is the integral of all preceding 14C creation , post processed by and exponential decay. Again, it’s rather like borehole temperature. You don’t get the temperature TS by plotting temp vs depth.
Since per mil is a ratio it makes the vertical scale like a log scale and flattens the exp to a linear decay. So it should be possible to express the half-life as a slope and subtract it. The difference to that line is getting nearer to solar. The detrend will not be far from that.
However, the frequency content will change with time. Data in the recent section well under a half-life will still have a lot of higher frequency content. Older stuff will have filtered this out. This is the borehole problem. ( Though borehole is heat diffusion, it’s similar. )
This is why the data appears low-pass filtered in the spectrum.
Canman October 17, 2016 at 7:33 am
It’s not really clear to me what the vertical axis means. The “delta” must mean some kind of change, since the graphs go below zero at the end. Does the “(per mil)” mean atoms per million, atoms per millennium or something else?
‘Per mil’ means ‘part per thousand’. The ‘delta’ represents the per mil depletion in sample carbon 14 relative to a modern carbon sample (1955 Oxalic acid).
Well it’s not depletion if it’s +ve but , yes in principal.
We call it radioactive ‘decay’ for a reason!
So d14C should be plotted negative 😉
In periods of low solar activity changes Earth’s magnetic field will affect the atmosphere due to the modulation of the GCR.
http://www.esa.int/Our_Activities/Observing_the_Earth/Swarm/Earth_s_magnetic_heartbeat
Excellent work Willis.
As I noted when “Javier” posted his surprsing results, there was no attached data and no attached methods ( Code)
How many years have you and I been asking for the same BASIC STUFF. And yet folks on both sides will swallow BS as long as it supports their cherished notions. fake skeptics all.
I do have one problem with your post
‘So to recap: IF the claims are true that the changes in ∆14C shown in Figure 6 reflect changes in cosmic rays and that the changes in cosmic rays result in the claimed changes in temperature, then twenty thousand years ago the earth should have been 100°C cooler. Even if I’m wrong by 100%, it is still saying that it was 50°C cooler back then … didn’t happen.”
One problem with cosmic rays and cloudiness is this. It’s threshholded.
Lets imagine a response curve with number of CCN on the X axis and Cloudiness on the Y axis.
The Theory goes that as GCR increase CCN, then cloudiness goes up.
Fair enough. We have CCN from terrestrial sources and at times these are augmented by CCN formed from GCR.. granted for the sake of argument..
However, the response –cloudiness– is thresholded. Hard to get less than zero clouds and more that 100% cloudy.
Consequently its somewhat unfair to extrapolate the LIA response linearly to suggest a 100C cooler
Put it this way.. Say for the sake of argument that we are at 70% cloudy.. increasing CCN cant make it anyomore cloudy than 100% so there is threshold of temperature drop.
The problem of threshholding hit me when I was looking at GCR and cloud data from satellites. If an are of the earth is already 100% cloudy… well GCRs are an utter on a bull.. Or if you are in a dry area with not enough water vapor.. all the CCN in the universe wont help you.
Any way. good work.
Mosh’ & Willis.
As I explained above the ‘trend’ of the graph is basically the exponential decay plotted on a proportional axis scale. So detrending the data is ( roughly ) just removing this. That means that the 100 deg. C argument is spurious.
There is also the heavier damping of the early record and the recent section ( where you pick out the 2 deg C scaling ) which is a lot more sensitive.
Now I’m not saying I find the overlay analysis at all convincing. As Peter Sable said, this is Mickey Mann type work.
This record is not a direct record of 14C , it’s more like a borehole temp profile is to a temp TS but it will have bumps in about the right place to give some idea of the presence of any cycles. This will be distorted because of varying frequency filtering but the bumps are there and probably are rough indication of any cycle change in 14C creation.
It’s a kludge and all these caveats were not presented in the article of cited paper. But the 100 deg. argument seems to come from a lack of time spent trying to understand how the data relates to 14C generations in the atmosphere and how it is modified over time.
The line you are trying to use for linear regression and projection way outside the tiny calibration period you have chosen is just the 5730y exp. decay process. And sorry , it’s not linear.
Steven, as I told you at Judith’s blog, that is a totally invalid request. My article is a review. I have not used any data nor any methods. Everything is peer reviewed and published in the scientific literature. If you disagree you can take it to the original authors.
That you keep asking for nonexistent data or methods indicates that you don’t have anything to say.
Milankovich cycles can explain long term cycles to some extent but fail to tell us when the next ice age will start. Maybe we need the cosmic ray flux to explain that.
How many parameters was it does it take to fit an Elephant ?
My problem with the INTCAL13 Proxy is that if direct measurements of neutrons fluctuate +/- 5% on average over a solar cycle, then the INTCAL 13 Proxy indicates there were many thousands of times more cosmic rays striking earths atmosphere 20K years ago than currently, assuming the OULU record can be correlated with the INTCAL13 proxy over the same time period.
http://cosmicrays.oulu.fi/webform/monitor.gif
“My problem with the INTCAL13 Proxy is…”
Jeez, INTCAL13 is not a proxy, it’s a calibration curve for radio-carbon dating. There may be some proxy info in there but it’s NOT figure 1.
It may be something similar to the detrended line.
Without giving my own critiques and evaluations, I want to thank Javier and Willis Eschenbach for an interesting discussion.
“It is a record of historical variations in the levels of the carbon isotope 14C.”
A record of historical variations? . . . crazy talk, to me.
Slightly OT but in reading “The first three minutes” recently by Steven Weinburg, I came across an issue with galaxies which potentially impacts on the Shaviv hypothesis that very long term (100s of millions of yrs) cycles in cosmic ray abundance are linked to our galaxy’s rotation and the passage of our solar system, near the outer end of a galactic arm, through patches of clean and dirty space.
Consider our solar system. How fast do Mercury, Venus and Earth orbit the sun? Many tens, even hundreds of times faster than the outer planets like Uranus and Neptune. The speed and timing of orbit is linked to proximity to the sun and strength of gravitation.
Now consider a typical galaxy with its evocatively curved arms. The arms’ curvature shows that the outer arms orbit a little slower than the center; however the difference in orbital speed between the center and the outer margins is much smaller than in with planetary orbits in a solar system. If luminous lines were connected between our solar system planets in the manner of a galactic arm, then within a single orbit of an outer planet this line would be stretched and broken multiple times by hundreds of orbits of the inner planets.
This is a very big difference – the orbit of galactic arms does not fall off with distance from the galactic center as do planetary orbits. This can only mean that the galaxy’s mass is not concentrated in the center as the light based image of the galaxy would suggest. This leads cosmologists to the conclusion that galaxies are enveloped in a disc, or even a doughnut, of invisible dark matter which nonetheless exerts gravitational pull.
Now if the rotating galaxy has similar orbital speeds along its arms due to a cloud of dark matter orbiting with it, then it follows that any cosmic ray and dust clouds will also be carried around with the galaxy’s rotation.
This contradicts the picture of galactic arms orbiting through (relatively) static regions if space. If galaxys orbit while embedded in dark matter clouds, and both orbit together, this makes it impossible for galactic arms to orbit through nonmoving clouds of dust – all neighboring material would be gravitationally caught up in the orbiting of the galaxy with its dark matter halo.
recent work shows that gravitational rotation varies with visible matter, regardless of galaxy type. this contradicts the dark matter hypothesis, because dark matter must vary by galaxy type to maintain observed rotation.
which suggests that the theory of gravity is incomplete, and that the dark matter hypothesis is wrong.
IMHO dark matter is a desperate fudge factor.
ferd, any particular link to the “recent work”?
Ptolemy2
It works better if one allows for two types of additional matter: Dark Matter and what I call Darker Matter. DM and DrM.
A shell of DrM much larger than the DM shell causes things to balance with standard gravity. One of the strangest shapes, gravitationally, is the barred spiral galaxy yet they are very common.
If it is true that DrM and DM exist, it changes conclusions about anything attributed wholly to visible mass bending light. It also means, for any meaningful purpose, there is an ‘ethereal’ shell of matter, interactive or not, through which we are passing at all times.
As you have noted, DM leaves conundrums and I propose that DrM solves them. The shell of DrM is very much larger than the DM.
“Consider our solar system. How fast do Mercury, Venus and Earth orbit the sun? Many tens, even hundreds of times faster than the outer planets like Uranus and Neptune. The speed and timing of orbit is linked to proximity to the sun and strength of gravitation.
Now consider a typical galaxy with its evocatively curved arms. The arms’ curvature shows that the outer arms orbit a little slower than the center; however the difference in orbital speed between the center and the outer margins is much smaller than in with planetary orbits in a solar system . . .
This is a very big difference – the orbit of galactic arms does not fall off with distance from the galactic center as do planetary orbits. This can only mean that the galaxy’s mass is not concentrated in the center as the light based image of the galaxy would suggest.’
No, there is a blatantly obvious alternative “meaning”, it seems to me; Those galaxies haven’t been rotating for billions of years.
I used to think it was impossible that modern science could be radically off on the whole notion of “deep time”, even after I witnessed things first hand (in my forties) that convinced me the God of the Book is for real . . and I sort of twisted the words in the Book to match up with the “deep time” concept I had always taken for granted . . but I’ve since seen so much assumptive reasoning in this realm, that I have grown rather skeptical of that old “truth” . .
Willis,
The mechanism saturates. You hence cannot extrapolate the cooling affect. The affect is real. It is difficult for any modern human to imagine the cyclic glacial phase. There have been 23 cycles.
The glacial cycle for the last 800,000 years has been 100,000 years in duration. The interglacial periods are short, start and end abruptly, and are around 10,000 years in duration. Note Canada, the Northern US states, and Northern Europe are covered by a 2 mile thick ice sheet for the 100,000 year glacial cycle.
You have no understanding as to what are the mechanisms. Note mechanisms is plural. You are not trying to solve the problem.
It is an observational fact (which has been proven in the last 10 years or so by the geomagnetic proxy specialists) that there are immense changes and extraordinarily rapid changes to the geomagnetic field strength and orientation.
The geomagnetic field strength is roughly 2 to 3 times less during the 100,000 year glacial cycle. Weaker geomagnetic field strength higher GCR striking the planet, more clouds, colder planet.
The problem (why the heck is the geomagnetic field abruptly and cyclically changing which is cause of glacial interglacial cycle) is impossible to solve as some of the dang assumptions are incorrect.
There are ruddy super high temperature burn marks and residue that is caused by massive plasma discharge on the surface of the planet at 18 locations on three continents which coincides with the last super large abrupt climate change ‘event’ (quotation marks around event as the YD cooling period lasted for 1200 years and the YD event is cyclic, not a one of. The YD event is a Heinrich event which causes both the initiation and termination of the interglacial period), the Younger Dryas abrupt cooling event (12,900 years ago) at which the time planet went from interglacial warm to glacial cold with 90% of the cooling occurring in less than a decade, at a time in which summer solar insolation at 65N was maximum.
There is the largest change in C14 in the Holocene at the time of the YD abrupt cooling event.
This is a holistic problem. There are piles and piles of anomalies and paradoxes (multiple fields) that have been ignored for decades. The paradoxes and anomalies all go away when the correct mechanisms are inserted.
The sun is significantly different than the standard model. There are more than 200 astronomical paradoxes and anomalies (in peer reviewed papers with author comments that the observations cannot be explained) that are connected with what happens when a very large body collapses which explains why there are burn marks on the surface of the earth and cyclic abrupt changes to the geomagnetic field.
William
The glacial cycle for the last 800,000 years has been 100,000 years in duration.
Wrong. For the first 2/3 of the Pleistocene, between 3 million and 1 million years ago, the glacial-interglacial cycles had a time period of about 40,000 years, following the obliquity cycle. Then came the “mid Pleistocene revolution” or MPR about 1 million years ago when the spacing of interglacials abruptly lengthened to its current 100,000 year periodicity, following approximately the eccentricity cycle.
This is not the first time I have corrected this mistake in your posts.
Sorry – you are right – I somehow overlooked the “800,000” in your text. :-/
Wrong. The 100 Kyr cycle is a myth. The arguments are too long to put in a comment. Article in preparation. But the myth was already exposed in 2005:
Maslin, M. A., & Ridgwell, A. J. (2005). Mid-Pleistocene revolution and the ‘eccentricity myth’. Geological Society, London, Special Publications, 247(1), 19-34.
William Astley @1:14
“burn marks on the surface of the earth”
Could you please give some more details about these (eg. ages and locations) or perhaps a reference.
Thanks.
Even if I’m wrong by 100%, it is still saying that it was 50°C cooler back then … didn’t happen.
=============
likely due to the 3 phases of water, earth’s temp never seems to go much outside of the range 11C to 22C, no matter what. Sort of like a car sitting in a deep U shaped valley with vertical sides. No matter how much gas you apply, unless you have a rocket motor, you are stuck between the bottom and the vertical sides.
For this reason, any attempt to extrapolate a temp change of 50°C is likely more than simply wrong by 100%. More likely it is 100% wrong.
ps: no one seems to have noticed the small hockey stick on Figure 4 around yr 2000. Modern warm period?
“no one seems to have noticed the small hockey stick on Figure 4 around yr 2000. Modern warm period?”
You bet. Nuclear bomb warming of the 14C record. We are producing all sorts of hockey sticks. This one will disappear in about only 50,000 years. It is one of the basis some people defend we are in a new geological period.
Javier October 17, 2016 at 3:46 pm
“no one seems to have noticed the small hockey stick on Figure 4 around yr 2000. Modern warm period?”
You bet. Nuclear bomb warming of the 14C record.
Fig 4 is supposed to be the INTCAL13 data in which case the most recent data is 1950, so it’s not nuclear in origin.
“likely due to the 3 phases of water,”
Likely due to being too quick to criticise and not thinking about the data.
Do you know the story about the guys who took a very short period of data from a non-linear system and foolishly extrapolated it WAY outside the domain of the calibration and then started making very confident claims about the extreme changes it predicted ?
” The wavelet spectrum of solar activity (Fig. 4B) shows that the amplitudes of these
periodicities have varied in time, that is, the de Vries cycle amplitude has varied with
a period of about 2,200 y, called the Hallstatt cycle (29). ”
. . . . . . . . . . . . . ( ren October 17, 2016 at 7:48 am )
As usual, ren gets it right !
And . . there is not only variability in the deVries/Suess but also in the Hallstatt cycle
itself. During inter-glacial and glacial periods, the Hallstatt cycle varies between 2208
and 2313 years respectively. The 2313 year long-Hallstatt cycle is an expression of
the planet’s influence over the sun. The 2208 year short-Hallstatt is an expression of
the sun’s momentum and acceleration influencing the planets.
The sun is 750 times more massive than all of its satellites. It is the acceleration of
our massive sun that generates force in our solar system, not the planets. Therefore
it is the 2208 year short-cycle that dominates during an inter-glacial. But . . during
glacial periods the sun loses much of its acceleration and the 2313 year long-cycle
then takes over.
There is a lot of confusion regarding the short Hallstatt cycle (2208 years), the long
Hallstatt cycle (2313 years) and the Charvatova cycle (2402 years). The Damon and
Sonnett 14C data has been used by everybody to show correlation. This is unfortunate
because this data does belong to the Hallstatt cycle.
The 2402 year Charvatova cycle is physically visible in the disordered pattern of the
sun’s orbit around the solar system’s center of mass. The Charvatova cycle is directly
linked to the earth’s axial precession, another physically visible event.
…….Dreschhoff, 2007. Paleo-Astrophysical data in relation to temporal characteristics
…….of the solar magnetic field. Proceedings of the 30th International Cosmic Ray
…….Conference vol. 1, 541-544.
…….
…….Damon and Sonnett, 1991. Solar and terrestrial components of the atmospheric
…….14C variation spectrum. The Sun in Time. The Univ. of Ariz. Press, 360-388.
…….
Please visit Weathercycles.wordpress
” Fibonacci and climate “
“When the combined magnetic field is strong, it deflects the cosmic rays away from the earth. When it is weak, more cosmic rays strike the earth.”
Surely the incidence of CR and GCR varies quite a bit? I can’t see teasing a signal out if it.
CR also come from the sun, not so? What fraction?
Maybe 14C is a poor proxy for CR. 10Be might serve far better. Does the 14C curve match the 10Be curve? Why not? If the proposed formation method is valid they should match perfectly.
Some plants may take up 14C preferentially just as bananas like Potassium 40 which explains why all bananas are radioactive. During an ice age that 14C gobbling activity might be suppressed. It could be something growing in the ocean.
I’d say a 2400 year cycle is not evident.
Javier October 17, 2016 at 5:16 am
Javier, first, thanks for showing up to defend your work. Many do not do so, I commend you.
But I said nothing about your unwillingness to sign your own words, neither by word, tone, nor intent. Any interpretation of that nature is all you. I was uncertain how to write that sentence and gave it some thought. I couldn’t really write “a paper by Javier saying …” because that seems to assume that the reader knows who Javier is and it sounds like a last name. So I settled on “someone named “Javier”. I’m sorry you took that as me casting shade on you, it was not my intention.
I find exactly three mentions of the Hallstatt cycle in Google Scholar prior to the 21st century … and Bray claimed the cycle was 2600 years, viz:
You and Clilverd and Bray all disagree about the length of the cycle … which is what I was pointing at. When that happens, I have to wonder if we’re talking about a real cycle, or just another of the many appearing and disappearing cycles we see in the sun at all the time scales.
For example, there is a claimed “Gleissberg Cycle” in the sunspot data. But when it is examined closely, it’s seen to exist only in the first half of the data, and to die out in the second half. Here is a Complete Ensemble Empirical Mode Decomposition (CEEMD) of the sunspot data (source and CEEMD description here):
ORIGINAL CAPTION Periodograms of each of the intrinsic modes C1 through C7 of the CEEMD analysis of the annual mean sunspot number, 1700-2014. These show the strength of waves of the various periods in each on the intrinsic modes.
The so-called “Gleissberg Cycle”, upon which much ink has been expended, is visible in Mode C6, with a frequency of about 90 years. Now, based on that you’d say that a) the Gleissberg Cycle is real, and b) it’s the second-largest signal in the sunspot data. But here’s the problem.
ORIGINAL CAPTION CEEMD analysis of the mean annual sunspot numbers. Top panel shows the sunspot data, standardized to a mean of zero and a standard deviation of one. Panels marked C1 – C7 show the intrinsic modes of the signal. The bottom line shows the residual, meaning what remains after the removal of modes C1 – C7 from the signal. Note that all intrinsic modes are displayed at their true size, with all scales being the same.
As you can see, the so-called “Gleissberg Cycle”, upon which much ink has been expended, is visible in Mode C6 … but it only exists in the first half of the data, and even then it only exists for a couple of cycles. After that it dies away totally.
I’ve seen this pattern over and over in natural datasets—an apparent “cycle” comes into existence, lasts for a few cycles, I’ve seen as many as five cycles … and then it dies away altogether. All of which has made me highly skeptical of arguments about some purported 2600 or 2400 or 7000 or 2300 or 88 year solar cycle … they come and go.
Next, please note that the so-called “Gleissberg Cycle” persisted for a century and a half and then died out entirely, so a hundred years of data is far from sufficient for deciding if a real cycle exists … but let me point out something even more amazing. Here is the CEEMD analysis of your exact data that you say contains a 2300-year cycle:
This is actually a lovely analysis, as it highlights several problems with the standard analysis. First, take a look at mode C8. It contains a strong cycle with a length of just under a thousand years, a cycle which shows up in a Fourier or periodicity analysis … but over the period of the record, it dies out to zero. And not quickly either. It gradually goes from a strong, clear cycle 9000 years ago to no cycle at all.
So let me ask you this, Javier. Is there a ~1000 year cycle in the C14 data? Well … yes and no. You see the problem? Apparent cycles appear, exist for a while, even for millennia, and then disappear …
And the situation with the cycle of around 2400 years is similarly complex. It’s shown in Mode C9. It shows a ~ 2100-year cycle for a few cycles, then a long cycle of about 2700 years, then a final cycle of about 2100 years. All of these combine together to give a best Fourier fit for a 2400-year cycle … but that is not what is actually happening. In fact it is a string of shorter cycles with a long cycle in the middle.
So again, let me ask you: is there 2400-year cycle in the ∆14c data? Well, not as we generally understand a 2400 year cycle. However, the CEEMD analysis does make it clear why y’all get different values for the putative cycle … because it is a mix of various cycles coming and going. And remember, this is just a short cherry-picked section of the data. If we add more years, things don’t get better …
And of course, just like the very solid 1000-year cycle in Mode C8 of the same data, over the next twelve millennia the 2400-year cycle may indeed disappear like the Cheshire Cat, leaving only a faint ripple in the ether.
The underlying problem is that the sun, like many natural systems, appears to be chaotic in nature at all time scales.
Finally, Usoskin did an analysis of the∆14C data itself to claim significance … but like you he threw away most of the data first, with the same weak excuse that before 6700BC it was too uncertain. Unlike you, he only used the data from 6700 BC … this is what I meant about cherry picking. Everyone just uses the part of the 14C data that supports their thesis, and waves their hands at the rest and utters the magic words “too uncertain” …
But that’s not my main point. All tha Usoskin may or may not have established is that there is a 2400-year cycle in the 14C data … but you seem to think that he’s established that there is a corresponding cycle in the sun.
Here is the INTCAL data with the error estimate from the folks who put it together:
You don’t like the data older than 9600 years because it differs from what your theory might claim. So you wave your hands at changes in the “carbon mass budget” … we don’t even understand the current carbon mass budget, much less that of ten millennia ago.
And surely if there is a 7000 year cycle in the recent data, a cycle of that size would be clearly detectable in the data out to at least 25000 BC, despite the greater uncertainty.
While it is true that uncertainty increases with age, this is true of all natural datasets. Since the variations in the signal are much, much greater than the uncertainty of the signal, there is absolutely no justification for throwing the earlier years out.
In particular, the idea that you can cherry-pick your 9600 BC starting date based on uncertainty and that Usoskin can make the same claim about 6700 BC is totally unjustified—the uncertainty is quite small out to at least 25000 BC, and the larger swings prior to that are assuredly as significant as the 7000-year swing that you have removed from the data.
Not true in any sense. First, we only have good sunspot data back to about 1700, so there is not a “400 year period of overlapping”. Instead, we have the 250-year period from 1700 to 1950, with samples every five years … in other words, we have only fifty-one samples in the period of overlap.
It gets worse from there. Both the sunspot and the ∆14C data are highly autocorrelated, with high Hurst exponents (∆14C data, Hurst exponent = 0.88; sunspots, Hurst exponent = 0.76). As a result of the small dataset and the large Hurst exponents, the correlation of the two datasets (sunspots and ∆14C) have a p-value of 0.3 … in other words, we do not have anywhere near enough actual observational data to back up your claim that the relationship is significant.
Javier, my problem is that folks seem to take claims like “400 years of overlap” or “Gleissberg Cycle” for granted, without ever actually doing the math including the adjustment for autocorrelation. I don’t shy from such scut work, because unlike far too many PhD scholars, I take “nullius in verba” quite seriously.
I’d be cautious about claiming to speak for Leif … speaking for myself, I do think that the ∆14C data does contain solar information. The questions are how much information is encoded there, and what the signal to noise ratio is, and how we can reliably distinguish signal from noise … questions I don’t think have been asked a lot, much less answered.
My profound apologies, you are quite correct. I have changed the head post to reflect your very valid objection, and said specifically that you do not discuss cosmic rays.
See above. I’ve changed the head post.
I’ve now left you out entirely, again my apologies for the offense … but that is indeed the result of the popular claim that cosmic rays rule the temperature. That claim is not my strawman, it is the strongly held belief of many.
Many people claim that cosmic rays are the connection between the sun and the climate. It appears you don’t think that is true, and neither do I… but that’s just you and I, lots of folks disagree. I was addressing them.
However, I’d be curious if and how you think the tiny variations in solar output (none of which exceed about a third of a watt per square metre on a global 24/7 basis) affect the climate.
Oooh! Vague insults based on personal opinions! ! Can I play too? Please? OK, here’s my contribution:
You see how pointless that kind of nonsense is? Did that personal attack convince you that you were wrong? Of course not, and your attempt at mudslinging is no different. Could we stick to the science, please?
In that regard, Javier, you are the one defending throwing away three-quarters of a perfectly fine dataset with an established error estimate as being good solid science, not me. You are the one defending removing a 12,000-year-long linear trend from the data based on a handwaving claim about a perfectly-straight-line-for-twelve-millennia change in “internal carbon system dynamics”, not me. You are the one wielding a magic cycle of exactly 7000 years that removes unwanted variations in the actual data … and please don’t claim that the 7000 years is observationally determined, nature is never that neat. You are the one claiming Bray was wrong about the length of the Bray Cycle.
You can see why I might be less than convinced by your arguments … but I do thank you for raising them. As I said, not many people do so. I tip my hat to you.
Regards,
w.
Javier seems to have detrended to data because that’s what everyone in climatology does with everything.
I appoligise to J if he did explain why he detrended the but his C. Etc. post was massively long and meandering and did not seem to have much substance so I ended up scanning and then skipping.
I too am sceptical of all ephemeral cycles that people manage to see in solar activity.
However, that slope just reflects the basic nature of exponential decay. IntCat13 data is a “calibration” curve if you compare col 1 and col 2 , as presented here it is the transfer fn from d14C to sample age.
It is the deviations that ( may ) reflect changes in 14C creation due to cosmic rays. So his detrend seems to be approximately right. I think there is probably a more accurate way to do this mathematically since the decay half-like is believed to be very constant in our understanding of the process.
I would criticise the lack of scientific reason for detrending but I think it’s about right.
The fact that the data remains fairly straight out to 20ka suggests that, despite increased uncertainty it may be usable. The circa 7ka ripple seems to be visible in that period.
Here is a quick look at the spectrum of this data. Not I used first diff rather than detrend which attenuates as 1/f . We also see the data appears to be low-pass fitlered, this I explained above is a result of the exponential decay damping out fast changes in the early record.
The “Gleissberg” period is equally well defined in both the 14ka and 6ka subsets. The 148, 208 less so.
The circa 2500 year periodicity is obviously less well defined in the shorter data but there seems to general agreement.
Then I apologize too. I have been insulted recently here at WUWT for not revealing my name.
https://wattsupwiththat.com/2016/10/07/evidence-that-multidecadal-arctic-sea-ice-has-turned-the-corner/#comment-2315034
Well, there are many more mentions of the ~ 2200-2400 periodicity in radiocarbon data. Roger Bray described the periodicity without using radiocarbon data that was not available in 1968, so the initial relationship between solar variability and climate was not established based on cosmic rays.
The classical citation for the radiocarbon data is Damon and Sonnet 1991, although they recognize Houtermans 1971 as the first report of the periodicity in 14C:
III. THE ~ 2300 YR PERIOD
Aside from the aforementioned long (secular?) variation, the strongest feature in the ∆14C record is the long period of ~ 2300 yr. This component of the ∆14C spectrum, in addition to the 208 yr period, was first reported by Houtermans (1971). Its source is enigmatic but probably not attributable to the geomagnetic dipole field, for no periodic geomagnetic dipole field change of the required amplitude has been detected.
Damon and Sonnet 1991, pg. 366
My bold. Damon, P. E., & Sonett, C. P. (1991). Solar and terrestrial components of the atmospheric C-14 variation spectrum. In The Sun in Time (Vol. 1, pp. 360-388).
The differences in periodicity are due to the different methods to establish it, and on the irregularity of the cycle. The 11 year cycle is actually 8-15 years, a ±33% variability that in the case of a 2300 yr cycle would give a ±700 years. We accept the 11 year cycle because we have 23 oscillations. For the ~ 2400 yr cycle we only have 5 oscillations in the last 11,000 years, and with very old and imprecise data. Solar cycles are also famous for their differences in amplitude. It is in their nature.
The situation that you describe is exactly the same for the 11-year sunspot solar cycle. It also disappears between 1650 and 1700. It has irregular length so if you measure it between 1850 and 1900 it will be a 12 yr cycle and if you measure it between 1900 and 1950 it will be a 10 yr cycle. So let me ask you this, Willis. Is there a ~11 year cycle in the sunspot data? Well … yes and no. You see the problem? Whether we think it is due to a chaotic nature or to a poorly understood cause for solar variability, we must accept that this is the nature of solar cycles or abandon its study. Most people seem to believe in the 11 year cycle by conveniently ignoring the same reasons they use to not believe in the ~ 2400 yr cycle. Not very consistent.
That there is a 2400-year cycle in the 14C data is not discussed. It was found from day one. That 14C is a proxy for solar variability is generally accepted. That the 2400-year cycle represents solar variability is a reasonable assumption that is extraordinarily common in the scientific community. You are correct that we have no proof that the Sun varied with a 2400-year cycle but extending that unreasonable demand means we cannot use any proxy for anything.
You are making a crucial mistake. You are assuming that the error in carbon dating determination (That’s what IntCal is) can be assumed to be the error in solar activity estimation. Solar activity estimation involves several steps that each one has its own error source, since it requires two box models, one for the biosphere and one for the oceans. The final error I have already stated that becomes unacceptable when data is older than 12,000 yr BP. It is panel b in this figure:
http://www.clim-past.net/9/1879/2013/cp-9-1879-2013.pdf
Don’t be ridiculous. If the data doesn’t support my hypothesis I abandon it. I have already abandoned two hypothesis for lack of data support being the first that the world is warming almost exclusively because of the increase in atmospheric CO2, and the second that the solar variability is just too small to produce significative climate changes. I have nothing against older data except that the experts refuse to use it because they consider it unreliable and I agree with them.
Ok. I count 300 years and it is good enough of a match for me.
http://i1039.photobucket.com/albums/a475/Knownuthing/Goslar14CSSN_zpsskwzxv52.png
Considering that for the ~ 2400 yr cycle we are talking exclusively about grand solar minima as the lows in the cycle are the highest 14C production periods of all, I don’t think the signal to noise issue is that relevant. If 14C data represents solar activity the 2400 yr cycle is real. As I said the robustness of this feature in the data is what it made it to be discovered from day one.
Fair enough. I am glad we have cleared that and thank you for correcting the article.
I agree on sticking to the science. I was angry because your criticism was naming me but was directed to the work of Clilverd et al., and to the beliefs of “lots of folks” as if I was responsible for that or shared it.
It is not actually me. It is the published science on the issue. The solar variability estimate has to be extracted from the ∆14C data using two different box models and a reference. The models do not work for out of the Holocene conditions and thus the estimate becomes too unreliable to be useful. It is very easy to defend that if all of the authors of the estimates (there are over 10 articles on the solar variability reconstruction issue) do not consider data older than 12,000 reliable, it would be unwise to use it to extract conclusions. I can imagine the critics for doing so.
Again it is not me. There are half a dozen solar reconstructions in the literature, and although made by different authors with different methodology, they all perform a detrending. I have to say however, that it does not matter how you do that, because the Bray cycle is based on the position of grand solar minima, and that doesn’t change independently on the methodology employed because it is in the raw data before models and detrendeing are applied. This is what it is usually called robust feature as Damon and Sonnet noticed in the cite above.
On the contrary. I am open to the existence of longer oscillations in solar activity. Some authors propose a 6000 yr solar cycle that could be related to the 6000 yr Heinrich oscillations in ice rafted depositions in the North Atlantic and in Polar Circulation Index and δ18O variations in ice cores. I find that the evidence for such cycle is still insufficient to defend it. However again, everybody finds the ~ 2400 year cycle in the data, whether they subtract the longer periodicity or not.
He might still be right. Determining the length of the cycle is difficult with so few instances. I have preferred to take the very well dated low at 10.3 Kyr BP (figure 4 in my article) and the very well dated Spører minimum to calculate the average duration over 10,000 years. The uncertainty in the cycle length has no relationship with whether it is real or not.
It is not my goal to convince but to provide information. My article contains 54 references:
https://curryja.files.wordpress.com/2016/09/bibliography.pdf
Even if you find one of them to be incorrect that doesn’t affect the conclusions. If Clilverd et al., 2005 are wrong, I will bring forward McCracken et al., 2004; Solanki et al., 2004; Vonmoos et al., 2006; Muscheler et al., 2007; Steinhilber et al., 2012; Inceoglu et al., 2015; Usoskin, 2013; Usoskin et al., 2014.
Willis says that Javier has:
1) thrown away three-quarters of the data,
2) removed a purported linear trend of unknown origin from the remainder,
3) subtracted a 7000-year cycle of unknown origin , and
4) ASSERTED that the remainder represents solar variations with an underlying 2,300 year period …
However, Javier has used the only reliable part of the record: The first 11,000 years when we can count the years backwards in time via tree rings AND measure the amount of C14 in the same tree ring. Before that, any error in dating samples for calibration produces an error in the calibration curve. Your interesting demonstration that these cycles and their effect on temperature must be bogus (-100 degC) depends on the accuracy of the much less reliable data from before 11,000 BP.
Removing a linear trend may be justified if the wrong half-life is used to calculate the difference between observed and C14 predicted for a constant rate of C14 production. That can be tested.
There are techniques for judging the statistical significant of empirical methods of abstracting a sinusoidal signal. Properly characterizing a 7000-year period is 11,000 years of data is impossible. Will the 2,300 year cycle remain statistically significant if you don’t remove the 7,000 year cycle?
What is missing from your and Javier’s analysis is a comparison of the B10 and C14 proxy records. Both are alleged to be measures of solar activity. But one rarely sees them together. And despite our best efforts (and no effort by some), it is very easy to cherry pick among many datasets and have your attention drawn to those that appear to show a correlation. Chaotic systems often show periods of sinusoidal behavior interspersed with non-sinusoidal behavior. However, if “solar activity” is controlled by the planets, there should be sinusoidal behavior all of the time.
Frank October 17, 2016 at 6:57 pm
What is missing from your and Javier’s analysis is a comparison of the B10 and C14 proxy records.
Should be ‘Be10’.
Phil: Absolutely right.
“However, if “solar activity” is controlled by the planets, there should be sinusoidal behavior all of the time.”
When there are many planets the result could well have sections with reasonably stable periodicity and then others where this breaksdown and seems absent.
I’m making a case for the planetary model, but what you say here is incorrect.
Greg: Willis discussed finding some data sets with periods of stable oscillations behavior followed by periods with no oscillations. This sort of behavior can be observed in some chaotic systems, but my point is that this wouldn’t happen if the planets caused the solar cycle.
If the planets modulate the sun’s output, you are correct in pointing out that the phrase “sinusoidal behavior” doesn’t accurately describe the vector sum of the gravitational force from multiple planets. The orbit of Jupiter alone could produce sinusoidal behavior, modulated by the other planets.
The tides on Earth are caused by the rotation of the Earth under the influence of a slowly orbiting Moon (sinusoidal behavior) modulated by the influence of the Sun. Would you call the tides “sinusoidal?”
“but my point is that this wouldn’t happen if the planets caused the solar cycle.”
They do, and the ‘breakdown’ is how solar grand minima happen.
Guys, if you look back at the article on planetary influence on solar cycles, it is quite clear that planetary influence is a small influence that is contributing to and synchronizing an already cyclical phenomenon; thus the whole language of “resonance”. There may be, and surely are, other contributing factors, perhaps even more powerful ones.
+10, but I think you mean Be10.
Javier,
Post your data and code and then you can begin to engage in a discussion of your work.
I’m surprised this is not a condition of you being allowed to post here.
Anthony?
Javier’s article was on Climate Etc. , he was not “allowed” to post here. It was Wlllis who chose to discuss it here. Perhaps you would prefer that Willis did not discuss anything that does not show it’s works.
Willis seems to have dropped his excellent habit of providing his R code in recent posts too. Maybe you wish to talk to AW about not “allowing” W to post either.
The calibration curve (as I understand it) is simply to allow C-14 measurements to be used to date items based on known reference points from known items (historical or from dendrochronology).
The curve CANNOT be used to measure cosmic ray production. Why? as the C-14 is diluted by ordinary CO2.
CO2 (with C-12 and C-14) is incorporated into plants (or carbonate deposits, marine shells etc).
We know that CO2 goes up and down with temperature, but we do not know true values.
So, C-14 production from N-14 is based on cosmic radiation level, which varies.
The dllution of C-14 by normal CO2 also varies based in temperature and other factors.
The calibration curve can be used to date samples, but in itself cannot be separated into the two factors: C14 production, and CO2 dilution.
End of Lesson!
I’d like to add this to the Lesson …
Here’s the conclusion ..
“7. Conclusions
Meteorological effects in the form of cloud cover
changes, atmospheric temperature changes, surface pressure
changes, and strengthening or weakening of winter
cyclones show correlations with the measured or inferred
changes in the ionosphere-earth current density Jz in the
global electric circuit. These responses are consistent in
onset time, duration and sign of the response with the Jz
changes associated with both solar activity and internal
atmospheric forcing. The responses are consistent with
the production of electric space charge in conductivity gradients
at the boundaries of cloud and aerosol layers by the
flow of Jz through them, and consistent with the theory of
electrical effects on scavenging of cloud condensation
nuclei and ice-forming nuclei by droplets. However, the
overall effect for climate of the consequent variations of
cloud cover in latitude, altitude and cloud type remain to
be worked out.
The large changes in galactic cosmic ray flux on time
scales from decades through millennia produce changes
in Jz that have the potential to account for records of
long-term climate variations that correlate with cosmic
ray flux changes. Also, changes in temperature and humidity
in the thunderstorm-generating regions of land masses
at low latitudes modulate the current density flowing everywhere
in the global circuit. This may affect cloud cover
everywhere, especially with surface temperature changes
on the longer time scales.”
http://gacc.nifc.gov/sacc/predictive/SOLAR_WEATHER-CLIMATE_STUDIES/GEC-Solar%20Effects%20on%20Global%20Electric%20Circuit%20on%20clouds%20and%20climate%20Tinsley%202007.pdf
And the Geomagnetic Field is created by the “flow of liquid iron generates electric currents, which in turn produce magnetic fields. Charged metals passing through these fields go on to create electric currents of their own, and so the cycle continues. This self-sustaining loop is known as the geodynamo.”
http://www.physics.org/article-questions.asp?id=64
It truly is a electric universe.
As I’ve commented above. It is the deviations which ( may ) reflect 14C production. Temperature dependence of update may explain why the curve deviates into a different, messy and uncertain from during the last glaciation.
It’s interesting that he roughly linear section goes all the way back to 20-22ka BP . Maybe there is something to be inferred about climate or temp. dependance of d14C in that observation.
Sorry , a bit garbled.
Temperature dependence of uptake may explain why the curve deviates into a different, messy and uncertain form during the last glaciation.
Greg, you pointed out in your 5:11am comment above , d14C measurement of 400 per mil you can choose between 14ka and 43ka !
I asked the question, “how good are the dendochronologies, “ that are critical to the calibration curve. If the calibration curve is remotely correct for periods prior to 14ka, How is it physically possible for a 43ka wood sample to show the same d14C as a 14ka wood sample? The difference in years is 30,000, roughly five half-lives, or 2^5 = 32. It that holds, we must conclude that somehow the atmospheric [14C]/[12C] concentration ratio 43ka was 32 times richer in 14C than it was 14ka.
I am at a complete loss how such an 32x enriched 14C environment could be present 43ka. Even if we suppose that 14C production is eight times higher that present day (or 14ka day), you’d be forced to quadruple the amount of fossil 12C (depleted in 14C) into the atmosphere.
Personally, I think the easier explanation is the dendochronologies and other references for 14C calibration at least prior to 23ka are horribly wrong.
An interesting graphic would be the calibration curve with the currently accepted [CO2] ppm, partial pressure, curves, the sea-level curve, and the paleo mag curves.
Further on paleomag. From Wikipedia ( Leschamp event 41.4 +/- 2 ka.
Ok, how much greater 14C production?
Introduction
Earth is permanently bombarded by high-energy nucleonic particles – cosmic rays, which
produce nucleonic-muon-electromagnetic cascades in the Earth’s atmosphere. As a subproduct
of the cascade, radioactive isotopes can be produced, called cosmogenic nuclides.
Measurements of the abundance of long-living cosmogenic radionuclides in the atmosphere
and terrestrial archives (ice cores, tree trunks, sediments, etc.) form a very important
tool to study atmospheric processes and interaction between different reservoirs (see, e.g.,
books by Dorman [2004] and Beer et al. [2012]). This also offers a reliable quantitative
method to study solar activity on the long time scale [McCracken et al., 2004; Solanki
et al., 2004; Vonmoos et al., 2006; Muscheler et al., 2007; Steinhilber et al., 2012; Inceoglu
et al., 2015; Usoskin, 2013; Usoskin et al., 2014]. Most important for these purposes
are cosmogenic isotopes 7Be (half-life ≈53 days), 22Na (2.6 years), 14C (5730 years), 36Cl
(3 · 10^5 years) and 10Be (1.4 · 10^6 years), and many studies are based on these data.
4.1. Solar cycle in 10Be
As an example of an application of the approach presented here, we have computed the
deposition flux of 10Be in the northern polar region and compared it with the measurements
in the NGRIP ice core [Berggren et al., 2009]. The deposition flux was calculated
in two steps. First, a 3D time varying pattern of the isotope atmospheric production was
calculated using the yield functions presented here and applying the reconstruction of
the modulation potential φ based on data from the global neutron monitor network since
1951 [Usoskin et al., 2011]. For the atmospheric transport we used a parameterization by
Heikkil¨a et al. [2009, see Table 3 there], applying the mean latitudinal height profile of the
tropopause. Finally, we calculated the deposition flux of 10Be in the Northern polar region.
A 1-year delay due to the transport was applied. The calculated 10Be flux is in very good
agreement with the real data, especially for the period 1951–1970 (see Figure 8). A minor
(about 5%) discrepancy after 1970 is most likely related to the post-deposition effects in
firn and/or to the regional climate variability on annual-decadal time scale [Pedro et al.,
2006, 2012]. The good agreement with data validates the yield-function for 10Be.
https://arxiv.org/pdf/1606.05899.pdf
Summary
We have performed a new consistent and precise computation of the production of five
cosmogenic isotopes, 7Be, 10Be, 14C, 22Na and 36Cl, in the Earth’s atmosphere by cosmic rays. Computations were made by means of a detailed Monte-Carlo simulation by the CRAC model using a recent version of the GEANT-4 tool. The results are presented in the Supporting information in the form of tabulated yield (production) functions for a wide set of atmospheric depths. We provide, for the first time, a full detailed set of the altitude profiles of the production functions which makes it possible to apply the results directly as input for atmospheric transport models. Our results are in good agreement with most of the earlier published works for columnar and global isotopic production rates. Comparison of the computations with measured data of 10Be for the last decades and also for a period around 780 AD validates the approach also in quantitative terms.
https://arxiv.org/pdf/1606.05899.pdf
The question is whether ionizing radiation can grow? Research shows that it can. Will greater ionization in the past hastened evolution? Probably so.
In 1965 Paul D. Jose published his discovery that both the motion of the Sun about the center of
mass of the solar system and periods comprised of eight Hale magnetic sunspot cycles with a
mean period of ~22.375 years have a matching periodicity of ~179 years. We have
investigated the implied link between solar barycentric torque cycles and sunspot cycles and
have found that the unsigned solar torque values from 1610 to 2058 are consistently phase and
magnitude coherent in ~179 year Jose Cycles. We are able to show that there is also a
surprisingly high degree of sunspot cycle phase coherence for times of minima in addition to
magnitude correlation of peaks between the nine Schwabe sunspot cycles of 1878 through 1976
(SC12 through SC20) and those of 1699 through 1797 (SC[-5] through SC4). We further identify
subsequent subcycles of predominantly non-coherent sunspot cycle phase. In addition we have
analyzed the empirical solar motion triggers of both sunspot cycle phase coherence and phase
coherence disruption, from which we boldly predict a future return to sunspot cycle phase
coherence at times of minima with SC12 to SC20 for SC28 to SC36. The resulting predicted start
times ± 1 year, 1 sigma, of future sunspot cycles SC28 to SC36 are tabulated.
https://arxiv.org/ftp/arxiv/papers/1610/1610.03553.pdf
Presented at this week’s Living Planet Symposium, new results from the constellation of Swarm satellites show where our protective field is weakening and strengthening, and importantly how fast these changes are taking place.
The animation above shows the strength of Earth’s magnetic field and how it changed between 1999 and May 2016.
Blue depicts where the field is weak and red shows regions where it is strong. As well as recent data from the Swarm constellation, information from the CHAMP and Ørsted satellites were also used to create the map.
It shows clearly that the field has weakened by about 3.5% at high latitudes over North America, while it has strengthened about 2% over Asia. The region where the field is at its weakest – the South Atlantic Anomaly – has moved steadily westward and weakened further by about 2%.
In addition, the magnetic north pole is wandering east, towards Asia.
http://www.esa.int/Our_Activities/Observing_the_Earth/Swarm/Earth_s_magnetic_heartbeat
GCR flux is not constant, so magnetic field variation isn’t the only cause of fluctuation in C14 production.
GCR flux also depends on where the solar system is in its orbit of the galactic barycenter.
http://www.sciencebits.com/ice-ages
Whew, Dr. S. cycle on top of cycle on top of cycle.
Here’s a new cycle for you..lol..the “OUT OF CHAOS,” cycle.
Please, no comment needed.
Without a thorough understanding of of Earth’s geomagnetic field in time this all seems frugal.
However, a period of about 1,000 years fluctuations GCR are dependent more on solar activity.
t is more likely that the Earth’s magnetic field depends somehow from the Sun’s magnetic field (as evidenced by the long periods of changes in Earth’s magnetic field).
Wow! What an interesting discussion.
Willis,
Here are my comments, some have been stated by others above and I apologize for any repetition.
There are problems and traps with 14C data, we all know that. But, the ~2300 (or 2400, or 2450 or 2500) year cycle is well known and well documented without 14C data. Let’s not lose the forest for the trees here.
“Then they throw away more than three-quarters of the data, leaving only the chunk since 9600 BC as shown in Figure 4.”
The data they throw away (prior to 9600BC) is so corrupted by the geomagnetic oscillations, the Younger Dryas warming and radical sea level changes it shouldn’t be used. The main geomagnetic oscillation has a 7,000 year cycle (John Southon, 2002, GRL), this had to be removed from the 11,000 year dataset they did use. There is no problem with the procedure recommended by Clilverd, et al. that I can see. He was conservative as some recent work by John Southon (2002 GRL) has tried to extend the useful 14C data back 14.5Kyrs, but given the Younger Dryas good luck with that (see Roth and Joos, 2013). 14C data is very difficult to work with and it is easy to make major errors with it. But, used carefully, it is helpful. Regarding the ~2300 year cycle, we would not want to depend only on 14C data, but in combination with paleoclimate data and 10Be data it does help.
“subtracted a 7000-year cycle of unknown origin , and”
The 7,000 year sinusoidal cycle removed is a well-known and well documented geomagnetic oscillation (John Southon, 2002 GRL)
“ASSERTED that the remainder represents solar variations with an underlying 2,300 year period …”
This “assertion” is also well known and supported by multiple lines of evidence, including 10Be data. Paleoclimate data including geophysical, biological, ice raft data and glaciological data support a strong worldwide ~2300-year climate cycle. This cycle has been recognized by numerous studies going back to the original Bray article in 1968. That it exists is not in dispute that I know of. The 14C study by Clilverd is evidence, but it is not necessary to show the cycle exists. Neither is it necessary to show that it is a solar cycle. The 10Be data does that along with the worldwide glacier, paleontological and ice raft data. Other evidence suggesting a solar origin is found in an orbital oscillation of 2318 years identified by Nicola Scaffetta and others (Earth-Science Reviews, Nov. 2016). Historical records support the 1300 Wolf minimum, the 1500 Sporer minimum and the 1700 Maunder minimum. Clilverd’s comparison of these historical periods with 3 Bray (or Hallstatt) cycles ago in his Figure 2 is very impressive. So, using the term “assertion” is a bit over the top in light of all of the evidence gathered and published over the last 50 years on the ~2300 year cycle. I don’t think we can say the 2300 year cycle is proven or completely understood, but it is very well established in the peer-reviewed literature.
Your question regarding the removal of the linear trend (secular trend) in the data is a good one. No one knows about the very long solar trends, only that they are apparent in the data. It was removed to enhance the 2300 year cycle and study it. It is simply “detrending” the data, a useful practice. It was done by Wyatt and Curry to get their “Stadium Wave.”
How cosmic rays affect clouds and cloudiness is a subject of much debate right now. I don’t think we have figured this out yet, but this hypothesis is not relevant to the discussion of the Bray cycle.
This thread appears to be mildly alive, and I’ve completed some analysis using frequency domain analysis. (I really should be doing a wavelet decomposition, but I don’t have that library running yet in octave). So here goes.
?dl=0
?dl=0
Executive Summary: there are clear signals at ~1000 years and ~2400 years, and probably ~7000 years. I’m pretty picky about declaring valid signals in data but I’m satisfied it’s there.
I noticed in the data there’s an estimate of the error sigma so I included a measurement noise floor in the mix.
I did not investigate thoroughly the idea that the data is itself an autocorrelated process with 1/f noise spectrum. However if you mentally draw that line it’s pretty clear that the signals mentioned above are still above that kind of noise floor.
There’s a pile of other data (e.g. southern hemisphere, marine calibration curves) in the same directory as this data, I have not yet investigated to see if similar results will be obtained.
Also, I have no idea whether the signals are due to the method of creating this data. Not my area of expertise. I just do signal processing.
Source code and copy of the intcal13 data is here: https://www.dropbox.com/sh/8hchg7kw1ah4rkc/AACMdM0Ny9y3yYvJBCLUOBzHa?dl=0
uses code from: https://www.dropbox.com/sh/ej9eozfhyqgd0es/AACGnhc3yLzUDSXKBfZbLEEfa?dl=0
Ugh, horizontal units on 2nd graph are 5 years. Forgot to fix that.
Thanks Peter. I also noticed that a google search for the “Hallstatt cycle” turned up 154,000 items. Many of these were about the 2300-2500 year solar/climate cycle. One of them is this gem from the European geophysical society that does a power spectrum analysis of the data and has a very prominent peak at 2300 years, see figure 3. http://www.ann-geophys.net/20/115/2002/angeo-20-115-2002.pdf
They conclude that the 2400 year period is the dominant period and provide support that the cause is a solar cycle.
Abstract
We derive two principal components (PCs) of temporal magnetic field variations over the solar cycles 21-24 from full disk magnetograms covering about 39% of data variance, with λ=-0.67. These PCs are attributed to two main magnetic waves travelling from the opposite hemispheres with close frequencies and increasing phase shift. Using symbolic regeression analysis we also derive mathematical formulae for these waves and calculate their summary curve which we show is linked to solar activity index. Extrapolation of the PCs backward for 800 years reveals the two 350-year grand cycles superimposed on 22 year-cycles with the features showing a remarkable resemblance to sunspot activity reported in the past including the Maunder and Dalton minimum. The summary curve calculated for the next millennium predicts further three grand cycles with the closest grand minimum occurring in the forthcoming cycles 26-27 with the two magnetic field waves separating into the opposite hemispheres leading to strongly reduced solar activity. These grand cycle variations are probed by α-ω dynamo model with meridional circulation. Dynamo waves are found generated with close frequencies whose interaction leads to beating effects responsible for the grand cycles (350-400 years) superimposed on a standard 22 year cycle. This approach opens a new era in investigation and confident prediction of solar activity on a millenium timescale.
https://www.researchgate.net/publication/283862631_Heartbeat_of_the_Sun_from_Principal_Component_Analysis_and_prediction_of_solar_activity_on_a_millenium_timescale