Guest Post by Willis Eschenbach
In investigations of the past history of cosmic rays, the deposition rates (flux rates) of the beryllium isotope 10Be are often used as a proxy for the amount of cosmic rays. This is because 10Be is produced, inter alia, by cosmic rays in the atmosphere. Being a congenitally inquisitive type of fellow, I thought I’d look to see just how good a proxy 10Be might be for solar activity. Now most folks would likely do a search of the literature first, to find out what is currently known about the subject.
I don’t like doing that. Oh, the literature search is important, don’t get me wrong … but I postpone it as long as I possibly can. You see, I don’t want to be mesmerized by what is claimed to be already known. I want to look whatever it is with a fresh eye, what the Buddhists call “Beginner’s Mind”, unencumbered by decades of claims and counter-claims. In short, what I do when faced with a new field is to go find some data and analyze it. After I’ve found out what I can from the dataset, and only then, do I search the literature to find out what other folks might believe. Yes, it costs me sometimes … but usually it allows me to find things that other folks have overlooked.
In this case, I found a gem of a dataset. Here is the author’s summary:
Annually-resolved polar ice core 10Be records spanning the Neutron Monitor era
Abstract: Annually-resolved 10Be concentrations, stable water isotope ratios and accumulation rate data from the DSS site on Law Dome, East Antarctica (spanning 1936-2009) and the Das2 site, south-east Greenland (1936-2002).
The only thing better than data is recent data, because it is more likely to be accurate, and here we have seven decades of recent 10Be deposition rates (fluxes). So, without fanfare, here’s the data in question
Figure 1. 10Be flux rates from Law Dome in Antarctica and from Southeast Greenland. Bottom panel shows the annual average sunspot count.
So … what’s not to like about these records? Well … lots of things.
The first unlikable item is that the correlation between these two 10Be datasets is pathetic, only 0.07. Seems to me like this would be enough in itself to put the whole 10Be—cosmic rays connection into doubt. I mean, if the two best recent dataset don’t agree with each other, then what are we supposed to believe?
The next problem is even larger. It is the lack of any clear 11-year signal from the variations in cosmic rays. It is well-known that cosmic rays are deflected from the solar system by the magnetic field of the sun, which varies in general sync with the sunspots. As a result, the numbers of cosmic rays, and presumably the 10Be flux rates, vary in an 11-year cycle inversely to the sunspot cycle. Here’s what the relationship looks like:
Figure 2. Sunspots and cosmic rays (as indicated by the neutron count). SOURCE
So the relation between cosmic rays and sunspots is quite solid, as you can see above. However, the problem with the 10Be records in this regard is … they have no power in the 11-year cycle range. Sunspot data has power in that range, as does the neutron count data representing cosmic rays … but the 10Be data shows nothing in that range. Here’s the periodicity analysis (see here et seq. for details of periodicity analyses):
Figure 3. Periodicity analysis of the two datasets shown in Figure 1, 10Be flux from Greenland and Antarctica
As you can see, we have no power in either the 11-year or 22-year bands … and if you look at Figure 1, you can see that their correlation with the sunspots is … well … pathetic. The correlation between Greenland 10Be and sunspots is -0.10, and between Antarctica 10Be and sunspots is even worse, -0.03 … like I said, pathetic. A cross-correlation analysis shows slightly greater correlations with a 2 year lag, but not much. However, the lack of the 11-year peaks periodicity analysis (or visible 11-year peaks in the 10Be data) suggests that the lag is spurious.
The problem is, both the sunspots and the cosmic ray counts have a huge peak in periodicity at 10-11 years … but the 10Be records show nothing of the sort.
So, at this point I’m in as much mystery as when I started. We have two beryllium-10 records. They don’t agree with each other. And according to both periodicity and correlation analysis, they don’t show any sign of being connected to anything related to the sunspots, whether by way of cosmic rays, TSI, or anything else …
Now that I’ve finished the analysis, I find that the notes to the dataset say:
Cosmogenic 10Be in polar ice cores is a primary proxy for past solar activity. However, interpretation of the 10Be record is hindered by limited understanding of the physical processes governing its atmospheric transport and deposition to the ice sheets. This issue is addressed by evaluating two accurately dated, annually resolved ice core 10Be records against modern solar activity observations and instrumental and reanalysis climate data. The cores are sampled from the DSS site on Law Dome, East Antarctica (spanning 1936–2009) and the Das2 site, south-east Greenland (1936–2002), permitting inter-hemispheric comparisons.
Concentrations at both DSS and Das2 are significantly correlated to the 11-yr solar cycle modulation of cosmic ray intensity, r = 0.54 with 95% CI [0.31; 0.70], and r = 0.45 with 95% CI [0.22; 0.62], respectively. For both sites, if fluxes are used instead of concentrations then correlations with solar activity decrease.
If you use flux rates the “Correlations with solar activity decrease”??? Yeah, they do … they decrease to insignificance. And this is a big problem. It’s a good thing I didn’t read the notes first …
Now, my understanding is that using 10Be concentrations in ice cores doesn’t give valid results. This is because the 10Be is coming down from the sky … but so is the snow. As a result, the concentration is a factor of both the 10Be flux and the snow accumulation rate. So if we want to understand the production and subsequent deposition rate of 10Be, it is necessary to correct the 10Be concentrations by using the corresponding snow accumulation rate to give us the actual flux rate. So 10Be flux rates should show a better correlation with sunspots than concentrations, because they’re free of the confounding variable of snow accumulation rate.
As a result, I’ve used the flux rates and not the concentrations … and found nothing of interest. No correlation between the datasets, no 11-year periodicity, no relationship to the solar cycle.
What am I missing here? What am I doing wrong? How can they use the concentration of 10Be rather than the flux? Are we getting accurate results from the ice cores? If not, why not?
These questions and more … please note that I make no overarching claims about the utility of 10Be as a proxy for sunspots or cosmic rays. I’m just saying that this particular 10Be data would make a p-poor proxy for anything … and once again I’m raising what to me is an important question:
If the 10Be deposition rate is claimed to be a proxy for the long-term small changes in overall levels of cosmic rays … why is there no sign in these datasets of it responding to the much larger 11-year change in cosmic rays?
I have the same question about cosmic rays and temperature. There is no sign of an 11-year cycle in the temperature, meaning any influence of cosmic rays is tiny enough to be lost in the noise. So since temperature doesn’t respond to large 11-year fluctuations in cosmic rays, why would we expect temperature to track much smaller long-term changes in the cosmic ray levels?
Always more questions than answers, may it ever be so.
My regards to everyone, guest authors, commenters, and lurkers … and of course, Anthony and the tireless mods, without whom this whole circus wouldn’t work at all.
w.
COMMENTS: Please quote the exact words that you are referring to in your comment. I’m tired of trying to guess what folks are talking about. Quote’m or you won’t get traction from me. Even if the reference is blatantly obvious to you, it may not be to others. So please, quote the exact words.
DATA: 10Be original data, Excel spreadsheet
CODE: Just for fun, I’ll put it here to show how tough this particular analysis was:
source("~/periodicity functions.R")
par(mgp=c(2,1,0),cex.axis=1)
spotsraw=ts(read.csv("monthly ssn.csv")[,2],start=c(1749,1),frequency=12)
Annual.Sunspots=window(aggregate(spotsraw,frequency=1,FUN=mean),start=1937,end=2009)
plot(Annual.Sunspots)
theflux=ts(read.csv("Polar 10Be Flux.csv")[,2:3],start=1937,frequency=1)
theoxy=ts(read.csv("Polar 10Be Flux.csv")[,4:5],start=1937,frequency=1)
plot(cbind(theflux,theoxy))
fulldata=cbind(theflux[,1],theflux[,2],Annual.Sunspots)
colnames(fulldata) = c("Greenland 10Be Flux","Antarctica 10Be Flux","Sunspots")
plot(fulldata,main="",yax.flip=TRUE)
title(main="10Be Flux Rates in Greenland and Antarctica\n(atoms / square metre / second)",
line=1,cex.main=1.1)
cor(ts.intersect(fulldata),use="pairwise.complete.obs")
periodsd(theflux[,1],doplot=TRUE,timeinterval=1,add=FALSE,col="blue3",
maintitle="Periodicity Analysis, Ice Core 10Be Flux\nGreenland (blue) and Antarctica (red)")
periodsd(theflux[,2],doplot=TRUE,timeinterval=1,add=TRUE,col="green3")
You’ll need the code for the periodicity functions, it’s here.
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“…The deposition rates (flux rates) of the beryllium isotope 10Be are often used as a proxy for the amount of cosmic rays.. because 10Be is produced, inter alia, by cosmic rays in the atmosphere. .. the correlation between these two 10Be datasets [Antarctica, Greenland] is pathetic…[there is] lack of any clear 11-year signal from the variations in cosmic rays. [Clear? There is none]
I seem to remember Dr Svalgaard on another thread, when we were discussing historic Sunspot numbers, said that he believed that during the Maunder Minimum Solar activity [and thus presumably the TSI] was not reduced and he based that on the Be isotope evidence, (or some other eminent scientists did). I guess that belief is on somewhat shaky ground.
Tony
It fits remarkably well. Send me an email and I’ll send it to you
Don
Willis Eschenbach says:
April 13, 2014 at 7:20 pm
“You’ve linked to the Holgate sunspot nonsense, which I falsified in my post “Sunspots and Sea Level….“.
Willis,
You did two interesting posts in which you believe you falsified two claimed correlations with solar activity: sea level rise (e.g. Holgate) and the South American river. Here are my thoughts on these two:
1. South American river flow.
The first obvious thing was that the Mk 1 eyeball didn’t show any obvious correlation. It required sophisticated statistical methods to bring out the claimed correlation. As far as I’m concerned, if it requires this kind of data manipulation then either the correlation is so small as to be of no significance, or it doesn’t exist and it’s an artifact of the analysis.
I thought your analysis was excellent and I agree that you falsified this claim. Bad news for Brian Cox, who included this claim in his excellent series ‘Wonders of the Solar System’ and also the book version.
2. Sea level (Holgate etc).
There is an obvious contrast between the two: with the Holgate data the apparent correlation almost literally reaches out and grabs you by the throat. You can see apparent correlation with the sea level data, while you cannot with the river data.
Your one argument against real correlation was a very low r2 value. I don’t think you had any other arguments.
Trouble is, r2 is essentially useless for measuring correlation between variables that do not have simple, linear relationships. r2 works by first creating the best linear fit, and then measuring how well the data points match the linear fit.
There’s a well known saying that it’s impossible to prove a negative. I think this may apply to r2. If r2 returns a high value then it’s probably significant. But if it returns a low value it’s fairly meaningless. A low value would occur if there is very high correlation but the relationship is complex and non-linear.
I imagine r2 for two identical straight lines would be 1 (one). But in a sense there’s no correlation at all. There are no features that match. They’re just – well, straight lines, basically. But if two graphs have many features and they match well, then I would say there is good correlation.
A good example comes from the ice core temperature and CO2 records. There are huge numbers of features and they match amazingly well. All believers and sceptics would agree that there is very high correlation. Of course, as it turned out, the CO2 lags the temperatures, but the correlation is extraordinary.
I would rate the sea level apparent correlation as weaker than the ice core data, but nevertheless it’s still very strong.
You are clearly claiming that the apparent relationship is due to chance. Then prove it. Generate hundreds or thousands of graphs with random data (e.g. red noise) and see how many produce a similar apparent correlation. It’s a standard statistical test (Monte Carlo), I’m really surprised you haven’t done it.
Unless you can demonstrate this then I think your falsification score on these two is one out of two.
Keep up the good work. But, please, don’t rely on a low r2 score to claim falsification. If you get a low r2 value then you need another independent argument to prove falsification.
Chris
Hi Don
I’ve sent an email to what I think is your current address. If it doesn’t turn up please let me know.
tonyb
ghl says:
April 13, 2014 at 11:43 pm
I am having trouble imagining the apparatus that would count 150 atoms per square metre per second, especially in the ’50s.
The neutron monitors used back then are still in use. They can do that. As far as counting 10Be atoms, the apparatus can be seen in the upper left of Slide 13 of http://www.leif.org/research/On-Becoming-a-Scientist.pdf
note the man in the yellow oval. We can actually count the atoms one by one, see also http://en.wikipedia.org/wiki/Accelerator_mass_spectrometry
Scarface says:
April 14, 2014 at 12:21 am
1. Do I understand it correct that only 55g/yr is produced of 10Be?
Yes and that is the worldwide total.
2. If so, wouldn’t that make 10Be a very difficult proxy, because both its presence and chance of being found somewhere are so small?
55 gram is a lot of atoms and our measuring instruments [see just above] are exquisite sensitive.
3. Wouldn’t 14C make a better proxy? (slightly better; 8 kg if true isn’t much either)
For annual time resolution 14C is no goos as the residence time in the atmosphere is too long.
4. And is 10Be used because it’s in the ice-cores instead of in treerings? Or is 14C also present in CO2 that is captured in icecore bubbles?
There is also 14C in the CO2, but see your point 3.
5. Svensmarks theory is about clouds and cosmic rays. What would, in your opinion, be a good proxy for the nuclei that are said to be produced by cosmic rays?
well, the nuclei themselves are fine. No need for proxy.
Thanks again, Willis. I was just thinking this needed addressing — Dr Svalgaard’s repeated cautions on beryllium proxies was seemingly being ignored. Beryllium proxies are similar to Mann’s tree-rings — too many potential influences to be very useful.
tonyb: Here is my reconstruction of CET from 1659 to 1538. It is evident that the period around `1500 to the start of the reconstruction will turn out to be rather warm. The 50 years from 1450 look as if they were rather cold.
http://curryja.files.wordpress.com/2011/12/11.jpg
If you overlay your plot against this extended record how does it look?
========
I take it is something different to the ‘official’ Met. Office CET. How did you derive it? Could you post the data to a dropbox or host it somewhere for download?
I would recommend fixing the lag in the running mean before comparing to anything else. Even better use a decent low pass filter that won’t give you troughs where peaks should be 😉
http://climategrog.wordpress.com/2013/05/19/triple-running-mean-filters/
Don Easterbrook: “Seems like a bit of a stretch to conclude that these longer term correlations are just coincidence”
It’s quite possible for two quantities to correlate at low frequency but much more poorly at monthly resolution. This is one of the problems with “you should NEVER smooth before doing analysis”.
If “smoothing” is just that I agree. Sadly this word is also commonly used for low-pass filtering intended to remove a specific signal (like annual). If you want to look at long term correlation, removing HF noise may be legit. It is just necessary to adjust the number of data points when subsequently doing stats since you’ve reduced the degrees of freedom in the data. (eg if you filtered monthly data with a 12mo low-pass , divide N by 12. If you are looking at R or R^2 then you need to re-evaluate what value constitute significance. )
Most recent reconstruction of the
solar activity for the past 9000 years is by Steinhilber et al
with another dozen co-writers, including McCracken, Abreu, Beer, Miyahara, etc. highly respected scientists.
Some errors in the reconstructions appear to be due to subtracting geomagnetic portion of modulation, based on the dipole data that is grossly over-filtered.
I did my own calculation, Dr. McCracken (one of the authors, ex NASA and the world expert in the field) commented :
“…….In that light, your plot is very interesting and could quantify “minor” in the above statement . What are the units of both quantities on the Y axis. Are these amplitude or power spectra. In particular, do you have the percentage amplitudes of the spectral lines in the dipole strength for T > 500 years. That would allow us to compute the periodic changes in the geomagnetic cut-off rigidity (see (1) above), and from that, compute the amplitudes of the periodic variations in 10Be and 14C due to the secular changes in the geomagnetic field. That would be a very useful finding.
Ken “
The Steinhilber et al paper’s link, the plot Dr. McCracken refers to and relevant answer to his question can be found here:
GCR-etc.pdf
There was no need to explain your approach. It is evident in most articles that you don’t care about what is known; instead, you blast out with some lengthy article on things that boggle your mind, and which wouldn’t boggle at all if you had openend a book or mag for 5 minutes. This got to be the least productive approach of them all.
No need to use historical data in order to observe the effects of GCR. It is a pity that some people are no at time.
The only data that would make sense is not the 10Be level, but the ratio of 10Be level to 9Be, to show how much is produced. This means the total concentration must be found separately from the 10Be level. If this is done, I expect a much better correlation should be found.
But how can that be, given the convincing data that Willis and Leif have shown?
==============
the 10Be data suggests:
1. the mechanism that produces 10Be is not the same mechanism that deposits 10Be on the surface.
2. there is a lag between 10Be production and deposition.
Perhaps the mechanism is molecular weight? 10Be atoms weight less than N2, O2, H2O. Perhaps they float around in the atmosphere for years before being rained out to the surface. This would have the effect of smearing the production rate over the short term (years). Only longer term production rates would be apparent (decades, centuries).
Leonard Weinstein says:
April 14, 2014 at 6:38 am
The only data that would make sense is not the 10Be level, but the ratio of 10Be level to 9Be, to show how much is produced.
The problem is that 9Be is not radioactive so is very hard to measure and furthermore doesn’t fall out of the sky to be deposited in the ice as 10Be does, so there isn’t any.
@ur momisugly Leif Svalgaard (April 14, 2014 at 4:48 am)
Thank you very much! A final question though, wrt 10Be.
How long is the residence time in the atmosphere on average before an atom is caught in the ice?
Is it evenly produced in the atmosphere? Could winds, rainfall and/or jetstreams prevent arrival at the poles, and thus in the ice cores?
(btw, I’m still rather speechless about the annual weight of the produced 10Be; I believe you that you can count the atoms seperately, but the distribution around the globe and the need for getting caught in the ice at the poles seem to make it a difficult proxy)
Scarface says:
April 14, 2014 at 6:51 am
How long is the residence time in the atmosphere on average before an atom is caught in the ice?
one to two years
Is it evenly produced in the atmosphere? Could winds, rainfall and/or jetstreams prevent arrival at the poles, and thus in the ice cores?
Most is produced at lower latitudes simply because there is more area down there. Atmospheric motions determine how much is transported to the poles.
Hi Willis, hope I did not miss this in the comments but if you are hitting the atmosphere with cosmic rays, such as neutrons or protons, to create Be10 you need high energy cosmic rays for that to happen. Solar cosmic rays are not energetic, and the source of the cosmic rays for spallation in the atmosphere is I believe extra solar. That means that there should in fact be no correlation between solar activity and 10Be.
For a proton to hit the nucleus and interact with it, it needs enough energy to overcome the coulomb repulsion it experiences with the nucleus, which like the proton, is positively charged. (This is what makes nuclear fusion so hard to do). Low energy protons would simply interact with the electron cloud and cause no Be10 formation.
Low energy neutrons can hit the nucleus and be absorbed, but the resultant nucleus will either be stable or beta decay back to stability. To get Be10 you need to hit a target nucleus like )16 or N14 with a whack of energy to create a highly energetic excited state that has some probability of decaying to Be10, because the decay fragments will also have to overcome the coulomb barrier for it to be possible.
That means that you have to have high energy cosmic rays, and I do not think they come from the sun.
I must confess to greater confidence on the nuclear physics as opposed to solar cosmic rays, no expertise in cosmic rays, but I am pretty sure they are due to the solar wind and are low energy, 100s of eV instead of the 10s MeV required for spallation.
***
Don Easterbrook says:
April 14, 2014 at 1:43 am
I’m looking at a plot of 10Be from 1400 AD to the present and I can easily pick out the Wolf, Sporer, Maunder, Dalton, and 1880-1915 Solar Minimums from just the 10Be curve. And plotting δ18O from the GISP2 Greenland ice core data and overlaying it on the 10Be curve gives a good correlation with paleotemperature. Overlaying it on the CET temperature curve also gives a reasonably good fit—not perfect, but discernable.
***
My guess is that the climate itself is influencing the 10Be (deposition) — not the other way around.
In reply to lsvalgaard says:
April 13, 2014 at 8:48 pm
William Astley says:
April 13, 2014 at 8:26 pm
This site provides a direct measurement of GCR.
http://cosmicrays.oulu.fi/webform/query.cgi?startday=13&startmonth=03&startyear=1968&starttime=00%3A00&endday=04&endmonth=04&endyear=2014&endtime=23%3A30&resolution=Automatic+choice&picture=on
William:
I would highly recommend the Oulu site as it includes a software option to select the start and end date to see how GCR has changed solar cycle by solar cycle.
http://cosmicrays.oulu.fi/
As I noted in my comment GCR modulation of planetary clouds is inhibited by solar wind burst that remove cloud forming ions. If there are a high number of strong solar wind bursts during the end of solar cycle the solar wind bursts remove the ions formed by the GCR making appear that high GCR does not modulate planetary clouds.
As the Oulu data shows GCR (galactic cosmic rays also called cosmic ray flux. GCR/CRF are mostly high speed protons that created by super nova explosions. The GCR strike the earth’s atmosphere creating ions that create clouds.), at the maximum of solar cycle 24 is roughly the same as the average GCR in other solar cycles. As solar cycle 24 declines cloud forming GCR will reach the highest levels in 100 years. The resultant of the high GCR will be the planet will cool.
http://cosmicrays.oulu.fi/webform/query.cgi?startday=13&startmonth=03&startyear=1968&starttime=00%3A00&endday=04&endmonth=04&endyear=2014&endtime=23%3A30&resolution=Automatic+choice&picture=on
Due to the configuration of the earth’s magnetic field the GCR affect is strongest at high latitudes (see Svensmark’s book Chilling Stars, available in most public libraries for an overview of the GCR mechanism).
http://www.amazon.com/The-Chilling-Stars-Cosmic-Climate/dp/1840468661
It is interesting to note the majority of the warming in the last 70 years has been at high latitudes which does not match the signature of warming if CO2 was the forcing mechanism.
http://bobtisdale.files.wordpress.com/2013/11/figure-72.png
As would be expected the high latitude regions of the planet are now starting to cool due to the high GCR.
http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/seaice.anomaly.antarctic.png
eg if you filtered monthly data with a 12mo low-pass , divide N by 12. If you are looking at R or R^2 then you need to re-evaluate what value constitute significance.
===============
exactly!! instead whole branches of “science” process their data to “reduce noise” then naively apply statistical tests as though they were dealing with raw data. And low and behold when they find a significant R value, they can’t understand that the statistics is measuring their methods, not their data.
Statistics cannot separate data from methods. When you process the data ahead of your statistics, the statistical results reflect both the data and the methods. Maybe the significance is a result of the data, but maybe it is a result of your methods. As a result you cannot be confident in what the statistics are telling you.
The current epidemic of false positives in scientific papers is by and large a result of naively applying statistics to processed data, without considering that it is the processing that is creating a false statistical confidence.
There should be a standard rule when analyzing scientific papers. If the authors are applying statistics to filtered or processed data, the result is as likely to be garbage as not. Thus, all such papers should be rejected.
If such papers were routinely rejected, a great deal of false scientific conclusions would have been eliminated over the years.
@ur momisugly Leif Svalgaard
Thank you very much for replying so quickly again!
The question why Willis Eschenbach couldn’t find any clear 11-year signal from the variations in cosmic rays via 10Be as a proxy looks to be solved with your answers, as far as I am concerned.
10Be records seem to represent long time averages of atoms, produced at different moments in time, which must somehow, someday, through a chaotic atmosphere, reach any of the poles and get caught in ice.
William Handler says:
April 14, 2014 at 7:05 am
the source of the cosmic rays for spallation in the atmosphere is I believe extra solar.
Yes, they come from the Galaxy [created in supernova explosions and accelerated en-route by encounters with the interstellar medium]. But the Sun’s magnetic field [extending into interplanetary space] is capable of deflecting some of the protons back out of the solar system, so the Sun modulates the galactic cosmic ray flux by about 10%.
Scarface says:
April 14, 2014 at 7:16 am
10Be records seem to represent long time averages of atoms, produced at different moments in time, which must somehow, someday, through a chaotic atmosphere, reach any of the poles and get caught in ice.
Not too long, only a couple of years, but a lot can happen to them during that time.
Lake sediments provide useful climate records because the annual varves can provide accurate dating.
For 10Be and solar cycles see.
http://gfzpublic.gfz-potsdam.de/pubman/faces/viewItemFullPage.jsp?itemId=escidoc:240535
Here is the abstract r
“Annually resolved terrestrial 10Be archives other than those in polar ice sheets are heretofore unexplored sources of information about past solar activity and climate. Until now, it has proven difficult to find natural archives that have captured and retained a 10Be production signal, and that allow for annual sampling and contain sufficient 10Be for AMS measurement. We report the first annually resolved record of 10Be in varved lake sediments. The record comes from Lake Lehmilampi, eastern Finland, which lies at 63°37′N, 29°06′E, 95.8 m a.s.l. The focus on the last 100 years provided an unprecedented opportunity to compare sediment 10Be data with annual ice core, neutron monitor and sunspot number data. Results indicate successful recovery of 10Be atoms from as little as 20 mg sediment. Sediment 10Be accumulation rates suggest control by solar activity, manifested as a reflection of the 11-year Schwabe solar cycle and its amplitude variations throughout the investigated period. These results open the possibility of using varved lake sediment 10Be records as a new proxy for solar activity, thus providing a new approach for synchronization of paleoclimate events worldwide.”
Here is another paper tying climate changes reflected in the sedimentary record to longer term solar cycles including the 1000 year cycle which I use in my forecasts at
http//climatesense-norpag.blogspot.com.
http://fallmeeting.agu.org/2012/eposters/eposter/pp33a-2077/
From the abstract.
” Based on an already established age model the study covers about two millennia of Late Miocene time with a resolution of ~13.7 years per sample. No major ecological turnovers are expected in respect to this very short interval. Thus, the pollen record suggests rather stable wetland vegetation with a forested hinterland. Shifts in the spectra can be mainly attributed to variations in transport mechanism, represented by few phases of fluvial input but mainly by changes in wind intensity and probably also wind direction. Even within this short time span, dinoflagellates document rapid changes between oligotrophic and eutrophic conditions, which are frequently coupled with lake stratification and dysoxic bottom waters. These phases prevented ostracods and molluscs from settling and fostered the activity of sulfur bacteria. Several of the studied proxies reveal iterative patterns. To compare and detect these repetitive signals REDFIT spectra were generated and Gaussian filters were applied. The resulting cycles correspond to the lower and upper Gleissberg, the de Vries/Suess, the unnamed 500-year, 1000-year 1,500-year and the Hallstatt cycles. To test the solar-forcing-hypothesis, our data have been compared with those from a Holocene isotope dataset. Our data represent a first unequivocal detection of solar cycles in pre-Pleistocene sediments.
Here is a quote from one of my posts re solar effects on climate in general
“NOTE !! the connection between solar “activity” and climate is poorly understood and highly controversial. Solar ” activity” encompasses changes in solar magnetic field strength, IMF, CRF, TSI ,EUV ,solar wind density and velocity, CMEs, proton events etc. The idea of using the neutron count as a useful proxy for changing solar activity and temperature forecasting is agnostic as to the physical mechanisms involved.”
William Astley says:
April 14, 2014 at 7:12 am
I would highly recommend the Oulu site as it includes a software option to select the start and end date to see how GCR has changed solar cycle by solar cycle.
Many other sites do that too, but I would nor recommend Oulu as its counts lately has run above what other stations show.
As I noted in my comment GCR modulation of planetary clouds is inhibited by solar wind burst that remove cloud forming ions.
No, there is no evidence for that.