Cosmic Rays, Sunspots, and Beryllium

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

10be flux rates greenland antarcticaFigure 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:

thule greenland neutron monitorFigure 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):

periodicity analysis greenland antarcticaFigure 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

Extracted Data for Use In R

Monthly Sunspot Data SIDC

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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ren
April 14, 2014 7:55 am

GCR in the north most ionizes the ozone layer over Canada and Western Siberia, which indicates a magnetic field. There radiation is bent toward the surface of the Earth. Weak solar activity means the repetition of weather types in the stratosphere and what is important for predictions.
http://oi61.tinypic.com/2llepw3.jpg
http://oi58.tinypic.com/5aot1u.jpg

April 14, 2014 8:19 am

“A proxy does not have to be 100% perfect. Sunspots aren’t either, though just throwing hands up in the air and saying one knew nothing about past solar activity wouldn’t be remotely true.”
unless it’s tree rings

Reply to  Steven Mosher
April 14, 2014 8:50 am

@mosher sunspots do have one distinct advantage over tree rings as a proxy – they aren’t subject to the many variables of Leibig’s Law of the Minimum

William Astley
April 14, 2014 8:49 am

In reply to:
lsvalgaard says:
April 14, 2014 at 7:43 am
William:
Your comment is not correct. Solar wind bursts create a space charge differential in the ionosphere which remove cloud forming ions.
The following is a review paper that describes the mechanism, a more recent paper that provides to data confirm the electroscavenging mechanism, and finally a paper that notes there were solar wind bursts in during the declining phase of solar cycle 23 which partially explains why the planet did not cool due to the increased GCR.
The mechanisms that were inhibiting GCR modulation of planetary cloud are abating. Observational evidence to support that assertion is sudden and unexplained in sea ice both poles.
http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/seaice.anomaly.antarctic.png
http://www.utdallas.edu/physics/pdf/Atmos_060302.pdf
Atmospheric Ionization and Clouds as Links Between Solar Activity and Climate
Observations of changes in cloud properties that correlate with the 11-year cycles observed in space particle fluxes are reviewed. The correlations can be understood in terms of one or both of two microphysical processes; ion mediated nucleation (IMN) and electroscavenging. IMN relies on the presence of ions to provide the condensation sites for sulfuric acid and water vapors to produce new aerosol particles, which, under certain conditions, might grow into sizes that can be activated as cloud condensation nuclei (CCN). Electroscavenging depends on the buildup of space charge at the tops and bottoms of clouds as the vertical current density (J) in the global electric circuit encounters the increased electrical resistivity of the clouds. Space charge is electrostatic charge density due to a difference between the concentrations of positive and negative ions.
http://www.sciencedirect.com/science/article/pii/S0273117707001135
The role of the global electric circuit in solar and internal forcing of clouds and climate by Brian A. Tinsley, G.B. Burns, Limin Zhou
The observed short-term meteorological responses to these five inputs are of small amplitude but high statistical significance for repeated Jz changes of order 5% for low latitudes increasing to 25–30% at high latitudes. On the timescales of multidecadal solar minima, such as the Maunder minimum, changes in tropospheric dynamics and climate related to Jz are also larger at high latitudes, and correlate with the lower energy component (_1 GeV) of the cosmic ray flux increasing by as much as a factor of two relative to present values. Also, there are comparable cosmic ray flux changes and climate responses on millennial timescales. The persistence of the longer-term Jz changes for many decades to many centuries would produce an integrated effect on climate that could dominate over short-term weather and climate variations, and explain the observed correlations.
http://www.agu.org/pubs/crossref/2009/2009JA014342.shtml
If the Sun is so quiet, why is the Earth ringing? A comparison of two solar minimum intervals.
Observations from the recent Whole Heliosphere Interval (WHI) solar minimum campaign are compared to last cycle’s Whole Sun Month (WSM) to demonstrate that sunspot numbers, while providing a good measure of solar activity, do not provide sufficient information to gauge solar and heliospheric magnetic complexity and its effect at the Earth. The present solar minimum is exceptionally quiet, with sunspot numbers at their lowest in 75 years and solar wind magnetic field strength lower than ever observed. Despite, or perhaps because of, a global weakness in the heliospheric magnetic field, large near-equatorial coronal holes lingered even as the sunspots disappeared. Consequently, for the months surrounding the WHI campaign, strong, long, and recurring high-speed streams in the solar wind intercepted the Earth in contrast to the weaker and more sporadic streams that occurred around the time of last cycle’s WSM campaign.

April 14, 2014 8:51 am

“Overlaying it on the CET temperature curve also gives a reasonably good fit—not perfect, but discernable. But how can that be, given the convincing data that Willis and Leif have shown? How can both be correct? Seems like a bit of a stretch to conclude that these longer term correlations are just coincidence, or that the data isn’t very good and just happens to match up, or something unrelated to solar variation is responsible. ”
1. what is a reasonable fit?
2. CET is from a location that is quite unique geographically speaking. That is, it is not representative. Try the long records from any other location.
3. what do you mean the data isnt good? just cause it doesnt match theory? sarc off
4. “something unrelated to solar”, yes save the theory at all costs.
What you see here folks are the troubles that plague all OBSERVATIONAL SCIENCE.
what is observational science and how does it differ from lab science.
Well, in lab science we can formulate a theory and we can test a theory. We identify the variables
that we think matter, and we do controlled experiments. Like the cloud experiments at CERN.
All controlled. Theory is built, hypothesis are derived from the theory, hypothesis are tested.
Ideally everything is controlled, planned, and tested. “We predict and increase in particle X, we do the test, we see the increase”
Then comes the mistake. The mistake is thinking that all science, that all knowing, that all practical reliable knowledge and understanding comes through this method. Let’s start by granting a special status to this kind of knowledge. However, even if we do grant it a special status, it’s a mistake to make this approach to understanding and explanation, the only approach. And that is where observational
science comes in. Let’s take Leif’s solar science. Leif cannot do controlled experiments with the sun. He cannot, for example, remove jupiter to test the effect of the Jupiter on sun Spots. So what are we left with?
1. Data that cannot speak for itself. You have data that was collect haphazardly, data that was
collected for other purposes, with changing instruments, data lost, data recovered.
In short the data will always be entangled with the theory and so subject to doubt and
contention. worshippers of raw data from the lab sciences, will have a fit.
2. No way to do controlled experiments. You must wait for nature to show you what she will.
That is why this historical period is very interesting.
3. Models. because you cannot do controlled experiments you are stuck with having to model
things. These range from statistical models to physical models. Because your theory is drawn from observations that you cant control, you cant do parameter exploration unless you model. And without parameter exploration ( vary parameter x, from y to z) you really dont have a complete theory.
4. Arguments that cannot be settled by the lab method. In the end observational scientists try to construct an understanding that makes the “most sense” of all the data, that ties together with other physics, that maximizes coherence and minimizes discord. It is a making sense of the past.. more a history constrained by math, logic and physics than anything else

William Astley
April 14, 2014 8:58 am

The link in my above comment to the electroscavenging and GCR review paper did not work. The following is a new link to the same review paper.
http://www.agu.org/books/gm/v141/141GM22/141GM22.pdf
Atmospheric Ionization and Clouds as Links Between Solar Activity and Climate
Figure 3. Solar wind variations modulate the fluxes of GeV galactic cosmic rays and the MeV electrons coming into the atmosphere, and the ionospheric potential in the polar caps. The fluxes of energetic particles change the vertical column resistance between the ionosphere and the surface, particularly at middle and high latitudes, and this together with the variations in ionospheric potential, change the electrical currents flowing down from the ionosphere into clouds.

tonyb
Editor
April 14, 2014 9:03 am

Don Easterbrook
My email to you has been returned so guess I found the wrng address. Can you contact me so you can send me the overlay?
TONYATClimatereasonDOTcom
thanks
tonyb

April 14, 2014 9:09 am

William Astley says:
April 14, 2014 at 8:49 am
Your comment is not correct. Solar wind bursts create a space charge differential in the ionosphere which remove cloud forming ions.
There are no cloud forming ions in the ionosphere.
With all due respect to my friend Brian Tinsley, his mechanism is not generally accepted as valid.
The global circuit is maintained by thunderstorms not by the solar wind. Please don’t pollute the blog with long quotes. The link should be enough, possibly with a few lines added that make the essential point.
If the Sun is so quiet, why is the Earth ringing? A comparison of two solar minimum intervals.
You dredge up an irrelevant paper, and the WHI analysis is just over-interpretation of too little data. The Sun rings just before solar minimum and has been doing that for centuries, e.g. http://www.leif.org/research/Historical%20Solar%20Cycle%20Context.pdf

April 14, 2014 9:13 am

William Astley says:
April 14, 2014 at 8:58 am
change the electrical currents flowing down from the ionosphere into clouds.
The current flow is down, but that just means that the electrons [the charges] are moving up from the [thunder]clouds.

Greg Goodman
April 14, 2014 9:15 am

A quick look at spectra from flux :
cross-correlation: main peaks
19.1 9.7, 4.0
Law Dome:
20.2 # 2nd
14.4 # 1st (strongest)
10.0
8.51
6.84
4.96 #3rd
Greenland
30.2 # small
16.8
10.0 #1st (strongest)
3.9 #2nd
3.0
Nothing that looks solar in any of that , maybe in concentration.

Greg Goodman
April 14, 2014 9:19 am

Mosh’ says: “2. CET is from a location that is quite unique geographically speaking. That is, it is not representative. Try the long records from any other location.”
What long records would that be ?

climatereason
Editor
April 14, 2014 9:29 am

Mosh
Please be consistent. You have previously said the exact opposite;
“Odd the way your crappy BEST moving average is so far outside the data in 1780. ”
Another idiot comment from greg.
The BEST Data at 1780 is the average of the entire field. the small patch of england tony refers to as well as most of europe and some of north america.
Tony is comparing CET ( a few square miles) to a much larger area.
That location (CET) along with a few others has reasonable correlation with the entire globe, although with CET ( and others) you will find years in which it is at odds with the rest of the world.
In other words, the thing you point out is expected and not anything odd.
—– ——
I don’t know which Greg Mosh was referring to but he needs to make up his mind \about CET and not contradict himself. I am happy that CET has much broader relevance and so are numerous scientists and organisation from Lamb to Jones, De Bilt to the Met Office and -depending on his mood- Mosh himself.
tonyb

Greg Goodman
April 14, 2014 9:30 am

ferd berple “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.”
Probably one cause of this is people now doing data processing using spreadsheets.
Click of “fit trend” and it gives you “the R^2” statistic. This makes massive assumptions about the data and is probably more often wrong than right.
When climategate emails showed Phil (pour Phil) Jones saying he did not know how to fit a line using a spreadsheet , he got a lot derogatory remarks here.
As far as I’m concerned he scores points for never having been stupid enough to use a spreadsheet for scientific data processing.

Paul Linsay
April 14, 2014 9:39 am

This appears to be a very convincing plot showing strong correlation of sunspots and 10 Be in a Greenland ice core. I just went to the Wikipedia page on 10 Be to find it.
http://en.wikipedia.org/wiki/File:Solar_Activity_Proxies.png

April 14, 2014 9:44 am

Paul Linsay says:
April 14, 2014 at 9:39 am
This appears to be a very convincing plot showing strong correlation of sunspots and 10 Be in a Greenland ice core
There is a crude correlation, but not a detailed one as Willis showed.

April 14, 2014 9:49 am

Steven Mosher says:
April 14, 2014 at 8:51 am
CET is from a location that is quite unique geographically speaking. That is, it is not representative. ……..
in Defence of the CET Records
CET is from a location that is quite unique geographically speaking.
Correct
That is, it is not representative.
I would respectfully disagree.
CET is to very large extent influenced by the N.Atlantic SST, from which the AMO is derived.
I have plotted HERE three sets of data:
– CET
– North Hemisphere temperature anomaly
– Global Temperature Anomaly
then calculated R2 as recommended by Dr. Svalgaard (5 year box)
and they are 0.74 and 0.71 respectively.
To conclude:
CET is the longest, the most scrutinised, least fiddled and hence most accurate temperature record the science has. Further more its specific geographic location gives it advantage of being under control of the strongest and the most important natural variability, the AMO.
I suggest your statement
“That is, it (CET) is not representative” can not be taken seriously.
Don’t ask for code and data, Excel calculates accurate R2, and data you know where to get.

milodonharlani
April 14, 2014 10:06 am

Records in the CET:
Coldest Winter (December–February) −1.17 °C (29.89 °F) 1683/1684
Hottest Winter (December–February) 6.77 °C (44.19 °F) 1868/1869
Anyone who wants temperatures to return to “pre-industrial” levels (ie, the LIA) is a stark, raving loon. The need to burn fossil fuels would zoom higher.
The Modern Warming Period started off with a bang that still hasn’t been equaled, let alone exceeded.

milodonharlani
April 14, 2014 10:10 am

Of course there probably was a lot of CO2 locally available in the Midlands in 1868, but also in the cold winters of previous industrial decades. In some industrial cities, CO2 concentration might have been higher in the late 19th century than the early 21st.

April 14, 2014 10:11 am

On a centenary scale there is fair correlation between 10Be and 14C, so obviously there is a lot of smoothing happening in the 10Be signal.

April 14, 2014 10:55 am

Mosher says
“4. Arguments that cannot be settled by the lab method. In the end observational scientists try to construct an understanding that makes the “most sense” of all the data, that ties together with other physics, that maximizes coherence and minimizes discord. It is a making sense of the past.. more a history constrained by math, logic and physics than anything else”
He is entirely right. Much of the disagreements on threads on this topic come from the fact that scientists with backgrounds in physics, maths and engineering have little experience in correlating multiple natural events in time and space. This is mainly what geologists do. I would recommend that interested reader would do well to borrow a copy of vol1 of ” The Geological Time Scale 2012.”
Gradstein et al EdsThis volume lays out in some details some of the methods used. Overall it is a bit like assembling a four dimensional jig saw with many of the bits missing. It says
“The stratigraphic record that is used includes litho-,bio,chrono,cyclo and magnetostratigraphy”
all these records vary in quality from time to time and place to place so that correlations are best made using the widest possible knowledge of the various records.
Similarly as a simple example when correlating well logs ( which have multiple tracks recording various data streams).you will find sections missing or even repeated.because of faulting, or unconformities and the apparent thickness of a section on the log will vary because of the dip of the beds- even sometimes to the point of being upside down . At the same time you may or may not have data mentioned in the previous paragraph for that same area .
The best correlation is made using expert informed judgment on all available data.
In the oil business how expert you may be is usually tested in fairly short order by the expenditure of millions of dollars. This tends to concentrate the mind onto the key observations when drawing inferences and making forecasts.
Calculating correlation coefficients on a couple of variables doesn’t enter into the proceedings as a useful tool except in very limited circumstances.

milodonharlani
April 14, 2014 10:57 am

The coal burning phase of the Industrial Revolution would have increased the number of cloud condensation nuclei in Europe, just as it’s doing in China now. Maybe water vapor in the air in those regions already had all the CCNs it could use, so cloudiness wouldn’t necessarily increase.
Soot from the dark, satanic mills has been blamed for the retreat of European glaciers from c. 1860 to 1930 (link includes obligatory CACA caca):
http://www.livescience.com/39388-soot-melts-alps.html
One explanation for the high temperatures of the Cretaceous was low biological productivity in the remarkably hot tropical oceans of the Period, leading to less cloud cover. Phytoplankton contribute a lot of CCNs.
Soot or “black carbon” has also been suggested as a cause for some recent Arctic sea ice & Greenland ice sheet melting. So in ways other than CO2 human activity may well have some small effect on climate (as with cooling aerosols), but whether the net effect is to cool or warm the planet, who can say? In any case, the effect is negligible. So far increased CO2 has been beneficial.

April 14, 2014 10:59 am

Dr Norman Page says:
April 14, 2014 at 10:55 am
The best correlation is made using expert informed judgment on all available data.
Then why don’t you listen to what I say? and heed my ‘expert informed judgement.

Greg Goodman
April 14, 2014 11:08 am

Willis:
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.
=====
It appears that this “understanding” is your own personal speculation of how it happens. The snow captures the Be in the atmosphere and traps it in the snow. Now unless the snowfall is significantly depleting the atmospheric concentration you’ll just get more snow with the current atmospheric concentration. So if concentration gives more coherent results that is probably why.
Now it remains to be seen whether there is in fact a solar signal in concentration, or is that just wishful thinking?

Greg Goodman
April 14, 2014 11:13 am

lsvalgaard says:

Dr Norman Page says:
April 14, 2014 at 10:55 am
The best correlation is made using expert informed judgment on all available data.

Then why don’t you listen to what I say? and heed my ‘expert informed judgement.
For the same reason as I don’t listen to the “expert opinion” of the IPCC.

milodonharlani
April 14, 2014 11:19 am

Dr Norman Page says:
April 14, 2014 at 10:55 am
“Science is the belief in the ignorance of experts.”
–Richard Phillips Feynman (1918 – 1988), in his address, “What is Science?”, presented at the 15th annual meeting of the National Science Teachers Association, in New York City (1966), published in The Physics Teacher, volume 7, issue 6 (1969), pages 313-320.

Greg Goodman
April 14, 2014 11:29 am

NOAA has archived concentration from Law Dome. Can’t find any archived for the Beer paper at Greenland Dye3 used by R. Rhonde in his “global warming art” on WP.
” To our knowledge, this is the first published ice core data spanning the recent exceptional solar minimum of solar cycle 23. 10Be concentrations are significantly correlated to the cosmic ray flux recorded by the McMurdo neutron monitor (rxy = 0.64, with 95 % CI of 0.53 to 0.71), suggesting that solar modulation of the atmospheric production rate may explain up to ~40 % of the variance in 10Be concentrations at DSS. Sharp concentration peaks occur in most years during the summer-to-autumn, possibly caused by stratospheric incursions. Our results underscore the presence of both production and meteorological signals in ice core 10Be data.”
http://hurricane.ncdc.noaa.gov/pls/paleox/f?p=519:1:::::P1_study_id:13564 (slow)

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