Chinese Sunspots

Guest Post by Willis Eschenbach

[See also the new Update at the end of the post.]

I see that there is a new paper from China causing a great disturbance in the solar force … as discussed here on WUWT, the claim is that the El Nino Modoki Index, which is an index of sea surface temperatures, is significantly affected by some sunspot-related solar variable.

The first problem with their study is that the sea surface temperature (SST) “data” they have used to establish the relationship is not data as we understand it. It is not observations. It is not measurements of the actual sea surface temperature (SST). It is not stout-hearted men of oak going out and dipping up a bucket of water and inserting a thermometer.

Instead, their sea surface temperature “data” is the output of a climate model, a type called a reanalysis model. This reanalysis model is “tested” and adjusted by comparing it with the output of another climate model. That model is called the GFDL CM2.1.

So, we’re not looking at observed SST. Instead, we’re looking at the output of a couple of climate models.

This means the Chinese have found a correlation between sunspots and climate model output.

Now, having considered the OUTPUT of the climate models, would you care to guess what is used as the INPUT to the climate models?

According to one of the cited underlying documents, the inputs include variations in forcings by greenhouse gases, aerosols, and the “best available estimates of solar radiation changes”.

That means that the authors claim to have found statistically significant evidence of sunspot-related variations in the output of a climate model whose input includes sunspot-related variations … sorry, not impressed even if it were true.

However, there is a much deeper problem, which is that the claim of statistical significance is not true. Their results are not statistically significant, it’s just statistics gone bad. Let me see if I can explain the problems using mostly pictures. I’ll start by clarifying their underlying hypothesis.

Their basic claim is that the small ~11-year variations in the sun affect the sea surface temperature in some unspecified manner and by means of some unspecified solar phenomenon (TOA, solar wind, sunspots, heliomagnetism, etc.). And to their everlasting credit, and unlike far too many climate science authors, they have provided links in the paper to the datasets used in the study.

So, being a data guy, I went and got the ERSST sea surface temperature (SST) data they were using. At least when I got it I thought it was data, and I’m sure some of it is real data … but I digress. They used it, so we’ll use it.

Now, the obvious first step in this is to compare the global sea surface temperature to the sunspot record.  Being a graphics-oriented guy, I calculated the correlation between each and every 1°x1° gridcell on the surface of the ocean, and the sunspot record. However, as Figure 1 shows, there is basically no correlation between the sunspots and the global average ERSST sea surface temperature (0.008).

correlation-sst-sunspotsFigure 1. Gridcell by gridcell correlation, monthly sunspots and monthly sea surface temperatures. Colored boxes from left to right are the west, central, and eastern Pacific areas used in calculating the El Nino Modoki Index. The El Nino Modoki Index is calculated as the red box sea surface temperature anomaly minus half the temperature anomaly in each of the blue boxes (all values detrended). 

Now, when I saw that graphic, I didn’t much believe it. At this point I’ve looked at this exact kind of map displaying dozens and dozens of different variables—rainfall, SST, atmospheric absorption, cloud reflection, correlation of albedo and temperature, the list goes on and on. As a result, I’ve grown used to the shapes and the forms of real relationships.

And Figure 1 is not much like any of the global climate-related maps I’ve seen. There’s no trace of the usual suspects like the inter-tropical convergence zone (ITCZ) or the typically bi-polar nature of the North Pacific. Instead, it’s just peculiar, too random.

Now as Figure 1 shows, there is basically zero global correlation of sea surface temperature with sunspots. So they are looking at correlation of the sunspots with the sea surface temperatures in the three El Nino Modoki boxes shown in blue and red.

According to the paper the “El Nino Modoki” index is defined as:

In this work, the El Niño Modoki Index (EMI) is defined as (Ashok, Behera, and Rao 2007)

EMI = [SSTA]C − 0.5 × [SSTA]E − 0.5 × [SSTA]W, (1)

where the square bracketed terms [SSTA]C, [SSTA]E, and [SSTA]W represent the area-averaged SST anomalies in the central Pacific region (C (10°S–10°N, 165°E–140°W)), eastern Pacific region (E (15°S–5°N, 110–70°W)), and western Pacific region (W (10°S–20°N, 125–145°E)), respectively.

The problem with Figure 1 is that those individual El Nino Modoki areas don’t particularly match up with the variations in correlation. As mentioned above, the El Nino Modoki index is the red box temperature anomaly minus half of each of the blue box anomalies. So ideally, to see the greatest correlation you’d want the blue boxes in areas of negative correlation and the red box to be in positive correlation … not happening.

In addition, the overall global correlation of SST and sunspots is basically zero (correlation of 0.008). In such a situation we’d expect to find individual areas with small positive or small negative correlation … and due to the high spatial autocorrelation in ocean temperatures, we’d expect the positive and the negative gridcells to be grouped into large areas.

In other words, Figure 1 looks about like what we’d expect if there is no connection between the ~11-year solar variations and the ocean temperatures. So to determine whether the pattern is representative of some real enduring sunspot–>SST relationship that persists over time, I repeated the exercise using only the first half of the data, and then using only the last half of the data. Figures 2 shows the early data up to 1935, and Figure 3 shows the more recent half of the data.

correlation-sst-sunspots-first-halfFigure 2. As in Figure 1, but for only the first half (976 months) of the data.

In this earlier half of the dataset, the pattern is very different from that of the full dataset. This is a clear sign we’re not looking at a stable enduring relationship In addition, the El Nino Modoki areas are even more poorly placed than in the full dataset. There’s almost no correlation between the Index and the sunspots during this period. The red box, which was in the hot spot, is now in the cold spot.

Compare those first two with the recent half of the data.

correlation-sst-sunspots-last-halfFigure 3. As in Figure 1 and 2, but for only the last half (976 months) of the data.

As you might expect by now, the pattern of positive and negative correlations in this one is once again totally different from both the full dataset (Figure 1) and the early data (Figure 2). However, presumably by coincidence, the variations in correlation happen to line up well with the El Modoki areas … blue boxes where there’s negative correlation and the red box where there’s positive correlation.

So which of these time spans have the authors used? Well … none of them. Instead, they’ve picked 1890 as their starting date. Here are the correlations for the data from 1890 to the present

correlation-monthly-ersst-sunspots-1890Figure 4. As in Figures 1, 2, & 3, except starting in 1890 and continuing to the present.

So now, we have a fourth different and distinct pattern of positive and negative correlation. In this case of this particular pattern, the blue and red boxes line up pretty well with the negative and positive sections of the correlation map.

And as a result, the authors of the study found a statistically significant correlation between the El Nino Modoki index and the sunspots. But only if you include a two-year lag from sunspots to El Modoki variations.

And to be fair, my own standard statistical analysis of these results says that they are indeed significant at the 95% level. The usual statistical tests give a p-value of 0.03, which is less than their significance level of 0.05.

However, that usual statistical analysis is wrong for four reasons. First, they’ve looked for results in more than one place, so they need to divide the desired p-value (0.05) by the number of places they looked. Second, they have not allowed for autocorrelation. Third, they have not allowed for the strongly cyclical nature of the sunspot data. Finally, they have not shown that the correlation they’ve demonstrated is stable over time.

Looking in lots of places – the effect of repeated trials

Consider. If you pick up ten coins, flip them all in the air, and every one comes down heads, you’d suspect that the coins were weighted. Why? Because the odds of that happening by chance are less than one in a thousand. So it would be a statistically significant occurrence, with a p-value less than 0.001.

But suppose you flipped that batch of ten coins a thousand times, and you find one flip that ends up with ten heads. Is that still significant? No, because the more trials, the more chance you have of finding something unusual. If you look in lots of places, you’re likely to find odd things … but that does NOT make them statistically significant.

As a result, when you look in more places, your criteria for significance has to become more stringent. The usual correction is called “Bonferroni’s correction”. What you do is to divide the initially required p-value (e.g 0.05) by the number of trials, and that’s the p-value you need to find for it to be significant in that many trials.

So if you look in five places for results, and you desire significance at a p-value of less than 0.05 (the usual standard in climate science), you need to find something with a p-value of less than 0.05 / 5 trials = 0.01. Not so easy.

And therein lies the first problem. We’ve already looked for significance in the whole ocean for the whole time period, and for the whole ocean for the first half and last half of the time period. No joy in any of those. So now, we’re looking at three small boxed-in areas out of the whole ocean, in a period limited to only the time since 1890 … and those three boxes represent just under eight percent of the ocean area.

How many places in time and space have we searched the ocean so far for the elusive solar signal?

Whatever the appropriate Bonferroni correction number might be for this calculation, at this point we’ve established that a “significant” correlation (p-value of 0.03) can be found if we turn our sights to a specially selected 8% of the ocean during a particular time period … you’ll forgive me if I find that less than significant.

The first problem is, no Bonferroni correction, and we’ve already looked a lot of places …

The pernicious effect of autocorrelation

Autocorrelation is a measure how much today is like yesterday. For example, the time of sunrise is constantly changing, but it never changes much. So today is a lot like yesterday in that regard. With air temperature there is less regularity than with sunrise times. But it is rare to have a sweltering hot day followed by a freezing day. So air temperature is less autocorrelated than is sunrise time.

Ocean temperatures, however, are very highly autocorrelated, because the thermal mass of the water means that today is very much like yesterday. And this is a problem for statistics, because autocorrelation increases the uncertainty. How much? Well, in the case of highly autocorrelated datasets, the answer is, a shocking amount.

For example. The El Nino Modoki/sunspot correlation has a p-value of 0.03. But adjusted for autocorrelation (using the method of Koutsoyiannis, see note at end) the p-value goes up to 0.37, a long, long ways from significant.

So the second problem is, no adjustment for autocorrelation.

Statistics of a cyclical signal

There are special problems and special procedures needed when looking at correlations with a signal with a strong varying-length, varying-amplitude cycle … like say sunspots. Again let me explain this with pictures. First, here is the cross-correlation of the post-1890 El Nino Modoki and the sunspots. It shows how well the Index and the sunspots correlate at a variety of lags. In it you can see the best correlation at a two-year lag (El Nino Modoki Index responding two years after the sunspots) that the authors discuss.

ccf-el-nino-modoki-vs-sunspotsFigure 5. Cross correlation, El Nino Modoki Index and sunspots. The blue lines show the correlations at various time lags between the sunspots and the El Nino Modoki Index.

So Figure 5 looks convincing, it looks like it represents a real correlation … as far as it goes. And again according to standard statistics it is supposed to be significant. But is it? Let’s expand the boundaries of our same analysis out to say thirty years …

ccf-el-nino-modoki-vs-sunspots-30-yrsFigure 6. The exact same analysis as in figure 5, but this time with a wider time window.

I’m sure that you can see the problems. First off, there’s a better correlation at 13 years than at two years. And there’s a strong negative correlation out eighteen years … warming sun now means cooling eighteen years from now? Say what?

The difficulty is two-fold. First, if there are a couple of bumps or dips of any kind in the data, doing a cross-correlation with a cyclical signal like sunspots will give you alternating correlations as seen above. Second, the result is likely to appear significant at the peaks, without actually being significant.

Let me demonstrate this problem with pseudo-data. Here are nine instances of pseudodata modeled on the actual El Nino Modoki Index, along with the actual El Nino Modoki Index itself.

pseudodata-for-el-nino-modokiFigure 7. Nine instances of pseudodata. The real El Nino Modoki Index data is Series 7

And here’s what you get when you run a cross-correlation of that selection of pseudodata with the highly cyclical sunspot data:

cross-correlation-pseudodata-and-sunspotsFigure 8. Cross correlations, sunspots with the pseudodata shown in Figure 7. As before, the actual cross correlation of the El Nino Modoki Index and the sunspot data is Series 7.

Not a pretty picture … as you can see, the results of the pseudodata are indistinguishable from those of the real data. We know the pseudodata has no connection with the sun but it still gives strong correlations that appear to be significant. So the third problem is that have not considered the effect of the cyclical nature of the sunspot data.

Duration Over Time

Natural climate-related datasets are maddeningly tantalizing because they appear to contain stable natural cycles, but the dang things have an ugly habit of suddenly appearing and disappearing without warning. After some period where there is no correlation, a correlation with say sunspots will suddenly pop up, and it will last and last, sometimes for as long as five full sunspot cycles … and then it will just vanish. Gone. Perhaps it will be replaced by a cycle with some other longer or shorter period, perhaps not, perhaps we’ll just get random noise for a while before another cycle pops up.

This is visible in the examination of the maps of the early (Figure 2) and late (Figure 3) halves of the data. In each one there are things that seem to be strong, significant correlations. And since each half is eighty years long, you’d sure think that over that time the random fluctuations would have evened out …

Fuggeddaboutit. The two halves of the one single dataset are widely different, the differences have not averaged out. The observational climate datasets tend to be self-similar at all scales. Daily data is no less chaotic and full of appearing and disappearing cycles than is monthly data, which has as many apparent but evanescent cycles as does yearly data, which in turn is no less chaotic than a century or a millennium. At all time scales, apparently real and regular cycles appear and disappear at unpredictable times.

Now, are there long-term, enduring relationships in there? Definitely … but you cannot assume you are looking at such a stable relationship, as the examination of this dataset shows. Even averaged over eighty years the relationships are not stable. Their fourth problem is, they provide no verification of the stability of the purported relationship.

Conclusions:

The paper claims that a climate model that is fed solar variations will reflect those variations in its output. However, whether or not that is the case, the paper has four much more serious issues with their statistical analysis:

They have not used the Bonferroni correction to adjust for the number of places that they have looked at in order to come up with the 8% of the ocean’s surface that they find “significant”.

They have not allowed for autocorrelation in their calculations of claimed significance.

They have not considered the effect of the strongly cyclical nature of the sunspot data on the calculation of significance.

They have assumed that the signal they found is stable over time, where in fact it is very different in the early and late parts of the same dataset.

The effect of any single one of these statistical errors is enough to invalidate their results. The combined effect of all four errors is … well, words fail me.

Here’s the odd part. Look, I’m no statistician. As with all of my scientific knowledge, I’m entirely self-taught. I never took one single class in statistics. What are the odds of that?

My question is, if a self-tutored man like myself knows about the Bonferroni correction and the need to adjust for autocorrelation … what’s up with these PhD folks all across the climate landscape who apparently never heard of those concepts?

Final Reflections

Many folks seem to misunderstand my position in all of this. I started out a firm believer in the “It’s The Sun” mantra. I thought the sunspot cycle truly did affect wheat prices as Herschel had speculated in the 1700’s. I thought that there were a number of climate phenomena that were affected by something related to the sunspot cycle. I didn’t know whether that “something” was the solar wind, or the changes in total solar insolation, or changes in the far UV, or variations in the heliomagnetic field, but I sincerely believed that there was a clear sun/climate connection related in some manner to the sunspot cycle. I thought that all I had to do to verify that solar connection was look up in the daytime.

And as a result, I thought it would be a piece of cake to find solid scientific evidence to back up what I took to be a fact—that the small ~ 11-year variations in the sun’s output would leave their mark somewhere on the earth’s climate. I had no doubt that was true.

But then I encountered something strange. None of the studies I found had any more solidity than does the Chinese study I just analyzed above. Almost all of them had some or all of the same four huge problems with the statistics exhibited above—no Bonferroni, no correction for autocorrelation, no allowance for strong cycles in the sunspots data, and no investigation of the long-term stability of the claimed relationship.

So I looked and looked, and found nothing. To try to winnow through the literally hundreds of sunspot-related claims, I asked people who thought they had a solid scientific study establishing the connection between the ~ 11-year solar variations and some surface climate variable to send me two links—one link to the study, and a second link, to the actual data used in the study.

Many, perhaps most folks couldn’t seem to grasp the “two links” concept of the request. But it’s essential to have a link to the data as well. I was able to do the above analysis only because I had access to the data that they used. Without that link to the dat there is nothing to analyze. So for people who sent in one link, it went straight to the circular file …

But even when I got two links to some piece or other of research that I was assured was the best, their claims melted like snowflakes in the Sahara when examined closely. Like this study above, it wasn’t just small flaws. It was huge problems, and often the very same four problems I listed above

And as a result, as an honest man I have to say that despite looking for something that I started out truly and completely believing existed, and despite examining a long string of solar-related studies, to date I have not found convincing evidence of such a connection between the ~11-year solar cycles and the climate here at the surface where we live. Now, if the facts change I’ll change my mind, but as it stands I haven’t yet found the requisite evidence.

We had condensing fog last night. When I woke up the deck was soaked and the ground wet. Cold and overcast all day. Where is global warming when I need it?

My best to all,

w.

 

Please: If you disagree with someone, have the courtesy to quote the exact words you disagree with. This gives all of us clarity on the exact nature of your objection.

Autocorrelation: My discussion of the Koutsoyiannis method for calculating effective N is here.

[Update]: For those of you who still think that the correlation of sunspots with the El Nino Modoki Index is significant, after reading the comments I realized that there was a simple test I could apply. This was to compare the El Nino Modoki Index, not with the sunspots, but with the time-reversed sunspots. I just swapped the full sunspot record end for end, and then I compared that reversed record to the individual gridcells as in Figures 1 to 3.

correlation-ersst-and-reversted-sunspots

As you can see, despite the “sunspot” data in the Figure above being meaningless because it is time-reversed, the correlations are very similar to those of the actual sunspots.

Which of course means that their results are as meaningless as those from time-reversed sunspots …

High-Altitude Effects: As an erstwhile ham radio operator (H44WE), I’m well aware that the sunspot cycle affects long-range radio transmission (DXing) by messing with the beautifully named “Heaviside Layer” … what I can’t find is any solid evidence of any corresponding 11-year variation down here on the ground where we live. And yes, I do know that Heaviside is someone’s name, but I still think it’s a great name.

Further Reading: As I said above, I’ve investigated a lot of these claims. Here is a list in chronological order of my previous posts on the subject …

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1saveenergy
September 12, 2016 11:56 pm

Willis, from a skim read, that look’s like another nice analysis.
You say –
“if a self-tutored man like myself knows about the Bonferroni correction and the need to adjust for autocorrelation … what’s up with these PhD folks all across the climate landscape who apparently never heard of those concepts?”
You are the small peasant boy who sees the Emperors new clothes for what they are…..more junk pseudo-science.
Well done.

Toneb
Reply to  1saveenergy
September 13, 2016 1:59 am

““if a self-tutored man like myself knows about the Bonferroni correction and the need to adjust for autocorrelation … what’s up with these PhD folks all across the climate landscape who apparently never heard of those concepts?”
You are the small peasant boy who sees the Emperors new clothes for what they are…..more junk pseudo-science.
Well done.”
On the contrary to me that above statement by Willis, is just another demonstration of the hubris on daily display here at WUWT.
My question is, but why, why, would you, anyone, ASSUME that experts in a field that you “self tutored” yourself in would no be aware?
That that does not flag itself in minds on here is what staggers me.
Oh, as well as the cheer-boys that bolster that hubris.

Charles Nelson
Reply to  Toneb
September 13, 2016 2:15 am

Speaking of the ’emperor’s new clothes’ I often ask this question ‘in the voice of a small peasant boy’….
“If water vapour is the cardinal greenhouse gas, by an order of magnitude, and is in limitless supply…why should we be pooping our pants over CO2, which comprises 1/25th part of ONE PERCENT of the atmosphere and has risen by 1/5th part of that 1/25th part of ONE PERCENT since records began?”
I have no ‘hubris’. this is an honest question to which I’ve never been given a satisfactory answer.
I simply cannot for the life of me see those fine clothes! Where are the fine clothes?….
Given the amount of hubris Toneb displays, maybe he could explain it?

TA
Reply to  Toneb
September 13, 2016 6:34 am

“My question is, but why, why, would you, anyone, ASSUME that experts in a field that you “self tutored” yourself in would no be aware?
That that does not flag itself in minds on here is what staggers me.
Oh, as well as the cheer-boys that bolster that hubris.”
Isn’t that better than assuming the “experts” are being deliberately deceptive? The experts Willis is referring to don’t use the techniques they are supposed to know to use, so what are we supposed to assume about that? Answer: Either they don’t know to use them, or they deliberately don’t use them to get a certain result they want. Is there any other explanation for failing to use standard techniques?

TDBraun
Reply to  Toneb
September 13, 2016 9:14 am

Toneb, All you have to do to prove Willis’ hubris is to prove his criticism to be wrong, or link to such a proof, or link to a discussion by the study’s authors that purport to show why the Bonferroni correction is not needed in this case. Just saying that the guys with PhDs must know about these possible pitfalls — and therefore if they didn’t correct for them it is only because they aren’t needed — isn’t good enough.
Also, give credit for Willis being equally critical of a theory that, if true, is contrary to standard IPCC theory; just as he frequently criticizes shoddy pro-AGW claims.

Bob Boder
Reply to  Toneb
September 13, 2016 9:21 am

Toneb;
All true discoveries are made by self taught people.

Reply to  Toneb
September 13, 2016 12:57 pm

I am a physician and failry expert on clinical research in my field and I can assure you that whether clinical researchers are aware or not of the statistical issues that Willis raises they frequently ignore them when publishing nonsense in the medical literature. Willis has it nailed. Much of what is wrong in medical practice is exactly due to this type of misuse of statistics. The study in questions is not much different from finding a shocking correlation between a person’s height and their shoe size. Worse it is as I if they were allowed to sift through multiple groups of people and report the few groups with a strong correlation while ignoring others with no or negative correlation and then pretend the few reflect the whole.

RWturner
Reply to  Toneb
September 13, 2016 1:01 pm

“what’s up with these PhD folks”
K-Mart had a blue-light special on climatology degrees.

Reply to  Toneb
September 13, 2016 1:18 pm

ToneB,
You extremely naively to assume that a “so-called” expert is always beyond reproach. Or that they are infallible and all knowing. I know many good biologists who struggle with statistics. While many professional statisticians have bemoaned the way biologists will abuse statistics. But you seem to embrace the attempts to create omniscient cult heroes out of everyday climate scientists.
Scientists are under a publish or perish culture. They are pressured into publishing results in a year that would better years
Most humans, once they publicly profess a hypothesis want to prove their surmize was correct and lose sight and lose sight of alternative explanations as well as adopting whatever statistical tool first supports their beliefs. Sometimes political beliefs cause people not critially examine their assumptions and methods
I have observed several published papers presenting bogus conclusions based on bad methods that are glaringly obvious. http://landscapesandcycles.net/American_Meterological_Society_half-truth.html

Jay Hope
Reply to  1saveenergy
September 13, 2016 9:25 am

‘From a skim read’. Perhaps you should read it more closely before forming an opinion. Otherwise you’re just another member of the Wilis and Lief a** licking club. Sadly, there are many members on this group…

DonM
Reply to  Jay Hope
September 13, 2016 5:30 pm

… insults and personal attacks … prove that one can’t follow the story, so they kick and scream.
I agree.

afonzarelli
Reply to  Jay Hope
September 13, 2016 5:39 pm

Willis, whether it’s real or not, there is a strong perception that both yourself and Dr. Sv. are at the core of “anti-solar warming” group think. i never get the impression that either one of you are doing the “feynman thing” by bending over backwards to help others understand exactly where you’re coming from. These are just impressions as i don’t follow y’all very closely (in part because of these impressions). I just wanted to point this out as a help and not a hurt. Always remember feynman and the example of Dr Spencer as well. (in my mind no one boils it down and makes complex things more understandable than spencer) i think this will go a long way for you in helping your nay sayers understand where your coming from. Yours are awesome posts (and you’re an awesome fellow). i hope my “less than awesome” comment here is of some help…
f.

Reply to  afonzarelli
September 13, 2016 5:48 pm

I never get the impression that either one of you are doing the “feynman thing” by bending over backwards to help others understand exactly where you’re coming from.
Coming from? Sounds like having a preconceived opinion. For me, that is not how I think about this. I have been studying this for about half a century and have learned a lot from the data we have accumulated by ever improving technology. I think my comments go to great length to explain my hard-earned views. If you feel that there are specific areas where I have failed to help you personally, please let me know [even by email] if you don’t want to share with the blog.

Reply to  afonzarelli
September 13, 2016 8:31 pm

yourself and Dr. Sv. are at the core of “anti-solar warming” group think
Not to speak about the “it’s the Sun, stupid’ group think and newspeak.
Perhaps some background will be useful.
Back in the 1950s and 1960s, sun-weather/sun-climate [SWSC] research was effectively dead. For centuries before that [all the way back to Riccioli in 1651] there were claims of SWSC effects, but neither the data nor the physical/theoretical knowledge back then were up to the task of establishing compelling relationships or mechanisms [although there were a thousand papers claiming such]. In [considered at the time – 1973 – as] a landmark paper in Science Magazine I and colleagues published the famous Vorticity Area Index paper [which today is still one of my most often cited papers] http://www.leif.org/research/VAI-Sector-Structure.pdf
The paper revived the SWSC field and numerous conferences were held and books published, and we all envisioned a new Golden Age and rapid progress in this [now] vibrant scientific field. Alas, as time went on and new data were in, the effects faded and the field died again.
http://www.leif.org/research/Inquiry-died.png
There are still papers with glorious claims of SWSC being published, but, it anything, their quality has been declining and the field is still dead as a door nail. The more data we accumulate, the less compelling the SWSC hypotheses become because our knowledge has expanded to the point where vague references to unknown causes and not-understood physics don’t work anymore.

Mickey Reno
Reply to  Jay Hope
September 13, 2016 8:25 pm

Well, double dumb ass on you. (h/t Captain Kirk)

afonzarelli
Reply to  Jay Hope
September 13, 2016 8:25 pm

“…and in return i get ugly accusations from someone like you concealed behind an alias, a man or whatever, unwilling to sign your own name to your words?”
Sorry that you took my comment that way… Yes, i know about your epiphany. I was actually referring to your science in general. Many would think that someone would have to have their head up their a** in not seeing the obvious solar connection. Weber oft shows the “climate4you” graph depicting the solar cycle and temps. You link to your post which links to spencer’s 2010 post which shows an excellent correlation between solar cycle and had3 data. So, i’m just saying, “think feynman”. Bend over backwards to explain to the bob webers of the world why it is that what their lyin’ eyes are seeing ain’t true. And if you think you’re already doing the feynman thing, fine. But, it doesn’t hurt to take a step back every now and again, read feynman, and approach things with a renewed attitude. Personally, i think we could ALL do a better job at living up to feynman’s ideals…
BTW, fonzie is my real nick name as i actually look like the “king of cool”. Word Press wouldn’t let me use fonzie, fonz nor fonzarelli (all taken?) so i ended up with afonzarelli. It’s my prerogative to use my nick name. (after all, it still is a free country) Further more, i don’t take these climate blogs all that seriously, so for me using my nick name is a good fit…

afonzarelli
Reply to  Jay Hope
September 13, 2016 9:06 pm

Thankyou, Dr Svalgaard, very interesting…

Duster
Reply to  1saveenergy
September 13, 2016 11:47 am

The answer to Willis’ question about the likelihood of Ph Ds not having learned about basic statistical checks and balances is that the likelihood is quite high. Most specialties expect students to take separate mathematics and statistics courses, while some “specialized” “applied” methods endemic to the discipline are taught within core classes. As a student, unless you are lucky enough to have a professor with some awareness of the methodological and theoretical of mathematical and statistical methods, you could graduate with nary a clue. On many campuses, statistics is taught outside the mathematics department, often in Social Sciences, and the more insecure “hard” sciences like climatology are particularly averse to exposing their students to “soft” scientific views. That means that to be aware of the actual hazards of statistical methods you are likely to be either a student of a very good department, a statistician, or an autodidact like Willis. Another reality is that where a discipline relies heavily on cartography and cartographic products, there is a definite tendency to regard autocorellation as a useful tool, e.g.:
http://help.arcgis.com/EN/arcgisdesktop/10.0/help/index.html#//009z00000076000000.htm
rather than a problem.

Jay Hope
Reply to  Duster
September 13, 2016 2:55 pm

Willis, I have a scientific objection to someone who admits that they form an opinion based on skimming the material. No need for you to get your knickers in a twist!

Reply to  Duster
September 13, 2016 3:09 pm

@ Jay Hope…and this is your idea of a science based objection? …”.. Otherwise you’re just another member of the Wilis and Lief a** licking club…”.
Is that what you learned back in your school days as an appropriate response in a science debate?

charles nelson
September 13, 2016 12:03 am

Look, Lief says that the sun has no impact on the earth’s climate…let’s just leave it at that shall we.

TedM
Reply to  charles nelson
September 13, 2016 3:47 am

No!

Tom in Florida
Reply to  charles nelson
September 13, 2016 5:01 am

That is incorrect. Leif always says the changes in the Sun have a very small impact.

Reply to  Willis Eschenbach
September 13, 2016 12:19 pm

Willis,
A blog like this brings out the worst in some people, and the worst of people. We see so may repeat offenders here that one can actually predict that they [the same contingent] will show up as clockwork.

Les
Reply to  Willis Eschenbach
September 13, 2016 6:22 pm

too bad they don’t have an 11 year cycle without any real effect! 😉

September 13, 2016 1:13 am

Sir, your articles are *always* worth reading. Thank you.
You may have taught yourself statistics, but you seem to have learned your lessons awesomely well. You are also, IMHO, doing a great job of teaching the concepts to others. You’ve done something I personally appreciate very much: you’ve gone to the data, you’ve looked to see what it tells you (not just whether it tells you what you want to know), and you’ve checked for *basic* problems in the paper you were looking at.
I used to teach part of a bioinformatics paper. I told students there were two kinds of approximations, BIG approximations and little approximations. The little approximations are things like mistakes in computer programs, coping with the (cough) quirks of floating-point arithmetic, and so on. The BIG approximations are in our Procrustean attempts to cast a real-world problem into something the computer can deal with. The problems in this paper appear to be not in what they got the computer to do for them, but in asking the computer to do the wrong things due to BIG picture oversights. Little approximation problems often take deep technical expertise to notice, let alone deal with. BIG approximation problems show up when a 10-year-old asks an embarrassing question.
I remember one data mining project that a proud author was explaining to me. He was calculating and displaying correlations. I said something like “You do know that these don’t make much sense for data like this, don’t you?” The reply was “Yes, but if I do the right thing my clients won’t understand it and they won’t pay me.” A mad world, my masters.

Marcus
September 13, 2016 1:26 am

Another great post Willis, how do you find the time ? One little typo though..
“The first problem is, no Bonferroni correction, and we’ve already looked (AT) a lot of places …

September 13, 2016 1:43 am

Willis, This was a readable and informative review of the recent paper and a wonderful explanation of the autocorrelation that has been addressed in previous Antarctic-related articles. In fact the recent batch of WUWT articles have been very enlightening to come to grips with several of the aspects involved in attempting to have a civil conversation about climatic conditions.
As to a sun-climate relationship it is difficult to fail to see the impactful correspondence of MM with a cold period and C20th optimum with a warm period and it is worth pursuing, so that, perhaps, the thing being looked for will be found in the proverbial last place. It is worth pursuing for the simple act of eliminating false findings.
It is also perhaps timely for a sun-El Niño relationship, seeing as the neutral-cum-La Niña trade winds have blown the warm slops of ’14-16 to the West Pacific Pool and producing a tongue of cold water extending westward along the equatorial East Pacific.
It’s the sunlight warming of the cool waters eventually piling up into the WPPool that, should they stall the trades, end up yielding an El Niño. So is it at this time of exposure to sunlight of the colder water the time relevant to study in some detail? ie from when old warm is cleared and new cold enters the arena.
Is there a sun-related factor of intensity, wavelength or whatever, that if greater/lesser at this time leads to a greater/lesser chance of a trade wind stall rather than a continuation of a usual Pacific system?
If so, is it a solar cycle-related impact, or rather a greater regime of solar optimum /minimum generating a generally greater chance of El Niño and so stepwise warming?
If so, how does one go about approaching this?
cheers,
John – let;s say John from Coogee to differentiate from others of my same first name.

Richard Saumarez
September 13, 2016 2:46 am

Well, as you say you are a self tutored man. Signal processing is a difficult field mathematically and has a huge number of traps for the unwary. The “common-sense” approach is often wrong and has to be replaced by proper analysis, which is why people do PhDs in the theory of signal processing.
The nature of cross-correlation depends on the cross-phase and bandwidth of the signals in question.
Why should a periodic signal not have a periodic cross-correlation? If the 1D discrete Fourier transform of the signals are not constrained by time-domain windowing, the CCF MUST be periodic. (See Oppenheim, Wilsky and Young “Signals and systems”, Oppenheim and Schafer “Digital Signal processing”)

Reply to  Richard Saumarez
September 13, 2016 3:19 am

Agree, there’s a reason why experts in signal processing with PhDs have earned their PhD degrees. In this case we have forcing which are nonlinear, with no fix frequencies and that act usually with varying time delays, which make analyses with statically regression and frequency analysis difficult, to say the least. Besides sunspot numbers is a poor proxy for Sun’s effect on Earth’s climate.

Reply to  Richard Saumarez
September 13, 2016 3:53 am

I am a little puzzled by Richard Saumarez’s contribution to this thread. It sounds awfully like an attack on Willis Eschenbach. Well, I took the trouble to read the paper he linked to. It is as he described it. And while some people surely do PhDs in signal processing, the paper does NOT describe using any sophisticated signal processing algorithm. To repeat, the paper is as he described it. If you are rubbishing the approach of simply cherry-picking correlations, then you are *agreeing with* Willis, because that’s precisely what he’s criticising the paper for doing.
If you have some definite alternative method of analysis in mind, offer to collaborate with the authors on an improved paper.

TA
Reply to  Richard A. O'Keefe
September 13, 2016 6:53 am

“If you have some definite alternative method of analysis in mind, offer to collaborate with the authors on an improved paper.”
Yes. Don’t be shy. We are all searching for the truth here. If you have a better version, we want to hear it.

daved46
Reply to  Richard Saumarez
September 13, 2016 11:21 am

If people would think about what you learn at any level of education, the really important thing is learning how to learn. This means beinf self-tutored not that much of a problem. I’ve had lots of education, but since I know how to learn, its primarily a matter of applying proper technique to get good results. Willis clearly knows how to learn new subjects and to apply that learning, and how to communicate the results. And, unlike many people, he’s learned to accept correction, when it’s valid.

ulriclyons
September 13, 2016 3:46 am

“And as a result, as an honest man I have to say that despite looking for something that I started out truly and completely believing existed, and despite examining a long string of solar-related studies, to date I have not found convincing evidence of such a connection between the ~11-year solar cycles and the climate here at the surface where we live”
You still have not admitted that the coldest periods on CET were all during solar minima. You just poked fun at me for calling the late 1800’s solar minimum the Gleissberg Minimum as if I was making it up.
There is a very strong association between the AMO and sunspot cycles, which because of the phase change, can only be driven by the solar wind as no other solar metric could cause such a phase reversal.
http://www.woodfortrees.org/graph/esrl-amo/from:1880/mean:13/plot/sidc-ssn/from:1880/normalise

Reply to  ulriclyons
September 13, 2016 6:09 am

The ones who want to stick to no solar /climate correlations are going to do just that Ulric in spite of the data and in spite of the one simple fact which is the sun drives the climate therefore any changes in solar activity have to effect the climate to one degree or another.
The problem here is I think everyone does agree if solar conditions were to change enough the climate would be impacted. What is not agreed is do solar changes change enough to accomplish this or is the noise in the climate system so great that it is able to obscure all of the solar impacts especially when the sun is in it’s normal 11 year sunspot cycle.
This is how, when I reviewed the historical climatic record versus solar activity I was able to come up with a set of solar parameters which I think are needed in order to see a more clear cut solar climate connection.
The solar parameters are pretty extreme and do not come about unless the sun enters a prolonged solar minimum period of time.
I think the historical climatic record supports my view and I also think there is a pretty good chance going forward these low average solar parameters I have come up with will be realized.
This in turn will allow us to see if the climate is influenced through terrestrial changes due to extreme solar conditions. These terrestrial changes ranging from volcanic activity , to atmospheric circulation changes to global cloud coverage changes, global snow coverage changes to global sea ice and sea surface temperature changes.
Again I say based on the historical data it seems to take place.
This is why I am quite confident the global temperature trend will be down and I think it has already started although this first stage is tied in large part to the ending of the recent El Nino in contrast to extreme solar changes.

Rob
Reply to  ulriclyons
September 13, 2016 9:06 am

I think this is the problem – because there is a correlation between solar minima (periods of low solar activity) and the (albeit mostly anecdotal as they are a long time ago) periods of colder global temperatures, people are trying to find something in the solar cycle that would give a handle on the longer term effects.
What Willis has done (and continues to do very painstakingly) is to show that there really isn’t anything in the solar cycle which really correlates with temperatures. This doesn’t really affect the correlations between low solar activity (across multiple cycles) and temps, but it throws a spanner in the works of people trying to find explanations or mechanisms for the longer term variations by studying the cycles. it doesn’t invalidate the correlation between cycles and temps, just means that we can’t really use the variation within cycles to study it.

Reply to  Rob
September 13, 2016 11:24 am

Yes ROB that is where I am coming from.

ulric lyons
Reply to  Willis Eschenbach
September 13, 2016 2:53 pm

Willis writes:
“I’m happy to look at this claimed correlation, but I can’t do it based on your incoherent accusations accompanied by energetic handwaving.”
It’s in your post of course, and of course you ignored every occasion where I said that the coldest periods on CET were all during solar minima.
https://wattsupwiththat.com/2014/06/23/maunder-and-dalton-sunspot-minima/
Including your private joke:
https://wattsupwiththat.com/2014/06/23/maunder-and-dalton-sunspot-minima/#comment-1668105

ulric lyons
Reply to  Willis Eschenbach
September 15, 2016 3:23 pm

“As you can see, there is very little support for the “solar minima cause cool temperatures”
The three coldest periods on CET are all during solar minima, no one in their right mind should deny that. The intelligent and pertinent question to ask is ‘why do only certain parts of solar minima see such regional cooling?’.

ulric lyons
Reply to  Willis Eschenbach
September 13, 2016 3:19 pm

The phase change predicts that the solar factor responsible must be weaker around the sunspot maxima and generally stronger in between the sunspot maxima during a cold AMO, and the full reverse of that during a warm AMO, being stronger around the sunspot maxima, and generally weaker between the sunspot maxima. Making that the most meaningful graph in climate science because it reveals the solar forcing of what is universally assumed to be internal variability, and it pins the relevant solar metric down to one option only.
I guess you must be the expert that doesn’t find patterns where they do exist. Have another squint and try see when the coldest periods occurred:comment image?w=840

ulric lyons
Reply to  Willis Eschenbach
September 13, 2016 3:39 pm

“Unless you have a serious physically based explanation for a claim that in the physical world real things suddenly start doing the opposite of what they’d been doing for decades..”
It’s pretty simple really, weaker solar increases negative NAO/AO driving a warm AMO, as from 1995 onwards, and stronger solar increases positive NAO/AO driving a cold AMO.

ulric lyons
Reply to  Willis Eschenbach
September 13, 2016 4:35 pm

“You’re kidding, right? The graph you linked to shows no such thing as you are claiming. I went to WFT, downloaded the data, and analyzed it, and I encourage you to do the same. The correlation of the AMO and the sunspot cycles is a ludicrous – 0.01.”
Well you must be kidding, I never claimed the simple type of correlation that you are testing for.

ulric lyons
Reply to  Willis Eschenbach
September 13, 2016 5:07 pm

“But then in situations like the AMO and sunspots, when the two cycles go in and out of phase because they’re unrelated, you utter the magic words “phase change””
The magic words appear to be your “because they’re unrelated”. You don’t know that, and the cycles do show a phase reversal.

ShrNfr
September 13, 2016 3:48 am

Correlation is not causation. The latest models show that the El Nino causes sunspots. It is accepted seance (sic) after all.

Roy Spencer
September 13, 2016 3:56 am

Good stuff, Willis.

kim
September 13, 2016 4:47 am

Weeeeell, as observed in China, or maybe it’s elsewhere, the Maunder sunspots were ‘large, sparse, and primarily southern hemispherical’. I believe Leif assures us that TSI didn’t drop during that time, and that proxy reconstruction of cosmic rays didn’t change much either.
And yet it was cold; some blame vulcanism. But why the prolonged hemispheric asymmetry? Was there mere co-incidence of cold with asymmetry, or is there a causal connection?
=================

Nylo
September 13, 2016 6:42 am

I bought my pop corn too early, I had already run out of it! I will have to read all the attacks to this non-refutable master piece of common sense from Willis later, after I buy some more.

JDN
September 13, 2016 6:42 am

@Willis: We have the global warming on the east coast. I think we have it all this year. I’m hoping it continues well into November.

Reply to  JDN
September 13, 2016 2:36 pm

How does one “have global warming” in a small area of the planet?

JDN
Reply to  goldminor
September 13, 2016 8:10 pm

One doesn’t. It’s a joke. We’re having nice weather in September in the mid-Atlantic coast. I’m hoping it stays this way into November.

Javier
September 13, 2016 6:49 am

“Many folks seem to misunderstand my position in all of this. I started out a firm believer in the “It’s The Sun” mantra.”
Willis, too bad you started in the right camp and moved to the wrong one.
I suggest you read this paper:
Haigh, J. D. (1996) “The impact of solar variability on climate.” Science 272, 5264, 981-984.
http://workspace.imperial.ac.uk/physics/Public/spat/jo/The%20impact%20of%20solar%20variability%20on%20climate.pdf
Reanalysis data is not modeled data. It is an admixture of model data and real data that gets updated and grounded on real conditions every 4 hours or more often. It is the data on which meteorological predictions rely and the lives of many people depend on that data. Unlike temperature data, this data is not being tampered with. ECMWF, the European Centre for Medium‑Range Weather Forecast, is a consortium of 34 countries that produces the best medium-range weather forecast in the world from their reanalysis data, ERA interim.
The hypothesis of Joanna Haigh about the impact of solar variability on climate is supported both by paleoclimatic data and reanalysis data in numerous articles. You are just not looking in the right direction, and are wasting your time fighting windmills, bad science papers that don’t deserve anybody’s attention, like the paper you comment here. You will have to continue your education until you end again in the right camp.
Cheers

Dave in Canmore
Reply to  Javier
September 13, 2016 8:30 am

Javier says “I suggest you read this paper…”
The paper you quote compares solar variability to a simulated climate model. Not sure who is going to be impressed (or surprised) by their result!

Javier
Reply to  Dave in Canmore
September 13, 2016 9:29 am

It turns out that that paper has 681 citations, so a lot of scientists are impressed enough about those results to cite them. That paper provides a valid mechanism for the action of solar variability on climate. A mechanism that is actually physically plausible. Now you can continue your handwaving.

kim
Reply to  Dave in Canmore
September 13, 2016 3:51 pm

Running along the sidelines here, and stepping out of bounds repeatedly, but I’d like to see the study correlating Nile River levels with aurorae boreales looked at again. It is a long term study with good data. It’s from NASA and there is a Feynman attached to it, but not THE Feynman.
=================

kim
Reply to  Dave in Canmore
September 13, 2016 6:27 pm

Joan Feynman, I believe, from NASA JPL, sometimes in the mid 90s. Leif can connect you with the paper much more easily than can I. And thanks for the interest. I’m a little surprised you’ve never heard of this one.
=============

dp
Reply to  Javier
September 13, 2016 10:37 am

That the cited paper is popular is not an indication it is accurate. It may appeal to corrupt bastards that rely on bad science to attract grant money.

kim
Reply to  dp
September 13, 2016 11:24 am

Heh, what you just said.
========

Javier
Reply to  dp
September 13, 2016 12:27 pm

It is a lot more probable that a widely cited article is relevant, than a seldom cited one. That’s why that is an important metric to judge scientific output.
That I have to explain these things indicates a low level of scientific literacy.

kim
Reply to  dp
September 13, 2016 3:19 pm

Weak, willis; this quibble is beneath you. Stick to the good stuff.
=========

Javier
Reply to  dp
September 13, 2016 3:36 pm

Willis,

Instead, their sea surface temperature “data” is the output of a climate model, a type called a reanalysis model.

I hope that at least you have learned that reanalysis data is not the output of a model. As ECMWF explains it:
“What is climate reanalysis?
A climate reanalysis gives a numerical description of the recent climate, produced by combining models with observations. It contains estimates of atmospheric parameters such as air temperature, pressure and wind at different altitudes, and surface parameters such as rainfall, soil moisture content, and sea-surface temperature. The estimates are produced for all locations on earth, and they span a long time period that can extend back by decades or more.”

Reanalysis is observation based, not model based. It ingests 7-9 million observations at every time step

kim
Reply to  dp
September 13, 2016 3:38 pm

There is an interesting question here, but way off topic. I can imagine a metric of the health of any particular scientific field in which the correlation of reproducibility of studies within it and citation count is high.
==============

September 13, 2016 6:55 am

“…Instead, their sea surface temperature “data” is the output of a climate model, a type called a reanalysis model.”
One of the comments I received when I once referred to Trenberth et al 2011jcli24, “Atmospheric Moisture Transports from Ocean to Land and Global Energy Flows in Reanalyses” was that I probably didn’t even know what “reanalysis” means. Well I know in general what the word means, but there might be a more specific meaning so I searched for a more field specific meaning. Here is what I discovered.
“Reanalysis” is “waterboarding” of the data, torturing it statistically until it yields the desired answer. Trenberth was disappointed on the paper cited above because it ended up with atmospheric cooling instead of warming. When the data contradicts the theory, question the data not the theory.

Javier
September 13, 2016 7:11 am

Willis, in case you are interested in actually learning about reanalysis data, this is the aspect that the temperature at 2 m above the ground has:
http://i1039.photobucket.com/albums/a475/Knownuthing/ECMWF%20ERA_zps9hlvfftn.png
Source: http://www.ecmwf.int/en/research/climate-reanalysis
As you can see displays a prominent cooling between 1958 and 1976 and very much like satellites a flat to slightly decreasing temperatures between 2002 and 2012.
The publication for the ERA Interim system can be found here:
http://onlinelibrary.wiley.com/doi/10.1002/qj.828/pdf
The data can be found here:
https://climatedataguide.ucar.edu/climate-data/era-interim

John M. Ware
September 13, 2016 7:24 am

I think I have an experience that confirms, in a way, Willis’s method in this essay. His method, as I read it, is to test, in as many ways as are available, the assertions in the referenced article. His tests use the data at hand and subject them to a certain rigor in execution that reveals the article’s shortcomings.
Years ago I was a real estate salesman and associate broker; I listed and sold real property for others, and I brought potential buyers to view properties on the market. I held open houses at properties and received guests, both possible buyers and other brokers. Once, in an open house, I got a visit from a well-known and highly productive agent named Jack, a friendly but very businesslike fellow who said he had a couple of buyers that were out of town that day, but that he would like to bring by if the house survived his inspection. “Great!” I said. “Inspect away.” Everything went fine, verifying all that was advertised about the house and its worthiness to be on the market, until he got to the downstairs toilet, which he flushed three times in rapid succession (of course, one would never do that in ordinary use). The third flush overflowed, at which Jack said, “Whoops!” and then helped me clean up. I was astonished that he would do that, but it surely revealed a plumbing problem under the house. Needless to say, his customers did not buy the house, and I told my sellers about the problem, which angered them quite a bit. That triple flush was Jack’s “certain rigor in execution” that showed me a problem in marketing that house (a problem the sellers finally consented to have fixed–it turned out to be tree roots in the cleanout line). Unlike Willis’s reluctant or negligent scientists, I had no choice–having found out about an issue, I had to prod the sellers until they had it fixed. Unlike a house on the market, a scientific article has no enforceable warranty, and the authors can’t be sued for specific performance or damages. The authors of the study that Willis tested do not, of course, have to do anything about Willis’s response; but if they are responsible and true scientists, they will.

gnomish
Reply to  John M. Ware
September 14, 2016 5:12 pm

wow. i’m astonished at a water supply that can fill a toilet tank 3 times in rapid succession.
gallons per second is some formidable plumbing.
incredible
really.

Editor
September 13, 2016 7:45 am

The problem with looking for the answer in sunspots and solar cycles is the fact that Earth has two very large “filters”: The oceans and the atmosphere. I have little doubt that the underlying driver of obvious Holocene climatic cycles (quasi-periodic fluctuations) is the Sun. The problem is that the subtle variations in solar activities, are filtered through the atmosphere and the oceans, which never react exactly the same way as they did to previous solar variations.

Reply to  David Middleton
September 13, 2016 8:28 am

Exactly David, which is one of my points.

Bob Weber
September 13, 2016 8:59 am

Willis says, “Now, if the facts change I’ll change my mind, but as it stands I haven’t yet found the requisite evidence.”
I commented about the data and evidence for the solar cause of this ENSO as it happened, here at WUWT for two years, how the sun’s activity caused the El Nino. I’m not going to go back and list the large number of my factual evidence filled comments about that, because that would be bragging too much, like Willis did here again with his long laundry list of anti-solar articles.
My experiences with Willis and Leif has taught me they can always find something wrong with anything.
Today I’m not here to argue about the paper or the statistics, but to show how some fundamentals are being misunderstood. I note that Willis was once again careful not to proclaim the sun didn’t cause the El Ninos, rather that the paper(s) he has reviewed including this one came up short for whatever reason.
My problem with Willis’ solar ideology, based on his assumptions from using statistics, is that the same interpretive problems recur, no matter how many times the situation is explained. One more time:
The use of sunspot numbers is a problem for climate studies, as TSI is not always temporally synced to SSN.
For example, the Chinese solar paper was supposed to be about how the 2015/6 El Nino was caused by high solar activity in SC24.
They shouldn’t have started an analysis on this going back to the 1800’s with SSNs studying only a certain type of ENSO, when they could have used measured TSI instead, which tells a different tale than the SSNs, and they should have covered all ENSOs going back further than the modern instrumental era, and they should have made explicit caveats regarding the use of SSNs during the pre-TSI era.
From the TSI gold standard: http://lasp.colorado.edu/data/sorce/tsi_data/daily/sorce_tsi_L3_c24h_latest.txt, freshly calculated an hour ago with today’s data:
Year 1au TSI, F10.7, SSN
2015, 1361.4321, 117.4, 69.8
2014, 1361.3966, 146.2, 113.3
2013, 1361.3587, 122.8, 94.0
2012, 1361.2413, 119.6, 84.5
2011, 1361.0752, 115.3, 80.8
2016, 1361.0602, 92.3, 42.1
2003, 1361.0292, 129.2, 99.3
2004, 1360.9192, 104.7, 65.3
2010, 1360.8027, 80.0, 24.9
2005, 1360.7518, 93.6, 45.8
2006, 1360.6735, 80.7, 24.7
2007, 1360.5710, 72.7, 12.6
2009, 1360.5565, 70.6, 4.8
2008, 1360.5382, 68.6, 4.2
Obviously SSNs don’t tell the whole story. The Chinese authors relied on the 2014 SSN peak, when instead they should have known that 2015 had higher TSI. They blew it right there. As does everyone else who uses SSNs when they should/can use TSI.
http://www.esrl.noaa.gov/psd/enso/mei/ts.gif
http://www.pmodwrc.ch/tsi/composite/pics/comp_neu_42_65_1608.png
Post solar maximum ENSOs are a lagged response to solar max TSI, and in the case of post solar minimum ENSOs, a high rate of TSI increase at the onset of the cycle rising phase. We are in La NIna now because TSI has dropped off considerably this year.
As the sole person on Earth who quickly, decisively, and correctly determined the solar cause of the recent ENSO back in 2014, as it started, as the only one who told you what was happening with the ENSO as it happened for the last two and half years, who said in January that this year won’t be a record temperature year because of low TSI this year, a path we are clearly on,
I can say with authority that Willis Eschenbach has a long way to go before his opinions on these matters are taken seriously by me, if ever.
-Bob Weber

ren
Reply to  Bob Weber
September 13, 2016 9:14 am

It is connected to the maximal activity geomagnetic cycle 24, which affects the circulation in the equatorial region. The upper winds are important in the development of El Niño, as well as hurricanes.

Bob Weber
Reply to  ren
September 13, 2016 7:58 pm

ren, yes the geomagnetic activity affects circulation at the equator and the pole (vortex) as you know, and I also have proof of that, it’s part of my solar supersensitivity evidence.
The Earth is super sensitive to the variable power of the sun’s radiation and particle effluence. My full message of solar supersensitivity – of the sun’s tremendous power over the earth’s weather and climate, is on the way, after two and a half years of research.
For the rest of the audience, imho, ren is the premier solar-geomagnetic observer I know of on the blogs.
When he speaks, you should listen. He is continually on top of what is happening every day. Good job ren!
The ENSO wouldn’t have happened however without the seven years of rising TSI – the heat.

ren
Reply to  ren
September 13, 2016 11:09 pm

It seems that this circulation will accelerate the development of La Niña. We shall soon see.
https://earth.nullschool.net/#2016/09/17/2100Z/wind/isobaric/250hPa/orthographic=-242.63,-7.76,452

Reply to  Bob Weber
September 13, 2016 10:38 am

The use of sunspot numbers is a problem for climate studies, as TSI is not always temporally synced to SSN.
TSI is a simple function of the sunspot number [more accurately the Group Number]: TSI = A + B * SSN^0.7 within the uncertainty in TSI [and the SSN]
Claus Froehlich has a recent paper on the uncertainties in measuring TSI:
http://www.leif.org/EOS/TSI-Uncertainties-Froehlich.pdf
and suggests to use the square root of the SSN as the gold standard that TSI should match. As I showed, the TSI-SSN^0.5 relation is not quite linear and SSN^0.7 is the better fit.
The idea of using some power of the SSN as a measure of TSI hinges on the realization that the changing solar magnetic field is the origin of variations in TSI. Way back in 2002-2003 we showed that it is possible to determine the interplanetary [i.e. ultimately the solar] magnetic field by defining two new geomagnetic indices with different dependencies on solar wind physical parameters and found that the solar wind magnetic field varied as the square root of the SSN:
http://www.leif.org/research/Determination%20IMF,%20SW,%20EUV,%201890-2003.pdf
Such a relationship is also expected on theoretical grounds [Wang, 2003].
Bottom line: any claims to errors, fits, agreements, etc better than 0.2 [or even 0.5] W/m2 are not based on facts.

Bob Weber
Reply to  lsvalgaard
September 13, 2016 8:21 pm

Remember, there is a 39% error in the first year of hindcast in your model, 2015, which invalidates it in my opinion for climate study purposes. That indicates there are guaranteed to be more large errors going further back in time. Monthly TSI models are really needed to understand the solar-enso connection, at a better uncertainty than 0.5W/m2.
The 316 year v2 SSN median of annual numbers is 66.7, which your model computes as a TSI of 1361.0670. At 0.5W/m2 uncertainty, the uncertainty range for TSI @SSN=66.7 is down to solar min levels or up to the solar max range, which is not very effective for determining whether or not there was high enough TSI for an ENSO a hundred years ago with sufficient certainty. That uncertainty range would’ve swamped the whole range of TSI for any former cycle of the same relative size as SC24.

Reply to  Bob Weber
September 14, 2016 11:47 am

Monthly TSI models are really needed to understand the solar-enso connection, at a better uncertainty than 0.5W/m2
Except that there aren’t any. Your calculation of ‘error’ is quite spurious.
For 2015 there is, indeed, something strange going on as I showed last year:
http://www.leif.org/research/New-Group-Number-and-TSI.pdf
The jury is still out whether this is instrumental [either in TSI or in Group Number]. In any case, the deviation is still within the stated uncertainty of TSI. [or SSN for that matter].

Carla
Reply to  lsvalgaard
September 13, 2016 9:10 pm

lsvalgaard September 13, 2016 at 10:38 am
…”” by defining two new geomagnetic indices with different dependencies on solar wind physical parameters and found that the solar wind magnetic field varied as the square root of the SSN:…”’
———————————————————-
Speaking of the solar wind and magnetic field
Was on the spaceweather.com website and noticed the current solar wind speed was under 300 km/s. So thought I might check out ACE.
Dah, WattsUpWithThat?
http://services.swpc.noaa.gov/images/ace-mag-swepam-7-day.gif
Did make a dramatic effect on the solar wind speed…lol

Reply to  Carla
September 13, 2016 9:59 pm

Did make a dramatic effect on the solar wind speed
What made a dramatic effect? Not you just looking at it…
It is quite normal that the solar wind speed drops steadily at the end of a coronal hole traversal across the disk. The speed will pick up again then the next polarity sector begins, probably tomorrow.

dp
Reply to  Bob Weber
September 13, 2016 10:42 am

Not sure TSI is a useful data set. Spectrum variation, on the other hand, does offer promise as a climate influence.

Reply to  dp
September 13, 2016 10:45 am

TSI is where the energy is. The spectral variation is but a tiny part of TSI.

richard verney
Reply to  dp
September 13, 2016 1:11 pm

Just throwing out a point to consider:
Even if TSI does not vary significantly, spectral variation could impact upon where energy is being absorbed by this water world on which we live since the absorption characteristics depend upon wavelength.

September 13, 2016 9:00 am

It seems obvious that variations in climate are solar related, but the lack of good evidence also makes the obvious not really that supportable. Another good post, Willis.

Bob Boder
September 13, 2016 9:09 am

Willis
” As with all of my scientific knowledge, I’m entirely self-taught. I never took one single class in statistics”
And yet somehow you don’t rush to conclusions and actually try to let the data take you where it leads unlike all the not self taught, educated, PH’d stat geniuses out there.
thanks as always for the a good read.

William Astley
September 13, 2016 9:23 am

Willis why do you continue to plot sunspot number vs whatever? What is your methodology for problem solving? What is your objective? What problem(s) are you ‘helping’ to solve?
There is an astonishing number of anomalies and paradoxes that have recently occurred and that have occurred in the past, that appear to be connected.
1) Why did the North geomagnetic pole drift velocity increase by a factor of 5 starting in the mid 1990s? Note in the last couple of years the North geomagnetic pole drift velocity has suddenly again changed.
– Hint there is no mechanism to suddenly cause massive movement of magma in the earth.
2) Why do abrupt cyclic geomagnetic field changes (changes in the geomagnetic field orientation and abrupt changes to the geomagnetic field intensity) correlate with cyclic abrupt changes?
3) What is causing the cyclic abrupt changes to the geomagnetic field?
– Hint there is an increase in volcanic activity in the same time periods. Has there an increase in volcanic activity due to weird long solar cycle 23/24 minimum? Yup.
4) Why are there massive high temperature burn marks and evidence of intense electrical currents at 18 locations on the planet at the time of the Younger Dryas abrupt cooling event? Why is there a geomagnetic excursion at the same time as the YD?
– P.S. The YD is a Heinrich ‘event’. Event is in quotations as Heinrich ‘events’ occur roughly every 10,000 years.
5) Why do the cyclic warming and cooling periods, including abrupt cooling events, on the earth correlate with solar cycle changes?
It appears we are going to experience significant abrupt cooling. GCR is now at its highest level in recorded history for this stage in a solar cycle. The cooling due to the increased GCR has inhibited by solar wind bursts caused by astonishing large coronal holes that appeared on the surface of the sun during solar cycle 24. The warm blob in the Pacific Ocean has caused by the same phenomena that enables the solar cycle changes to abruptly change the geomagnetic field and to cause volcanic eruptions.
P.S. The Pacific Ocean warm blob is gone. There is now weird cooling weather in high latitude regions of the North hemisphere and there has been an increase in jet stream speed. There is a massive increase in wind speed during Heinrich event (factor of 100 more dust deposit on the Greenland ice during each Heiny event, there was a large increase in wind speed during the Maunder minimum and a large increase in high rainfall events, during the Little Ice Age/Maunder Minimum)
http://www.sciencealert.com/a-lightning-strike-just-killed-300-reindeer-in-norway
P.S. Same anomalous extreme lightning observed in high latitude North America in regions that seldom have lightning strikes, due to the cool summers and hence lack of large cumulus nimbus clouds. Anomalous due to duration of lightning period. Record rainfall in the period where there is extreme lightning.
2008
http://wattsupwiththat.com/2008/12/16/earths-ionosphere-drops-to-a-new-low/

Boundary Between Earth’s Upper Atmosphere And Space Has Moved To Extraordinarily Low Altitudes, NASA Instruments Document

Increase in volcanic eruptions and earthquakes following extreme solar minimum? Yep.
2010
http://www.msnbc.msn.com/id/39934297/ns/world_news-asiapacific/

Indonesia, a vast archipelago of 235 million people, straddles a series of fault lines and volcanoes known as the Pacific “Ring of Fire.”
The fault line that caused last week’s 7.7-magnitude earthquake and killer wave that followed — and also the 2004 tsunami that killed 230,000 people in a dozen countries — is the meeting point of the Eurasian and Pacific tectonic plates that have been pushing against and under each other for millions of years, causing huge stresses to build up. It runs the length of the west coast of Sumatra island.
Heightened volcano alerts 
The government has raised alert levels of 21 other volcanoes to the second- and third- highest levels in the last two months because they have shown an increase in activity, said Syamsul Rizal, a state volcanologist, said monday. Many of those are already rumbling and belching out heavy black ash.
Indonesia has several volcanos smoldering at any given time, but another government volcanologist Gede Swantika said there are normally only five to 10 on the third-highest alert level, indicating an increase in seismic activity and visible changes in the crater, and none at the second-highest, signifying an eruption is possible within two weeks. He said monitors noticed more volcanos were exhibiting seismic activity starting Sept. 2.
“We can say this is quite extraordinary, about 20 at the same time,” Swantika said. “We have to keep an eye on those mountains. … But I cannot say or predict which will erupt. What we can do is monitor patterns.”

Increase in volcanic eruptions during past solar minimums? Yep.
http://www.agu.org/pubs/crossref/1989/JB094iB12p17371.shtml

Volcanic Eruptions and Solar Activity
The historical record of large volcanic eruptions from 1500 to 1980, as contained in two recent eruption catalogs, is subjected to detailed time series analysis. Two weak, but probably statistically significant, periodicities of approx. 11 and 80 years are detected. Both cycles appear to correlate with well-known cycles of solar activity; the phasing is such that the frequency of volcanic eruptions increases (decreases) slightly around the times of solar minimum (maximum). The weak quasi-biennial solar cycle is not obviously seen in the eruption data, nor are the two slow lunar tidal cycles of 8.85 and 18.6 years.
Time series analysis of the volcanogenic acidities in a deep ice core from Greenland, covering the years 553–1972, reveals several very long periods that range from approx. 80 to 350 years and are similar to the very slow solar cycles previously detected in auroral and carbon 14 records.

http://onlinelibrary.wiley.com/doi/10.1029/2010EO510001/pdf

What Caused Recent Acceleration of the North Magnetic Pole Drift?
The north magnetic pole (NMP) is the point at the Earth’s surface where the geomagnetic field is directed vertically downward. It drifts in time as a result of core convection, which sustains the Earth’s main magnetic field through the geodynamo process. During the 1990s the NMP drift speed suddenly increased from 15 kilometers per year at the start of the decade to 55 kilometers per year by the decade’s end. This acceleration was all the more surprising given that the NMP drift speed had remained less than 15 kilometers per year over the previous 150 years of observation.
Why did NMP drift accelerate in the 1990s? Answering this question may require revising a long-held assumption about processes in the core at the origin of fluctuations in the intensity and direction of the Earth’s magnetic field on decadal to secular time scales, and hints at the existence of a hidden plume rising within the core under the Arctic.

http://sciences.blogs.liberation.fr/home/files/Courtillot07EPSL.pdf
http://geosci.uchicago.edu/~rtp1/BardPapers/responseCourtillotEPSL07.pdf

Are there connections between the Earth’s magnetic field and climate? (William: And what the heck is causing the Geomagnetic field to abruptly, cyclically change?)
Response to Comment on “Are there connections between Earth’s magnetic field and climate?, Earth Planet. Sci. Lett., 253, 328–339, 2007”
Also, we wish to recall that evidence of a correlation between archeomagnetic jerks and cooling events (in a region extending from the eastern North Atlantic to the Middle East) now covers a period of 5 millenia and involves 10 events (see f.i. Figure 1 of Gallet and Genevey, 2007). The climatic record uses a combination of results from Bond et al (2001), history of Swiss glaciers (Holzhauser et al, 2005) and historical accounts reviewed by Le Roy Ladurie (2004). Recent high-resolution paleomagnetic records (e.g. Snowball and Sandgren, 2004; St-Onge et al., 2003) and global geomagnetic field modeling (Korte and Constable, 2006) support the idea that part of the centennial-scale fluctuations in 14C production may have been influenced by previously unmodeled rapid dipole field variations. In any case, the relationship between climate, the Sun and the geomagnetic field could be more complex than previously imagined. And the previous points allow the possibility for some connection between the geomagnetic field and climate over these time scales.

http://eprints.whiterose.ac.uk/416/1/gubbinsd4.pdf

Is the geodynamo process intrinsically unstable?
Recent palaeomagnetic studies suggest that excursions of the geomagnetic field, during which the intensity drops suddenly by a factor of 5 to 10 and the local direction changes dramatically, are more common than previously expected. The `normal’ state of the geomagnetic field, dominated by an axial dipole, seems to be interrupted every 30 to 100 kyr; it may not therefore be as stable as we thought. We have investigated a possible mechanism for the instability of the geodynamo by calculating the critical Rayleigh number (Rc) for the onset of convection in a rotating spherical shell permeated by an imposed magnetic field with both toroidal and poloidal components.

TA
Reply to  William Astley
September 16, 2016 1:52 pm

Thanks for the very informative post, William Astley. You covered a lot of ground and have given me a lot to study about the possible interactions between the Sun and the Earth.

September 13, 2016 10:02 am

Because of the earth’s axial tilt the angle of the sun’s rays and TSI vary over the hemispherical surface of the earth’s atmosphere, parallel when directly above, oblique when not. The oblique angle spreads the energy over a great area and reduces the W/m^2 intensity.
My location is about 40 degrees north. On Jun 21 the ToA (top of atmosphere, 100 km) solar insolation on a flat surface is 1,356 W/m^2, close to maximum. On Dec 21 the ToA solar insolation on a flat surface is 555 W/m^2. The swing in TSI from summer to winter is 774 W/m^2. Yet, somehow the earth manages to adjust and survive.

commieBob
September 13, 2016 10:25 am

… what’s up with these PhD folks all across the climate landscape who apparently never heard of those [statistics] concepts?

They have the same problem you and I have … they’re not very well versed in statistics. You and I recognize our limitations and they don’t.
It’s way too easy to plug some data into Matlab and produce something that looks like it might be a valid result.
There should be a rule that any paper, that relies on statistical methods, should be required to have an actual statistician as one of its authors. Failing that, at least one of the reviewers should be a statistician.
People have been trying to forecast the climate using sunspots all the way back to William Herschel (1738 – 1822). If our august team of PhDs had been aware of that, they might not have been so brave.

September 13, 2016 11:56 am

Good essay.
One comment on Bonferroni corrections: With Bonferroni corrections, no true relationship with an R^2 = 0.035 will ever be statistically confirmed. Well, maybe not “never”: at alpha = 5%, maybe 10% of studies might report “statistically significant” relationships in such cases; it’s a problem in “statistical power analysis”.
And as a result, as an honest man I have to say that despite looking for something that I started out truly and completely believing existed, and despite examining a long string of solar-related studies, to date I have not found convincing evidence of such a connection between the ~11-year solar cycles and the climate here at the surface where we live. Now, if the facts change I’ll change my mind, but as it stands I haven’t yet found the requisite evidence.
If you are using appropriate statistics (I am not assuming otherwise), and if you are gauging your results with an alpha level of 5%, and if there is truly no signal in any of those analyses, then you ought to be getting statistically significant results in 5% of your analyses. Is that what you are getting?
Some propositions I wrote yesterday, in pairs.
A. 1 All of the effects of the solar variation on climate are known.
2. There are effects of solar variation on climate that are not yet known.
B. 1. The remaining effects of solar variation on climate have large R^2 values.
2. The remaining effects of solar variation on climate have R^2 values less than 4%.
If A2 and B2 are both correct, then we are in a bind: all studies than can be done with the existant relatively short data segments will continue to have low power. It will take a long time to evaluate all of the remaining solar effects, and every study will be unconvincing.
If something other than CO2 has caused most of the increase in global mean temp since 1880 (the “lukewarmer” position, which I think is supported by the quantitative analyses of CO2 effects at the surface and atmosphere), then what was it? This is the “Limbo” of which I wrote, hopefully not permanent like the Catholic Limbo.

Bob Weber
Reply to  matthewrmarler
September 13, 2016 9:33 pm

“It will take a long time to evaluate all of the remaining solar effects, and every study will be unconvincing.”
No it won’t take a long time, it is already largely done. The only reason you are so depressed about this is because of the regular reinforcement here from a few that the sun doesn’t affect the climate, and because you might lack the knowledge to have the confidence to know how and why the sun does affect the weather and climate.
The limbo you speak of will end soon. The holdouts will have nothing to talk about in another year. The smart ones will get it this year. Science itself will be undergoing a sea change over the next few years as the sun’s output power drops even more, to the point where the holdouts and fence sitters will have no other choice to accept reality if they wish to be seen as intellectually honest. The lukewarmers and warmists will be facing that music together.
About your propositions:
A.1. True & False. The solar warming/cooling effects are already known, but not accepted by all, as evidenced on this blog regularly.
2. False. There are no forms of solar energy that are unknown that provide sensible heat other than TSI.
B.1. There are no other remaining solar effects after solar radiation and particle effects (which cosmic rays ie particles are part of). Particle effects don’t add heat, but tend to cool the earth via atmospheric processes. UV is a part of TSI. When the UV index is high in the US, it’s hot where the index is high. It’s not a coincidence. That can even happen under low TSI such as it did this summer, all summer long.
2. False. Solar effects always have earthly effects. ALWAYS. The mystery has been how does it work. My research shows solar effects are layered and time dependent. Determining r-values depends entirely on what and how research questions are posed and what data is used. For example the Chinese authors had lower r values using SSN because it’s really not the right indice – they should have used TSI instead.
The literature is loaded with papers on radiation and particle effects. I don’t want to leave you empty handed, so here’s some reinforcement from others’ findings:
http://notrickszone.com/skeptic-papers-2016/ and http://www.earth-syst-dynam-discuss.net/esd-2016-38/

Reply to  Bob Weber
September 13, 2016 10:05 pm

The limbo you speak of will end soon. The holdouts will have nothing to talk about in another year. The smart ones will get it this year. Science itself will be undergoing a sea change over the next few years as the sun’s output power drops even more
We are moving towards solar minimum as we do in every sunspots cycle. Then comes SC25 will looks to be a bit stronger than the current cycle, so we will move towards the next solar maximum, and then down again to the next minimum, and so on. The magnetic cycles continue unabated as they did during the Maunder Minimum. There are signs that sunspots will be less visible, but solar activity as such is not in for dramatic change.

Reply to  Bob Weber
September 14, 2016 10:27 am

Bob Weber: http://notrickszone.com/skeptic-papers-2016/ and http://www.earth-syst-dynam-discuss.net/esd-2016-38/
Thank you for the links. Whenever I read those papers, I come away thinking that the solar hypothesis is “on life support”, with at best a bunch of small and inconsistent results (or perhaps a large and inconsistently selected and reported results.) But first a clarification, before I dive in: Are you saying that the studies taken together are largely concordant as to the mechanisms and sizes of the effects, or that the R^2 relations between solar variation and climate variation are larger than 4% (or both)?
I grant you that UV on a summer day can cause a sunburn, but I have not seen very clear evidence that variations in UV content of inbound radiation are correlated with climate changes globally or regionally (neither do I rule out the possibility.)
Some solar scientists have predicted big declines in solar output in the upcoming decade, and a subsequent decline in global mean Earth temp. Actual forecasts of future solar activity have not been terrifically accurate, though post-fitting of the data looks good. I look forward to the future to clarify, but it looks to me now like the relationship will still be murky for at least a decade.

TA
Reply to  Bob Weber
September 14, 2016 2:41 pm

“B.1. There are no other remaining solar effects after solar radiation and particle effects”
What about the Sun’s magnetic field interacting with the Earth’s magnetic field?

Reply to  TA
September 14, 2016 3:22 pm

Yeah, what about it? What is your well-founded estimate of of the magnitude of the effect from that?

Bob Weber
Reply to  Bob Weber
September 15, 2016 9:47 am

I agree with you Leif that there will not be dramatic changes in the sun’s output unlike we’ve seen before, and that could include a possible future MM, which I’m not saying is going to happen, but even that period was within the normal solar activity range.
Because whatever the sun does is “normal” and “natural” – sometimes people don’t appreciate that.
What I am bringing forward is a mathematical way to understand how SSTs and OHC change over time as heat either accumulates in or dissipates from the ocean under enduring low or high range TSI conditions.
The key to understanding this is realizing that the earth’s solar warming/cooling threshold is like the freezing point of water, a determinable value. Ice melts at a specific temperature, a specific energy level, likewise the earth SST/OHC warms and cools at a specific amount of solar energy over time. I figured that out to be 1361.25 w/m2, near the middle of the “normal” TSI range we’ve measured.
Since the sun is rarely in the highest TSI range for long periods, but can be in the low range for extended periods, the main points to understand wrt solar supersensitivity are
1) Whether TSI is above or below the 1361.25 line and for how long
2) Whether TSI is falling or rising.
3) The lag time for solar energy to accumulate and dissipate, short and long-term.
4) The effect of changes in TSI are identifiable in several data sets/product images.
The sea change I speak of will occur when it is glaringly obvious the earth is cooling to even the most recalcitrant. I can show you several lines of evidence that that the earth is cooling under low TSI now, if you’re interested.

Bob Weber
Reply to  Bob Weber
September 15, 2016 10:08 am

TA asks “What about the Sun’s magnetic field interacting with the Earth’s magnetic field?”
That falls within “particle effects”, or more technically precise, “electric-, magnetic-, electromagnetic effects”, or my short-hand “electric weather effects” (synonyms: ‘magnetic weather effects’, ‘electromagnetic weather effects’.
Particles effects involve the quantity and motion of electrically charged particles, mostly protons and electrons, that are responsible for the magnetic field changes on the sun, in the IMF, and within the earth’s GEC (global electric circuit)/GMF (geomagnetic field).
http://www.nasa.gov/feature/goddard/2016/understanding-the-magnetic-sun
My research covers the gamut of earthly responses to the sun’s radiation & particle effects, ie “electric weather effects’ and ‘solar supersensitivity’.

TA
Reply to  Bob Weber
September 15, 2016 10:39 am

lsvalgaard, September 14, 2016 at 3:22 pm wrote: “Yeah, what about it [Sun’s magnetic field interaction with Earth’s atmosphere]? What is your well-founded estimate of of the magnitude of the effect from that?”
I wasn’t proposing any theory, Isvalgaard, I was asking a question and trying to learn something.
I just happened to read an article in Astronomy magazine a while back that talked about the Sun’s magnetic field interacting with the Earth and Venus (the article’s focus was on Venus lack of a magnetic field), and they mentioned this having an effect on cloud cover on both planets, so I was just wondering how the Sun’s magnetic field interactions figured into that, if at all.

Reply to  TA
September 15, 2016 10:55 am

If a planet has no magnetic field, the solar wind will over hundreds of millions of years slowly erode the atmosphere. But since the Earth does have a magnetic field we are shielded from the eroding effect of the solar wind [which would anyway be an extremely slow process, so not relevant for the current debate].

richard@rbaguley.plus.com
Reply to  Bob Weber
September 15, 2016 11:15 am

Venus has no magnetic field, but it sure does have an atmosphere. In fact, being closer to the Sun, it experiences the solar wind to a greater extent than the Earth.

TA
Reply to  Bob Weber
September 16, 2016 2:01 pm

Thanks, Bob Weber, for the link to understanding the magnetic sun. This is a fascinating subject.

TA
Reply to  Bob Weber
September 17, 2016 7:47 am

richard@rbaguley.plus.com September 15, 2016 at 11:15 am wrote:
“Venus has no magnetic field, but it sure does have an atmosphere. In fact, being closer to the Sun, it experiences the solar wind to a greater extent than the Earth.”
http://sci.esa.int/venus-express/50246-a-magnetic-surprise-for-venus-express/
“05 April 2012
Venus is a rarity among planets – a world that does not internally generate a magnetic field. Despite the absence of a large protective magnetosphere, the near-Venus environment does exhibit a number of similarities with planets such as Earth. The latest, surprising, example is the evidence for magnetic reconnection in Venus’ induced magnetotail.
Planets which generate magnetic fields in their interiors, such as Earth, Mercury, Jupiter and Saturn, are surrounded by invisible magnetospheres. Their magnetic fields deflect the charged particles of the solar wind (electrons and protons) as they stream away from the Sun. This deflection creates a magnetosphere – a protective “bubble” around the planet – which ends in an elongated magnetotail on the lee side of the magnetosphere.
Since Venus has no intrinsic magnetic field to act as a shield against incoming charged particles, the solar wind sometimes interacts directly with the upper atmosphere. However, Venus is partially protected by an induced magnetic field.”

Reply to  matthewrmarler
September 16, 2016 5:43 pm

Richard,
“Venus has no magnetic field, but it sure does have an atmosphere.”
I’ve read that the active volcanoes of Venus replace the atmosphere lost to the solar wind.

richard@rbaguley.plus.com
Reply to  Editor of the Fabius Maximus website
September 16, 2016 5:56 pm

I suggest you re-read what you read, and pay close attention the the words “may,” “might,” and could. As you know the instruments landed on the surface didn’t last long enough to determine if the planet was seismically active.
.
.
PS, did the hypothetical volcanoes spew CO2 or SO2 ?

MB
September 13, 2016 12:51 pm

This seems like valid criticism to me. Probably the article by Huo and Xiao should never have been published in this form, but since it has been, why don’t you write up your your main points up in a 3 page paper and send it to “Atmospheric and Oceanic Science Letters”? This should not be much work for you, and I believe that the points you bring up are so serious that the journal would have to react.

William Astley
September 13, 2016 12:51 pm

Willis,
You write article after article about the sun and appear to have never investigated how the sun changes and how the sun affects planetary climate (i.e. read papers about the subject and thought about the subject).
Sun spot count (closed magnetic flux on the surface of the sun) is a rough measure of one of two solar phenomena that create solar wind bursts. The solar wind bursts remove cloud forming ions from the high latitude regions and the tropics changing the amount of cloud cover and the properties of the clouds, by creating a space charge differential in the ionosphere.
The process where solar wind bursts remove and add ions to the clouds is called electroscavenging. Electroscavenging is what amplifies or inhibits El Niño events.
Coronal holes, open magnetic flux regions on the sun, also cause solar wind bursts. What causes coronal holes to form is not known.
Comment: For some unexplained reason the sun is now covered with coronal holes. The coronal holes of course cause solar wind bursts which explains why the planet has not cooled due to the increase in high speed cosmic particles that are now striking the earth.
Coronal holes can persist for months and have for some unknown reason occurred late in the solar cycle in low latitude regions thereby causing solar wind bursts to occur when there are few sun spots on the surface of the sun or no sunspots. Coronal holes make it appear that the solar magnetic cycle is not the primary modulator of the earth’s.
Comment:
The solar magnetic cycle also modulates the amount of high speed particles (called cosmic ray flux (CRF) or galactic cosmic rays (GCR) for historical reasons, the discoverers thought the phenomena was caused by a ray rather than a particle and the misleading name stuck) that strike the earth’s atmosphere creating cloud forming ions. Solar wind bursts remove and change the ions in the atmosphere, so solar wind bursts change make it appear that an increase in CRF/GRF does not cause there to be an increase in cloud cover in high latitude regions.
This peer reviewed paper notes planetary temperature changes closely correlates with solar cycle changes when solar wind bursts and GCR changes are both taken into account.
http://sait.oat.ts.astro.it/MmSAI/76/PDF/969.pdf

Once again about global warming and solar activity
Solar activity, together with human activity, is considered a possible factor for the global warming observed in the last century. However, in the last decades solar activity has remained more or less constant while surface air temperature has continued to increase, which is interpreted as an evidence that in this period human activity is the main factor for global warming. We show that the index commonly used for quantifying long-term changes in solar activity, the sunspot number, accounts for only one part of solar activity (William: Closed magnetic field) and using this index leads to the underestimation of the role of solar activity in the global warming in the recent decades. A more suitable index is the geomagnetic activity (William: Short term abrupt changes to the geomagnetic field caused by solar wind bursts, which are measured by the short term geomagnetic field change parameter Ak. Note the parameter is Ak rather than the month average with Leif provides a graph for. The effect is determined by the number of short term wind bursts. A single very large event has less affect than a number of events. As Coronal holes can persist for months and years and as the solar wind burst affect lasts for roughly week, a coronal hole has a significant effect on planetary temperature) which reflects all solar activity, and it is highly correlated to global temperature variations in the whole period for which we have data. ….
…The geomagnetic activity reflects the impact of solar activity originating from both closed and open magnetic field regions, so it is a better indicator of solar activity than the sunspot number which is related to only closed magnetic field regions. It has been noted that in the last century the correlation between sunspot number and geomagnetic activity has been steadily decreasing from – 0.76 in the period 1868- 1890, to 0.35 in the period 1960-1982, while the lag has increased from 0 to 3 years (Vieira
et al. 2001).
…In Figure 6 the long-term variations in global temperature are compared to the long-term variations in geomagnetic activity as expressed by the ak-index (Nevanlinna and Kataja 2003). The correlation between the two quantities is 0.85 with p<0.01 for the whole period studied. It could therefore be concluded that both the decreasing correlation between sunspot number and geomagnetic activity, and the deviation of the global temperature long-term trend from solar activity as expressed by sunspot index are due to the increased number of high-speed streams of solar wind on the declining phase and in the minimum of sunspot cycle in the last decades.

The following is a review paper that discusses some of the mechanisms by which solar changes modulate planetary climate.
http://www.klimarealistene.com/web-content/Bibliografi/Tinsley2007,GlobalElectricCircuit.pdf

Atmospheric Ionization and Clouds as Links between Solar Activity and Climate, By Brian Tinsley and Fangqun Yu
The GCR flux is responsible for almost all of the production of ionization below 15 km altitude, that determines the conductivity in that region. The MeV electrons and their associated X-rays produce ionization in the stratosphere, and affect the conductivity there. The current flow in the global electric circuit is generated mainly by charge separation in deep convective clouds in the tropics, and maintains the global ionosphere at a potential of about 250 kV (250,000 volts). Variations above and below this value occur in the high latitude regions due to solar wind – magnetosphere – ionosphere coupling processes. The current density Jz varies horizontally due to variations in the local vertical column resistance (this is affected by the GCR and MeV electron fluxes) and by variations in the local ionospheric potential (especially to those in the high latitude regions). Because Jz flowing through clouds in the troposphere responds to conductivity and potential changes occurring all the way up to 120 km altitude, it is a very effective coupling agent for linking inputs in the stratosphere and ionosphere with cloud levels.

Solar wind bursts cause the planet to warm by creating a space charge differential in the ionosphere which in turn causes an electric current flow from high latitude regions of the planet to the equator. The return path for the current is in the ocean. This process is called electroscavenging.
Sunspots and coronal holes both affect the strength and extent of the solar heliosphere which is the name for the tenuous solar ionized gas and pieces of the magnetic field that are thrown off the sun. The heliosphere extends well past the orbit of Pluto. The solar heliosphere blocks GCR (galactic cosmic rays, mostly high speed protons). So when the solar heliosphere is strong the pieces of magnetic field in the solar heliosphere block GCR so there are less GCR striking the earth.
The increased GCR will cause the planet to cool at high latitude regions, if there are no solar wind bursts to remove the cloud forming ions. GCR will only cause the planet to cool at high latitude regions as the earth’s magnetic field in lower latitudes blocks the GCR.
Note the difference in the regions of the planet that are affected by solar wind bursts and solar heliosphere’s modulation of the amount of GCR that strikes the earth. Electroscavenging affects both high latitude regions and the equator while strength of the solar heliosphere which in turn affect GCR amounts only high latitude regions. This comment is true as long as the geomagnetic field is not strongly tilted or is in an excursion.
http://sait.oat.ts.astro.it/MmSAI/76/PDF/969.pdf

Once again about global warming and solar activity
By K. Georgieva, C. Bianchi and B. Kirov
Solar activity, together with human activity, is considered a possible factor for the global warming observed in the last century. However, in the last decades solar activity has remained more or less constant while surface air temperature has continued to increase, which is interpreted as an evidence that in this period human activity is the main factor forglobal warming. We show that the index commonly used for quantifying long-term changes in solar activity, the sunspot number, accounts for only one part of solar activity and using this index leads to the underestimation of the role of solar activity in the global warming in the recent decades. A more suitable index is the geomagnetic activity which reflects all solar activity, and it is highly correlated to global temperature variations in the whole period for which we have data.
In Figure 6 the long-term variations in global temperature are compared to the long-term variations in geomagnetic activity as expressed by the ak-index (Nevanlinna and Kataja 2003). The correlation between the two quantities is 0.85 with p<0.01 for the whole period studied. It could therefore be concluded that both the decreasing correlation between sunspot number and geomagnetic activity, and the deviation of the global temperature long-term trend from solar activity as expressed by sunspot index are due to the increased number of high-speed streams of solar wind on the declining phase and in the minimum of sunspot cycle in the last decades

http://gacc.nifc.gov/sacc/predictive/SOLAR_WEATHER-CLIMATE_STUDIES/GEC-Solar%20Effects%20on%20Global%20Electric%20Circuit%20on%20clouds%20and%20climate%20Tinsley%202007.pdf

The role of the global electric circuit in solar and internal forcing of clouds and climate
The solar wind affects the galactic cosmic ray flux, the precipitation of relativistic electrons, and the ionospheric potential distribution in the polar cap, and each of these modulates the ionosphere-earth current density. On the basis of the current density-cloud hypothesis the variations in the current density change the charge status of aerosols that affect the ice production rate and hence the cloud microphysics and climate [e.g., Tinsley and Dean, 1991; Tinsley, 2000]. The underlying mechanism is that charged aerosols are more effective than neutral aerosols as ice nuclei (i.e., electrofreezing) and that the enhanced collections of charged evaporation nuclei by supercooled droplets enhance the production of ice by contact ice nucleation (i.e., electroscavenging).
Both electrofreezing and electroscavenging involve an increase in ice production with increasing current density [e.g, Tinsley and Dean, 1991; Tinsley, 2000]. The current density-cloud hypothesis appears to explain solar cycle effects on winter storm dynamics as well as the day to-day changes of Wilcox and Roberts Effects [e.g., Tinsley, 2000]. Kniveton and Todd [2001] found evidence of a statistically strong relationship between cosmic ray flux, precipitation and precipitation efficiency over ocean.

This peer reviewed paper notes that has been an astonishing increase in coronal holes late in the solar cycle when then there are no or few sunspots. The solar wind bursts from the coronal holes of course remove cloud forming ions which makes it appear that increase in
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.

http://www.ann-geophys.net/27/2045/2009/angeo-27-2045-2009.pdf

On the long term change in the geomagnetic activity during the 20th century Published: 5 May 2009
The analysis of the aa index series presented in this paper clearly shows that during the last century (1900 to 2000) the number of quiet days (Aa<20 nT) drastically diminished from a mean annual value greater than 270 days per year at the end of the nineteenth century to a mean value of 160 quiet days per year one hundred years later. This decrease is mainly due to the decrease of the number of very quiet days (Aa<13 nT). We show that the so-evidenced decrease in the number of quiet days cannot be accounted for by drift in the aa baseline resulting in a systematic underestimation of aa during the first quarter of the century: a 2–3 nT overestimation in the aa increase during the 20th century would lead to a 20–40% overestimation in the decrease of the number of quiet days during the same period.

Carla
Reply to  William Astley
September 13, 2016 9:48 pm

Lots going on in the sun/earth system William.
Thanks for showing us some of those complexities.
When Willis goes off on one of his debunkers, it’s through a single paramenter, such as SSN or TSI and supoosedly having a single effect on something or another.
This is because of the different authors which use a single parameters for their studies.
Multiple solar parameters occur over a solar cycle.
The suns output is not just SSN which result in a number of CME super blasts which hit our planet, but coronal hole high speed streams and TSI eeek (TSI) and HCS crossings, solar wind speed dips, increases and decreases in Galactic Radiation GCR.
There is a waxing and waning in rotation, geomagnetic effects, electric field variations etc…
ALL these things together need to be considered over a time period
There are multiple effects, over a given period, on the Earth system, some of which you have mentioned above.
Lots that go on..over the rising and falling of solar cycles in time .. and in just the 11 and 22 year cycles. lol

Reply to  Carla
September 13, 2016 10:07 pm

The suns output is not just SSN which result in a number of CME super blasts which hit our planet, but coronal hole high speed streams and TSI eeek (TSI) and HCS crossings, solar wind speed dips, increases and decreases in Galactic Radiation GCR.
There is a waxing and waning in rotation, geomagnetic effects, electric field variations etc…

And all of these things vary together in the regular cycle. So if they have any effects, the effects will follow the same cycle.

Reply to  William Astley
September 13, 2016 10:19 pm

As usual, most of what you say is muddled or nonsense. E.g. we do know how and why and when in the cycle coronal holes form. It is quite normal that coronal holes form at this point in the declining cycle [and we know why] as they do in every cycle, as I have explained elsewhere.

Reply to  lsvalgaard
September 14, 2016 10:32 am

lsvalgaard: As usual, most of what you say is muddled or nonsense.
Was that addressed to William Astley?

Reply to  matthewrmarler
September 14, 2016 10:35 am

Obviously, yes.

Reply to  lsvalgaard
September 15, 2016 7:32 am

lsvalgaard: Obviously, yes.
I am mistaken about much of what is “obvious”. So I had to ask.

Reply to  William Astley
September 13, 2016 10:40 pm

From https://wattsupwiththat.com/2016/09/10/chinese-scientists-claim-peak-solar-activity-drove-201516-el-nio/
lsvalgaard September 12, 2016 at 10:24 am
Coronal holes form from the magnetic debris from decaying sunspots. For a hole to open up, the magnetic areas with uniform polarity must be large enough. If there are many sunspots, they will inject mixed polarities [sunspots are bipolar] and so destroy the uni-polarity of an area. So, as the cycle declines this destruction will also decline [the survival rate will increase] so the chance of a hole will increase. On the other hand, as the cycle declines, so will the number of sunspots and hence the amount of magnetic debris, so that the chance of a hole will decrease. You can see the result of those two opposing trends here:
http://www.leif.org/research/CH-Chances.png
There will be a ‘sweet’ spot [oval] somewhere during the declining phase.
Geomagnetic activity will maximize during that sweet spot.
For the Maunder Minimum, the situation is interesting. Some people claim that the sun was one big coronal hole and other people claim that there were no coronal holes. We know from cosmic ray proxies that the modulation of the GCRs was strong and healthy during the MM. Also that comet tails [produced by the solar wind coming from coronal holes] were clearly present, so perhaps coronal holes were common. If so, geomagnetic activity should have been significant.

Carla
Reply to  lsvalgaard
September 14, 2016 8:22 pm

lsvalgaard September 13, 2016 at 10:40 pm
From https://wattsupwiththat.com/2016/09/10/chinese-scientists-claim-peak-solar-activity-drove-201516-el-nio/
lsvalgaard September 12, 2016 at 10:24
————————————————————
Thanks Dr. S., we call that post a ‘keeper.’
Which solar hemisphere will be leading in spot production for cycle 25?

Reply to  Carla
September 14, 2016 8:44 pm

we call that post a ‘keeper.’
Who are ‘we’?
Which solar hemisphere will be leading in spot production for cycle 25?
Usually, the hemisphere changes in the middle of the cycle.
For the past several cycles, the North was the most productive in the beginning of the cycle.
See http://www.leif.org/research/ApJ88587.pdf
Some people think there is a regularity in this, see
Slide 33 of http://www.leif.org/research/Asymmetric-Solar-Polar-Field-Reversals-talk.pdf
I am generally leery of cyclomania, so am sitting on the fence on this one.
Short: I don’t know.

Carla
Reply to  lsvalgaard
September 15, 2016 7:09 am

lsvalgaard September 14, 2016 at 8:44 pm
we call that post a ‘keeper.’
Who are ‘we’?
__________________________________
Thanks for the reply Dr. S., the solar hemispheric asymmetries are a bit of a conundrum.
A ‘keeper,’ is a fishing term around these parts indicating that this one gets cleaned and eaten and not thrown back in the lake to grow up.
‘We,’ is the frog in my back pocket. lol ribbit ribbit

kim
Reply to  lsvalgaard
September 15, 2016 7:15 am

In my sadly uniformed opinion, the hemispheric asymmetry during the Maunder Minimum is a big clue. To what, I dunno.
==============

Carla
Reply to  lsvalgaard
September 15, 2016 7:39 am

lsvalgaard September 14, 2016 at 8:44 pm
Which solar hemisphere will be leading in spot production for cycle 25?
Usually, the hemisphere changes in the middle of the cycle.
For the past several cycles, the North was the most productive in the beginning of the cycle.
See http://www.leif.org/research/ApJ88587.pdf
Some people think there is a regularity in this, see
Slide 33 of http://www.leif.org/research/Asymmetric-Solar-Polar-Field-Reversals-talk.pdf
I am generally leery of cyclomania, so am sitting on the fence on this one.
Short: I don’t know.
————————————————————
Another question if I may…
Is there a relationship to the hemispheric extent of the HCS ?
The neutral line sometimes extends more southward or northward of the equator bringing downward/upward either more positive/negative flux to a given hemisphere..

Reply to  Carla
September 15, 2016 7:49 am

The neutral line sometimes extends more southward or northward of the equator bringing downward/upward either more positive/negative flux to a given hemisphere..
Causality flows the other way: it is an already existing hemispheric asymmetry that causes warps and asymmetries in the ‘neutral line’.

Carla
Reply to  lsvalgaard
September 15, 2016 7:45 am

One more quick question before I start getting ready for work..
Why can’t the Interstellar pressures (wind/magnetic/density) have an effect on the on the HCS (helio current sheet)?

Reply to  Carla
September 15, 2016 7:54 am

The answer is the same as always: because the solar wind is supersonic. and because the pressure in the inner solar system is MUCH larger than in interstellar space.

kim
Reply to  lsvalgaard
September 15, 2016 8:04 am

???? ‘supersonic’. What is the meaning of supersonic in this medium. And ‘much larger’ seems to me to mean that any effect may be very small and difficult to detect.
I know I’m pretty ignorant, but there seems to be a logic fail here. Moar, please.
============

Reply to  kim
September 15, 2016 8:23 am

In a plasma there is a speed limit to how fast magnetic changes can propagate [called the Alfven speed]. The solar wind moves away from the sun ten times faster [near the Earth] than the Alfven speed. Its ‘Alfvenic Mach’ number is thus about 10, meaning that the plasma moves away from the sun 10 times faster than any external changes can move towards the sun.
MUCH means something like this: The solar wind that flows past the Earth has a certain density. As the interstellar medium begins 100 times further out, the wind out there [which is the same as was near the Earth a year ago] has now been diluted 10,000 times.

kim
Reply to  lsvalgaard
September 15, 2016 8:27 am

That’s helpful, thanks. I now understand the meaning of ‘supersonic’ as used.
=========

Carla
Reply to  lsvalgaard
September 15, 2016 9:23 am

kim September 15, 2016 at 8:04 am
————————————————-
Don’t stop wondering about how something might propagate inward through the “supersonic” solar wind.
An inspirational video for you and everyone else. Baffled scientists when it happened, tooooo…
https://youtu.be/YxPehCj-ouU
Dec. 16, 2011
Comet Lovejoy Plunges into the Sun and Survives
http://www.nasa.gov/mission_pages/sunearth/news/comet-lovejoy.html
This morning, an armada of spacecraft witnessed something that many experts thought impossible. Comet Lovejoy flew through the hot atmosphere of the sun and emerged intact.
“It’s absolutely astounding,” says Karl Battams of the Naval Research Lab in Washington DC. “I did not think the comet’s icy core was big enough to survive plunging through the several million degree solar corona for close to an hour, but Comet Lovejoy is still with us.”
The comet’s close encounter was recorded by at least five spacecraft: NASA’s Solar Dynamics Observatory and twin STEREO probes, Europe’s Proba2 microsatellite, and the ESA/NASA Solar and Heliospheric Observatory. The most dramatic footage so far comes from SDO, which saw the comet go in (below) and then come back out again (above)……………………………………………………………………………..
tick tock goes the clock, bye bye

Reply to  Carla
September 15, 2016 9:37 am

Don’t stop wondering about how something might propagate inward through the “supersonic” solar wind.
And our spacecraft also propagate inwards. The difference is that the comet and our spacecraft are not conducting plasma. You still have not understood anything.

Carla
Reply to  lsvalgaard
September 15, 2016 6:58 pm

lsvalgaard September 15, 2016 at 9:37 am
Don’t stop wondering about how something might propagate inward through the “supersonic” solar wind.
And our spacecraft also propagate inwards. The difference is that the comet and our spacecraft are not conducting plasma.
————————————————————
Turbulence Dr. S., think turbulence..
Turbulence in the interstellar regions where two or more interstellar clouds converge (an interaction region whose size may last several solar cycles in depth) or interstellar size corotating super shells. The size of which would exceed the puny little heliosphere.
The supersonic solar winds are more swiss cheese like at distance containing subsonic regions.
But this is more interesting for now.
“Warning” this video contains a water pistol.
Sept. 1, 2016
Images From Sun’s Edge Reveal Origins of Solar Wind
http://www.nasa.gov/feature/goddard/2016/images-from-sun-s-edge-reveal-origins-of-solar-wind
…”””Both near Earth and far past Pluto, our space environment is dominated by activity on the sun. The sun and its atmosphere are made of plasma – a mix of positively and negatively charged particles which have separated at extremely high temperatures, that both carries and travels along magnetic field lines. Material from the corona streams out into space, filling the solar system with the solar wind.
But scientists found that as the plasma travels further away from the sun, things change: The sun begins to lose magnetic control, forming the boundary that defines the outer corona – the very edge of the sun.
“As you go farther from the sun, the magnetic field strength drops faster than the pressure of the material does,” said Craig DeForest, lead author of the paper and a solar physicist at the Southwest Research Institute in Boulder, Colorado. “Eventually, the material starts to act more like a gas, and less like a magnetically structured plasma.”
The breakup of the rays is similar to the way water shoots out from a squirt gun. First, the water is a smooth and unified stream, but it eventually breaks up into droplets, then smaller drops and eventually a fine, misty spray. The images in this study capture the plasma at the same stage where a stream of water gradually disintegrates into droplets.”””…
https://youtu.be/QYM2_ytkjQo

Reply to  Carla
September 15, 2016 9:53 pm

Turbulence Dr. S., think turbulence
Not needed, as it does not aid inward propagation. On the contrary, turbulence helps make the heliosphere more difficult to traverse, e.g. for cosmic rays. One can only admire your steadfast devotion to your delusion.

Carla
Reply to  lsvalgaard
September 15, 2016 7:14 pm

Have a look at this video from IRIS.
I purposely stopped this at 5 seconds. It LOOKs as though this magnetic field segment was out in the outer corona and then reattached it self to the surface? Of forming out there and not coming from the surface at all?
https://youtu.be/sfKZHto7acw?t=5s
Aug. 5, 2016
IRIS Spots Plasma Rain on Sun’s Surface
http://www.nasa.gov/feature/goddard/2016/iris-spots-plasma-rain-on-suns-surface
…”””As the video continues, solar material cascades down to the solar surface in great loops, a flare-driven event called post-flare loops or coronal rain. This material is plasma, a gas in which positively and negatively charged particles have separated, forming a superhot mix that follows paths guided by complex magnetic forces in the sun’s atmosphere. As the plasma falls down, it rapidly cools – from millions down to a few tens of thousands of kelvins. The corona is much hotter than the sun’s surface; the details of how this happens is a mystery that scientists continue to puzzle out. Bright pixels that appear at the end of the video aren’t caused by the solar flare, but occur when high-energy particles bombard IRIS’s charge-coupled device camera – an instrument used to detect photons.”””
My bold above

Reply to  Carla
September 15, 2016 9:58 pm

I purposely stopped this at 5 seconds. It LOOKs as though this magnetic field segment was out in the outer corona and then reattached it self to the surface? Of forming out there and not coming from the surface at all?
Almost everything that is thrown out from the sun [e.g. a CME] actually falls right back in, because the sun’s gravity is strong [27 times stronger than the Earths at their surfaces]. Often it is difficult to see how the material is connected because its temperature determines what we can see, so a change in temperature [e.g. when the stuff balloons outward and cools] will make the material invisible.

September 13, 2016 1:19 pm

Willis’s arguments are strongly statistical in nature and yet many of the contradictory replies are anecdotal or rely on authority or popularity (literature citations). I don’t believe Willis has proven or attempted to prove that there is no correlation between solar activity and significant climate events on Earth such as ENSO. Trying to prove a negative is generally a fools game anyway. Wills has however very effectively shredded an attempt to document a solar-ENSO correlation by using strong statistical testing. In a battle of wits, statistics beats anecdote and reputation. If Willis is self-taught he had an excellent teacher.

Bubba Cow
September 13, 2016 2:47 pm

The article referenced violates a research integrity – it is a fishing expedition. Proper research methods in the actual scientific method requires researchers to plan everything ahead including every comparison and correlation they will conduct. And set degrees of freedom, confidence levels … You don’t just grab data and sift through it, as they did here. Think about it – that introduces researcher discovery bias. These people have had inadequate instructors or they have deliberately violated the principles of research which separate the searchers from the data discoveries – i.e. they had no hypothesis. This is shameful behavior in “research” methods. I have had many undergraduates who would have known better.
Thanks, Willis, although I am aghast. You did your part exposing this.

Javier
Reply to  Willis Eschenbach
September 14, 2016 8:08 am

Willis,
The only way you can propose a physical mechanism on the atmosphere is through a model. Ask, Leif. He can confirm that they use models to try to understand what happens in the inside of the Sun. That is what models are for, to try to understand things, not to predict the future. So there is no problem that Haigh uses models for that, as there is no other way.
Once the hypothesis is established, then it is the time for evidence gathering to support the hypothesis. That is the stage now, and that is why it is getting so many citations. The support is coming not only from atmospheric studies, but also from paleoclimatology.

Part of the input is solar variations … so we would expect to find solar variations in the output.

You can say the same from the climate, as solar variations are part of the input there. Obviously they are not going to omit solar variations from the input, as they do not omit anything. Perhaps the answer that you are working so hard to disprove is that we should expect to find solar variations in the climatic output. That you did not find them does not say that they are not there, perhaps you did not look at the right place and time.

Reply to  Javier
September 14, 2016 10:38 am

Ask, Leif. He can confirm that they use models to try to understand what happens in the inside of the Sun
No, the model is a summary of what we have learned from observations.

Javier
Reply to  Javier
September 14, 2016 2:21 pm

According to that theory, there could have been no physical mechanisms proposed for the atmosphere until the late 20th century when computer models were developed

Sure, and Galen made a lot of discoveries in medicine without modern methods, but if you want to push an atmospheric hypothesis nowadays you will be required to provide evidence from respected models before being accepted for publication in any decent journal. Your combination of naivety and nonsense accusations is startling. You may disagree, but that is the way things are and outsiders like you and me should not come telling them how to conduct their research. I am sure they are doing the best they can. If you think you can do better, you are welcome to try.
As I am an empiricist, I am so lucky as to have never needed a model, so I won’t get into a discussion about them. I understand that they are tools and, as long as you use them properly, useful. The output of a model should never be treated as real evidence, and models should be validated before too much credit is placed on them, but some people get enthused over their toys.

despite the ~ 11-year sunspot variations being clear in the sun, there is no trace of them in the climate. And that is the problem … despite literally centuries of looking, we still haven’t found any actual evidence that is definitive and bulletproof that connects the tiny ~11-year variations with anything down here on the surface.

As you say the tiny 11-year variations are hard to see because the effect they produce is small and the noise of the system is high. However regarding the effect of solar variability on climate, the longer the solar cycle the stronger the climatic effect. The effect of the ~ 2400 and ~ 1000 year solar cycles on the climate is huge and well recorded in paleoclimatology. Once the effects are past, the recovery takes centuries. The effects are consistent with Haigh’s hypothesis. We know that the Hadley cells are expanding and that it is not due to GHGs, but probably ozone. Proxies indicate the expansion has been taking place for more than 100 years and probably since the end of the LIA. The expansion of the Hadley cells, about 1-2° since 1979 means the tropical areas expand and the entire atmosphere and climate of the planet reorganizes towards a warmer state with a change in wind and precipitation patterns.
As the atmosphere changes quite a lot with the seasons, the effect of the 11-year cycle is just too small compared to seasonal changes. The experts think that the effect is more noticeable during the winter months, and point to a higher frequency of high pressure blocking days over the North Atlantic with an increased frequency of very cold winters over Western-Central Europe with a 1-2 year delay with the solar cycle minimum like the 2010 cold winter after the 2009 solar minimum. Perhaps cold winters coming to Europe for 2019-20.

Reply to  Javier
September 14, 2016 2:28 pm

The effect of the ~ 2400 and ~ 1000 year solar cycles on the climate is huge and well recorded in paleoclimatology.
There is very little evidence that those climate cycles are solar-related. The cosmic ray record is contaminated by climate and have uncertain calibration [e.g. different ice cores disagree].

Javier
Reply to  Javier
September 14, 2016 2:28 pm

No, the model is a summary of what we have learned from observations

Exactly what climate scientists say about their models. And then models are used to test new ideas. If the new idea does not agree with the model one has a problem. Before the idea is accepted the model has to be proven wrong.

Reply to  Javier
September 14, 2016 2:32 pm

You missed the point: what we know about the solar interior is not derived from models, but from observations of solar pulsations [like oil prospecting uses seismic waves to learn about the interior of the Earth] and from observations of the neutrino flux.

Javier
Reply to  Javier
September 14, 2016 2:32 pm

There is very little evidence that those climate cycles are solar-related. The cosmic ray record is contaminated by climate and have uncertain calibration [e.g. different ice cores disagree].

14C is not recorded in ice-cores but tree rings and there is an entire archeological field based on its calibration.

Reply to  Javier
September 14, 2016 3:20 pm

The 14C record is derived from modelling the atmospheric circulation [due to the long residence time of the isotope]. Here are some raw data:
http://www.leif.org/research/INTCAL13.png
where are the 2400-yr cycle [and the 1000-yr to boot]?

Javier
Reply to  Javier
September 14, 2016 2:36 pm

You missed the point: what we know about the solar interior is not derived from models, but from observations of solar pulsations [like oil prospecting uses seismic waves to learn about the interior of the Earth] and from observations of the neutrino flux.

And what we know about the atmosphere is not derived from models but observations. I fail to see the difference.

Reply to  Javier
September 14, 2016 3:14 pm

That you fail to see the difference does not mean there isn’t any.
The knowledge of the atmosphere [which by the way we were not discussing – it was the interior, remember] is derived from observations of limb darkening and strength of spectral lines.
The knowledge about the interior is derived from measurements of the sound speed in the interior, which in turn is derived from direct observation of the travel time of seismic waves.
We do construct models to compare with the observations and find excellent agreement.

Javier
Reply to  Javier
September 14, 2016 6:38 pm

The 14C record is derived from modelling the atmospheric circulation [due to the long residence time of the isotope].

What long residence time? The atomic bomb pulse of 14C that duplicated the concentration of 14C in the atmosphere has taken a mere 60 years to 90% decay. The changes due to solar variability are much smaller and decay in just a few years. And we are talking centuries here.comment image
https://cams.llnl.gov/cams-competencies/forensics/14c-bomb-pulse-forensics
You don’t need any modelling of 14C to see the cycles. This is detrended raw data:
http://www.euanmearns.com/wp-content/uploads/2016/05/Figure-4.png
http://euanmearns.com/periodicities-in-solar-variability-and-climate-change-a-simple-model/

Reply to  Javier
September 14, 2016 7:54 pm

You clearly have a bad case of cyclomania. There are enough ‘cycles’ to go around to fit almost any wild ideas.

Reply to  Javier
September 14, 2016 9:06 pm

An FFT of the raw data shows none of your peaks:
http://www.leif.org/research/FFT-INTCAL13.png

Javier
Reply to  Javier
September 14, 2016 6:46 pm

That you fail to see the difference does not mean there isn’t any.
The knowledge of the atmosphere [which by the way we were not discussing – it was the interior, remember]

We do construct models to compare with the observations and find excellent agreement.

I was comparing the models that climatologists make about Earth’s atmosphere, with the models that you make about the Sun. I don’t see much difference. They are both based on observations and physics laws. Obviously you believe that solar physicists make much better models, but after all nobody is asking you to predict solar climate. I don’t believe you would be very successful predicting solar storms.

Reply to  Javier
September 14, 2016 7:58 pm

but after all nobody is asking you to predict solar climate.
On the contrary, that is precisely what I am asked to predict.
I don’t believe you would be very successful predicting solar storms.
As successful as weather forecasters are in predicting lightning strikes.
Solar storms are weather, and can be predicted to occur quite well if a big, complex active region is on the solar disk.

Javier
Reply to  Javier
September 15, 2016 3:08 am

You clearly have a bad case of cyclomania. There are enough ‘cycles’ to go around to fit almost any wild ideas.

I don’t think so. The 2400 year solar cycle is confirmed by terrestrial climate evidence and reported multiple times since 1971, Cyclomania is believing in cycles not supported by evidence. Perhaps you have a bad case of cyclophobia, not believing in cycles that are real and supported by evidence.

An FFT of the raw data shows none of your peaks:

They are not my peaks and they were reported multiple times based on non-modeled data. This one is from:
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).
http://i1039.photobucket.com/albums/a475/Knownuthing/DamonampSonnet1991_zpsgx24rhpj.png
I am sure you have a copy of that book somewhere. You can go an accuse Damon and Sonnet of cyclomaniacs.

Reply to  Javier
September 15, 2016 6:25 am

Your link mentions peaks at 65 87 105 130 148 208 350 510 708 976 1126 1301 1768 and 2310 years. That is far too many for my taste. Now, the question is whether these peaks are solar or climate peaks. You claimed a 2400-yr period in detrended 14C data, and with some good will, one can see hints of peaks in the detrended version:
http://www.leif.org/research/INTCAL13-All-Data.png
The FFT power spectrum looks like this:
http://www.leif.org/research/INTCAL13-14C-FFT.png
And does show power in the 1500-4000 year range, but note that the amplitude of the peaks in the time series varies in a curious way, being much larger during the glaciation before 14K years. The Sun does know about the glaciation, so it would seem that the climate had a large influence on the 14C. Perhaps all the peaks in the 1500-4000 year range are simply climate-related, in which case it is no wonder that there is a correlation with the paleoclimate record.
It is curious that some people will not accept that the climate has natural variation of its own, but happily claim that the Sun has.

Reply to  Javier
September 15, 2016 6:41 am

The Sun does know about the glaciation,
The Sun does not know about the glaciation,

Javier
Reply to  Javier
September 15, 2016 1:32 pm

Your link mentions peaks at 65 87 105 130 148 208 350 510 708 976 1126 1301 1768 and 2310 years. That is far too many for my taste.

Most peaks in a frequency analysis do not represent real cycles. They need to be confirmed by other type of evidence.
Damon and Sonnet state the following:

“There seems little doubt that fundamental periods (ca. 2300, 208 and 88 yr) exist in the radiocarbon spectrum.”
Damon & Sonnet, 1991

To that I add the ~ 1000 yr cycle. Those periodicities come up repeatedly in cosmogenic proxies and climate proxies.

the amplitude of the peaks in the time series varies in a curious way, being much larger during the glaciation before 14K years. The Sun does not know about the glaciation, so it would seem that the climate had a large influence on the 14C.

It has already been noted. 14C data can be relied on for the Holocene. During the glacial period and specially during deglaciation the CO2 exchange with the oceans was very much changed and makes the interpretation a lot more difficult as our understanding of the carbon cycle during that time is poor.

Perhaps all the peaks in the 1500-4000 year range are simply climate-related

Experts say they represent changes in solar variability, and since the overlap period when we have data both for solar variability and 14C changes agrees, I have no reason to doubt it.

Reply to  Javier
September 15, 2016 1:39 pm

Most peaks in a frequency analysis do not represent real cycles
Correct. One has to cherry pick the ones that match one’s ideas.
Experts say they represent changes in solar variability…I have no reason to doubt it
I am an expert, and I doubt it.

Javier
Reply to  Javier
September 16, 2016 8:30 am

One has to cherry pick the ones that match one’s ideas.

That’s not how it should be done. One has to let the data speak. See if the lows or the highs of the cycles match known lows or highs in the climate. If the climate has the same periodicity then the cycle has a chance of being real.

“Experts say they represent changes in solar variability…I have no reason to doubt it”
I am an expert, and I doubt it.

I have a great deal of respect for you and your scientific capability, but on this one I will go with the consensus. Not personal.

Javier
Reply to  Willis Eschenbach
September 14, 2016 7:04 pm

I always love it when someone points to unidentified “experts”. It gives just that extra soupçon of authenticity to a vague legend.
In any case, the question you should be asking is, did the experts consider the Bonferroni correction?

I’ve got over 20 papers on my hard disk on the effects of solar variability on the atmosphere and this is just a small sample of probably hundreds on the issue. I could put the list up with little effort, but why bother? If they use reanalysis they are no good because solar signal is an input. If they use models they are no good because models can’t be trusted. If they use real data they will always miss one of your favorite statistical tests. Why should I bother? The evidence available doesn’t convince you. That’s ok. You set the bar for that. But don’t say that there is no evidence. It is published.
There is a field of scientists where there is a huge consensus that solar variability plays an important role in climate change, and that is paleoclimatology, because they are faced with the evidence all the time. So we have this curious disconnect between solar physicists and paleoclimaologists that will have to be resolved one day, and I am pretty sure that it will be resolved to the side of those that have the evidence, not to the side of those that have the theory.

Reply to  Javier
September 15, 2016 4:28 am

Javier we know the data show clearly that there is a solar /climate relationship when the sun enters extreme periods of activity. The studies lend further evidence that this is indeed the case.

Javier
Reply to  Javier
September 15, 2016 12:19 pm

Willis,
That is your criteria, and clearly not the only valid one. Scientific journals with professional editors and scientists reviewers set their own criteria.
I am not going to review those papers to see what statistic tests they report in their methods, and it is not possible to know what tests they did apply but are not reporting. But mainly because they are not “my idols” because as I said:

…the tiny 11-year variations are hard to see because the effect they produce is small and the noise of the system is high. However regarding the effect of solar variability on climate, the longer the solar cycle the stronger the climatic effect. The effect of the ~ 2400 and ~ 1000 year solar cycles on the climate is huge and well recorded in paleoclimatology.

I am interested in the long cycles where the climatic effect is clear. In the last five lows of the 2400-yr cycle there has been a very strong climatic effect that is very well established and that coincides very precisely with the reductions in solar activity. That is 5 out of 5 and a global effect.

Reply to  Javier
September 15, 2016 12:35 pm

In the last five lows of the 2400-yr cycle there has been a very strong climatic effect that is very well established and that coincides very precisely with the reductions in solar activity.
It is very likely that those variations a simply climate variations and not solar related. You assume that they are solar, but there is evidence [as I have shown you] that they are not necessarily so.

Reply to  Javier
September 15, 2016 1:11 pm

In the last five lows of the 2400-yr cycle there has been a very strong climatic effect
as shown [NOT] here:
http://c3headlines.typepad.com/.a/6a010536b58035970c01b7c7c6a5cb970b-pi

Javier
Reply to  Javier
September 16, 2016 8:20 am

In the last five lows of the 2400-yr cycle there has been a very strong climatic effect
as shown [NOT] here:
http://c3headlines.typepad.com/.a/6a010536b58035970c01b7c7c6a5cb970b-pi

This is some type of joke, right Leif? I mean, you don’t seriously believe that polar ice cores adequately represent Earth’s climatic variability during the Holocene, do you?
For a start Greenland and Antarctic ice cores profoundly disagree with each other regarding Holocene variability. This agrees well with the fact that the poles appear to be doing the opposite of each other during the modern warm period.
http://static.skepticalscience.com/pics/Bond-events2.png
The Holocene has quite a few significant cooling events between the Pre-Boreal Oscillation and the LIA. They are very well known to paleoclimatologists and registered in proxies and glacier advances all over the world.

Lenny
September 13, 2016 6:46 pm

Willis thanks again for your work.
I’m in the same camp as the logic behind the sun did it is so compelling, it is doubles its energy output we cook, if it halves it energy output we freeze.
But the energy passes through essentially a low band filter, in the oceans, that I personally think obscure / filter out the relationships. As a consequence, I do not think you will see any direct correlation between the sun and climate temps.
I’m starting to see the logic behind Salvatore Del Prete position around multiple points of influence over a longer time period.
The need to have the large amount of energy change over a period of time to essentially get beyond the system noise.
The more I read, the less I realize I know. – L

kevin kilty
September 13, 2016 7:08 pm

““if a self-tutored man like myself knows about the Bonferroni correction and the need to adjust for autocorrelation … what’s up with these PhD folks all across the climate landscape who apparently never heard of those concepts?”
It would take several courses in statistics to gain real proficiency, but most advanced degrees do not require even one statistics course, even though many accept statistics as an elective. Where I work the Statistics Department offers a course to new graduate students and newly hired science faculty. I have no idea why the Statistics Department offers this course, but maybe they saw it filled a need.

September 13, 2016 10:34 pm

Willis
Does your requirement for Bonferroni correction assume that climate data at different places on the earth’s surface are independent of eachother?
This would make it an unduly stringent requirement since there is no such independence.
Thus spatial autocorrelation could undermine your Bonferroni argument.

Reply to  Willis Eschenbach
September 15, 2016 8:23 am

Here’s a problem with the Bonferroni correction in settings of multiple tests with low power. Say the tests (which may be in multiple studies) have 10% power at the nominal 5% alpha level. You only expect one study out of every 10 to produce a statistically significant result, p = 0.03, say, with R^2 about 4%. The Bonferroni correction requires the nominal p-value to be 0.005 for an overall significance level of 0.05, so your p = 0.03 is not statistically significant. It continues with 2 results out of 20 at p=0.03 or so, 3 out of 30, and so on. Even though you get the expected result, Bonferroni corrections essentially reduce the power of the sequence of studies to 0.
It is about the same if power is 25%. Then you expect about 1 out of 4 tests to be statistically significant at a nominal level of 5%; a p-value of a single study say p=0.03, is compared to a Bonferroni-corrected 0.05/4 = 0.0125.
If this is the case with solar effects on climate, many low power studies pursuing effects that have R^2 = 0.04 or less, then the Bonferroni corrections prevent any set of expected results (expected under the alternate hypothesis) from confirming the alternate hypothesis. Something better is needed. In laboratory research you can arrange conditions to increase the statistical power of studies. With purely observational research, that is not possible.
What to do? Right now, I think the best approach is the empirical Bayes approach of Prof Bradley Efron of Stanford, who has used the approach in genome-wide association studies. Best single reference is probably his book “Large Scale Inference”, published by the Institute of Mathematical Statistics, 260 pp. But he has papers in journals: Annals of Applied Statistics, Annals of Statistics, Journal of the American Statistical Association. As applied to solar effects on climate, many more studies are required before the method can be used.
If the null hypotheses are really true, then about 5% of tests will produce apparently statistically significant results, if not Bonferroni-corrected. The Bonferroni correction reduces that to 0, the appropriate thing to do if in fact all the null hypotheses are true. Whatever you might think you believe, if you are using the Bonferroni correction you are placing a strong bet that there are no small effects. That might not be the best thing to do if there are small effects with significant consequences on large time or space scales — say something that might over a century raise the global mean temperature about 1C.

Reply to  matthewrmarler
September 15, 2016 8:34 am

something that might over a century raise the global mean temperature about 1C.
As the Earth is open to space, it also radiates away the solar input. If the temperature goes up, the Earth radiates even more.

kim
Reply to  Willis Eschenbach
September 15, 2016 8:38 am

Meh, matt shows a possible bias to understanding.
======

Reply to  Willis Eschenbach
September 15, 2016 12:43 pm

lsvalgaard: If the temperature goes up, the Earth radiates even more.
A complementary theory to that one is that the temperature has to increase before the outbound radiation can increase, pretty much in accordance with the Stefan-Boltzmann law.
Also, there are claims that the Earth mean temperature has in fact increased about 1 C over the past century or so. Something might have caused it. If the lukewarm position with regard to CO2 is correct, as asserted for example by ristvan, might the cause have been an increase in solar output of some kind? To me, each attempted explanation is full of holes (Willis Eschenbach has gone good work exposing holes in the solar case, as here), so I consider the cause unknown.

Reply to  matthewrmarler
September 15, 2016 1:02 pm

A complementary theory to that one is that the temperature has to increase before the outbound radiation can increase
I think that is what I just said.

Reply to  Willis Eschenbach
September 15, 2016 9:08 pm

Willis Eschenbach: I also don’t understand why you’d ever use a test with a 10% hit rate as you describe. This means it has a 90% false alarm rate …
Low power at a 5% (or other given) significance level does not imply a high false alarm rate. It only implies a low power, and a 90% false negative rate. “you’d use a test with a 10% hit rate” probably because of not considering power in the first place, and then working with the data as have been collected. When you reanalyze someone else’s data, as you and the Chinese here, you are using a test with a low power.
We’re not doing that here. We’re just measuring correlation and deciding if it is significant.
Your analysis and decision of whether it is significant is a procedure with low power against weak alternative hypotheses (e.g. R^2 = 0.04). If you then perform the Bonferroni correction, you reduce the power to 0, as I wrote.
Is there some reason why you think your procedure has high power (> 0.25, for example) against reasonable alternative hypotheses?
This is why I call it “limbo”: the statistical methods available to us now do not lend confidence to any conclusions. “Rejecting the null hypothesis” without considering the multiplicity of tests is not very good evidence that the null hypothesis is false; accepting the null hypothesis with a procedure (data collection plus analysis) that has low power is not very good evidence that the null hypothesis is true.

Reply to  Willis Eschenbach
September 16, 2016 8:24 am

Willis Eschenbach: I’m not understanding your definition of “power” and “low power”.
That might be true. The power of the procedure (data collection plus analysis) is the probability of rejecting the null hypothesis (at the given alpha level) if the alternative hypothesis is true.
If in this case the alternative hypothesis is true, the Chinese authors have a lucky hit from using a test with an inflated alpha, and the Bonferroni correction turns that into a false negative.
If in this case the alternative hypothesis is false, the Chinese authors have a false positive, and the Bonferroni correction turns that into a true negative.
If, as a Bayesian, one had prior probabilities on H0 and Ha, this evidence would produce posterior probabilities nearly equal to the priors. I only do Bayesian inference when there is good evidence supporting the prior probabilities, and in this case there isn’t any such evidence.
In medical terminology, the posterior probability that the diagnosis is true, given that a condition (e.g. cancer) is judged present is called the “positive predictive power” (PPV) of the test. The posterior probability that the diagnosis is true given that the condition (e.g. cancer) is judged absent is called the “negative predictive power” (NPV) of the test. In your phrase “hits divided by hits plus false alarms” you might be referring to the positive predictive power. In the famous case of breast cancer screening, the procedure has a low PPV in women under 40 because the actual (and well estimated) base rate of the disease, taken as the “prior”, is very low — and they have large counts of actual true and false positives.
In this case, I think it is undecidable whether H0 or Ha be true.

Reply to  Willis Eschenbach
September 16, 2016 8:34 pm

Willis Eschenbach: I still don’t understand why you think the Bonferroni correction “reduce[s] the power to 0”. All it means is that the more places you look, the more unusual a result must be in order to be considered statistically significant.
If you are studying a lot of phenomena with small effect sizes, say relationships with small R^2 value, and if your tests have low power at the given alpha level, then the obtained p-values will never be small enough to be statistically significant after the Bonferroni corrections, even when the relationships are there.
The tests have low power because the effects are small and the time series are not long. So if there are a lot of solar effects awaiting discovery, say things like a rainfall pattern in the Indian Ocean that is somewhat responsive to changes in the intensity of a particular band of UV light, those relationships will never be revealed by Bonferroni-corrected null hypothesis testing. The problem is analogous to looking for quantitative trait loci in genome-wide association studies, where it is known a priori that most genes are unrelated to the trait at issue, and each gene that is related has a weak effect — say genes related to clinical depression, resistance to pneumonia, obesity, or type 2 diabetes.
I realize I am repetitive: lots of hypotheses, low power tests, weak effects and relationships.

Reply to  ptolemy2
September 15, 2016 8:47 pm

lsvalgaard:
I think that is what I just said.

oh, sorry. I read an implication that wasn’t there.

September 14, 2016 5:39 am

The thought that if extreme solar conditions prevail long enough in duration will result in a global cool down are supported through the historical climatic record .
I think as we move forward the global temperature response will be down if prolonged minimum solar conditions meet my criteria.
Thus far I see no arguments or data to suggest my thoughts may be wrong.

Chuck Bradley
September 14, 2016 9:46 pm

We have been asked to quote the exact words we disagree with. Here is the quoted summary.
“And as a result, as an honest man I have to say that despite looking for something that I started out truly and completely believing existed, and despite examining a long string of solar-related studies, to date I have not found convincing evidence of such a connection between the ~11-year solar cycles and the climate here at the surface where we live. Now, if the facts change I’ll change my mind, but as it stands I haven’t yet found the requisite evidence.”
I disagree with the many comments that claim Willis denies any connection between sun changes and climate changes. Read the quote. He does not find any strong evidence for any of the claimed connections. Reading between the lines, I might conclude he is starting to doubt that any evidence will be found, or perhaps that he is confident no such evidence will ever be found. But that would be my imagination or fantasy, not his words or claim.

kim
Reply to  Willis Eschenbach
September 15, 2016 7:19 am

I’m counting on your marvelous curiosity, willis. The Feynman Nile/aurorae correlation is perhaps the main reason I cling so bitterly to the idea that the sun has a climate connection on shorter than Milankovitch time scales. See what you can do with it; I’m genuinely curious, and await your analysis with eagerness.
It’s been a long time, and I can’t be sure, but I vaguely remember Leif dismissing the study with something like ‘correlation is not causation’. Please correct me if I’m wrong, Leif.
===========

kim
Reply to  Willis Eschenbach
September 15, 2016 7:39 am

It’s Ruzmaikin, Feynman and Yung in 2006. I found it in 15 seconds searching ‘Joan Feynman NASA JPL Nile aurorae’ on Yahoo.
One critique talks of wiggle matching. I’d forgotten that an 88 and 200 year signal were found.
Go for it.
======

kim
Reply to  Willis Eschenbach
September 15, 2016 10:42 am

Heh, do it for yourself, not for me.
============

kim
Reply to  Willis Eschenbach
September 15, 2016 6:15 pm

Hoohaw, I popped up on that thread with the same study. I would still like to see your analysis of it, but I have no idea how to send you the data.
==================

kim
Reply to  Willis Eschenbach
September 15, 2016 6:27 pm

C’mon, willis, this is your chance to look at something other than the 11 year cycle for a sun climate connection. Leif has pretty much convinced me that looking there is a fool’s errand.
Again, this study suggests a sun climate connection on shorter than Milankovitch time scales. If it’s debunkable, let’s hear it.
===============

kim
Reply to  Willis Eschenbach
September 15, 2016 11:34 pm

You can lead a horse to water but you cannot make it look at the night sky.
==================

kim
Reply to  Willis Eschenbach
September 15, 2016 11:38 pm

Look, I’m not nearly as committed to this study as you seem committed to ignore it. I believe it is a good study, with good data over a long period. I’d hoped you could explain to me why that wasn’t so, but you haven’t. My loss. I wish it weren’t your loss, too.
You are the one with the meta-argument that you’ve looked everywhere for a sun/climate connection but haven’t found it. Your lack of curiosity about this surprises me.
==============

kim
Reply to  Willis Eschenbach
September 16, 2016 12:57 am

I’ve already told you, and you’ve repeated it, that I don’t know how to send you the data. You’ve agreed that the study ‘sounds interesting’ yet you won’t interest yourself in it unless I perform some act that I cannot do.
This is mere petulance and intellectually impoverishing.
==============

kim
Reply to  Willis Eschenbach
September 16, 2016 1:17 am

Thanks, we are getting somewhere now. Willis, I confess that I don’t even know how to find the data, or a link to it.
Now I’ve claimed that I believe that it is good data. How can I do that without looking at it? I think the observations of aurorae and of Nile River levels is reliable enough to render good data.
================

kim
Reply to  Chuck Bradley
September 15, 2016 4:25 pm

Heh, I knew you couldn’t resist a peek at it. Go ahead, blow it up. I’m all ears.
============

September 15, 2016 3:53 am

My claim is the 11 year sunspot so called normal cycle and the climate will not show a relationship because the noise in the climate system obscures the slight solar changes not to mention the variations within the 11 year sunspot cycle from maximum to minimum conditions cancel each other out.
Only when the sun enters extreme prolonged periods of inactivity or activity for that matter are those two issues nullified and hence a solar /climate connection is able to be established. It is no longer obscured.
I have come up with the minimum solar parameters needed in order to accomplish this by looking at the historical climatic record and how it has responded to solar activity. It shows each and every time the sun enters a protracted period of extreme inactivity the response in global temperatures has been down.
That is fact and until data shows otherwise I think the case for a solar/climate relationship is strong.
In addition the sun drives the climate therefore logic follows that any change in solar conditions has to have an effect on the climate to one degree or another. The point is how large is the effect and is it large enough to overcome the noise in the climate system which can obscure small minor solar changes.
The other side is what are the extreme solar changes in regards to degree of magnitude and duration of time needed to change the climate through solar activity changes themselves and associates secondary solar effects?
I am sure every one agrees that if solar changes are extreme enough there would be a point where a solar/climate relationship would be obvious. The question is what does the solar change have to be in order to be extreme enough to show an obvious solar/climate relationship?
Again I have listed the solar parameters which I think satisfy this issue.

Reply to  Salvatore Del Prete
September 15, 2016 7:09 am

The other side is what are the extreme solar changes in regards to degree of magnitude and duration of time needed to change the climate through solar activity changes themselves and associates secondary solar effects?
By definition, ‘extremes’ are rare and thus the effects you advocate will be rare too, and thus not important in the greater scheme of things. E.g. you would not attribute the recent ‘global warming’ to the influence of solar activity.

September 15, 2016 8:58 am

Extremes are rare and this is why solar /climate correlations tend to be obscure over short periods of time.
Example – the sun spends much more of it’s time in a regular 11 year sunspot state in contrast to a Maunder Minimum state but the Maunder Minimum state or to a lesser degree the Dalton state does happen from time to time.
Maybe this time a Dalton type of situation evolves and if it happens I think as in the past the global temperature response will cool off to one degree or another.

William Larson
September 15, 2016 11:18 am

W. E.: “As an erstwhile ham radio operator (H44WE), I’m well aware that the sunspot cycle affects long-range radio transmission (DXing) by messing with the beautifully named “Heaviside Layer” … what I can’t find is any solid evidence of any corresponding 11-year variation down here on the ground where we live. And yes, I do know that Heaviside is someone’s name, but I still think it’s a great name.”
Up up up
Past the Russell Hotel,
Up up up up
To the Heaviside Layer.
–“Cats”

Reply to  William Larson
September 15, 2016 11:23 am
September 16, 2016 5:16 am

Notice the sun was in a regular mode of operation from 1854- 2005.
I maintain when the sun does enter a prolonged solar minimum not only are the sea surface temperatures going to fall but a weak El NINO not La Nina might be superimposed upon the overall lower sea surface temperatures. It is speculation on my part. I am thinking it would be tied to weaker atmospheric circulation changes.

Javier
September 16, 2016 8:43 am

How do they dare publishing things like this in Nature Communications, where they defend that the Sun has a role in climate change? Outrageous.
Ersek, Vasile, et al. “Holocene winter climate variability in mid-latitude western North America.” Nature communications 3 (2012): 1219.
“Water resources in western North America depend on winter precipitation, yet our knowledge of its sensitivity to climate change remains limited. Similarly, understanding the potential for future loss of winter snow pack requires a longer perspective on natural climate variability. Here we use stable isotopes from a speleothem in southwestern Oregon to reconstruct winter climate change for much of the past 13,000 years. We find that on millennial time scales there were abrupt transitions between warm-dry and cold-wet regimes. Temperature and precipitation changes on multi-decadal to century timescales are consistent with ocean-atmosphere interactions that arise from mechanisms similar to the Pacific Decadal Oscillation. Extreme cold-wet and warm-dry events that punctuated the Holocene appear to be sensitive to solar forcing, possibly through the influence of the equatorial Pacific on the winter storm tracks reaching the US Pacific Northwest region.”
http://www.nature.com/article-assets/npg/ncomms/journal/v3/n11/images_hires/w926/ncomms2222-f4.jpg
(a) Detrended δ18O time series at OCNM [Oregon Cave National Monument] smoothed at 50-year resolution. (b) OCNM δ13C record smoothed at 50 years, with particularly pronounced negative excursions in the δ13C record identified as events a–h. Black diamonds below the δ13C time series represent the U-Th ages and associated 2σ uncertainties. (c) Estimated 14C production rate. (d) Estimated 10Be flux in a Greenland ice core. Both nuclide time series (c,d), inferred to reflect total solar irradiance, were filtered to remove periods >1,800 years and subdecadal noise, then interpolated at 50-year resolution.
Oh Gosh, it turns out the Sun’s variability does seem to have an effect on climate variability.

Reply to  Javier
September 16, 2016 9:21 am

Both nuclide time series (c,d), inferred to reflect total solar irradiance, were filtered to remove periods gt 1,800 years and subdecadal noise, then interpolated at 50-year resolution.
A good example of data torture. The actual data [with 5 year resolution] is very spiky [of short duration] and does not support the ponderous ‘cycles’ claimed. And some [perhaps most] of the variation is due to climate variation in the first place:
http://www.leif.org/research/10Be-Filtered-Raw.png

Javier
Reply to  lsvalgaard
September 16, 2016 10:51 am

And some [perhaps most] of the variation is due to climate variation in the first place

You keep saying this despite the evidence not supporting your belief.
http://i1039.photobucket.com/albums/a475/Knownuthing/Stuiver14CSSN_zps5s8epeni.png
From: Stuiver, Minze, and Paul D. Quay. “Changes in atmospheric carbon-14 attributed to a variable sun.” Science 207.4426 (1980): 11-19.
http://i1039.photobucket.com/albums/a475/Knownuthing/Goslar14CSSN_zpsskwzxv52.png
From: Goslar, Tomasz. “14C as an indicator of solar variability.” PAGES News 11.2/3 (2003): 12-14.
Do you have any published evidence that indicates that 14C is not an indicator of solar variability but mainly an indicator of climate variability? If not you should stop bringing up unsupported beliefs. People here might think that you being a well respected solar scientist your opinion on carbon-14 not being an indicator of solar variability is shared within the scientific community.

Reply to  Javier
September 16, 2016 10:59 am

carbon-14 not being an indicator of solar variability is shared within the scientific community.
You are overplaying your hand. 14C and 10B are indicators of solar variability, except that both records are contaminated by climate influence, especially for the minima values. This is also generally accepted by the ‘scientific community’ or rather by workers in the field of cosmic ray research.

Gabro
Reply to  lsvalgaard
September 16, 2016 11:02 am

Great effort has gone into calibrating C14 years with calendar years. IMO at least this isotope is well understood.

Reply to  Gabro
September 16, 2016 11:23 am

Indeed, but that does not resolve the problem of the cause of the variations of the record. Some of it is solar, and come of it is climate controlled.

Reply to  Gabro
September 16, 2016 11:26 am

A third [and much larger] cause of the observed variation is due to the varying strength of the Earth’s magnetic field. And the variation of that also has uncertainty [which grows when going back in time].

Javier
Reply to  lsvalgaard
September 16, 2016 11:48 am

both records are contaminated by climate influence, especially for the minima values. This is also generally accepted by the ‘scientific community’ or rather by workers in the field of cosmic ray research.

So you can’t produce any evidence of what you say and there is no quantification of the climate contamination effect of the 14C records. Yet the evidence from the overlapping period 1640-1950 (three hundred years) shows no significant climate contamination during the Maunder minimum. So we should trust your word over the evidence and a long publication record, that 14C data is not to be trusted.

Reply to  Javier
September 16, 2016 12:08 pm

I have already [several times] referred you to the literature on this. I’m sure you can google the problem and find these back. Try Berggren, Webber, Higbie, and others. One quantification is that half of the values for the minima in “are as large as or larger than the production changes themselves, are occurring. These influences could be climatic or instrumentally based.”
“Indeed this implies that more than 50% the 10Be flux increase around, e.g., 1700 A.D., 1810 A.D. and 1895 A.D. is due to non-production related increases!”
As the 14C data largely agree with the 10Be data [as shown in your own Figure in a recent comment] it would seem that we have similar problems with the 14C record. Now, you are welcome to ignore the uncertainties and indications as would be the usual reaction of people wedding to some view. But ignoring the problem does not make it go away.

Javier
Reply to  lsvalgaard
September 16, 2016 2:11 pm

I have already [several times] referred you to the literature on this.

No, not me. You did linked once in an answer to one of my comments to an unpublished article by Webber on the unreliability of 10Be archived in arXiv, but that is a double no: not published and not on 14C. Nevertheless I downloaded it and read it.

Now, you are welcome to ignore the uncertainties and indications as would be the usual reaction of people wedding to some view.

You tend to think the worst of people, right? I want my data and my conclusions to be as solid as possible. Despite the Webber article being unpublished I decided not to trust 10Be alone and only use 14C and combinations of both (Steinhilber 2012 method). And I have redone several of my figures. If I ask is because I am genuinely interested. I do think that you are exaggerating and that 14C can essentially be trusted, and that over 90% of the grand solar minima indicated by the 14C record are real. We have seen 3 grand solar minima in the last 1000 years, so it seems reasonable that grand solar minima are a millennial feature of the Sun.
And for the record I believed that the Sun had little relation with climate variability for a long time in part due to your comments. But then I checked the data myself and changed my view. I am not espoused to any particular view, but to what the evidence shows.

Reply to  Javier
September 16, 2016 2:38 pm

I do think that you are exaggerating and that 14C can essentially be trusted
I tend to be more skeptical of that and to have a higher bar for what to trust. This is partly because I know how the ‘sausage is made’. Not pretty. Here is recent paper But it is not my aim to convince anybody who is convinced otherwise. Only to say why I hold the view I have. This is take it or leave it thing.
You may want to read: http://www.leif.org/EOS/14C-Model-Calibration.pdf
showing how the recycling of CO2 [and hence 14C] through the ocean circulation, ice conditions, and wind pattern affects the modeled 14C production.

Javier
Reply to  lsvalgaard
September 16, 2016 5:04 pm

Here is recent paper But it is not my aim to convince anybody who is convinced otherwise. Only to say why I hold the view I have. This is take it or leave it thing.
You may want to read: http://www.leif.org/EOS/14C-Model-Calibration.pdf
showing how the recycling of CO2 [and hence 14C] through the ocean circulation, ice conditions, and wind pattern affects the modeled 14C production.

Thank you for the reference, but of course that refers to the Younger Dryas. Everybody knows that changes in CO2 levels affect 14C levels, obviously. But changes in CO2 levels are much smaller once you reach the Holocene. That’s why solar variability reconstructions only go 11,000 years back. You are pretty safe as long as you keep within the Holocene because according to ice cores, CO2 has only changed between 258-282 ppm within the pre-industrial Holocene, that is a 10% variation. More importantly the centennial wiggles in CO2 are at most a fifth of that, again according to ice cores. The biggest drop was from 282 to 275 ppm during the LIA, that is only a 2.5% change in CO2 levels. That is taken into account in the carbon models for solar reconstructions, but even if it wasn’t, a change of 2.5% is not going to change a grand solar minimum much.
I like the last phrase in the abstract:

The rapid ∆14Catm rise at the YD onset documented in the marine record, however, remains unexplained.

12,800 years before present, the YD onset, coincides with a minimum in the ~ 2400 year cycle.
12800 / 10250 / 7800 / 5350 / 2900 / 450 (LIA)
That is as good an explanation as any.