Guest Post by Willis Eschenbach
Dr. Nir Shaviv has kindly replied in the comments to my previous post. There, he says:
Nir Shaviv August 15, 2015 at 2:51 pm
There is very little truth about any of the points raised by Eschenbach in this article. In particular, his analysis excludes the fact that the ocean has a large heat capacity such that one expects the sea level change rate to vary in sync with the solar forcing (which it does) and not the sea level itself. This basic physics mistake is the reason he finds no correlation. If you’re interested in reading more, I tried to address his main mistakes in: http://www.sciencebits.com/reply-eschenbach
I will not answer any comments on this page, since after Eschenbach expressed his derogatory remarks I see no point.
Also, since I am traveling, I will have little time to answer comments on my blog, but I will try.
At the referenced blog page, he summarizes his arguments as follows:
Let me summarize Eschenbach’s mistakes. Some are trivially wrong, some much worse.
• Eschenbach assumed in his analysis that if the sun has a strong solar forcing, the sea level should be in phase with it. This is plain wrong. Because of the high heat capacity of the ocean system, one roughly expects the sea level change rate (and not the sea level itself) to be proportional to the solar forcing. If one looks at the slope of the sea level, it does indeed correlate nicely with solar activity.
• Given that we explained how and why we carried out the fit using a harmonic analysis, we did not deceive anyone. Writing that we did is libelous.
• The reason we used a harmonic analysis is because it makes the analysis more transparent. If one uses a solar forcing proxy (such as the cosmic ray flux), one finds a similar fit. Namely, writing that by using actual solar proxies one obtains a bad fit is simply wrong. (Again, one has to remember the heat capacity of the oceans!)
• The model has 6 and not 7 parameters. Having all of them is necessary to compare the sea level to the physical model. To ridicule us that we used many parameters is totally irrelevant and inappropriate.
• Eschenbach wrote that I haven’t heard of von Neumann’s Elephant quote. I did many years ago, and even mentioned it in a 2007 blog post on my blog. Trivially wrong, but reflects the low standards of that article.
Dr. Shaviv, thanks for your comments, and for listing your objections in such a concise manner. I will address them one at a time below, after first clarifying my main objection to your work.
My Main Objection To The Study
I wrote my previous post because I was blown away when I found out that your “solar” study has no solar data at all in it. As a result, I said that calling it a solar analysis was “deceptive”. I apologize for that without reservation, it was an incorrect claim. I forgot a very important distinction—the fact that I felt deceived doesn’t make you deceptive.
I should have said that your analysis was misleading. This is much more accurate, as it describes the effect of the analysis and not the authors’ intentions. To show that this is not an empty apology, I have gone back to my original post and removed all references to deception.
Now, I understand you don’t like me saying that your study is highly misleading. But given that there is no data of any kind regarding the sun in your study, why do you call it a study of the sun? How is that NOT a mis-statement of the facts?
Here is a precis of the section of your study describing the data used:
2. Data Sets Used
The altimetry data set used is derived from the TOPEX/Poseidon and Jason altimeter missions with the seasonal signals removed [Nerem et al., 2010] (data electronically available at http://sealevel.colorado.edu/). The data we use have the inverse barometer and glacial isostatic adjustment corrections applied, and it covers the time period between mid-1993 to early 2013. … (more etc. re sea level data)
For the El Nino–Southern Oscillation we use the NINO3.4 index [Trenberth,1997], which is based on the sea surface temperature in the middle of the Pacific (bounded by 120◦W, 170◦W, 5◦S, and 5◦N). Because this index is directly related to the oceanic temperature while the Southern Oscillation Index depends on atmospheric pressures, we expect the former to have less variations and to more directly reflect the ocean heat content … (more etc. re ENSO data)
… the end of section 2 …
I read that and I got to the end and I thought “That’s the end? … That’s it for the data sets? Where’s the solar data?”
According to Section 2, we have the sea level dataset and the ENSO dataset. This means your study is indeed about sea level and ENSO. But since it doesn’t contain any solar data, I don’t understand how you can claim it is about the sun. Where is the “solar forcing” data you are referring to in the abstract?
Instead of solar, you’ve just put in a fitted sine wave. You have made no connection of any kind, statistical or otherwise, between this sine wave and the sun. While this converts your study from a ‘sea level as a function of ENSO’ study to a ‘sea level as a function of ENSO plus a fitted sine wave’ study, it doesn’t magically turn it into a solar study. This is particularly true since the sine wave is not related to the actual solar data by anything but a common period.
So I ask again—how can you call this a solar study? You have made no effort to statistically relate the sine wave to the actual solar forcing over the period. What gives you the right to say this is about “The Sun and ENSO”? I can understand the “ENSO” part … but how does the sun ever rise on a study which contains no solar data?
Replies to Dr. Shaviv’s Particular Objections
Having apologized to Dr. Shaviv, and having re-stated my main problem with the study, let me go through Dr. Shaviv’s objections one at a time.
OBJECTION ONE
Eschenbach assumed in his analysis that if the sun has a strong solar forcing, the sea level should be in phase with it. This is plain wrong. Because of the high heat capacity of the ocean system, one roughly expects the sea level change rate (and not the sea level itself) to be proportional to the solar forcing. If one looks at the slope of the sea level, it does indeed correlate nicely with solar activity.
Dr. Shaviv, looking at the change rate rather than at the sea level height is indeed what I started out believing you had done. And from an initial examination of your model formula, at first it appeared to me that you had done exactly that, viz:
I looked at that, and I thought, this looks fine. In your Equation (1), t is time in fractional years. In the text above it says that “h is the sea level height”, which means of course that ∆h is not the sea level height, but the change in sea level height discussed in your Objection 1. That is the usual meaning of the delta (∆) in the ∆h. It means the change in something. In the case of Equation (1) the delta in ∆h means the change in the sea level height h. So your formula said the change in sea level height ∆h(t) was a function of the values at time t of a sine wave plus ENSO plus the integral of ENSO plus a trend. So far, so good.
But then I tried to implement your formula, and after much confusion and head scratching I realized that no, in your notation, for some unknown reason ∆h is NOT the change in the sea level height h. Instead, you are using the notation ∆h for the sea height itself! Most peculiar.
I verified this oddity in a couple of ways. First, the fitted variable h1 in Equation (1) is the size of the annual trend in the model results. In your study you give a list of the fitted parameters which includes:
Table 1. The Model Fit Parameters
Parameter Value
h1 3.29 ± 0.04 mm/yr
But 3.29 mm/year is absolutely not the trend in ∆h, the rate of sea level change. That is the trend in h, the sea level height itself.
Next, consider. If ∆h(t) in Equation 1 actually does represent change in sea level, and the change in sea level is increasing by 3.3 mm per year as the parameter h1 shows, twenty years after the start of the record the sea level would be rising by a six centimetres (about 2.5 inches) per year … not happening.
As a final piece of evidence that for unknown reasons you are incorrectly using ∆h for sea level height, look at Figure 1 from your study. It shows the detrended and smoothed sea level height h from the University of Colorado, and I have duplicated that result to verify that it is indeed correct … but then look at the label on the vertical “Y” axis:
You show the linearly detrended sea height h by means of the blue dots, but you have labeled it “∆h” on the Y-axis. You have also incorrectly referred to the sea height h in the caption as ∆h. Clearly this is not just a typo, it is an ongoing misunderstanding.
So in fact, despite telling me that I screwed up by comparing solar forcing to sea level height h instead of comparing it to what you call the “sea level change rate”, which is ∆h … that is exactly what you did in your analysis.
As a result, when you say that “It is quite upsetting that Eschenbach did this mistake even though it was clearly explained in our paper”, I’m sorry, but although you are correct that it was clearly explained in your paper, that’s not what you did in your paper. Look at your equation 1. You are not calculating the change in height ∆h as you think, not with a trend of 3mm per year—you are calculating the sea height h itself. In other words, you did precisely what you accuse me of doing.
Now, I discovered this while replicating your work in the course of researching for my previous post. As a result, I was left in a quandary regarding how to handle this additional and very separate issue. I didn’t want to get into all of these h versus ∆h questions in my previous post. I like my posts to have a fairly narrow focus, and just mentioning this ∆h problem would have sidetracked or entirely derailed my main point, which was that your paper has nothing to do with the sun.
So after thinking it over, I took another tack. I decided to compare the solar forcing, not against ∆h as you said you’d done, but directly against the sea height h, just as you had actually done in your model. I figured that if it went by without comment, no harm, no foul … and if someone complained about my not using ∆h, I could give the explanation I just gave.
What I didn’t expect was that you’d be the one to bust me for it, but that’s OK. It just makes the issue clearer.
OBJECTION TWO
Given that we explained how and why we carried out the fit using a harmonic analysis, we did not deceive anyone. Writing that we did is libelous.
I have withdrawn the term “deceptive” entirely. However, from reading the comments on your paper at blogs like Tallbloke’s Talkshop, it seems there were many people who were misled by your work. Neither the commenters nor Tallbloke himself noticed that your paper had no solar data of any kind.
And I was certainly misled. Based on the title and the comments I’d seen on Tallbloke’s blog, I went into this expecting a study about solar forcing. Imagine my surprise when halfway through I realized I’d gotten a paper about sine waves with no solar in sight.
I started as usual by reading the title, all about solar effects on the sea level. I read the abstract, all about solar and solar cycles. Not a word about harmonic analysis. According to the abstract it was as the title said, a study of solar and ENSO components of sea level. Looked good.
So I read the introduction, more about the sun and its effects, about solar cycles and solar forcing. And again, nothing about sine waves, it was all solar, solar, solar. Onwards.
Everything was going swimmingly, until I got to the end of Section 2, Data Sets Used. I got to the end of that section and I though “Huh? What solar dataset did they use?” I thought I’d missed something so I re-read Section 2 … still nothing about solar.
Now as you point out, you did say in the later sections of the paper that “The above empirical fit assumed a harmonic solar forcing.” But you described the sine wave as a “harmonic solar component”, which it is not unless you can show it is, and you haven’t done that. You call it “harmonic solar forcing”, but there is no solar, it is 100% harmonic. You titled your paper as being about “The solar and Southern Oscillation components in the satellite altimetry data”, but there is nothing remotely solar about it. Let me repeat my example from my last post:
Suppose I’m studying the effect of gamma rays on marigold growth. And unfortunately for my lovely hypothesis, the gamma ray data is poorly correlated with the marigold growth data.
But an inspiration hits me. I notice a sine wave can be fitted to the marigold growth data quite well, and the sine wave kinda sorta looks like my gamma ray data, and even better, using the sine wave allows me to “significantly simplify the analysis” … sound familiar? It should, that is your justification for using a sine wave in place of the real solar data.
So I set aside all of my gamma ray data, and I just use the fitted sine wave in my computations. Here are the questions about my analysis of marigold growth.
Given that there is no gamma ray data of any kind in my study, and given that I have made no statistical or other connection between the sine wave and the gamma ray data, am I justified in calling the sine wave a “harmonic gamma ray component”?
Can I validly call the cycle of the sine wave the “gamma ray cycle”?
Is it legit to discuss “gamma ray forcing” without gamma ray data?
Can I title my sine-wave paper “The gamma ray components in the growth of marigolds” given the total absence of a single gamma-ray observation in the entire paper?
Or on the other hand: given that my paper has no gamma ray data of any kind in it and I have made no connection between the sine wave and the gamma rays, are all of those claims about gamma rays misleading?
I call those actions highly misleading. Their effect is to convince the reader that the sine wave data is gamma ray data. I say when someone leaves out every bit of gamma ray data in their analysis and then puts “gamma ray” in the title of their analysis, and calls a bog-simple sine wave a “harmonic gamma ray component” and talks knowingly of “gamma ray cycles” and “gamma ray forcing”, their analysis misleadingly describes a sine wave analysis as a gamma ray analysis, no matter what explanation they put into their small print.
Yes, as you say, it may well “significantly simplify the analysis”. And yes, as you explained in your objection, you “carried out the fit using a harmonic analysis”. That is 100% true. You did do a harmonic analysis.
But that is all it is, a HARMONIC analysis. It is not a “solar” analysis of any kind. The components are harmonic components, not “harmonic solar components” as you claim. You have made no connection at all between the sun and the sine. The cycles are harmonic cycles, not “solar cycles” as you assert. The calculated forcing, if it exists at all, is harmonic forcing, not “solar forcing”.
And the study is actually about “The harmonic and Southern Oscillation components in the satellite altimetry data”, not about the solar components as your actual title incorrectly states.
So no, Dr. Shaviv, it is far from enough to claim in the small print as you did that you are using “harmonic solar forcing”. It is harmonic forcing, pure and simple, nothing solar about it.
When your title and your abstract both claim the study is about the sun and solar forcing and solar cycles, a statement halfway through the study that your solar component is actually “harmonic solar forcing” just muddies the waters. Your study is no more about the sun and solar forcing and solar cycles than my analysis above with no gamma ray data is about gamma rays and gamma ray forcing and gamma ray cycles …
OBJECTION THREE
The reason we used a harmonic analysis is because it makes the analysis more transparent. If one uses a solar forcing proxy (such as the cosmic ray flux), one finds a similar fit. Namely, writing that by using actual solar proxies one obtains a bad fit is simply wrong. (Again, one has to remember the heat capacity of the oceans!)
I’m sure using a sine wave simplifies the computations, and makes the analysis more transparent. My issue is that it also makes the analysis an “ENSO and sine wave” analysis, not an “ENSO and sun” analysis as you seem to think.
And yes, I suspect you can get a “similar fit” with sunspots, or with any of a dozen other datasets, whether solar datasets or any of a number of kinds. That’s the beauty of fitting cycles with lots of tuned parameters as you are doing. You can get a “similar fit” lots of ways, particularly since “similar fit” doesn’t mean “better fit”. For example, I can show a “similar fit” between historical 20th century sea levels and the cost of US postage stamps. But that doesn’t turn a harmonic analysis into a postage stamp analysis.
And I do remember the heat capacity of the oceans. See my reply to Objection One above …
OBJECTION FOUR
The model has 6 and not 7 parameters. Having all of them is necessary to compare the sea level to the physical model. To ridicule us that we used many parameters is totally irrelevant and inappropriate.
Six or seven, either is too many. Consider: exactly your same argument might have been made by Freeman Dyson to Fermi, and he had only four parameters. The four parameters were certainly “necessary” to Dyson’s model, just like the six parameters are assuredly “necessary” to your model … so what? It’s still a six-parameter fitted model. And not just any fitted model. It is a sine-wave-containing model fitted to a dataset that is not even two full sine-wave cycles in length. If you couldn’t fit the sea level under those conditions, I’d be shocked.
I’d be especially shocked if you couldn’t get a good match because contrary to good modeling practice you have included outcome information among your independent variables in the form of ENSO. Let me explain exactly how this has happened.
The ENSO measure you’ve used is the temperature of a large expanse of the Pacific Ocean. Because water expands at a known rate as it warms, ocean temperature can be used to calculate ocean height, and vice versa. We know the expansion coefficient of sea water, so if the ocean is heated by a certain amount, to calculate the resulting thermal change in sea level height ∆h we simply multiply the change in temperature by the coefficient of expansion. And of course, the reverse is true—if the sea level height goes up because of temperature, we can calculate the corresponding change in temperature necessary to produce that rise in sea level by dividing the sea level change by the coefficient of expansion.
The important point to note is that change in global ocean temperature is calculable as a function of change in sea level. Now, let’s see what this means in terms of ENSO.
If we divide the areas of the ocean into areas A1 … An with temperatures T1 … Tn, we can state the temperature/sea level relationship as h ≈ Coef.of.Expansion * mean(T1, T2, T3, T4 … Tn). In English, the global sea level is a function inter alia of the average ocean temperature.
Now, you’ve taken the temperature of a part of the ocean, the ENSO3.4 area. Let’s call that temperature T1. You’ve fitted T1 as a global ocean temperature proxy to the sea height h, and subtracted out the fitted values.
Now, lets imagine that instead of just using the temperature of the ENSO 3.4 area T1, you also use the temperatures of three other areas T2, T3, and T4 … since you now have more data about the ocean temperature, your estimate of the global ocean temperature will be more accurate, and as a result your calculated value of the sea level height h will be better as well.
But how can this be, that your model gets more and more accurate? Take it to the logical conclusion. If you included the temperature of every ocean area T1 to Tn as part of your “independent” variables, you’d be able to model the temperature dependent sea height h exactly … but that is only because you are directly including information about the dependent variable “h” in the so-called “independent” variables. So it’s no surprise at all that you can model the sea level so well—you have badly contaminated your sole “independent” variable with outcome information. As noted above, the relationship works both ways, which means that global ocean temperature change is a function of sea level change … which in turn means we can calculate your “independent” variable ENSO as a function of sea level. And that means your “independent” variable is a function of the dependent variable.
And when I say “badly contaminated”, I mean “terminally”. You are using the ENSO information at time t in Equation (1) (identified as S3.4(t)) to calculate the sea level height at time t. But ENSO temperature is composed entirely of outcome information, that is to say the ENSO information is a function of and can be calculated from the sea level data you are trying to model.
The problem is that this information coming from looking at the outcome before calculating your results is meaningless in terms of actual modeling. This is because the only thing that information about the outcome can tell us is that the outcome looks like the outcome … not useful at all. It’s like saying “I can forecast todays average temperature with very good accuracy … as long as I know the temperatures at 3 pm and 3 am” … not impressive, right? It is unimpressive because you are using information about the outcome to predict the outcome. Bad model, no cookies. Same thing with ENSO and sea level.
This means that in your model you have three things:
1. Useless ENSO information which is a function of the outcome to be modeled, but dang, it looks so good.
2. A sine wave with no connection to reality, but which reminds you of the sun, and
3. A linear trend.
Since there is no solar data, and the ENSO temperature is contaminated with outcome information, that leaves your study containing no independent observational variables of any kind …
There is another related problem with your model. When you measure the ENSO 3.4 ocean temperature, that ocean temperature is created, modified, and maintained by the sun. As a result, the ENSO data already contains the solar signal including any possible effects of the tiny ~ 11-year variations. Again, imagine that we know all of the ocean temperatures T1 … Tn. Inter alia, that temperature determines the sea level … and every bit of the solar signal is present in the temperature, including tiny solar variations. This means that when you use the ENSO data to remove part of the signal, you are removing part of the solar signal as well …
Curiously, in your case that doesn’t matter much because as you point out yours is NOT an ENSO/solar analysis, it’s actually an ENSO/sine wave analysis that you are merely calling a solar analysis …
But that in itself makes the analysis strange, because now you have both solar data mixed in with the ENSO data, which is contaminated from snooping the outcome, plus the sine wave data acting as a clumsy proxy for the solar data … messy.
So those are my objections to your model itself. You have used a six-parameter tuned model which takes as input ENSO and a sine wave. You have fit this model to a sea level dataset barely one-and-a-half sine wave cycles in length. Your one “independent” variable is not independent, it is contaminated with outcome information. And you have picked independent variables that are not independent of each other, because the solar signal is present in the ENSO data.
Like I said above about your strange use of ∆h in place of h, I let all of this go without comment in my last post because I was so shocked that you would say your study is about the sun, and I didn’t want to distract people with a bunch of other issues. But since you brought it up … your model fails not just because it is a multi-parameter tuned fit. It fails for those other reasons I just listed.
OBJECTION FIVE
Eschenbach wrote that I haven’t heard of von Neumann’s Elephant quote. I did many years ago, and even mentioned it in a 2007 blog post on my blog. Trivially wrong, but reflects the low standards of that article.
You are correct, Dr. Shaviv, my apologies. What I wrote was:
Have these folks never heard the story of Von Neumann’s elephant? Obviously not … so I attach it for their edification.
My bad. I didn’t even consider the possibility that you could have heard that critical cautionary tale and then gone ahead and designed that model. My apologies, I was wrong to say you hadn’t read it, bad assumptions on my part.
I should have said that if you’d read it, that unfortunately you hadn’t taken it to heart. Freeman Dyson didn’t tell that story just to be passing the time. Model fitting, particularly to a short dataset, is both very easy and very meaningless, as you have just proven once again. Let me repeat the quote from Enrico Fermi regarding how to do calculations, as his words apply directly to your analysis:
One way, and this is the way I prefer, is to have a clear physical picture of the process that you are calculating. The other way is to have a precise and self-consistent mathematical formalism. You have neither.
CONCLUSIONS
Dr. Shaviv, I understand that I upset you by saying that your work was “deceptive”, and I have apologized to you for that. Let me say instead that your work strongly tends to mislead the reader into thinking you are talking about the sun.
I think it is accurate to say that describing a study which contains no gamma ray data as a “gamma ray study” that is using a “harmonic gamma ray component” and “gamma ray cycles” to calculate “gamma ray forcing” is highly misleading. Similarly, I think that entitling a study containing no gamma ray data “The gamma ray and ENSO components of satellite sea levels” is misleading … and they are misleading even if in the small print you hedge your claims by saying you are using “harmonic gamma ray components”.
I also want to emphasize that your model is NOT as you have described it. It is NOT a model that calculates ∆h, the change in sea height as you have claimed. It is a model that directly calculates h, the sea level height … so you’ve busted me very emphatically for doing exactly what you did.
Moving on, you say you don’t want to discuss these matters here on WUWT because you have received “derogatory remarks” … if I followed that curious guideline, I’d never be able to comment on a host of sites, including both your site and this one. On this site, I take “derogatory remarks” that are much worse than being called “deceptive” on a daily basis … so what? I just man up and march on. On your site, you’ve busted me, in a derogatory manner, for doing exactly what you did in your study. Again, so what? That kind of thing happens all the time, and it doesn’t stop me from commenting here, there, or on any of the other web sites where I regularly take many, many more derogatory remarks than you’ve ever gotten from me.
I’ve responded to you here on WUWT, for a couple reasons. Fiirst, you didn’t enable the comments on your reply to my analysis, so neither I nor anyone else can comment there. This means you’ve refused to discuss it here, and you’ve entirely choked off comments there … I’m getting the feeling that WUWT is not actually the problem …
Additionally, I responded here because here both of us can use graphics in the discussion. It’s hard to discuss complex relationships without graphs.
Finally, you close your post by saying:
I should also add another point which is directed primarily to Anthony Watts. The Wattsupwiththat website used to keep very high standards. It also served as a very important outlet where discussions about various climate views, including those which do not conform to the dogmatic mainstream could be heard. However, the low standards borne from Eschenbach’s article, both in science and in style should be avoided. Anthony Watts should not expose himself to libelous type of writing, which is exactly what Eschenbach has done. Writing false statements is one thing, it is Eschenbach’s right for free speech, but writing that my colleagues and have “deceived” as well as other derogatory remarks that intend to tarnish our scientific integrity has no place in any scientific discussion.
Let me say in passing that I enjoy watching how everyone loves WUWT and thinks it is great until it is their own work being discussed … and then they jump up and down and complain how the WUWT standards have slipped from the good old days. Rarely fails. I note that Dr. Shaviv has never to my knowledge complained about the standards of WUWT when other peoples’ work was on the table …
Dr. Shaviv, I have apologized to you for calling you and the other authors “deceptive”. That was uncalled-for. However, people have indeed been misled by your study, a quick cruise around the web is enough to confirm that. In essence, you’ve claimed gamma rays and gamma ray cycles and gamma ray forcing where there is not a single gamma ray to be found. That is misleading.
Do I “intend to tarnish your scientific integrity”? Well, in a single paper you’ve claimed that a harmonic study is a solar study, you’ve included outcome information in your one “independent” variable and thus left yourself with no independent variables in your model, you’ve confused ∆h and h while accusing me of not understanding the difference, and you’ve used enough tunable parameters to make an elephant deliver obscene gestures with his proboscis … and you think I’m the one tarnishing your reputation?
Yes, I could have been nicer and more polite about what I’ve said, wrapped it all up in sugar, used all kinds of waffle words to muffle the impact of what I am saying. But I’ve had it up to here with bogus solar studies. I have tried to look at each one as they are brought to my attention, which I am regularly abused for doing. To date they’ve all been pathetic, all potatoes and no meat. Not as bad as your study, though—for some odd reason, almost every solar study except yours actually uses, you know … solar data … go figure.
So when I saw the title of your study, it sounded quite interesting. However, when I took the trouble to download your study and then to work my way through to the middle, I must confess I lost it when I realized I’d been a sucker, that it was not a solar study in any sense of the word. Instead, in your words, it was merely a “harmonic analysis”.
When I found that out, I fear I lost the plot, I waxed wroth and I said not one but a plethora of bad words. And while I left out the plethoretceteras in writing my post about your analysis, I know that some of my language in my post was still intemperate and unwarranted, and I apologize for that.
My best wishes to you,
w.
A Fervent Plea: misunderstanding is the bane of the web. To reduce misunderstanding, if you disagree with what someone has said, please quote the exact words you disagree with. That way we can all be crystal clear about both who and what you are talking about.
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I agree that instead of just presenting the science and pointing out errors the site tone over time has become more personal and emotional. I enjoy the technical discussion and excellent reference pages. Lets have a reduction in personal attack and keep up the analysis. The warmists have always appealed to emotions and used character assassination, lets avoid that at all costs please.
Please, gentlemen!
To an educated layman, this sounds like a food fight.
But, this discussion does focus attention on the fact that so much of what is called climate research is really mathematical modelling using very noisy data. With sufficient vigor, any set of numbers can be tortured until they give us the answer we want. Non-mathematical types have understood this for a long time.
And, it must be very tempting for people with strong mathematical backgrounds to develop a condescending attitude towards people with an inferior math background. But, remember math nerds, they may seen clueless but look in the mirror occasionally. Being better at math than others doesn’t necessarily mean you know enough math to predict what mother nature will be doing in 10, 50, or 100 years. There is absolutely no record of such a thing ever having been done.
Maybe nobody is clever enough. They observed about Churchill during WW II: “Winston wins all the arguments but loses all the battles.” (For example, Anzio.) That was because battles are not decided by clever arguments by men a long way from the action, but by cruel, unforgiving facts on the ground. I doubt mother nature is any more forgiving.
So have some humility. It is easy to be dismissive of other people, but you can’t out-argue nature.
I started a food fight once. In a restaurant. It was a support group thing made up of parents of difficult (as in very) teenagers. We made a mess but we tipped a massive amount of coinage. Relieved a lot of stress.
I find it interesting that Dr. Shaviv does not actually answer what I view as Eschenbach’s main point, which was that the paper in question DID in fact use a harmonic function, and not solar forcing at all.
Shaviv argues that he linked to a similar study that included solar data, but that is irrelevant to the actual paper under discussion.
Regardless of the “h” versus “delta h” question, if I had read the paper based on the title and the abstract, I would still come away feeling that the authors cheated, and that the paper was not entirely true to its title and abstract.
That was not a “similar study” that was supplementary material that was cut from the final published paper. That makes it part of the same study.
That was not a “similar study” that was supplementary material that was cut from the final published paper. That makes it part of the same study.
What ‘Directory’ was it in?
Right here, 3×2:
http://phys.huji.ac.il/~shaviv/articles/Altimetry-AdditionalModel.pdf
Nir linked to it on his blog.
Anne Ominous: Shaviv argues that he linked to a similar study that included solar data, but that is irrelevant to the actual paper under discussion.
Few papers are published without important parts getting left out. Editors pare everything down to reserve journal space for the papers of other authors. This is especially true of mathematical and statistical details, but not limited to them. More and more, the supplementary online material is available, and integral to the paper.
You can call it the editor’s fault, then, but that has zero bearing on what I wrote. Either the paper as published was about solar forcing, or it wasn’t. If it wasn’t, then the title and abstract are misleading, regardless of whose “fault” that is.
Willis said (in the previous post): “But then, the TSI/sunpots inconveniently peak around 2001 and bottom out around 2008-2009. Meanwhile, sea level peaks at around 2006, about five years after the TSI/sunspots, and doesn’t bottom out until 2011 … no bueno for their lovely theory.”
And now Willis says: “Dr. Shaviv, looking at the change rate rather than at the sea level height is indeed what I started out believing you had done. “
Sorry, Willis, but you are still missing the point. They pointed out that the RATE of change should be related to insolation, ie the SLOPE. You are focusing on the DIFFERENCE from some baseline. In other words d(∆h)/dt should be related to the solar changes.
In fact, you should re-read your own post here: http://wattsupwiththat.com/2012/06/18/time-lags-in-the-climate-system/ . You discuss this exact same idea — that temperatures changes (and hence sea level changes due to temperature changes) will lag well behind the periodic driving force.
There SHOULD be a lag in the sea level rise behind the oscillating solar driving force. So this is muy bueno for their results.
Are you saying that the sea level rise SHOULD exhibit a 11-year pattern? Does it?
I am saying that WILLIS’S OWN ANALYSIS shows an 11 year pattern, with the sea level rise lagging behind the solar forcing, exactly as Dr. Nir Shaviv was saying should happen. Furthermore, Willis has previously demonstrated that he knows why this lag should occur. But in this case, Willis is confusing the ‘anomaly’ with the ‘rate of change of the anomaly’ and misinterpreting that results.
Whether the data is really robust enough to be conclusive is another matter, but the data does generally support the hypothesis.
I saw one post here by Nir Shaviv , and he doesn’t address the main point of contention, – was solar data used in his analysis? Maybe he thinks harmonic analysis is solar data. His figure 1 is sunspot data. Does he use this in his analysis?
Did you entirely miss the part where he pointed to supplementary material that was cut from the published paper where solar data was used?
Maybe I did, did Willis miss it – that is the issue – I have no idea.
Willis linked to the blog post he’s criticizing, didn’t he? Don’t tell me you read Willis’s criticism but not the post he was criticizing?
We can see why a real atmospheric physicists or Freeman Dyson ect would never reply to anything on this site concerning Climate or meteorology or physics ect LOL especially with these Willis/Moshers/ types/fellows. A great apology is owed tp Steven Goddard. Within 2 years time this site will be more anti-warming ect than SG. Lukewarmers will be banished at this rate.LOL
A nice reminder here http://ocean.dmi.dk/arctic/old_icecover.uk.php
“In English, the global sea level is a function inter alia of the average ocean temperature.”
I find it misleading to call that English, when it plainly contains a Latin term.
Steven Mosher, I theorize that you have been beating your wife.
Unless you have a better theory my theory wins.
Nah, we can all make our own judgments. Unless you have evidence, I’m going to assume he doesn’t.
Bill 2,
You just guess at your hypothesis according to Feynman and indirectly with Popper. Evidence of the hypothesis is not necessary per their philosophy of science. They only require theory be in principle falsifiable.
So, this is the weakness of Popper and Feynman philosophy of science.
John
Steve Oregon on August 17, 2015 at 7:00 pm
– – – – – –
Steve Oregon,
Mosher should say to you, “Touché!”.
John
Since I dont have one, you are wrong
Steven Mosher, thanks for sharing the raw data and concisely pointing out the flaw in Steve Oregon’s theory.
I theorize that if you had a wife, you would be beating the hell out of her. Cyclically, your violence would increase by 40% around Super Bowl.
Unless you have a better theory my theory wins. For pragmatic reasons.
Thanks also for your contribution to the theory of science.
Assuming the error bar is plus or minus 1/2 wife and utilizing proxy-wife data from an unarchived file, it appears the wife beating theory still can pass peer review.
I think that makes his point. In politics and law decisions need to be made to satisfy the constituents and litigants. They can’t wait a hundred years for science to finally come up with the correct answer so governments and judiciaries have to go with the best guess. So in that sense Mosher is right. Whoever has the best theory wins, for the time being, in politics and law.
Somehow the scientific community never gets this through their heads, that politics and law really are religious based systems, and religions always have an answer. So whoever seems to come up with the best answer wins.
Howdy Willis.
I have great admiration for you in your willingness, determination and intellect to take on
anything put out there, in which you have an interest, and turn it upside down and sideways to shake it out to the proper, final conclusion. Thanks for doing this for the less mathematically and scientifically inclined of me. More people like you are needed to both shake the trees and see what BS artists are hiding in them and to let the others, who may be considering pulling the wool over peoples eyes, that there are “peers” (or just regular smart folks) out here who are ready and able to catch them in their BS and call them out on it.
Whatever the outcome, sometimes shaking the trees is a really good thing in any institution and should be done on a regular basis. And anyone in the science community who has a problem with being called out to explain themselves probably has a bigger problem with his/her science than with their egos.
Thanks Willis. You’re a PUNK rocker.
Dahlquist
Fascinating drama, but so what?
1) IPCC has no idea how much CO2 between 1750 and 2011 was caused by industrialized man mostly because there are no reliable numbers for natural sources.
2) The 2 W/m^2 RF (W is power, energy over time, not energy per se) of the additional CO2 between 1750 and 2011 and the 4.5, 6.0 and 8.5 W/m^2 RFs of the RCPs are lost in the decimal points with ToA at 340 W/m^2 +/- 10 as well as the uncertainty bands of reflection, absorption by clouds, ground, oceans, albedos, etc. The oceans suck it up and spit it out a hundred times faster that GHGs can make it.
3) As evidenced by the pause/hiatus/lull/whatever and as admitted by IPCC, the IPCC models are useless.
Hey Willis,
Your credibility is already toast! I am not going to waste any more time reading anything you write. Leave science to scientists! 🙂
As a quick question — if clouds reflect sunlight back into space, what effect do clouds have on preventing heat from leaving the earth? Which effect is greater?
There have been a number of posts on clouds trapping heat but i can’t remember any of the conclusions. Clouds trapping heat is sort of a hothead thing, I realize.
Short answer will do.
Eugene WR Gallun
IPCC has the RF of clouds at -20 W/m^2. That’s ten times the cooling of CO2’s heating. And have you noticed how steady state clouds are? (sarc)
A formula for Δh is not a formula for Δh/Δt.
rokshox: A formula for Δh is not a formula for Δh/Δt.
With constant spacing in t there is no important difference: the results differ only by the scaling constant
1/Δt.
In principle you can get slightly more accurate results by modeling a non-parametric estimate of the derivative in place of .Δh/Δt. or Δh, but with a smooth function the improvement would be negligible. When modeling with sines and cosines there would be no measurable improvement at all.
lsvalgaard sunspot number: 32 ?
http://sohowww.nascom.nasa.gov/data/realtime/hmi_igr/1024/latest.html
More like something near 50. There are three groups, that gives you 30, then about 15-25 small spots, for a total of 30+15 to 30+25 or 45 to 55. SILSO has 42, Kanzelhohe has 55. Granted that the spots are tiny so different observers are likely to differ.
Eugene WR Gallun.
The answer to your question which effect of clouds is greater is – it depends. Some factors are;
a) time of day when the clouds were around (daytime clouds reflects some incident light back to space before conversion to longer wavelengths where as night clouds only trap radiation closer to surface)
b) how much cloud cover area there was as a % of the sky is a factor in the equation relating to energy wavelength change at earths surface.
c) what type of clouds they were (depth)
d) what the surface albedo of the ground underneath the clouds normally is.
e) precipitation – if it snows under the clouds that are present this will change the surface albedo and may even persist (or not) when clouds depart.
f) what angle is the sunlight to the earths surface where the cloud is (lattitude on the earths surface) – clouds at the equator would reflect more intense incident energy than clouds at the poles going through more atmosphere before getting to the cloud but would serve equally well as a blanket to trap radiation from the earths surface.
Rising sea levels – that aren’t, melting ice – that isn’t, sad polar bears – actually quite happy, confused walri – just doin’ their thing, and temperature anomalies “adjusted” to appear the hottest ever – when the actuals aren’t – just the warmists yelling to the proles, media and politicians, “See, we told you so!” when what they told us doesn’t have a leg to stand on.
Willis, thank you very much.
This article is very good, not only about language and personal interactions, but about the integrity of science and scientific debate.
Perhaps Dr. Shaviv’s recent reply could get P.S. to the post?
Willis Eschenbach: I should have said that your analysis was misleading. This is much more accurate, as it describes the effect of the analysis and not the authors’ intentions. To show that this is not an empty apology, I have gone back to my original post and removed all references to deception.
I appreciate your apologizing for a mistake, as we all make them and they are no fun in public. However, I did not and do not think that Dr. Shaviv’s paper was “misleading”.
I did. Huge difference between using real solar data and an artificial construct harmonic derived from a 12.6 wholly contrived sinusoidal and then given a solar name in the title.
I have a good theory which is easy to understand ,and is straight forward and easily falsified if wrong.
No spin like all the others have but rather factual solar parameters that will give an x result when taken into consideration with other items which effect the climatic system of the earth.
In addition my theory conforms to the historical climatic record unlike AGW theory which tries to make the historical climatic record conform to it.
My theory is one of the best out there and it is 1000x better then AGW theory.
Here is what I have concluded. My explanation as to how the climate may change conforms to the historical climatic data record which has led me to this type of an explanation. It does not try to make the historical climatic record conform to my explanation. It is in two parts.
PART ONE
HOW THE CLIMATE MAY CHANGE
Below are my thoughts about how the climatic system may work. It starts with interesting observations made by Don Easterbrook. I then reply and ask some intriguing questions at the end which I hope might generate some feedback responses. I then conclude with my own thoughts to the questions I pose.
From Don Easterbrook – Aside from the statistical analyses, there are very serious problems with the Milankovitch theory. For example, (1) as John Mercer pointed out decades ago, the synchronicity of glaciations in both hemispheres is ‘’a fly in the Malankovitch soup,’ (2) glaciations typically end very abruptly, not slowly, (3) the Dansgaard-Oeschger events are so abrupt that they could not possibility be caused by Milankovitch changes (this is why the YD is so significant), and (4) since the magnitude of the Younger Dryas changes were from full non-glacial to full glacial temperatures for 1000+ years and back to full non-glacial temperatures (20+ degrees in a century), it is clear that something other than Milankovitch cycles can cause full Pleistocene glaciations. Until we more clearly understand abrupt climate changes that are simultaneous in both hemispheres we will not understand the cause of glaciations and climate changes.
My explanation:
I agree that the data does give rise to the questions/thoughts Don Easterbrook, presents in the above. That data in turn leads me to believe along with the questions I pose at the end of this article, that a climatic variable force which changes often which is superimposed upon the climate trend has to be at play in the changing climatic scheme of things. The most likely candidate for that climatic variable force that comes to mind is solar variability (because I can think of no other force that can change or reverse in a different trend often enough, and quick enough to account for the historical climatic record,, and can perhaps result in primary and secondary climatic effects (due to solar variability),which I feel are a significant player in glacial/inter-glacial cycles, counter climatic trends when taken into consideration with these factors which are , land/ocean arrangements , mean land elevation ,mean magnetic field strength of the earth(magnetic excursions), the mean state of the climate (average global temperature gradient equator to pole), the initial state of the earth’s climate(how close to interglacial-glacial threshold condition it is/ average global temperature) the state of random terrestrial(violent volcanic eruption, or a random atmospheric circulation/oceanic pattern that feeds upon itself possibly) /extra terrestrial events (super-nova in vicinity of earth or a random impact) along with Milankovitch Cycles.
What I think happens is land /ocean arrangements, mean land elevation, mean magnetic field strength of the earth, the mean state of the climate, the initial state of the climate, and Milankovitch Cycles, keep the climate of the earth moving in a general trend toward either cooling or warming on a very loose cyclic or semi cyclic beat(1470 years or so) but get consistently interrupted by solar variability and the associated primary and secondary effects associated with this solar variability, and on occasion from random terrestrial/extra terrestrial events, which brings about at times counter trends in the climate of the earth within the overall trend. While at other times when the factors I have mentioned setting the gradual background for the climate trend for either cooling or warming, those being land/ocean arrangements, mean land elevation, mean state of the climate, initial state of the climate, Milankovitch Cycles , then drive the climate of the earth gradually into a cooler/warmer trend(unless interrupted by a random terrestrial or extra terrestrial event in which case it would drive the climate to a different state much more rapidly even if the climate initially was far from the glacial /inter-glacial threshold, or whatever general trend it may have been in ) UNTIL it is near that inter- glacial/glacial threshold or climate intersection at which time allows any solar variability and the associated secondary effects, and or other forcing no matter how SLIGHT at that point to be enough to not only promote a counter trend to the climate, but cascade the climate into an abrupt climatic change. The back ground for the abrupt climatic change being in the making all along until the threshold glacial/inter-glacial intersection for the climate is reached ,which then gives rise to the abrupt climatic changes that occur and possibly feed upon themselves while the climate is around that glacial/inter-glacial threshold resulting in dramatic semi cyclic constant swings in the climate from glacial to inter-glacial while factors allow such an occurrence to take place. Which was the case 20000 years ago to 10000 years ago.
The climatic back ground factors (those factors being previously mentioned) driving the climate gradually toward or away from the climate intersection or threshold of glacial versus interglacial. However when the climate is at the intersection the climate gets wild and abrupt, while once away from that intersection the climate is more stable. Although random terrestrial events and extra terrestrial events could be involved some times to account for some of the dramatic swings in the climatic history of the earth( perhaps to the tune of 10% ) at any time , while solar variability and the associated secondary effects are superimposed upon the otherwise gradual climatic trend, resulting in counter climatic trends, no matter where the initial state of the climate is although the further from the glacial/inter-glacial threshold the climate is the less dramatic the overall climatic change should be, all other items being equal.
The climate is chaotic, random, and non linear, but in addition it is never in the same mean state or initial state which gives rise to given forcing to the climatic system always resulting in a different climatic out-come although the semi cyclic nature of the climate can still be derived to a degree amongst all the noise and counter trends within the main trend.
QUESTIONS:
Why is it when ever the climate changes the climate does not stray indefinitely from it’s mean in either a positive or negative direction? Why or rather what ALWAYS brings the climate back toward it’s mean value ? Why does the climate never go in the same direction once it heads in that direction?
Along those lines ,why is it that when the ice sheets expand the higher albedo /lower temperature more ice expansion positive feedback cycle does not keep going on once it is set into motion? What causes it not only to stop but reverse?
Vice Versa why is it when the Paleocene – Eocene Thermal Maximum once set into motion, that being an increase in CO2/higher temperature positive feedback cycle did not feed upon itself? Again it did not only stop but reversed?
My conclusion is the climate system is always in a general gradual trend toward a warmer or cooler climate in a semi cyclic fashion which at times brings the climate system toward thresholds which make it subject to dramatic change with the slightest change of force superimposed upon the general trend and applied to it. While at other times the climate is subject to randomness being brought about from terrestrial /extra terrestrial events which can set up a rapid counter trend within the general slow moving climatic trend.
.
Despite this ,if enough time goes by (much time) the same factors that drive the climate toward a general gradual warming trend or cooling trend will prevail bringing the climate away from glacial/inter-glacial threshold conditions it had once brought the climate toward ending abrupt climatic change periods eventually, or reversing over time dramatic climate changes from randomness, because the climate is always under a semi extra terrestrial cyclic beat which stops the climate from going in one direction for eternity.
NOTE 1- Thermohaline Circulation Changes are more likely in my opinion when the climate is near the glacial/
inter-glacial threshold probably due to greater sources of fresh water input into the North Atlantic.
PART TWO
HOW THE CLIMATE MAY CHANGE
Below I list my low average solar parameters criteria which I think will result in secondary effects being exerted upon the climatic system.
My biggest hurdle I think is not if these low average solar parameters would exert an influence upon the climate but rather will they be reached and if reached for how long a period of time?
I think each of the items I list , both primary and secondary effects due to solar variability if reached are more then enough to bring the global temperatures down by at least .5c in the coming years.
Even a .15 % decrease from just solar irradiance alone is going to bring the average global temperature down by .2c or so all other things being equal. That is 40% of the .5c drop I think can be attained. Never mind the contribution from everything else that is mentioned.
What I am going to do is look into research on sun like stars to try to get some sort of a gage as to how much possible variation might be inherent with the total solar irradiance of the sun. That said we know EUV light varies by much greater amounts, and within the spectrum of total solar irradiance some of it is in anti phase which mask total variability within the spectrum. It makes the total irradiance variation seem less then it is.
I also think the .1% variation that is so acceptable for TSI is on flimsy ground in that measurements for this item are not consistent and the history of measuring this item with instrumentation is just to short to draw these conclusions not to mention I know some sun like stars (which I am going to look into more) have much greater variability of .1%.
I think Milankovich Cycles, the Initial State of the Climate or Mean State of the Climate , State of Earth’s Magnetic Field set the background for long run climate change and how effective given solar variability will be when it changes when combined with those items. Nevertheless I think solar variability within itself will always be able to exert some kind of an influence on the climate regardless if , and that is my hurdle IF the solar variability is great enough in magnitude and duration of time. Sometimes solar variability acting in concert with factors setting the long term climatic trend while at other times acting in opposition.
THE CRITERIA
Solar Flux avg. sub 90
Solar Wind avg. sub 350 km/sec
AP index avg. sub 5.0
Cosmic ray counts north of 6500 counts per minute
Total Solar Irradiance off .15% or more
EUV light average 0-105 nm sub 100 units (or off 100% or more) and longer UV light emissions around 300 nm off by several percent.
IMF around 4.0 nt or lower.
The above solar parameter averages following several years of sub solar activity in general which commenced in year 2005. The key is duration of time because although sunspot activity can diminish it takes a much longer time for coronal holes to dissipate which can keep the solar wind elevated which was the case during the recent solar lull of 2008-2010 ,which in turn keep solar climatic effects more at bay. Duration of time therefore being key.
If , these average solar parameters are the rule going forward for the remainder of this decade expect global average temperatures to fall by -.5C, with the largest global temperature declines occurring over the high latitudes of N.H. land areas.
The decline in temperatures should begin to start to take place within six months after the ending of the maximum of solar cycle 24,if sub- solar conditions have been in place for 10 years + which we have now had. Again the solar wind will be needed to get to an average of below 350km/sec. in order to realize the full solar effects which I believe can be attained quite easily.
Secondary Effects With Prolonged Minimum Solar Activity. A Brief Overview. Even if one or two should turn out to be true it would be enough to accomplish the solar /climatic connection.
A Greater Meridional Atmospheric Circulation- due to less UV Light Lower Ozone in Lower Stratosphere.
Increase In Low Clouds- due to an increase in Galactic Cosmic Rays.
Greater Snow-Ice Cover- associated with a Meridional Atmospheric Circulation/an Increase In Clouds.
Greater Snow-Ice Cover probably resulting over time to a more Zonal Atmospheric Circulation. This Circulation increasing the Aridity over the Ice Sheets eventually. Dust probably increasing into the atmosphere over time.
Increase in Volcanic Activity – Since 1600 AD, data shows 85 % approximately of all major Volcanic eruptions have been associated with Prolonged Solar Minimum Conditions. Data from the Space and Science Center headed by Dr. Casey.
Volcanic Activity -acting as a cooling agent for the climate,(SO2) and enhancing Aerosols possibly aiding in greater Cloud formation.
Decrease In Ocean Heat Content/Sea Surface Temperature -due to a decline in Visible Light and Near UV light.
This in turn should diminish the Greenhouse Gas Effect over time, while promoting a slow drying out of the atmosphere over time. This may be part of the reason why Aridity is very common with glacial periods.
In addition sea surface temperature distribution changes should come about ,which probably results in different oceanic current patterns.
[Long, interesting summary. Thank you. .mod]
Thanks, I appreciate that.
Lordy. Once again your theory is like throwing stew on the refrigerator in the hope some of it sticks. Even if you get lucky you have not explained the mechanism. What if we go through a period of La Nina’s? We do have those you know. And if we do, what goes in must eventually come out.
The main issue I have with your theory is that something as simple as cloud variations, which are poorly understood and modeled, can create such noise that any solar signal you seek will be buried in that noise, impossible to extract.
List all the parameters you want. Without solid mechanism, your theory is: Not a theory.
Wonder what your wonderful theory would be, Pam?
Lot of criticism of Mr. Steven Mosher in the above comments.
I think it is somewhat unfair, his opinions have evolved in the last 3-4 years, the fact that we don’t agree with many of his views, he should not be ostracised. Steven appears to have moved firmly into the ‘warming’ camp but he is not an extremist.
Not many AGWs (I don’t think he is a CAGW, not yet anyway) come here to present the more moderate views of the ‘opposition’, therefore his presence could only help to widen the debate. I often read his comments on the JC’s blog and must admit he occasionally makes lot of sense.
Despite the fact that once elsewhere he describe me as a ‘near lunatic’ I am still willing to read and consider what he has to say.
Drawing fire to take the heat of Willis is all in a days work
Steven, if you read my theory you may not agree with it but it is comprehensive and to the point and has clear guidelines from which to evaluate how correct or not it may eventually be.
So when you say us skeptics do not come up with alternative theories you are wrong.
What you are really saying is skeptics do not come up with theories that you embrace.
The only thing that matters is whose climate prediction is correct and the why behind it. Time will tell.
Willis,
Having read Dr. Shaviv et al.‘s paper (includind the supplementary material), it is clear that equation 1 should not contain the delta on the left hand side, Δh(t). The left hand side of the equation should be just h(t), the sea level height. It includes a linear component (h_0 and h_1 terms), an El Nino-Southern Oscillation component (b_0 and b_1 terms), and a sinusoidal term representing a solar component (a term).
In Figure 1 from Dr. Shaviv’s paper, the vertical axis is correctly labeled with the delta, Δh. In this case, the delta is not referring to the change in the height as you seem to have interpreted it. That is, the delta is not referring to the difference in height between two successive times. Rather the delta is referring to the difference between the height datum at a particular time and a reference value at the same time. The reference value is the value of the linear trend at that time. This is similar to the way the temperature anomolies are represented as ΔT; the difference between the temperature datum and an arbitrary reference value.
You complain that there is no solar data input into the model. But that misses the point of what Dr. Shaviv et al. are trying to do. They are not trying to overlay sunspot number data on top of the sea level rise data. As Dr. Shaviv pointed out, on physical grounds, one would not even expect those two data sets to be correlated. What Dr. Shaviv et al. are trying to is the following:
1. Assume that sea level rise has three components: linear trend, El Nino-Southern Oscillation, solar.
2. Detrend the sea level altimetry data (TOPEX/Poseidon and Jason) to eliminate the linear component.
3. Use the NINO 3.4 index to eliminate the El-Nino-Southern Oscillation component.
4. See if whatever is leftover can be accounted for by a sinusoidal function representing the solar component.
The sinusoidal must have the same period as the solar cycle (they have chosen T=12.6 years). Because the ocean system is huge, it will react slowly to any solar influence. Therefore, the sinusoidal, which represents the solar influence on the oceans, will not neccessarily have the same phase as the sunspot data. Dr. Shaviv et al. demonstrated that after accounting for the linear and El Nino components the remaining component could be reasonably well approximated by the sinusoidal, lending support to their claim that it is related to solar influence.
In the first sentence of the abstract, Shaviv, et al., state:
Don’t they mean “precision” rather than “accuracy”?
And given the extensive corrections, adjustments and filtering they applied to the raw data, perhaps they also meant “estimated” MSL, or “calculated”, rather than “measured”?
In fact, opluso, the truth is neither. Neither accurate nor precise. See the following videoclip, beginning at 4:15, and especially at 8:48 and further on. If you use a blank yardstick or meterstick, measuring inches or millimeters is fraught with peril, and ripe for data “adjusting,” manipulation, and other sometimes nefarious changes, none of which are accurate or precise. Here’s the clip:
http://climateconferences.heartland.org/thomas-wysmuller-iccc9/
Regarding: “You show the linearly detrended sea height h by means of the blue dots, but you have labeled it “∆h” on the Y-axis. You have also incorrectly referred to the sea height h in the caption as ∆h. Clearly this is not just a typo, it is an ongoing misunderstanding.”
The way I see it, a deviation from the flat linear trend in a detrended dataset can be expressed as a delta from that flat linear trend.
My money’s on Shaviv.