The Elusive ~ 60-year Sea Level Cycle

Guest Post by Willis Eschenbach

I was referred to a paywalled paper called “Is there a 60-year oscillation in global mean sea level?”  The authors’ answer to the eponymous question is “yes”, in fact, their answer boils down to “dangbetcha fer sure yes there is a 60-year oscillation”, viz:

We examine long tide gauge records in every ocean basin to examine whether a quasi 60-year oscillation observed in global mean sea level (GMSL) reconstructions reflects a true global oscillation, or an artifact associated with a small number of gauges. We find that there is a significant oscillation with a period around 60-years in the majority of the tide gauges examined during the 20th Century, and that it appears in every ocean basin.

So, as is my wont, to investigate this claim I got data. I went to the PSMSL, the Permanent Service for the Mean Sea Level, and downloaded all their monthly tidal records, a total of 1413 individual records. Now, the authors of the 60-year oscillation paper said they looked at the “long-term tide records”. If we’re looking for a 60-year signal, my rule of thumb says that you need three times that, 180 years of data, to place any confidence in the results. Bad news … it turns out only two of the 1,413 tidal gauge records, Brest and Swinoujscie, have 180 years of data. So, we’ll need to look at shorter records, maybe a minimum of two times the 60-year cycle we’re looking for. It’s sketchy to use that short of a record, but “needs must when the devil drives”, as the saying goes. There are twenty-two tidal datasets with 120 years or more of data. Figure 1a shows the first eight of them:

all tide records over 120 years 1-8Figure 1a. Tide gauge records with 1440 months (120 years) or more of records. These are all relative sea levels, meaning they are each set to an arbitrary baseline. Units are millimetres. Note that the scales are different, so the trends are not as uniform as they appear.

Now, there’s certainly no obvious 60-year cycles in those tidal records. But perhaps the subtleties are not visible at this scale. So the following figure shows the Gaussian averages of the same 8 tidal datasets. In order to reveal the underlying small changes in the average values, I have first detrended each of the datasets by removing any linear trend. So Figure 1b emphasizes any cycles regardless of size, and as a result you need to note the very different scales between the two figures 1a and 1b.

gauss all tide records over 120 years 1-8Figure 1b. Gaussian averages (14-year full-width half-maximum) of the linearly detrended eight tide gauge datasets shown in Figure 1a. Note the individual scales are different from Figure 1a.

Huh. Well, once the data is linearly detrended, we end up with all kinds of swings. The decadal swings are mostly on the order of 20-30 mm (one inch) peak to peak, although some are up to about twice that. The big problem is that the decadal swings don’t line up, they aren’t regular, and they don’t have any common shape. More to the current point, there certainly is no obvious 60-year cycle in any of those datasets.

Now, we can take a closer look at what underlying cycles are in each of those datasets by doing a periodicity analysis. (See the notes at the end for an explanation of periodicity analysis). It shows how much power there is in the various cycle lengths, in this case from two months to seventy years Figure 1c shows the periodicity analysis of the same eight long datasets. In each case, I’ve removed the seasonal (annual) variations in sea level before the periodicity analysis.

periodicity all tide records over 120 years 1-8Figure 1c. Periodicity analysis, first eight long-term tidal datasets.

Boooring … not much of anything anywhere. Top left one, Brest, has hints of about a 38-year cycle. New York shows a slight peak at about 48 years. Other than that there is no energy in the longer-term cycles, from say 30 to 70 years.

So let’s look at the rest of the 22 datasets. Here are the next eight tide gauge records, in the same order—first the raw record, then the Gaussian average, and finally the periodicity analysis.

all tide records over 120 years 9-16 gauss all tide records over 120 years 9-16 periodicity all tide records over 120 years 9-16Figures 2a, 2b, and 2c. Raw data, Gaussian averages, and periodicity analysis, next 8 stations longer than 120 years.

No joy. Same problem. All kinds of cycles, but none are regular. The largest problem is the same as in the first eight datasets—the cycles are irregular, and in addition they don’t line up with each other. Other than a small peak in Vlissingen at about 45 years, there is very little power in any of the longer cycles. Onwards. Here are the last six of the twenty-two 120-year or longer datasets:

all tide records over 120 years 17-22 gauss all tide records over 120 years 17-22 periodicity all tide records over 120 years 17-22

Figures 3a, 3b, and 3c. Data, Gaussian averages, and periodicity analysis as above, for the final six 120-year + tide gauge datasets. 

Dang, falling relative sea levels in Figure 3a. Obviously, we’re looking at some tidal records from areas with “post-glacial rebound” (PGR), meaning the land is still uplifting after the removal of trillions of tons of ice at the end of the last ice age. As a result, the land is rising faster than the ocean …

How bizarre. I just realized that people worry about sea-level rise as a result of global warming, and here, we have land-level rise as a result of global warming  … but I digress. The net result of the PGR in certain areas are the falling relative sea levels in four of the six datasets.

Like the other datasets, there are plenty of cycles of various kinds in these last six datasets in Figure 3, but as before, they don’t line up and they’re not regular. Only two of them have something in the way of power in the longer cycles. Marseille has a bit of power in the 40-year area. And dang, look at that … Poti, the top left dataset, actually has hints of a 60-year cycle … not much, but of the twenty-two datasets, that’s the only one with even a hint of power in the sixty-year range.

And that’s it. That’s all the datasets we have that are at least twice as long as the 60-year cycle we’re looking for. And we’ve seen basically no sign of any significant 60-year cycle.

Now, I suppose I could keep digging. However, all that are left are shorter datasets … and I’m sorry, but looking for a sixty-year cycle in a 90-year dataset just isn’t science on my planet. You can’t claim a cycle exists from only enough data to show one and a half swings of the cycle. That’s just wishful thinking. I don’t even like using just two cycles of data, I prefer three cycles, but two cycles is the best we’ve got.

Finally, you might ask, is it possible that if we average all of these 22 datasets together we might uncover the mystery 66-year cycle? Oh, man, I suppose so, I’d hoped you wouldn’t ask that. But looking at the mish-mash of those records shown above, would you believe it even if I found such a cycle? I don’t even like to think of it.

Ah, well, for my sins I’m a scientist, I am tormented by unanswered questions. I’d hoped to avoid it, so I’ve ignored it up until now, but hang on, let me do it. I plan to take the twenty-two long-term records, linearly detrend them, average them, and show the three graphs (raw data, Gaussian average, and periodicity analysis) as before. It’ll be a moment.

OK. Here we go. First the average of all of the detrended records, with the Gaussian average overlaid.

mean detrended 22 tide recordsFigure 4a. Mean of the detrended long-term tidal records. Red line shows a 14-year full-width half-maximum (FWHM) Gaussian average of the data, as was used in the earlier Figures 1b, 2b, 3b.

Well, I’m not seeing anything in the way of a 60-year cycle in there. Here’s the periodicity analysis of the same 22-station mean data:

periodicity mean detrended 22 tide recordsFigure 4b. Periodicity analysis of the data shown in Figure 4a immediately above.

Not much there at all. A very weak peak at about forty-five years that we saw in some of the individual records is the only long-term cycle I see in there at all.

Conclusions? Well, I don’t find the sixty-year cycle that they talk about, either in the individual or the mean data. In fact, I find very little in the way of any longer-term cycles at all in the tidal data. (Nor do I find cycles at around eleven years in step with the sunspots as some folks claim, although that’s a different question.) Remember that the authors said:

We find that there is a significant oscillation with a period around 60-years in the majority of the tide gauges examined during the 20th Century …

Not able to locate it, sorry. There are decadal swings of about 25 – 50 mm (an inch or two) in the individual tide gauge datasets.  I suppose you could call that “significant oscillations in the majority of the tide gauges”, although it’s a bit of a stretch.

But the “significant oscillations” aren’t regular. Look at the Gaussian averages in the first three sets of figures. The “significant oscillations” are all over the map. To start with, even within each individual record the swings vary greatly in amplitude and cycle length. So the cycles in each individual record don’t even agree with themselves.

Nor do they agree with each other. The swings in the various tidal records don’t line up in time, nor do they agree in amplitude.

And more to the point, none of them contain any strong approximately sixty-year signal. Only one of the twenty-two (Poti, top left in Figure 3a,b,c) shows any power at all in the ~ 60 year region in the periodicity analysis.

So I’m saying I can’t find any sign in those twenty-two long tidal datasets of any such sixty-year cycle. Note that this is different from saying that no such cycle exists in the datasets. I’m saying that I’ve pulled each one of them apart and examined them individually as best I know how, and I’m unable to find the claimed “significant oscillation with a period around 60-years” in any of them.

So I’m tossing the question over to you. For your ease in analyzing the data, which I obtained from the PSMSL as 1413 individual text files, I’ve collated the 1413 record tide station data into a 13 Mb Excel worksheet, and the 22 long-term tidal records into a much smaller CSV file. I link to those files below, and I invite you to try your hand at demonstrating the existence of the putative 60-year cycle in the 22-station long-term tidal data.

Some folks don’t seem to like my use of periodicity analysis, so please, use Fourier analysis, wavelet analysis, spectrum analysis, or whatever type of analysis you prefer to see if you can establish the existence of the putative “significant” 60-year cycles in any of those long-term tidal datasets.

Regards to all, and best of luck with the search,

w.

The Standard Request: If you disagree with something someone says, please have the courtesy to quote the exact words you disagree with. It avoids all kinds of trouble when everyone is clear what you are objecting to.

Periodicity Analysis: See the post “Solar Periodicity” and the included citations at the end of that post for a discussion of periodicity analysis, including an IEEE Transactions paper containing a full mathematical derivation of the process.

Data: I’ve taken all of the PSMSL data from the 1413 tidal stations and collated it into a single 13.3 Mb Excel worksheet here. However, for those who would like a more manageable spreadsheet, the 22 long-term datasets are here as a 325 kb comma-separated value (CSV) file.

[UPDATE] An alert commenter spots the following:

Jan Kjetil Andersen says:

April 26, 2014 at 2:38 pm

By Googling the title I found the article free on the internet here:

http://www.nc-20.com/pdf/2012GL052885.pdf

I don’t find it any convincing at all. They use the shorter series in the PSMSL sets, and claim to see 64 years oscillations even though the series are only 110 years long.

The article has no Fourier or periodicity analysis of the series.

/Jan

Thanks much for that, Jan. I just took a look at the paper. They are using annually averaged data … a very curious choice. Why would you use annual data when the underlying PSMSL dataset is monthly?

In any case, the problem with their analysis is that you can fit a sinusoidal curve to any period length in the tidal dataset and get a non-zero answer. As a result, their method (fit a 55 year sine wave to the data) is meaninglesswithout something with which to compare the results.

A bit of investigation, for example, gives the following result. I’ve used their method, of fitting a sinusoidal cycle to the data. Here are the results for Cascais, record #43. In their paper they give the amplitude (peak to peak as it turns out) of the fitted sine curve as being 22.3. I get an answer close to this, which likely comes from a slight difference in the optimization program.

First, let me show you the data they are using:

If anyone thinks they can extract an “~ 60 year” cycle from that, I fear for their sanity …

Not only that, but after all of their waffling on about an “approximately sixty year cycle”, they actually analyze for a 55-year cycle. Isn’t that false advertising?

Next, here are the results from their sine wave type of analysis analysis for the periods from 20 to 80 years. The following graph shows the P-P amplitude of the fitted sine wave at each period.

So yes, there is indeed a sinusoidal cycle of about the size they refer to at 55 years … but it is no different from the periods on either side of it. As such, it is meaningless.

The real problem is that when the cycle length gets that long compared to the data, the answers get very, very vague … they have less than a hundred years of data and they are looking for a 55-year cycle. Pitiful, in my opinion, not to mention impossible.

In any case, this analysis shows that their method (fit a 55-year sine wave to the data and report the amplitude) is absolutely useless because it doesn’t tell us anything about the relative strength of the cycles.

Which, of course, explains why they think they’ve found such a cycle … their method is nonsense.

Eternal thanks to Jan for finding the original document, turns out it is worse than I thought.

w.

 

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April 26, 2014 2:38 pm

By Googling the title I found the article free on the internet here:
http://www.nc-20.com/pdf/2012GL052885.pdf
I don’t find it any convincing at all. They use the shorter series in the PSMSL sets, and claim to see 64 years oscillations even though the series are only 110 years long.
The article has no Fourier or periodicity analysis of the series.
/Jan

otsar
April 26, 2014 3:56 pm

Let me add some confusion. I have not seen anywhere in the discussion or the literature consideration of the local water column density. The comings and goings of estuarine circulation near the tidal gauges, or the meanderings of oceanic currents with different densities are not at all considered. The continuous and dynamic isostatic adjustment of the water column is not considered. For example, if you have a change to a low column density by the gauge station, the water level will go higher, etc.

Greg
April 26, 2014 4:06 pm

The paper says the fitted harmonic fn explains between 4 and 10% of the variability after linear detrending. Pretty small.
The modulation I showed in NY Battery looks stronger than that. http://climategrog.wordpress.com/?attachment_id=936

SplatterPaterns
April 26, 2014 5:52 pm

Mr Eschenbach,
Movement of the Tanana ice at Nenana tripped the clock at 4:48 pm AkDT (UTC -10) on April 25. That’s the 8th (of 98) earliest ice-out.
http://www.newsminer.com/news/alaska_news/breakup-tripod-falls-on-the-tanana-river/article_80a4a176-ccde-11e3-bfd7-0017a43b2370.html
Though you’d want to know as you went to the trouble to write a feature that appeared the middle of last May about the abnormally, ultimately a new record (by ~3 1/2 hrs), late ice-out. I count 5 posts twixt yourself and Mr. Watts over the six days leading up to that event last year.

April 26, 2014 6:24 pm

“Whether or not you’ll notice the approx. 60-year sea-level oscillation depends on the mix of tide-gauges that you choose to examine.”
Yes, Mann learn the same trick with proxies

RoHa
April 26, 2014 7:07 pm

“So, as is my wont, to investigate this claim I got data.”
See, there’s your problem.

Neil Jordan
April 27, 2014 1:12 am

Re Willis Eschenbach says: April 26, 2014 at 10:59 pm
and Willis Eschenbach says: April 26, 2014 at 11:57 pm
Thank you for your comment re the LMSL, the challenge, and the Metonic cycle information. I wasn’t trying to ferret out another cycle and won’t step into that quagmire, but was trying to bring in an important aspect of sea level that defines a property boundary. The 19-year tidal epoch is an averaging period that is considered when establishing the boundary between public and private property. The current tidal epoch is 1983 through 2001 (the previous 19 years) per NOAA http://tidesandcurrents.noaa.gov/datum_options.html and is updated every 19 years except for a 5-year cycle in Alaska and Gulf of Mexico. Unfortunately, this technical reality tends to be overlooked by those who would arbitrarily define the boundary based on some future hypothesized sea level from a computer model rather than a sea level actually measured according to established procedures (e.g. “Evidence and Procedures for Boundary Location”). The complexity of this is described for example in “Tidal Boundary Delimitation: Some North American Perspectives”:
http://www.csc.noaa.gov/mbwg/_pdf/biblio/Nichols.pdf
The pages are out of order, but all are there. See the Borax decision on Page 563. The tidal boundary is indeed a quagmire. See “Rules of the Game: Establishing Property Lines”:
http://www.profsurv.com/magazine/article.aspx?i=70829

Greg
April 27, 2014 2:32 am

recall the triplet I found in the sub-annual peaks
# as A.M. 0.947 * 58.060 ; triplet asymmetry: -0.039 %
“I hate to say it, Greg, but for me that’s nothing but numerology. Fifty-seven point nine years? Six hundred sixteen years? Triplet asymmetry? Fifty-eight point zero six zero years, 58.060 … that’s six hundredths of a year with a claimed precision to the nearest thousandth of a year? A thousandth of a year is what, about eight hours?”
Look, that’s just the output of the calculation, I’m not suggesting it’s five figure accurate. Like I already comments earlier when I said 56.7 and 58 probably represented the same thing. So don’t get pedantic about the extra digits. That’s a distraction and nothing else.
If you don’t understand the significance of triplet asymmetry, this is a check against taking any three peaks in row a and saying “wow a triplet”. There are other checks but this is my first line sanity check, since amplitude modulation will produce a perfectly symmetric pattern in the frequency domain. Another check is the side-band having the same height.This also checks out in this case.
” As I said above, that looks vaguely like half a 120 year cycle, but there’s no 60 year cycle in there anywhere. Periodicity analysis of C&W finds a peak at 42 years, but nothing around 60 years.”
Well actually up-down-up would be the full “cycle” but I agree variability of that length is there, though we would both agree there is no grounds to call it a “cycle”. What I was trying point out is that unless you “detrend” for that too it will separate the other peaks which lie on the down slope and the up slope, leaving them separated by about 70y (visual est.).
To say “nothing around 60 years.” is to refuse to see the results of your own analysis.
http://wattsupwiththat.files.wordpress.com/2014/04/periodicity-analysis-amsterdam-1701-1925.jpg?w=560
The ‘power index’ at 60 is about 3.7 . That is not equal to “nothing”. There is also notable signals at 53 and 64 as I already pointed out. So there is significant energy in that part of the spectrum not “nothing”.
“You’re just pulling numbers out of your … immediate environment, with no visible limits on what you might grab, and not the slightest attempt at providing a physical mechanism.”
One visible limit is triplet asymmetry that you dismissed without understanding what it meant. Hopefully that is now clearer.
As for physical mechanism, hey what do you want? A PhD in each blog post? What is being discussed here is a first grasp of what patterns may or may not be present in the data. It is necessary to analyse the data and decide what is there FIRST. I’m not trying to colour my analysis by guessing about causation and specific mechanisms beyond the fact that some physical effects will be simply additive and will be superimposed, others will modulate each other physically, so this kind of A.M. should be expected to be present and should be actively sought out if we are get the most information from these noisy data sets.
“So I fear you’ll have to address your numerological insights to someone else. I’m not interested in sparring with someone who does that.”
Well unfortunately you always seem to regard this as a combative process. Almost all your replies to everyone’s comments are in the spirit of fending off an attack defending what you posted unchanged.
I prefer to contribute to a common effort to understanding the data and what it can tell us about climate. You have an incisive and enquiring mind and a broad life experience that gives you insights that desk bound academics lack. I also have a broad range of expertise and experience that I try to bring to bear.
If you are inclined to reject the idea of cyclic content that’s a useful check on what I’m seeing and argued objectively rather than dismissively it would be helpful. I too am not interested in intellectual sparring contests, pet theories and pet rebuttals. I’m interested in seeing what information can be extracted from this messy data.
Now as I pointed out above it looks like the circa 60y effect is more clearly seen in the modulation of the amplitude and that is what my spectral analysis suggested. Here we can clearly see this modulation in rate of change at NY Battery. No spectral mumbo jumbo, no numerology:
http://climategrog.wordpress.com/?attachment_id=936
Jevrejava’s SSA ; the freq. mean of your 53 and 64 PA periodicities; my sub-annual triplet and combination of 7.5 and 10.2 spectral peaks all point in the direction of 58 years that is seen directly at Battery.
It seems much clearer as a modulation than as a simple change in height, where the signal is admittedly weak ( the Chambers paper that was the subject of this post only finds small amplitude effects).
Now that is only the very first step of recognising the patterns. The next step is to try to understand how they relate to each other ( is the smaller height effect a non-linearity left-over from the modulation effect), how does this vary geographically. All that is necessary before we even begin to speculate about physical causation.

Greg
April 27, 2014 2:39 am

“Eternal thanks to Jan for finding the original document, turns out it is worse than I thought.”
I agree it was pretty poor. The only thing I like is they (attempt to ) investigate the geographic dependency rather than muddying everything into a global average.

Greg
April 27, 2014 2:42 am

Note there is a peak about 21y in Cascais there. This was a notable peak in the various spectra I’ve done. Particularly strong at Honolulu, which is one of the rare mid-ocean sites.

Greg
April 27, 2014 2:56 am

http://climategrog.wordpress.com/?attachment_id=937
quick spectral density from Honolulu. indicated peaks are circa 21.4 , 9.1 and 5.37 (=21.5/4)
cursor readouts are a little approximate but that looks a lot like solar and lunar signals.

Greg
April 27, 2014 3:10 am

“My threads are not the place for them.”
This is still an open forum for discussion last time I looked, or do you somehow imagine you “own” the discussion every time you post an article? It’s not the first time you’ve made such comments to others.
“… on your planet the statement you made has deep and profound meaning. ”
Hmm, that sounds a little like Lew-talk to me.
“However, my inability to find anything of value in your work doesn’t mean it has no value. ”
Indeed. It is difficult to explain technical stuff like interference patterns and modulation sidebands in blog comments. I’m sorry I have not been able to get this across. I think the fact you have clearly made up your mind and are fairly dismissive and refractory to the idea does not help. Hopefully it may click for others.
best regards, Greg.

Greg
April 27, 2014 3:40 am

Correction to earlier comments I made about NY Battery. It is the beat period that is close to 60y (this is half the modulation frequency). In fact I’d put this nearer to 63 years.
Willis’ P.A. graph of Amsterdam found a peak at 64 in tide height. These are similar latitude sites. Again, as with SST, geography is probably important in understanding all this Lumping everything into a global is must like mixing all the colour in the paint box. You end up with muddy brown water.

April 27, 2014 4:40 am

Greg says
Lumping everything into a global is must like mixing all the colour in the paint box. You end up with muddy brown water. (sic, you are writing too fast?)
Henry says
Truth is that most data sets that study climate are not globally representative.
This is (apparently) because nobody has spent some good time thinking on how to get a globally representative sample.
I found / recommend that there is a basic set of rules to follow:
1) the number of sample stations SH and NH must be equal
2) the sum of latitudes of all sampling stations must balance to zero or close to it
3) longitude is not important if you (want to) observe the average change per annum,
One year includes the effect of seasonal shifts and irradiation + earth rotates once every 24 hours. So balancing on longitude is not required as the differences due to longitude cancel each other out over a year.
4) if you study temp. or weather, chose your stations 70% at sea/ 30% inland
5) if possible, all continents included
6) subject to the sampling procedure 1-5 above, samples must be selected randomly, any place on earth. They maybe even close to each other, if the conditions 1-5 are met.
Pity there is not one global data set that keeps to these (very) simple rules. That is why I trust my own data set more than any other.
.

Greg
April 27, 2014 5:01 am

“Truth is that most data sets that study climate are not globally representative.”
Neither are effects global. Nor are the feedbacks the same in the tropics and at temperature latitudes. So the mixing does nothing but muddy the waters. Even if done carefully.
This is to a large extent a convenient non-accident. Having mangled any evidence of how climate really operates they just turn round and say “it’s stochastic” ! They then focalise on carefully cropped period with upwards trend and conclude AGW+noise.

April 27, 2014 5:25 am

Greg says
Neither are effects global.
Henry says
Ultimately what we get from the sun – or what is allowed through the atmosphere –
affects the whole of earth. Nothing else is really relevant. Greenery and man made greenery may trap the heat a little bit, but it is not much compared to the sum total.(0.5 degrees C?)
Based on my own results for the change in (global) maxima, I can predict that we will enjoy global cooling for the next 35 or 40 years.
Had I known about the diminishing strengths of the solar polar fields:
https://www.google.co.za/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=Zf89nf4rQ3_kNM&tbnid=x0HB82mkwt-syM:&ved=0CAUQjRw&url=http%3A%2F%2Fice-period.com%2F&ei=zPNcU8GRI6HW0QXui4DYAQ&bvm=bv.65397613,d.ZGU&psig=AFQjCNHOdANkKQwNlTCXv6eSmUS2CWij-Q&ust=1398687049323680
beforehand, I could have seen what is coming. I refer to that graph as the scissors. The key lies in knowing what is happening TOA as a result. Based on my results, I predict that around 2016 the solar poles will switch again. Then we start the scissor in the opposite direction.

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