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 25, 2014 7:49 pm

David
“Hi Willis
Scafetta is another author showing an ~ 60 year cycle in long sea level data.”
in one station. New York City.
Here is a clue. You have a bunch of stations. if you look at enough of them you will find a cycle.
The bottom line is why would anyone think you could find a cycle.

TRG
April 25, 2014 7:50 pm

Willis, thank you for this, and for all of your excellent work.

bones
April 25, 2014 8:24 pm

Pat Frank says:
April 25, 2014 at 4:03 pm
Willis, is it possible that the tide gauge data need to be corrected for any isostatic movement of the land-base?
———————————————–
Whether isostatic rebound or subsidence, wouldn’t that just be automatically discarded by the linear detrending?

April 25, 2014 9:34 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.
For instance, the North American Atlantic coast displays a significant oscillation, but there’s an “inflection point” somewhere around Cape Hatteras, NC. North of Cape Hatteras (about 35.3°N latitude) the sea is currently “sloshing up” (but nearing its peak rate of sea-level rise), and south of Cape Hatteras it’s “sloshing down” (but nearing its trough). (Note that this slow “sloshing” is in addition to the linear trends, which also vary by location, due to PGR, land subsidence, etc.)
So along the northeastern U.S. Atlantic coast, between northern NC and Eastport, ME, if you compare the rate of sea-level rise now to 10 to 30 years ago, you’ll see a measurable acceleration (increase in rate). That’s why the NOAA-calculated long-term average rate of sea-level rise at those stations is slightly higher when calculated using measurements through 2011 than when calculated using measurements through 2006.
But along the southeastern U.S. Atlantic coast, between Wilmington, NC and the Florida border, if you compare the rate of sea-level rise now to 10 to 30 years ago you’ll see a measurable deceleration. That’s why the NOAA-calculated long-term average rate of sea-level rise at those stations is slightly lower when calculated using measurements through 2011 than when calculated using measurements through 2006.
Here’s a spreadsheet. You can view it as a web page, or load it into Microsoft Excel or Kingsoft Office:
http://sealevel.info/US_Atlantic_coast_sea-level_trends.html
The column labeled “2006 trend” shows the trend calculated by linear regression of all sea-level measurement data through 2006, and the column labeled “2011 trend” shows the trend calculated using data through 2011. For the northern coast, Virginia-to-Maine, the 2011 trends are slightly higher than the 2006 trends, but for the southern coast, North Carolina-to-Georgia, the 2011 trends are slightly lower than the 2006 trends.
BTW, you might notice that the northeastern U.S. “hot-spot” of apparently accelerated sea-level rise encompasses a stretch of Atlantic coastline that is about twice as long as the southeastern U.S. “cold-spot” of apparently decelerated sea-level rise. But before you make the mistake of concluding that that means the overall trend is acceleration, I should warn you that the entire U.S. Pacific coast is showing deceleration, all the way from Seattle to San Diego:
http://sealevel.info/MSL_global_trendtable4.html
The bottom line is that, due to small but measurable multi-decadal regional oscillations in sea-level, with the most noticeable oscillation period equal to about 60 years, when sea-level trends are calculated over short time spans (meaning less than 50-60 years), some stretches of coastline show apparent acceleration, and other stretches show apparent deceleration, neither of which are real long term trends.
Overall, there’s been little or no change in the rate of sea-level rise in the last 85-90 years, despite the fact that atmospheric CO2 levels increased by about 90-95 ppm (30%). That’s about 4/5-ths of the total anthropogenic CO2 increase since the start of the industrial age. Yet it has caused no detectable acceleration in the rate of sea-level rise. In fact, the best studies show a very slight deceleration.
BTW, who can guess which of those two opposing “trends” (apparent acceleration in some places, apparent deceleration in others) got written up in a high-profile paper in Nature? Now let’s not always see the same hands.

April 25, 2014 10:28 pm

Why does anyone expect to find a 60 year cycle in sea level? I’m personally convinced of 60 year atmospheric cycles, but water is so quickly isotactic that when you make a pile of it (like the enso warm pool), the rest of the ocean drops. Meltwater and steric change are surely insignificant at this timescale.

April 25, 2014 11:24 pm

Very interesting work, Willis, but your analysis is limited to datasets in the PSMSL database. As PSMSL writes; there exist several important long datasets not included in the PSMLS database:
http://www.psmsl.org/data/longrecords/
For example:
Amsterdam from 1700
Stockholm from 1774
Kronstadt from 1773
Liverpool from 1768
Brest from 1711
I would guess that the pay-walled paper is based on some these. They are long enough for at least 3 cycles of a 60 year period.
/Jan

tonyb
Editor
April 25, 2014 11:45 pm

Jan
The longer records are very interesting but as far as I am aware the tide gauges in all of them have been physically moved at least once so they are not necessarily like for like.
Also isostatic change needs to be taken into account which is often greater than sea level rise (or fall)
The rate of sea level change around the UK (up and down) can be seen in this paper-this would cover Liverpool but assumes isostatic change has always been constant.
http://www.geosociety.org/gsatoday/archive/19/9/pdf/i1052-5173-19-9-52.pdf
tonyb

April 25, 2014 11:48 pm

@Willis; I commend your effort to personally examine the data and check the science.
I personally can not see how anything can effect sea levels on so short a time scale. As you know so well the oceans are MASSIVE and leveled by gravity, The land surface/ocean interface is much more likely to move a bit then the amount of volume in the oceans.

April 25, 2014 11:59 pm

“Why does anyone expect to find a 60 year cycle in sea level?”
good question.
why do people want to find the cycle is a better question

charles nelson
April 26, 2014 12:02 am

Nice to see a clear analysis of some (relatively) concrete and reliable data. Interesting and informative.

Roy
April 26, 2014 12:20 am

Shouldn’t there be a hockey stick somewhere among all those graphs?

April 26, 2014 1:03 am

Interesting that the records for places close together on the Dutch coast are so dissimilar, for example Amsterdam, Ijmuiden, Hook of Holland, Den Helder, but then you would need to look at the river freshwater height as well. The amount of rain upriver days or weeks before can have a massive influence on the height of tide at any time.
But very worthwhile digging.
It would be interesting to look at somewhere with no land effect – Rockall, St. Helena, somewhere in the Azores?

Greg
April 26, 2014 1:23 am

“There’s a strong cycle around 37 years, and a smaller peak at 53 years, but nothing around 60 years.”
I found 57/58 years and the paper actuall is fitting 55 years. Don’t know why they report this as “60y”.
http://onlinelibrary.wiley.com/store/10.1029/2012GL052885/asset/supinfo/grl29523-sup-0005-t02.txt?v=1&s=0603509b8451e52b1b7109d1181c2521b37ccae4
” Phase, and Implied Trend for 1993-2011 of a 55-Year Oscillation for Long-Tide Gauge Recordsa”
It seems they decided 55 was about right and fitted it to each one by OLS. I see no indication of a method that in some way regressed all the data collectively. But I have not paid to get the full text.
Steve Mosher says “The bottom line is why would anyone think you could find a cycle.”
Will since there is 60y component is AMO, at least, that should be refelcted in the thermal component of MSL which we are told is a world threatening large problem.

Greg
April 26, 2014 1:39 am

Willis Eschenbach says:
April 25, 2014 at 8:31 pm
“While there is nothing resembling a 60-year cycle anywhere in that data. And since the purported 60-year cycle is the subject of this post, I’m taking that as supporting evidence that such a cycle isn’t there …”
As you say C7W and JJ look similar in form. Jevrejava plot has a peak around 1890 and and 1960. That’s a separation of ~70. Now since the early one is on a strong downward slope the peak will be displaced earlier, contrariwise for later one. That does not seem incompatible with a circa 60 y cycle, for a rough eye-balling of the data.
This cooling trend to warming is significant feature of both MSL and surface temperature that does not fit the AGW theme tune. This is why a lot of studies prefer to start in 1900 so they have nice simple storey about monotonic rise.
If you fit an exponential or quadratic rise to support the foregone conclusion about GHG warming it goes badly wrong if your data goes back into 19th c. ( You can get away with 1880 as ‘internal variation’ but beyond that you’re in trouble).

Girma
April 26, 2014 1:54 am

Willis
Excellent work Willis.
Could you do the same on the HadCRUT4 dataset, PLEASE?

Greg
April 26, 2014 1:57 am

Looking at your P.A. for Amdterdam you will note as well as 53 there is peak at 64 and a smaller one at 60.
Now if you combine 53 and 64 as cos+cos = cos * cos, as I detailed above for the short cycles that will give the _frequency_ averaged result of 57.9y modulated by 616 years. I think this is what the JJ SSA plot is showing. This is typical of what SSA does it produces pairs of modulated harmonics that result in a long term variation in amplitude. Unfortunately I don’t think JJ reports any figures, so we’re left guessing from the graphics.
recall the triplet I found in the sub-annual peaks
# as A.M. 0.947 * 58.060 ; triplet asymmetry: -0.039 %
Almost identical modulation period.
Now I don’t see why Chambers et al are fitting 55 and report “60” years. But there is definitely some significant energy in that part of the spectrum.
My chirp-z analysis found two separate indications : 56.7 and 58 and your PA show 57.8. From such fundamentally different techniques, I think that can be regarded as corroborative.

Greg
April 26, 2014 2:04 am

W. “Haaiiiieee, please, stop assuming what you are trying to prove. You have definitely NOT established the existence of a 60-year cycle in the AMO, nor (despite lots of handwaving claims) has anyone that I know of.”
OK care with words . There is a circa 60y periodicity in last 120 y of SST , I am not concluding that this is permanent , fixed amplitude harmonic “cycle”. But if that variability is there is SST it could be expected to be reflected in MSL , which was the sense of my reply to Mosh’.

Greg
April 26, 2014 2:15 am

W “Not sure why you quoted that. I was looking at the Amsterdam record. They don’t use Amsterdam in what you cited. What am I missing?”
I was pointing out that they were fitting 55 not the reported “60”. Since your PA of Amsterdam has the two main peaks in that region with a mean freq corresponding to 57.9 , you are finding similar periods in one of the records they did not use.
Now if you are going fit a single sine (which is what their model does) it fit to the mean frequency. This is period of combined AM modulated result of the two frequencies your PA found.
The method is crude and their reporting inaccurate of their results but there is basic agreement with the more general frequency techniques that both you and I are applying.

Greg
April 26, 2014 2:44 am

W: “Finally, while you are correct that there are some small cycles at 8 years or so, as you can see they don’t do much.”
All this global averaging is stirring a lot different colours in the same pot. Hence you get muddy brown water. It takes spectral analysis to work out pigments were there before you stirred it up.
Both C&W and Jevrejava are pots of muddy water. Despite that some peaks are fairly well defined.
Indeed since most oceans communicate it all gets mixed anyway but with the added complication of varying lags. It’s actually surprising that anything survives.
http://climategrog.wordpress.com/?attachment_id=935
The amplitudes very small in the chirp-z plot because it is done at a very high spectral resolution and the frequency intervals a very narrow. However, we see just four peaks on the decadal scale.
Each peak is spread by noise and experimental errors. To get the total power of a peak it needs to be plotted in freq, not period and the area under the peak calculated. In fact the 20 y peak is no broader than the 7.5y one.
We can get a fair idea from the relative heights.