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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DougByMany
April 26, 2014 3:14 am

I remember watching a television show that had a mystery that needed to be solved. Divers in lake Erie were finding trees that died growing out of the lake bed 40-50 feet underwater.
It turns out, that as the land in the North continues to rebound from the last Glaciation, the Earth’s crust in the South is receding where it had been bulged out by the trillions of pounds of ice piled up at higher latitudes.
If one accepts that 20% of the tide gauges are actually falling in large measure due to isostatic rebound, then they could be forgiven for believing that at least an equal number are rising at an accelerated rate due to the crust receding. (I claim at least an equal number, due to the higher populations and numbers of tide gauges further south.)
Now I am no Climate Scientist, but from what I have seen, I have no doubt that they are pretty thorough in making adjustments where the land is rising and completely ignoring adjustments where it is falling.

Greg
April 26, 2014 3:36 am

“Now I am no Climate Scientist, but from what I have seen, I have no doubt that they are pretty thorough in making adjustments where the land is rising and completely ignoring adjustments where it is falling.”
Yep, that’s pretty much what happens at Boulder. Where we’re supposed to worry about rising “sea levels” that not of the wet variety.

Bloke down the pub
April 26, 2014 3:38 am

Perhaps they took into account a 60yr cycle in post-glacial rebound but forgot to mention it in their workings.

Patrick
April 26, 2014 3:49 am

A good read from Willis as usual. The “measures”, like anything in this global “debate” about minute changes over extremely insignificant geological timeframes, ie, the human timeframe, are unreliable. No mention of land level changes. And there are many examples of ZERO significant change in sea levels around the coast of England. Exeter, Plymouth, Gosport, Portsmouth, Emsworth to name a few sites that have shown ZERO signifgicant change in hundreds of years of Royal Naval history.

April 26, 2014 3:53 am

I wrote, “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.”
Willis replied, “When you show up with some evidence for that, we’ll talk. But assuming what is to be proven is not going to work.”
I already did, Willis.
First of all, I gave you that link, to a number of papers which claimed to have identified such an oscillation. Here are some quotes from some of those papers, and a couple of articles about them:
http://sealevel.info/Schlesinger_and_Ramankutty_1994_p1.png
http://pages.citebite.com/h3c1d6x3w8efh
http://pages.citebite.com/j2d0k3n9tqpc
http://pages.citebite.com/g3g1i6j3b9rrr
http://pages.citebite.com/i3c5o5e8tyff
http://pages.citebite.com/b3y1x6d4w0xjc
http://hockeyschtick.blogspot.com/2012/09/new-paper-finds-natural-60-year.html
http://www.worldclimatereport.com/index.php/2012/09/10/sea-level-acceleration-not-so-fast/
These two are less directly related, but still interesting:
http://archive.today/PheLu#selection-1217.138-1217.152 (this is about temperature, not SLR)
https://en.wikipedia.org/wiki/File:Amo_timeseries_1856-present.svg (this is a graph of the ~60 year AMO)
Note that the postulated ~60 oscillation is a regional effect. When the ocean is “sloshing up” in one place, it should be expected to be “sloshing down” in another. So if we had a good, even distribution of tide gauges, we wouldn’t expect to see the oscillation in a global average, because the peaks and troughs would cancel in the average.
To detect evidence of an oscillation you should be looking at regionally averaged, rather than globally averaged, data.
In fact, the actual worldwide distribution of long-term tide gauges is rather uneven, so it is not unimaginable that you might find some oscillation signal in a global average, but the lack of such a signal doesn’t tell you much. If you want to test whether there are ~60 year regional oscillation patterns, you need to examine regional data.
Now, with that in mind, recall that I wrote, about two such regions:

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.

NOAA did the linear regressions for those tide gauges. In 2007 they did them using sea-level measurement data through 2006 for each gauge. In 2012 they redid the calculations for the U.S. gauges (only), using data through 2011. (I see that they’ve since updated them again, using data through 2012, but I haven’t updated my spreadsheet — sorry.)
Now, if the ocean is “sloshing up” along one section of coast, and “sloshing down” along another, think about what you should expect to see when comparing the 2011 linear regressions to the 2006 linear regressions.
In regions where the ocean is “sloshing up,” it means that the current year-to-year rate of sea-level rise is temporarily higher than its long-term average. So in those regions, as the analyzed time interval is extended (from 2006 to 2011), the current temporarily higher rate of SLR should cause the long-term average to increase. That is what has happened along the U.S. Atlantic coast, from northern North Carolina through Maine. For example, here’s Boston:
http://tidesandcurrents.noaa.gov/sltrends/sltrends_update.shtml?stnid=8443970
In regions where the ocean is “sloshing down,” the current year-to-year rate of sea-level rise is lower than its long-term average. So in those regions as the analyzed time interval is extended (from 2006 to 2011), averaging in the current (lower) rate of SLR should cause the long-term average to decrease. That is what has happened along the U.S. Atlantic coast from mid- North Carolina through Georgia, as well as along the U.S. Pacific coast. For example, here’s Wilmington, NC:
http://tidesandcurrents.noaa.gov/sltrends/sltrends_update.shtml?stnid=8658120
So that gives some evidence of an oscillation, but it doesn’t tell us its period. The question is, how long does the “slosh” persist, before it persistently reverses?
That’s no mystery. Here’s a quote from Zervas: “there was statistically significant multidecadal variability on the U.S. east coast with higher rates in the 1930s, 1940s and 1950s and lower rates in the 1960s and 1970s.”
Do you see it? Three decades down, followed by at least two decades up. Noting that ~2/3 of the U.S. east coast is once again seeing higher SLR rates, and has been for at least 20 years, it looks like about a 50-60 year oscillation: 1930-1960 up, 1960-198x down, 198x-2014 up, which is roughly consistent with the other papers.

Bill Illis
April 26, 2014 4:50 am

I found sea level trends in the PMSL database to have a trend of 0.29 mms/year from 1930 to 1980 (there isn’t enough global coverage before 1930). The rate rose to 1.4 mms/year from 1980 to 2009. Tiny hint of a 60 year cycle in there.
http://s2.postimg.org/xcp9tsz6x/Sea_Level_Measurements_PMSL_1930_1980_2009.png
I recently checked the database to see which gauges had been updated for 2010 or 2011 data. 300 gauges had been updated for 2010 or 2010 and 2011 and the average rise was 2.26 mm/year over an average of 1.7 years.
I guess I am more interested in is there acceleration in sea level from the tide gauges (I don’t think we can trust the adjustment algorithms from the satellites). Sounds like you now have solid database Willis in order to do this very important work.

April 26, 2014 5:56 am

I guess greg missed my point while willis got it.

Greg
April 26, 2014 6:48 am

I agree. The amount of modelling, calibration and “bias” adjustments needed to get sub millimetre accuracy of sea level with a typical swell of about a metre when you can only see the bottom of the swell from 1,336 kilometres away is a joke.
There is just too much opportunity for personal bias and preconceptions to creep in, even if those involved are doing their best to be objective: which I seriously doubt in many cases anyway.
Tidal gauges are the best we have, though like all this geo stuff the goalposts are forever moving as well as the ground they are dug into.
” (there isn’t enough global coverage before 1930).”
Well that’s a problem if you’re going to just cut off in 1930 because you won’t see the pre-1990 drop that is apparent in a large proportion of these tidal records. That automatically invites the erroneous conclusion of a small rise becoming larger rise. And it’s a small step from there to erroneous “accelerated global warming”.
This whole obsession with drawing straight line “trends” through everything is one of the biggest problems in climate science.
A linear model is wholly inappropriate and has no place on any such graph. Draw another one since 1995 and you will equally conclude ‘decelerating’ sea rise. Draw another up to 1940 and and you start to see a long term cycle.
As always it is selection bias that determines the result.

Greg
April 26, 2014 6:53 am

Steven Mosher says: I guess greg missed my point while willis got it.
You do make an art of not saying what mean , so don’t complain if your cryptic insinuations are not always read correctly.
Greg says:
April 26, 2014 at 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’.
====
I think I get your point but if I don’t perhaps you ought state clearly what it is rather than let people have to guess what you intended to infer.

ferdberple
April 26, 2014 6:54 am

so why would there be a 60 year global cycle in tidal levels? Where would the water go? There might be cycles at individual stations, but if the water is low at one it must be high at another, so unless the volume changes any sort of global average would hide the effects.
There might be a lunar cycle, as the moon’s orbit carries it above and below the equator, moving water north and south. This might be related (18 years) to drought and locust cycles (17 years), but it may simply be co-incidence.

Greg
April 26, 2014 7:00 am

“Where would the water go? ” It does not go anywhere, it’s thermal expansion.

ferdberple
April 26, 2014 7:09 am

Greg says:
April 26, 2014 at 6:53 am
I think I get your point but if I don’t perhaps you ought state clearly what it is rather than let people have to guess what you intended to infer.
============
academics (like the Law) avoid plain language like the plague, trying to pretend the reason we lesser mortals can’t understand them is because they are smarter then everyone else. when in reality they are poor communicators.
the art of good communication is to take the complex and reduce it to plain language so that the meaning is clear to all. failure to achieve this reflects ego more than intelligence.

Greg
April 26, 2014 7:11 am

“This might be related (18 years) to drought and locust cycles (17 years), but it may simply be co-incidence.”
I think perigee (8.85y) is more important in tidal effects, though this is complicated by how this ties in with declination angle.
http://climategrog.wordpress.com/?attachment_id=935
The major challenge is to decrypt and identify any periodic signal in the various time series before trying to explain them. This is usually done backwards. Someone starts with a pet theory and goes out to look for a direct correlation. When it’s not there as a direct unchanging correlation someone comes along and claims “therefore X is not a factor in climate”.
Climate is complex and has many causal influences. Some add other modulate each other, some have two way feedbacks eg radiation – temperature – radiation. which leads to exponential convolution responses.
http://climategrog.files.wordpress.com/2014/04/tropical-feedback_resp-fcos.png?w=843
One thing it isn’t is simple direct correlations and straight line trends. Sorry fellas 😉

April 26, 2014 7:18 am

Steven Mosher says:
April 25, 2014 at 7:49 pm
The bottom line is why would anyone think you could find a cycle.
=======================================================
Easy
Everyday up, everyday down
Sometimes several times a day

ferdberple
April 26, 2014 7:22 am

“Where would the water go? ” It does not go anywhere, it’s thermal expansion.
=================
the thermal inertia of the oceans makes a mockery of trying to measure this. the signal would be smeared over hundreds of years. there is no practical means to separate this from the noise given the relatively short time we’ve been keeping records.

Greg
April 26, 2014 7:26 am

” failure to achieve this reflects ego more than intelligence.”
Well it could be the result of being trained in language as an art form rather than a as dry, a down to earth means communicating factual information. Females also seem to be good at communication by innuendo then claim men are stupid because they need everything explaining.
Personally being a stupid , science trained male , I prefer people to say want they mean first time rather than waste half a day with inappropriate replies and arguments about who said what and what they really meant.

Greg
April 26, 2014 7:29 am

“the thermal inertia of the oceans makes a mockery of trying to measure this”
I think if you read up on this you will find vertical mixing is very limited and the thermal effect is just as important as melting land bound ice caps.

Greg
April 26, 2014 7:32 am

Much of the height difference in W. Pac warm pool is due to a “lens” of lighter warmer water rather this the idea of it “piling up” because of trade winds. As you say water is not too good at piling up unless pulled by barometric effects or tidal forces.

Bill Illis
April 26, 2014 7:44 am

I guess I can update some of my charts. 1930 to 2011 for tide gauges (although the last two years only have updated records for 306 of the 500 gauges which are supposed to be included in the database now).
http://s24.postimg.org/66rsbwk6t/Tide_Gauges_Sea_Level_1930_1980_2011.png
And then compared to other sea level reconstructions back to 1960 and the satellite composite (updated to mid-February and with its methodology revised again for the 30th time with a rise of 3.26 mms/year).
http://s30.postimg.org/521y5vloh/Sea_Level_Comparisons.png

Latitude
April 26, 2014 8:07 am

Greg says:
April 26, 2014 at 7:32 am
Much of the height difference in W. Pac warm pool is due to a “lens” of lighter warmer water rather this the idea of it “piling up” because of trade winds. As you say water is not too good at piling up unless pulled by barometric effects or tidal forces.
====
Also gravity from sea floor mountains and volcanoes….

Latitude
April 26, 2014 8:09 am

Greg says:
April 25, 2014 at 7:26 pm
Latitude I advise you to read that paper carefully before jumping all over the result because you like it. I’m not impressed for a number of reasons.
===========
Greg says:
April 26, 2014 at 7:26 am
Personally being a stupid , science trained male , I prefer people to say want they mean first time rather than waste half a day with inappropriate replies and arguments about who said what and what they really meant.
====
I didn’t say one way or the other….care to take your own advice?

Don Easterbrook
April 26, 2014 8:29 am

Several months ago, while looking up past sea level records, I was intrigued by the recent fall in the rate of sea level rise which occurred during the cooling trend over the same period. So I thought it might be interesting to look at sea levels over the past several hundred years, and took a look at the sea level curve back to 1700 AD (Jevrejeva et al.,2008). I first picked out some peak warm and cool periods and looked for anything resembling the 60-year PDO/AMO cycles. There was a nice sea level spike in 1850 during that warm period and a big downward spike in ~1804 during the Dalton cool period, but those didn’t stay up or down very long. By and large, sea level seemed to be oblivious to global temperature trends and no 60-year cycle seemed apparent, just as Willis found in much greater detail.
But what was even more interesting was an obvious change in sea level pattern that began about 1850. From 1700 to 1850, although sea level bumped up and down, the 150 year trend was essentially flat. Sea level in 1850 was the same as it was in 1700. There was a warm period about 1850 and sea level showed a spike that lasted a few years, then dropped back down to the 150 year level. But then something remarkable happened–sea level broke out of its 150 year stable pattern and began to rise steadily at a rate of about 2 mm/year for the next 150 years and it’s still going on. The post 1850 rise doesn’t seem to show any obvious cyclic pattern and doesn’t seem to react to warming and cooling trends. So the really interesting question is, what happened about 1850 to change from a 150-year stable sea level pattern to a constantly rising sea level pattern that has lasted for 150 years with no apparent regard for global warming and cooling? You might expect that during warm periods, in addition to sea water expansion you would also get some contribution from glacier melting, but that isn’t obvious in the sea level record, at least at this scale. So the really interesting question here is, what happened after 1850 to change from a 150 year pattern of sea level stability to the present 150 year pattern of pretty constant sea level rise that seems to be oblivious to global temperature changes?

Greg
April 26, 2014 9:13 am

lat: “I didn’t say one way or the other….care to take your own advice?”
I said exactly what I meant. I’m not going to go into an detail appraisal of another paper and spam this discussion. I did leave a comment on the thread you linked to. I just suggested here that you read that paper carefully and make up your mind.
attractive as the idea of 1mm/y may be, their paper did not impress me enough to give any credence to their results. It has some good points but I would not trust it without reproducing it and I don’t have time for that.

Greg
April 26, 2014 9:20 am

http://wattsupwiththat.files.wordpress.com/2014/04/three-detrended-global-sea-level-datasets.jpg?w=560
Don, bearing in mind that Willis plotted this detended, I’d say there is about a 15 year lag between d/dt(GMSL) and SST(t) just as a rough visual appraisal. I would not conclude “oblivious”.

Greg
April 26, 2014 9:35 am

BTW since we would expect GMSL to vary with SST not it’s diff, I also note that 15y is pi/2 lag for a 60y cycle.