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 3:04 pm

Here are some relevant papers:
http://sealevel.info/papers.html#howlong

April 25, 2014 3:09 pm

http://climategrog.wordpress.com/?attachment_id=933
Last time I looked at this paper, I concluded there was not enough detail of the method to reproduce it but there seems to be a clear 60 y cycle in the rate of change. It’s a lot less visible in sea level data.

AJ
April 25, 2014 3:09 pm

Willis… if you need some code to import the psmsl data into a single R dataframe, the following might be of interest:
https://sites.google.com/site/climateadj/nh-sea-level-reconstruction

April 25, 2014 3:26 pm

JJ paper used SSA and some kind of 30 year filter, so very heavily damped.
Perhaps the most signficant bit is that for the last century it’s clearly hovering about 2mm/y , not the 3.4mm/y claimed by satellite altimetry crews.

Kev-in-Uk
April 25, 2014 3:42 pm

Look, it is real simple and obvious to all but the most blind of observers – there is simply no way we have enough accurate data for sea level analysis, land or ocean surface temperature analysis, or basically any other fecking type of analysis one might wish to ‘believe’ one can undertake from current ‘datasets’ – It ain’t happening, and the sooner we realise how little we actually know, the better.. The earth and its biosphere is simply a massive perpetually moving and changing interaction of a bazillion (or more!) different positive and negative effects, all on different periodicities and interactive levels, NONE, I repeat – NONE – of which are known in any great detail ! (I won’t even comment on these bazillion interqctions being condensed into ‘models’! LOL)
When folk finally realises this, the issue (whatever it may be) simply disappears. Willis has easily shown that even the best sea level data cannot be tortured and forced to give up any underlying trend – frankly, I don’t see that ANY of the current climate knowledge and data is any better.

Latitude
April 25, 2014 3:52 pm

Where’s that paper that said 65% of tide gauges either show sea levels falling or no sea level rise at all…

Roger Dewhurst
April 25, 2014 3:54 pm

Kev-in-UK hits the nail on the head.

April 25, 2014 4:03 pm

Willis, is it possible that the tide gauge data need to be corrected for any isostatic movement of the land-base?

April 25, 2014 4:10 pm

A guy wearing partially tied sneakers, no belt with his pants dragging down his butt gets a job at a dairy farm.
Day 1
Worker is not trusted with the tender areas of cows gets to clean up around the cows, lays down fresh hay, fills up the feed trough when he notices that his sneakers are a different color and filled with stuff. Has to borrow some twine to try and tie his pants up.
Day 2
Worker shows up with cheap calf high rubber boots. Discovers the manure gutter chain is jammed and spends a couple of hours working in a gutter full of soggy manure. Vomits a couple of times. His new rubber boots were too short and easily filled with the juicy stuff. Decides he really needs better fitting pants and a belt.
Day 3
Worker arrives with the cheapest pair of hip boots sold at the hardware store. Learns from the farmer that the gutter chain is under maintenance and it’s availability is still unknown. Worker spends the day filling a wheelbarrow and moving manure to the crap wagon. Worker falls into the wagon a couple of times trying to successfully dump the manure in the wagon. As often happens the worker learns that rubber boots keep things from leaking out very well. Worker realizes that he hasn’t lost his breakfast all day.
Day 4
Worker arrives at the farm wearing Carhartt overalls with good quality for the price clodhopper work boots. Sets to work without dilly or dallying.
My apologies for the dairy farm worker introduction Willis. Just that I am getting rather amazed that you can open some of these data bases without losing your lunch. Even with repeated exposure it must be hard to keep your cookies where they belong sometimes.
Thank you Willis for opening these cans of worm goo! Sixty year cycle… After living and fishing the Gulf of Mexico for a number of years with it’s odd tides I certainly believe that it is difficult to find common frequencies amongst tidal records.

nutso fasst
April 25, 2014 4:24 pm

Any studies on how much sea level rise can be attributed to displacement by post-glacial rebound?

David L. Hagen
April 25, 2014 4:46 pm

Hi Willis
Scafetta is another author showing an ~ 60 year cycle in long sea level data.
Discussion on common errors in analyzing sea level accelerations, solar trends and global warming Pattern Recognition in Physics 1, 37-58, doi:
10.5194/prp-1-37-2013, 2013

“(1) multidecadal natural oscillations (e.g. the quasi 60 yr Multidecadal Atlantic Oscillation (AMO), Norther Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO) need to be taken into account for properly quantifying anomalous background accelerations in tide gauge records such as in New York City;”

See Fig. 2, Fig. 3 analyzing New York’s 1893 to 2011 record.
Look forward to your evaluation or testing of his methods.

April 25, 2014 4:49 pm

power spectrum of Church and White GMSL
http://climategrog.wordpress.com/?attachment_id=935
This is just a quick rough but seems reminiscent of what I found looking at the Jevrejava data last time this came up.
circa 10.x and 20.x possibly suggestive of solar , and 8.82 pretty surely the lunar apsides yet again.
So the same conclusion I’ve been pointing to for a couple of years now: attempts to attibutre the solar signal has phase crisises because there is interference patterns with the close by lunar periodicity.
Until climatology gets a grip on the importance of lunar apsides which seems to crop up anywhere there is the subject of water, they will not find a stable solar signal.
But since that suits them fine and they can pretend it’s all “stochastic noise” + AGW , I don’t suppose they are going to be looking too hard.

April 25, 2014 4:54 pm

Yeah interesting that median rate of sea level rise is 1.8 mm/y. The same as what i get eyeballing Jevrejava’s rate of rise graph above.
Now if [satellite] alitmetry says 3.4mm/y this it must all be piling up in mid ocean where there are not tide gauges !!

Rob Dawg
April 25, 2014 5:31 pm

Thank you sir. It is so much more difficult to expose the null than it is to imply a trend/cycle. You have done the near impossible.

Latitude
April 25, 2014 5:31 pm

Out of that 820 records, about 20% of them show falling levels
===
Bingo!
Here’s what I was looking for:
Abstract
The location of tide gauges is not random. If their locations are positively (negatively) correlated with SLR, estimates of global SLR will be biased upwards (downwards). We show that the location of tide gauges in 2000 is independent of SLR as measured by satellite altimetry. Therefore PSMSL tide gauges constitute a quasi-random sample and inferences of SLR based on them are unbiased, and there is no need for data reconstructions. By contrast, tide gauges dating back to the 19th century were located where sea levels happened to be rising. Data reconstructions based on these tide gauges are therefore likely to over-estimate sea level rise.
We therefore study individual tide gauge data on sea levels from the Permanent Service for Mean Sea Level (PSMSL) during 1807 – 2010 without recourse to data reconstruction. Although mean sea levels are rising by 1mm/year, sea level rise is local rather than global, and is concentrated in the Baltic and Adriatic seas, South East Asia and the Atlantic coast of the United States. In these locations, covering 35 percent of tide gauges, sea levels rose on average by 3.8mm/year. Sea levels were stable in locations covered by 61 percent of tide gauges, and sea levels fell in locations covered by 4 percent of tide gauges. In these locations sea levels fell on average by almost 6mm/year.
https://suyts.wordpress.com/2013/09/20/vindication-for-suyts-new-tidal-gauge-sea-level-paper-out-reports-1mmyr-sea-level-rise/

April 25, 2014 5:37 pm

Looking at the power spectrum , I think I can see where Jevrejava’s 60 years cycle is coming from (assuming here data is similar to Church and White.
http://climategrog.wordpress.com/?attachment_id=935
cos(2.pi.x/7.5) + cos(2.pi.x/10.2) = cos (2.pi.x/56.67) * cos(2.pi.x/8.64)
It’s the old radio amplitude modulation thing again.
Now I’m not a expert on SSA but it’s a bit like principal component analysis and picks out pairs frequencies. So it seems to be pulling out the 57 year periodicity.
Now a limitation of Periodicity Analysis is that it will only pull out a direct and constant amplitude repetition. Much of climate is about resonances and interference patterns and I fear P.A. may not be the most flexible tool to dig this sort of thing out.
I did also find a strong and highly symmetric AM triplet in the sub-annual frequencies that shows a very similar modulation frquency:
p2=0.96225
pc=0.94693
p1=0.931378
# as A.M. 0.947 * 58.060 ; triplet asymmetry: -0.039 %
Now that’s close enough with the accuracy of extracting the modulator from a triplet that this is very likely the same thing.
Now looking at the SI of the Chambers paper that is the subject here they are fitting 55 years.
[ Willis, look at the SI and you will which records they used. ]

April 25, 2014 5:54 pm

Solid.
I hope people who have issues with what willis
Has done download the data and have a wack
At it. I suspect some will give willis homework. Or at least
Try to give him more work to do.
I have no issues.
Solid

April 25, 2014 6:08 pm

On this matter of sea levels rising there is huge variation amongst scientists, from Al Gore’s figure of 65m per century to NIWA’s 1998 Lyttelton study of 1mm per year (10cm per century); a disparity of 65,000%. That degree of error disqualifies claims of plausibility, even throwing doubt on NIWA’s work.
With that degree of uncertainty, it is difficult to see how anybody can be sure the sea is rising at all. How, it may be asked, can 1mm change in sea level be calculated, averaged over one entire year or a hundred years, when even a flat sea at rest undulates more than that with waves every few seconds, and tide height just in one day varies by some two metres?
To say a tide height is higher we require knowing higher than what? To fairly compare tide heights one needs a past reference height to compare with one in the present. Finding the former is not possible because (at least 10) factors that influence tide height do not together repeat. We are talking of phase of the moon, lunar declination, perigee cycle, high and low pressure zones that can suck heights up or depress them, and winds onshore that can blow water into a harbour or offshore depleting a bay.
Equinox tides are higher than solstice tides. The sea is warmer in summer, therefore higher. Underwater earthquakes, eruptions, and fissures raise local sea-levels, most non-recordable and/or undetectable. Rainfall at sea, river flows and land run-offs contribute to sea-levels. Temperature changes control density and water volumes, ever-shifting in the ocean, and the direction of currents both deep, mid and surface, alter sea height. Cycles of glaciers’ advance and retreat change heights of the ocean.
In short, we haven’t a clue how high sea levels are ever supposed to be in any fixed place, to a tolerance of 1mm per year, when everything connected to the sea is in constant flux. The sea is not a lake or a pond. No computer model can pretend that it is, just for the sake of a neat result. Examinating old photographs, sketches and tide markers reveals high watermarks unchanged on NZ and Australian beaches, apart from erosion due to changing currents.
Disappearing sand is a cycle, a function of lower than normal sea levels because lower water undermines foreshore and top sand collapses. Without higher water to re-deposit sand higher up the shoreline, over a long time period a beach can ebb slowly away. Higher tides deposit more sand because sand is heavier than water – surf brings sand in by momentum of wave action, and leaves it there when water recedes. Erosion cycles are just that, cycles. If this was not cyclic, all sand on all beaches would have gone long before now.
Without monitoring over all oceans we cannot know if sea-levels are rising. We only have measuring devices on 0.4% on the earth’s surface where humans live. Special buoys now report via satellite using Argos transmitters, but we need to wait several centuries to achieve a reliable average to comment on any future century’s departure from average.
Antarctic and Arctic ice are thickening, which means sea levels are dropping. On Tuvalu and other island atolls it is the land that is moving, not the sea. Small atolls like Tuvalu cannot be sliding under the sea whilst beaches in Australia and NZ stay unaffected. How would the sea decide which countries to send beneath the waves?
As we emerge from this interglacial the poles are the smallest they have been in a while and some sea-levels the highest they aspire to. Some countries are still rebounding after the last ice age- Scotland is rising and the south of England is lowering. The west of Australia is rising whilst the east is dropping. There is a similar differential between NZ’s north and south island.
The high watermark on any beach varies up and down the sand by about a metre every 10 minutes. To that add just 1 millimetre per year, the thickness of a grain of sand. If this varies over 60 years it may be 60mm, or about 2.5 inches. If you stood there for 60 years you could miss it if you blinked.

George Turner
April 25, 2014 7:18 pm

[sarcasm]
Tide gauges only measure the height of the tide, not the quality of the tide. Due to global warming we’re getting more and more rotten tides, the kind that dump heroin needles and dead whales (killed by ocean acidification, heat stroke, and depression) on our beaches. It won’t be safe for children to play in the surf no matter what the sea-level is unless we drastically curtail CO2 emissions so that the tides return to a healthy normal.
[/sarcasm]

April 25, 2014 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.

Kelly
April 25, 2014 7:33 pm

http://nweb.ngs.noaa.gov/heightmod/NOAANOSNGSTR50.pdf
http://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?stnid=8764311
Mean Sea Level Trends for Stations in Lousiana
Water-level records combine data on ocean fluctuations and vertical motion of the land at the station. The sea-level variations determined by these records include the linear trend, the average seasonal cycle, and the interannual variability at each station. Monthly data through the end of 2006 were used in the calculation, and all stations had data spanning a period of 30 years or more.

riparianinc
April 25, 2014 7:41 pm

Note that if the gauge is in a subsiding location, the sink rate of the gauge must be subtracted from the apparent rise in the ocean. My understanding is that something like 74% of the seeming rise in the Gulf around Louisiana is really the land subsiding. The causes of the land change/land loss are as hotly debated as anything else related to climate but there is general agreement on the subsidence problem even though the causes and thus the corrective action (if any) remain unresolved.
See:
http://nweb.ngs.noaa.gov/heightmod/NOAANOSNGSTR50.pdf
http://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?stnid=8764311
Mean Sea Level Trends for Stations in Lousiana [sic]
Water-level records combine data on ocean fluctuations and vertical motion of the land at the station. The sea-level variations determined by these records include the linear trend, the average seasonal cycle, and the interannual variability at each station. Monthly data through the end of 2006 were used in the calculation, and all stations had data spanning a period of 30 years or more.

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