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

Greg
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

Greg
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.

Pat Frank
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?

ATheoK
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?

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.

Greg
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.

Greg
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/

Greg
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]

Greg
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.

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

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?

Oldseadog
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.

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.

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.

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.

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

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.

Björn
April 26, 2014 9:36 am

Willis, there is a superfluous space character clinging to the right end of the url in the link you put up to the large .xlsx sheet with the 1412 stations data. It clobbers the intended purpose and you only get small (700 bytes of html text ) error notice from dropbox if you try to download directly from it.
[Didn’t see it. What paragraph? Mod]
[Fixed, thanks, Mod and Bjorn. -w.]

April 26, 2014 10:22 am

@ Don Easterbrook/ Bill Illis/Willis
I think the point is that warmer water expands and therefore takes up more volume.
On the other side, more rain will also cause increase in sea level.
As we consider this plot
http://www.woodfortrees.org/plot/hadcrut4gl/mean:60/plot/hadcrut3vgl/mean:60/plot/hadcrut4gl/trend/plot/hadcrut3vgl/trend/plot/hadcrut4gl/last:360/trend/plot/hadcrut3vgl/last:360/trend
and provided it is true,
it seems that the whole of earth warmed up a bit, since 1850
it follows that as the water was heated more, over the years, by the sun,
the subsequent increased evaporation provided that extra heat that gave us more warmth.
The warmth is good for the greening of earth. The subsequent greening (also of the oceans), also with the help of mankind, traps more heat. The biosphere is booming. Hence the explanation of increasing water levels.
I hope this explains it, Don?
Willis found the 44 or 45 year cycle in the record, also in Vlissingen and if you take the two Amsterdam cycles it also gives an average of 45.
Strangely enough, these results do make sense to me.
My own results on maximum temperatures led me to this plot:
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
This shows that events related to whatever drives the weather (i.e I mean rain mostly) is on some 87 or 88 year cycle, but after every half cycle of 44 years you are back to zero.
Various investigations which I can quote show that the Gleissberg and DeVries/Suess cycles are real and happening. In both cycles we are now coming to the cooling side of the wave.
Notwithstanding the “current” records
http://www.woodfortrees.org/plot/hadcrut4gl/from:1987/to:2015/plot/hadcrut4gl/from:2002/to:2015/trend/plot/hadcrut3gl/from:1987/to:2015/plot/hadcrut3gl/from:2002/to:2015/trend/plot/rss/from:1987/to:2015/plot/rss/from:2002/to:2015/trend/plot/hadsst2gl/from:1987/to:2015/plot/hadsst2gl/from:2002/to:2015/trend/plot/hadcrut4gl/from:1987/to:2002/trend/plot/hadcrut3gl/from:1987/to:2002/trend/plot/hadsst2gl/from:1987/to:2002/trend/plot/rss/from:1987/to:2002/trend
my results seem to point to a greater rate of global cooling,
happening now.

Matthew R Marler
April 26, 2014 10:25 am

Because the 60 year period was hypothesized based on considerations external to this data set, and prior to analysis of this data set, you can simply test (using a model that is a straight line plus a cosine curve with amplitude and phase estimated) whether there is a significant 60-year period in each series. Then count how many of the corresponding F-tests of the cosine curve, out of ca 1400, are statistically significant, or do the histogram/pdf estimate of the p-values. You don’t have too many parameters for each series: mean, slope, amplitude of cosine, phase of cosine, residual error variance, autocorrelation coefficient (most likely, first-order autoregressive noise is adequate for each series, something that you can test.)
Your rule of requiring a series at least 3 times as long as the longest period is a great rule for when exploring whether there is any periodicity in the data; but when the period is hypothesized a priori, it is not necessary. Also look at the histogram/pdf estimate of the phases to see whether the diverse series are all in phase. Given the dynamics and known lags (as in your “ENSO pump” graphical analysis), there is no necessity that the series all be in phase.
If you don’t want to, I may do this. I have done it lots of times with circadian rhythm modeling where the rhythm, if present, is known to have a period of 24 hours. (I said “if present”; it came as a surprise that there is a circadian rhythm in blood concentrations of prolactin in healthy men; no one to my knowledge has tested whether there is a circadian rhythm in blood testosterone in healthy women, but if there is one it has a period of 24 hours.) You only need data over one full period to estimate and test the rhythm. If you suspect some other periodicity, then you need at least 3 days data for exploratory analyses.

Matthew R Marler
April 26, 2014 10:34 am

some references, or blatant self-promotion:
9. M.R. Marler, R. Jacob, J.P. Lehoczky, and A. Shapiro. Statistical analysis of treatment and activity effects in 24hour ambulatory blood pressure monitoring. Statistics in Medicine 7:697716, 1988.
21. M.L. Rao, G. Gross, A. Halaris, G. Huber, M.R. Marler, B. Strebel, and P. Braunig. Hyperdopaminergia in Schizophreniform Psychosis: A Chronobiological Study. Psychiatry Research, 47: 187203, 1993.

BobG
April 26, 2014 10:50 am

The question was asked – why do we expect to see a 60 year cycle? For me, that brought up the question, what would I expect to see in the data given what I know and believe? Thinking about it, my answer was that I think that there has not been a great deal of change in the rate of melting of glaciers in the last 150 years – nothing out of the ordinary in the context of the Holocene. The same is true for the ice caps. Therefore, I think the main reason for sea level changes above and beyond that caused by sinking or rising land masses is changes in heat content of the ocean. The heat content of the ocean given it’s size and depth are long term slow changes. And given how the ocean sloshes around, I would expect the data to be somewhat noisy. Looking at Willis’s data, it seems consistent with this view. But what about oscillations in part of the ocean? On that point, there are “oscillations” that are well known such as the PDO or AMO among others. I would expect that those could have a regional impact on sea level gauges. I’m not sure about the degree of impact or the exact period of any oscillation but given the PDO and AMO are real and do have an impact on the ocean and planet, they should have some impact on sea level. Therefore, I would not be surprised if Daveburton is correct about regional oscillations.

Greg
April 26, 2014 10:57 am

[Didn’t see it. What paragraph? Mod]
You won’t “see” it , its come non displaying character. (maybe non-braking_space char)
Same problem with the CSV file. The .csv extension has an invisible cruft-char too.

Greg
April 26, 2014 11:03 am

Oh no, its a common space char #32 aka “%20” . Means if you do Save_as you get an error page in HTML and no data, that is mysteriously unavailable usless you quote the filename and add the invisible space after .csv
I suspect the others are the same.

Neil Jordan
April 26, 2014 11:22 am

Two general comments. First, The 18.6-year Metonic Cycle for tides is recognized as being large enough to affect surveyed coastal boundaries. I made a comment about that in “Sea level rate of rise shown to be partially a product of adjustments” Posted on January 24, 2013:
http://wattsupwiththat.com/2013/01/24/sea-level-rate-of-rise-shown-to-be-partially-a-product-of-adjustments/
In part, I quoted the American Council of Surveying and Mapping reference to an approximate 18.6-year cycle known for some time as the Metonic Cycle. The cycle is the basis for
the 19-year tidal epoch used to define the sea level datum. See ACSM Bulletin at the
NOAA website:
http://tidesandcurrents.noaa.gov/publications/Understanding_Sea_Level_Change.pdf
My full comment is at
http://wattsupwiththat.com/2013/01/24/sea-level-rate-of-rise-shown-to-be-partially-a-product-of-adjustments/#comment-1208839
Second, NOAA published a technical report on vertical land motion relative to sea level
http://tidesandcurrents.noaa.gov/publications/Technical_Report_NOS_CO-OPS_065.pdf
available at FEMA’s coastal website here
http://www.fema.gov/coastal-flood-risk-resources#Guidance
Technical Report NOS CO-OPS 065 “Estimating Vertical Land Motion from Long-Term Tide Gauge Records” is written for coastal engineering and design community, rather than the climate science community. Long term sea level rise is taken as 1.7 mm/year from IPCC 2007, not the often-quoted 3 plus values. Of particular note is this paragraph in the introduction:
[begin quote]
The purpose of the methodology is to provide a more accurate estimation of local VLM at tide stations with 30-60 years of data rather than just simply subtracting the estimated global sea level trend of 1.7mm/yr from the observed relative mean sea level trend. Relative sea level trends calculated from shorter data periods are more likely to be affected by anomalously high or low oceanographic levels at the beginning or end of their series. By removing the regional oceanographic variability as calculated based on longer-period stations, both more accurate and more precise estimates of land motion are possible at shorter-period stations.
[end quote]
Note “. . .anomalously high or low oceanographic levels at the beginning or end of their series.” These anomalies might be another consequence of what you described in your earlier post:
http://wattsupwiththat.com/2014/04/24/extreme-times/

April 26, 2014 11:32 am

Ah, well, something I hadn’t noticed before, the PSMSL archive happens to attach ID numbers by station age, so even though there’s no column for that, the ID column itself acts lets you list the stations by age, more or less.
http://www.psmsl.org/data/obtaining/
Some of the oldest *do* show some acceleration, mostly but not all via a pivot point in the 1920s between linear trends. But thankfully for skeptics at least, the official Church & White 2011 update finally included a simple average of tide gauges that I extracted and added a poor man’s trend line to, and it shows utterly no acceleration, one of the most devastating plots for climate alarmists since they are now claiming the impossible that the deep oceans are heating up but not then also expanding more than usual:
http://oi51.tinypic.com/28tkoix.jpg

Editor
April 26, 2014 11:38 am

Matthew R Marler says:
April 26, 2014 at 10:25 am
… you can simply test (using a model that is a straight line plus a cosine curve with amplitude and phase estimated) whether there is a significant 60-year period in each series. … If you don’t want to, I may do this. I have done it lots of times with circadian rhythm modeling where the rhythm, if present, is known to have a period of 24 hours.

Let me take you up on this then please.
The DMI has provided me with a text file from 2007 – 2013 for each hour’s dry bulb temperature, pressure,wet bulb temperature, wind speed and wind direction for an Arctic site at 80 north latitude.
My assumptions:
Each data field will vary over a 24 hour period.
However, each daily value – for example, Taverage (for the day), Tmaximum – Tminimum (for the day), relative humidity each hour, pressure, etc – will also vary periodicaly over the length of an entire year.
Given 7 years of data, I would expect to be able to generate a function adequately calculating each parameter as a function of hour-of-day and day-of-year, right?

Greg
April 26, 2014 11:40 am

Also seems what ever Willis is using stores csv files in old mac format with no linefeed chars.
dos2unix -c mac “Willis Files.cvs”

lgl
April 26, 2014 11:45 am

Sea level changed ~2 mm/yr first half of 20th and ~2,5 mm/yr last half of 20th but dropped to 0-0.5 mm/yr after high volcanic activity, so there should be a ~9 and a ~80 yr cycle.
http://virakkraft.com/Sea-level-change-volcanoes.png

April 26, 2014 11:49 am

lgl says
http://virakkraft.com/Sea-level-change-volcanoes.png
henry says
You want me to find a mirror?

Greg
April 26, 2014 11:59 am

“I would expect to be able to generate a function adequately calculating each parameter as a function of hour-of-day and day-of-year, right?”
A sort of 365.25×24 element climatology you mean?
Check out Wilis’ links to the PA software and use 365.25×24 as the window repetition.
“each daily value ….will also vary periodicaly over the length of an entire year.”
otherwise I have a simple awk script that can do this for an arbitrary window length. I can post that up if you’re interested.

Greg
April 26, 2014 12:05 pm

lgl says:
Sea level changed ~2 mm/yr first half of 20th and ~2,5 mm/yr last half of 20th but dropped to 0-0.5 mm/yr after high volcanic activity, so there should be a ~9 and a ~80 yr cycle.
http://virakkraft.com/Sea-level-change-volcanoes.png
===
Any correlation you are seeing there is in your own head.

Editor
April 26, 2014 1:01 pm

Greg says:
April 26, 2014 at 11:59 am

(replying to RACookPE)
“I would expect to be able to generate a function adequately calculating each parameter as a function of hour-of-day and day-of-year, right?”

A sort of 365.25×24 element climatology you mean?
Check out Wilis’ links to the PA software and use 365.25×24 as the window repetition.

“each daily value …. will also vary periodically over the length of an entire year.”

otherwise I have a simple awk script that can do this for an arbitrary window length. I can post that up if you’re interested.

If I understand you correctly, yes – sort of.
But if we were to create a look-up table with a simple average of each hour’s data, then the “weather” variations over every day would need further smoothing and manipulation, right? Since I’m trying to approximate the as-found average “weather” on an hour-by-hour basis up north to get hourly heat transfer approximations, I’d prefer to “smooth” the data over the entire year with a single function. However, since no part of any weather pattern is a simple sinusoid at any time interval, you can’t really reduce things to nice simple sine or cosine curves. (Which could be a part of the problem of trying to find “perfect” periodicities in past yearly data…)
For example, I can develop an equation adequately reproducing the DMI average temperature plot for 80 north latitude (from the WUWT Sea Ice page) over a 365 day year.
So, Tave(day-of-year) = A + B*(DOY) + C*(DOY)^2 + D*(DOY)^3 + E*(DOY)^4 + F*(DOY)^5 + … which works as long as DOY never gets below 0 nor higher than 366. Not elegant, but adequate.
Then, if Tmax-Tmin varies over the year over the 7 years of data, that too, can be calcualted on a day-of-year basis.
And, if T(hour) varies consistently and predictably over the year between Tmax (about 14:00 hours) and Tmin(05:00 hours), then getting T(hour-of-year) for every day of the year is straightforward.
From T(hour-of-year), P(hour-of-year), wind speed (hour-of-year), and relative humidity(hour-of-year), you can get Heat lost by evaporation(hour-of-year), heat lost by convection(hour-of-year), and heat lost by long-wave radiation (hour-of-year).

Greg
April 26, 2014 1:08 pm

Ah ha! As my spectral analysis of the Church & White reconstruction showed the 7.5 and 10.2 I found would produce a 57y modulation
I just dug NY Battery out of W’s csv file took the first diff and applied a 2y filter to make it more legible:
http://climategrog.wordpress.com/?attachment_id=936
The circa 60y modulation is clearly visible.
I also found a sub-annual periodicity had a 58 y modulation too.

Greg
April 26, 2014 1:25 pm

“Tave(day-of-year) = A + B*(DOY) + C*(DOY)^2 + D*(DOY)^3 + E*(DOY)^4 + F*(DOY)^5 + … which works as long as DOY never gets below 0 nor higher than 366. Not elegant, but adequate.”
How many poly terms will you need to represent 365 days worth of fluctuations?! I would have thought an FFT approach would have been more suitable. Or perhaps more flexible the PA breakdown that Willis used.
FFT is limiting because of the way the frequency intervals work. That’s why I use chirp-z. which frees it up. You can then pick off the precise frequencies of the main peaks and build a truncated harmonic reconstruction.
While I think of it, if you are working with wind speed consider whether v^2 is what you need to use. Most things like sea evaporation and energy depend upon the square.

lgl
April 26, 2014 1:27 pm

Greg
Who said correlation?
I said sea level change drops after high volcanic activity. Show me one large eruption without a sea level change drop a few years after.

Greg
April 26, 2014 1:28 pm

“And, if T(hour) varies consistently and predictably over the year between Tmax (about 14:00 hours) and Tmin(05:00 hours), then getting T(hour-of-year) for every day of the year is straightforward. ”
I very much doubt that you will find a constant-ish daily cycle that holds through the Arctic winter and the daylight periods.

Greg
April 26, 2014 1:41 pm

“Show me one large eruption without a sea level change drop a few years after.”
Well it’s hard to see on that messy upside down pastiche you presented but it looks like Santa Maria misses and for Mt Pinatubo the drops starts before the eruption so suggesting causation gets a bit tricky unless you close both eyes and peep through your lashes.
El Chichon happens once the AOD has nearly returned to normal , then you have massive heg swings that have nothing to do with any volcanic events. That again makes attributing coincident events rather speculative if they are not different from the variability in the rest of the data when there are no volcanoes.
That is why I mentioned correlation. If there’s a connection , as it appears you are trying to suggest, there must be a correlation. Otherwise the effect is a just like seeing a face in the clouds.

Kasuha
April 26, 2014 2:01 pm

Thank you for interesting and as far as I see correct analysis of data and final conclusion. I really wonder what method could have the paper authors used.
I tried to download your data files to take a look at it myself but I got an “Error (400)” for both links.

Greg
April 26, 2014 2:26 pm

See notes above for the link. There’s an extra spaced got added to the end like “.cvs ” and “.xlsx ”
Copy the link and paste in a new window, then edit off the space 😉

Greg
April 26, 2014 2:35 pm

Just had a look at Honolulu. 7.5 and 10.2 still notable peaks but very strong 9.08 and 21.4 y too.
This is the ubiquitous 9.1 +/-0.1 that can be found just about everywhere in SST it seems and Scafetta claims in aurora data. This is lunar. The 21.4 looks solidly Hale cycle . Surprised to see that come out so clearly.
It seems that, like SST, this needs to be analysed regionally otherwise a lot of valuable information gets muddied out.
Chambers et al got that much right and looked at the details of phase too. Its a shame that they did not do a more general frequency analysis.

Greg
April 26, 2014 2:37 pm

could a climate denier please fix the links to Willis’ files 😉
[Fixed. -w.]

April 26, 2014 2:38 pm

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

otsar
April 26, 2014 3:56 pm

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

Greg
April 26, 2014 4:06 pm

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

SplatterPaterns
April 26, 2014 5:52 pm

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

April 26, 2014 6:24 pm

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

RoHa
April 26, 2014 7:07 pm

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

Neil Jordan
April 27, 2014 1:12 am

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

Greg
April 27, 2014 2:32 am

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

Greg
April 27, 2014 2:39 am

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

Greg
April 27, 2014 2:42 am

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

Greg
April 27, 2014 2:56 am

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

Greg
April 27, 2014 3:10 am

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

Greg
April 27, 2014 3:40 am

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

April 27, 2014 4:40 am

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

Greg
April 27, 2014 5:01 am

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

April 27, 2014 5:25 am

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

April 27, 2014 5:29 am

Sorry.
it seems I copied and pasted the wrong link.
This is the graph I was referring to.
http://ice-period.com/wp-content/uploads/2013/03/sun2013.png

April 27, 2014 6:50 am

Willis says
I used to suffer from advanced cyclomania as well,
Henry says
In fact, a lot of people do, and a lot of people did,
before they started with the carbon dioxide nonsense.
Here is a good paper on that
http://www.cyclesresearchinstitute.org/cycles-astronomy/arnold_theory_order.pdf
Without the cycles we would not be here,
In fact the only way to understand climate is to identify the cycles we are in….
Here is my final report on that
http://blogs.24.com/henryp/2013/04/29/the-climate-is-changing/

Greg
April 27, 2014 8:35 am

Well, I’m just running power spectra for some of the long MSL records here and the one common factor so far is a strong circa 21 year peak.
Very little around 10.4-11 , nothing consistent.
Looks like polarity is fundamentally important. Just goes to show you never know what to expect before you get on your bike and start cycling 😉

Matthew R Marler
April 27, 2014 9:40 am

RACookPE1978:Each data field will vary over a 24 hour period.
However, each daily value – for example, Taverage (for the day), Tmaximum – Tminimum (for the day), relative humidity each hour, pressure, etc – will also vary periodicaly over the length of an entire year. Given 7 years of data, I would expect to be able to generate a function adequately calculating each parameter as a function of hour-of-day and day-of-year, right?

If you are fitting hourly data over several years, then you would add in the known periodicity of 365 days. You probably need an interaction term, as the day/night variation probably depends on the phase with respect to the 365 day period. I don’t know if “adequately” is correct here, but both the 24hr and 365day periods should be at least statistically significant for any station (e.g. series) with enough data. Note that NH and SH series should be a half period out of phase on the 365 day rhythm; the NH and SH series at the same longitude should be in phase on the 24hr rhythm.
As you wrote it, Tave is only once per day, so it should not have a 24 hour rhythm, but anything measured hourly probably does. If you expect a 24h or 365 day period, but not a sinusoidal shape, you can nonlinearly transform the cosine curve in a variety of ways to get a variety of shapes:
M. R. Marler, P. Gehrman, J. E. Martin, S. Ancoli-Israel, The Sigmoidally-transformed Cosine Curve: A Simple Mathematical Model for Circadian Rhythms with Symmetric Non-sinusoidal Shapes. Statistics in Medicine, 25:3893-3904, 2006, presented at the poster session at the Joint Statistical Meetings, Aug 2005.
Transforms like that have been used to model the on/off behavior of melatonin and cortisol secretion, among others.

Matthew R Marler
April 27, 2014 9:58 am

Willis Eschenbach: In other words, what you propose is exactly what I’ve done.
Except that you only used a small number of long sequences. You can’t find a weak signal that is present in all series that way. And from the point of view of a statistical test, you used up all the degrees of freedom on effects that are not there. Generally, if you have an actual hypothesis of a particular period, as here, you get better statistical power with a method that focuses on that period, and less chance of seeming to identify a spurious “period” in a selected series. (Lower type 1 and type 2 error rates.)
I wrote that, because of lags, the series will not all have the same phase, but they should have phases within a few years of each other. If you find that the phases are all concentrated in a narrow region of years, instead of being uniformly distributed, that is additional evidence that the period is actually there, assuming that it has some external driver. In the example of the prolactin rhythm in healthy adult men, for example, all the peak time (phase hour of the cosine) estimates were within a few hours of each other, though no peak or peak time was itself well estimated — something that has an extremely low probability of occurrence if in fact the rhythm is absent.)

April 27, 2014 9:59 am

Greg says
the one common factor so far is a strong circa 21 year peak.
Henry says
Well, you should concentrate on that one….!!!
Back in 1985, William Arnold had it all figured out that the Hale-Nicholson cycle of 21-22 years is steered by the motion of the planets. My own results merely confirmed his findings plus I was able to get the turning dates figured out, give or take a year.
The Hale-Nicholson cycle is exactly a quarter of the Gleissberg.
You will all figure it out if you study my final report on it.

Matthew R Marler
April 27, 2014 10:17 am

Willis Eschenbach: For example, for about three sunspot cycles in the second half of the 20th century, the sea level varied pretty much in parallel with the sunspots … and since the period of the sea level cycle is was hypothesized to be ~11 years from the sunspot period, then according to you only one 11-year cycle would be required to confirm the hypothesis, and three cycles would establish it beyond doubt..
That is definitely a good cautionary example. One would never want to draw too strong a conclusion from an analysis such as I presented. Is there a period in the data set that we have? That is only the first question, but I think it should be addressed with the statistically most powerful method. Does it persist in future data? Is it reliably related to hypothetical causal influences?
As always, thank you for your thoughtful work.

April 27, 2014 10:37 am

@Greg
Best is to ignore Willis. He is just like Leif. Must be horrible to live with people like that. No doubt they are single. They simply donot or cann ot accept anyone simply disagreeing with them.
Anyway, I forgot to tell you about the deVries/Suess cycle.:
http://www.nonlin-processes-geophys.net/17/585/2010/npg-17-585-2010.html
Abstract. Spectral analyses performed on records of cosmogenic nuclides reveal a group of dominant spectral components during the Holocene period. Only a few of them are related to known solar cycles, i.e., the De Vries/Suess, Gleissberg and Hallstatt cycles. The origin of the others remains uncertain. On the other hand, time series of North Atlantic atmospheric/sea surface temperatures during the last ice age display the existence of repeated large-scale warming events, called Dansgaard-Oeschger (DO) events, spaced around multiples of 1470 years. The De Vries/Suess and Gleissberg cycles with periods close to 1470/7 (~210) and 1470/17 (~86.5) years have been proposed to explain these observations. In this work we found that a conceptual bistable model forced with the De Vries/Suess and Gleissberg cycles plus noise displays a group of dominant frequencies similar to those obtained in the Fourier spectra from paleo-climate during the Holocene. Moreover, we show that simply changing the noise amplitude in the model we obtain similar power spectra to those corresponding to GISP2 δ18O (Greenland Ice Sheet Project 2) during the last ice age. These results give a general dynamical framework which allows us to interpret the main characteristic of paleoclimate records from the last 100 000 years
end quote
So the DeVries cycle is about 10 x the Hale-Nicholson cycle. I just wish I knew where we are in this cycle, I suspect we are on the cooling side? Have you any ideas on that?

April 27, 2014 11:50 am

Steven Mosher
I got one word
Henry says
Over the years you have proven yourself to be a man of few words.
They did not help much, either.

April 27, 2014 12:08 pm

Henry: RIF
but for you, here is a synopsis
“Business cycles, and their rhythms, have long fascinated and perplexed economists. Why do economic booms alternate with recessions, decade after decade? And why do graphs of long-term data on gross domestic product, employment and other economic indicators form undulating patterns similar to physical phenomena such as ocean waves or sound waves? Over the past 150 years, all sorts of explanations have been put forth for recurrent peaks and valleys in economic activity—economists have hypothesized forces as seemingly far-fetched as sunspot activity and rainfall patterns as the cause of these cyclical patterns in national and world economies.
By the early 20th century, some researchers believed that chance occurrences like wars, crop failures and technological innovations played a role in business cycles. But no one fully appreciated how crucial random (or “stochastic”) processes are to the workings of the economy until Eugen Slutsky, a Soviet statistician and econometrician, did the math. A middle-aged professor working at a Moscow think tank, Slutsky was virtually unknown to economists in Europe and the United States when he published his landmark paper on cyclical phenomena in 1927.1
In a bold statistical experiment, Slutsky demonstrated that random numbers subjected to statistical calculations similar to those used to reveal trends in economic time-series formed wavelike patterns indistinguishable from business cycles. The implication was that a similar stochastic process—“the summation of random causes,” as Slutsky described it—might be at work in the actual economy, causing prosperity to ebb and flow without the agency of sunspots, meteorological patterns or other cyclical forces.”
In short, cyclical behavior can arise from the summation of random forces.
Finding a cycle ( 60 year or otherwise) tell you Nothing about its cause. Even if it is correlated with another 60 cycle, that still tells you nothing about the cause.

April 27, 2014 1:43 pm

Now let me explain my question. People think they Will find a cycle because they hope the climate governed by one cause. Its not. Not just the sun and not just co2. Instead its controlled by many factors. Some increasing slowly some decreasing some with cycles some random shocks.

Greg
April 27, 2014 4:26 pm

Thank you.You were correct. I did not get what you meant. It would have been more effective to say that a few days ago when there was still some traffic on this article.
“… the climate governed by one cause. Its not. Not just the sun and not just co2. Instead its controlled by many factors. ”
I point i have re-iterated many times, including in this thread.
That is why global averages do not advance our understanding, they just muddy the waters.
It’s like listening to 20 different types of music all at once in the hope that it will all average out and you will discover some fundamental truth about musical structure.
If you choose the start and end points of the “ensemble” carefully you may conclude that, on the average, music tends to gets louder and louder the longer it goes on. At which point you’ll whip off the headphones before it reaches a tipping point and blows your ear-drums out.
Yes, the human mind does like simple explanations. Another favourite is the word stochastic.

April 27, 2014 7:59 pm

“That is why global averages do not advance our understanding, they just muddy the waters.”
Wrong.
As a system we know the climate is determined by certain governing equations: namely
energy out = energy in + energy stored. At equilibrium when its all said and done, energy out = energy in. When that system is out of balance we know it can restore balance by increasing
temperature. The global temperature (at 2m) is a system diagnostic. It does not tell us the whole picture, but it gives us a slice of the system state. The OHC is perhaps a better diagnostic but the record there is short. A global average doesnt muddy the water unless you look at it as the only metric. It provides a glimpse into the state of the system.

April 27, 2014 11:51 pm

Willis says
In this case, Mosh’s one word (accompanied by a very informative link) is all that was needed …
Henry says
well, it seems to me Mr. Mosher realizes that you cannot say that in one word, as he now says:
Steven Mosher says
energy out = energy in + energy stored. At equilibrium when its all said and done, energy out = energy in. When that system is out of balance we know it can restore balance by increasing
temperature. The global temperature (at 2m) is a system diagnostic. It does not tell us the whole picture, but it gives us a slice of the system state. The OHC is perhaps a better diagnostic but the record there is short. A global average doesnt muddy the water unless you look at it as the only metric. It provides a glimpse into the state of the system.
Henry says
I would re-phrase his equation:
energy-in = energy-out – energy stored.
A reasonable proxy for energy-in is maximum temperatures.
And who else but me is looking at that now?
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
A reasonable proxy for energy-out is means.
On my own results, because it has been globally balanced, I can do a reasonable bi-nomial fit on means as well.
Now, my A-C wave for the drop in maximum temperatures obviously does not reflect exactly at the same time what happens to temperatures on earth. As stated, earth has an intricate way of storing energy in the oceans. There is also earth’s own volcanic action, lunar interaction, the turning of Earth’s inner iron core, electromagnetic force changes, etc.
So, I am not looking for a 60 year cycle. I know what is important is to look at the cycle of what energy is coming in. That is the 87 year Gleissberg, consisting of 4 Hale-Nicholson cycles. These are the ones I can see.
I hope that my planets arrive in time, as otherwise I do know where we will end up with the global cooling.
If you are stubborn enough not wanting to take a look at the energy coming in, ie. that what is being allowed through the atmosphere, (not TSI only), then you will not be able to predict as to what climate change is coming.
http://blogs.24.com/henryp/2013/04/29/the-climate-is-changing/

Matthew R Marler
April 27, 2014 11:58 pm

Willis: However, I keep waiting to hear from you what “the statistically most powerful method” reveals about the putative signal, whatever that method might be.
Fair enough: if I think that the statistically most powerful method is to focus on the 60 year period in all the data, I ought to do it myself.

Matthew R Marler
April 28, 2014 12:27 am

Steven Mosher: http://economics.sas.upenn.edu/~fdiebold/Teaching/Course2010/slutsky.pdf
Good link.
It’s worse than that. Everything that you think you discover in a finite time series might not continue as the process that is measured continues. Every finite time series can be fit within any predefined accuracy by a polynomial of high enough order, and you can be nearly certain that the polynomial will not adequately predict the future. Contrariwise, a chaotic process with an approximate period does not stay in phase, and if you have a long enough time series you can’t identify the approximate period, even if it persists.
What to do when the “signal” you are looking for probably isn’t there, and is likely weak if it is there (due to many other causal agents acting concurrently)? Big Pharma tests thousands of compounds annually for clinically relevant biological activity, and abandons research on 99% of them. Some companies decide to skip that endeavor and manufacture drugs that other companies discover and patent. It might be more efficient not to do any research at all, and it certainly has a lower type 1 error rate, if that is what concerns you most; but if there is anything to discover, the generic companies won’t discover it.
Except for a few obvious rhythms, discovering periodicities requires assiduous work and produces a high type 1 error rate. I think we are stuck with that.

Greg
April 28, 2014 4:13 am

Mosh’ “A global average doesnt muddy the water unless you look at it as the only metric.”
Sadly the whole concept of “global warming” is, by definition, just that.
Then the magic work “stochastic” is used to discount everything but the long term trend as “internal” , gleefully ignoring that there is no reason that the long term variation is not , by equal argument, also “stochastic”.
We’ve wasted the last 30 years having heated arguments about a useless metric.

Alan Robertson
April 28, 2014 5:38 am

Steven Mosher says:
April 25, 2014 at 5:54 pm
“I have no issues.”
_________________
I ain’t touchin’ that…

April 28, 2014 6:48 am

Steven Mosher says
Not just the sun and not just co2. Instead its (the weather?) controlled by many factors. Some increasing slowly some decreasing some with cycles some random shocks.
Henry says
I cannot believe that after all these years you indeed still would think that a 100 ppm CO2 could possibly be a factor that is warming earth. I am sure I have explained this before but I will do it again. All that is happening as a result of a bit more CO2 is that the earth’s biosphere is booming.
http://wattsupwiththat.com/2011/03/24/the-earths-biosphere-is-booming-data-suggests-that-co2-is-the-cause-part-2/
Now as a result, the increasing greenery traps some heat. You can see that from my results. For example, in Las Vegas minimum temperatures rose sharply, as a desert was transformed into a green paradise. OTOH where mankind decided to cut the trees down, for example in Tandil, Argentina, minima dropped sharply, see here:
http://blogs.24.com/henryp/2011/11/10/de-forestation-causes-cooling/
So, all that is trapping some heat, is the increase in greenery. The problem is that people want more lawns, more trees and more crops. So in a nutshell, that is the whole AGW problem. It is as simple as that.
So, Mr. Mosher, I want to ask you a question. What do you want? We have grown used to you running away when you are asked something. But be honest now, don’t you think that more greenery and some* more warming is better than global cooling?
*Be careful. According to certain estimates from the 1970’s that (green) AGW cannot really be all that much, in total.
We will not be able to stop the natural global cooling, and subsequent loss in greenery, that is coming.
http://blogs.24.com/henryp/2013/04/29/the-climate-is-changing/

Greg
April 28, 2014 2:39 pm

W: “But then he thinks that the Jevrejeva smoothed data is susceptible to spectrum analysis”
No Greg thinks SSA _is_ a form of spectral analysis and Jevrejava did not report the numerical results, so I’m wondering/guessing what the components of that SSA were.
It looks similar to the 54 + 64 year periodicities you found in the Amsterdam long series but seem intent on insisting are not there.
As I pointed out many times, superposing two close cosines will produce a modulated cosine that has the average of the two components found by spectral analysis. Two non harmonic periodic repetitions will produce a similar effect plus some non harmonic “noise”.
It appears, as I said above, that there is some Mannain window-filling going at the start and end of JJ’s graph (simple repetition padding IMO).
http://climategrog.wordpress.com/?attachment_id=933
Just a quick lash up to reproduce that kind of form using values similar to (but different for brevity) the Amsterdam PA given by Willis:
http://climategrog.wordpress.com/?attachment_id=938
mean freq (54,64) = 58.6 years. This roughly reproduces the circa 60y bumps in J’s rate of change graph. This demonstrates how you can have a 58.6y variability with ZERO 58.6y component in the spectral analysis, be it FFT, chirp-z or P.A.
This is not numerology , it is pure, precise mathematics.
It would be preferable by far if scientists would actually publish their results rather than just pics, when they publish.
Now if that estimation of her results is correct the impression that acceleration is easing is false. There is a constant linear increase in rate of change in that plot.
So after all the virtual tide gauges, SSAs, EOFs and windowed wavelets we still don’t know the bottom line of Jevrejava’s study because she did not do us the courtesy of actually publishing her results.

Greg Goodman
April 28, 2014 4:22 pm

“In fact, multiple lines of evidence show that the system is highly resistant to changes in forcing”
That is one thing we agree on. At least in the tropics, which is a key region for the control of energy input.
The following article is still at a draft stage and lacks the punch line. The text needs work but I think the physics is pretty close.
Fitting the fully developed climate response not just the instananeous dT=lambda.dF gets closer to explaining what is going on.
http://climategrog.wordpress.com/?attachment_id=884
Having argued for some time that volcanic forcing was exaggerated, I found that it is under-estimated. It is just the final impact that is exaggerated.
Roy Spencer pointed out in on his site that TOA flux returned to pre-eruption levels after just a year, when AOD was still at 50% of its peak:
http://climategrog.files.wordpress.com/2014/03/tropical-feedback-adjusted.png?w=814
Because modellers refuse to use “parameters” that give the strong negative feedbacks like those Willis suggests they had to rig the carefully calculated optical forcing of Lacis et al in 1992.
I found the best fitted value was slightly more than Lacis ( 33 instead of 30) well with his range of values. But for that to work you need a strong negative tropical f/b that neuters the volcanic impact within a year.
The delay in response that comes from the thermal inertia explains the post-volcanic tropical recovery that I showed in my volcano stack analysis.
In view of the physics based work of Lacis , current values appear to be an attempt to fix the models by fudging the inputs instead of correcting the model.

1sky1
April 28, 2014 5:27 pm

“Periodicity analysis” in climatology pre-dates Sethares & Staley’s IEEE paper by at least half a century. That’s indeed how the annual cycle is established for subtraction from monthly data in obtaining “anomalies.” The authors clearly state, however, that “the p-periodic basis elemnts are fundamentally coupled together” and nowhere even hint that this a suitable technique for general signal analysis purposes. In fact, they call attention to the “integer periodicity limitation.”
Ironically, with dominant tidal constituents crudely removed by monthly averaging of tide-data and the annual cycle removed by Willis here, nothing truly periodic is left in the sea-level data to analyze with this simplistic technique.

Bart
April 28, 2014 6:48 pm

The ~60 year quasi-cyclical component contained within the temperature data is not some sorta’, kinda’ looks similar phantom. It’s an amazingly precise formation (given the quality of the data) which has repeated twice with extremely close repetition of amplitude and period. The likelihood of it being just a random luck of the draw is very small. The coolly dismissive reference to Slutsky is an exercise in burying one’s head in the sand.

April 28, 2014 11:41 pm

As predicted, it seems Steven Mosher has left the arena. He does not want to be challenged.
Look at the rubbish he writes here:
http://static.berkeleyearth.org/pdf/skeptics-guide-to-climate-change.pdf
All that wasted effort by climate scientists on the harmless 100 ppm CO2 having been added to the atmosphere instead of doing a new evaluation of exactly how much energy is really consumed by the biosphere (land + oceans)

Greg
April 29, 2014 1:31 am

Bart says The ~60 year quasi-cyclical component contained within the temperature data is not some sorta’, kinda’ looks similar phantom
Which part of the title are you having trouble following Bart?
“The Elusive ~ 60-year Sea Level Cycle”

Bart
April 29, 2014 8:33 am

Greg says:
April 29, 2014 at 1:31 am
Just trying to keep the obvious quasi-cyclicality in the temperature data from being tarred under the same rubric, Greg. As has been discussed elsewhere, I believe the ~60 year quasi-cycle in the temperature data results from a combination of lunar tidal and solar intensity forcings. So, I would not expect to see an actual kinetic ~60 year oscillation in the tides, themselves.
What I would expect to see in the tides is the intrinsic slosh modes of the ocean basins being excited by the rigid body motion of the Earth. I have very preliminary findings suggesting that this, in fact, can be observed. Eventually, I will post these results for others to review. But, this is a very complicated problem, involving transmission delay across the oceanic expanses and reverberations against the shorelines. I have not had time to thoroughly examine my results to make a strong case as of yet.

April 29, 2014 9:42 am
April 29, 2014 9:45 am

Willis says
http://wattsupwiththat.com/2014/04/25/the-elusive-60-year-sea-level-cycle/#comment-1624529
Henry says
why being so aggressive toward Bart?
What I have seen from him is that he is brilliant in mathematics, and he told us he is working on it, did he not?

April 29, 2014 11:05 am

Willis
‘Ah, the famous fallacy of the excluded middle. Once again you recycle the tired alarmist argument that when forcing gets “out of balance” the only way to restore balance is by increasing temperature.”
Wrong.
Quote my words. I never would argue this is the ONLY way to restore balance
There might be other ways to restore the balance. None have been identified.
Maybe its unicorns.
The argument that the system restores balance by warming is a hypothesis. There might be other ways, you are welcomed to describe in detail ( with equations) some other way.
Quote my words. I like that

April 29, 2014 11:26 am

Henry
Perhaps now you understand why I am cryptic. My hope is that you were curious. That the cryptic comment would get you to read, RATHER THAN BLATHER.
But even when I give you a synopsis you choose to blather.
“Steven Mosher says
Not just the sun and not just co2. Instead its (the weather?) controlled by many factors. Some increasing slowly some decreasing some with cycles some random shocks.
Henry says
I cannot believe that after all these years you indeed still would think that a 100 ppm CO2 could possibly be a factor that is warming earth. ”
#############################
of course its a factor. All the working physics I know tells me that if your increase the forcing
to a chaotic system That there will be an effect. Think butterflies on steriods. It will have an effect.
The question is : What effects? how big? when will manefest? will they make any noticeable difference. You farting will have an effect. Hopefully small.
##########
I am sure I have explained this before but I will do it again. All that is happening as a result of a bit more CO2 is that the earth’s biosphere is booming.
http://wattsupwiththat.com/2011/03/24/the-earths-biosphere-is-booming-data-suggests-that-co2-is-the-cause-part-2/
1. what makes you think that increase c02 has any effect here?
2. You havent proved that it isnt something else
3. The greening is well within natural variability
4. We have had a greener planet in the past with lower Co2
5. C02 cant cause the planet to green, its only a trace gas
/sarc off
####################
“So, Mr. Mosher, I want to ask you a question. What do you want?
1. world peace.
2. A conservative in the white house
3. A new pair of shoes.
“We have grown used to you running away when you are asked something. But be honest now, don’t you think that more greenery and some* more warming is better than global cooling?”
1. You dont owe me answers. I dont owe you answers.
2. I am under no rational obligation to ‘stick around’
3. I gave you something to read. I cannot demand you read it, you cannot demand
that I stick around to see if an old dog learned a new trick
4. Information is power. I choose who gets to learn. Your test is to take the clues
and learn. I will not spoon feed lazy people.
5. I provide a reading list. be a good student or not. your choice.
Now for your stupid question.
more greenery? how much
some warming? how much?
global cooling? how much?
better? better for who? better when? how much better?
I choose not to bother with value questions. The value judgement is conditioned by the facts.
And we dont know how much warmer or how much greener. We know the direction..
more c02 ( that trace gas) will create a warmer world ( all things being equal ) and will
create a greener world ( all things being equal)
How do we know?
Well we do lab experiements with plants and we do lab experiements with C02.
We know from these experiments that more c02 means a greener world and a warmer world.
And we know from biology (for plant growth) and from physics (for warming) why this is.
What next? well the world is not a lab. we cant do controlled experiments.
We can observe that in the real world when we add c02 we get a warmer world (as predicted in 1896) and we also get a greener world.
The evidence for both theories — more c02 = warmer greener– is about the same.
I accept both.

April 29, 2014 11:54 am

steven mosher says
blah blah blah
henry says
the question was if you want a greener world (= a warmer world)
or not

April 29, 2014 12:04 pm

Steven Mosher says
1. what makes you think that increase c02 has any effect here?
henry says
is it possible that S.Mosher really has never ever heard of photosynthesis?

Greg
April 29, 2014 12:06 pm

∆T = λ ∆F
where lambda ( λ ) is the climate sensitivity, delta-T (∆T) is the change in global surface air temperature, and delta-F (∆F) is the change in forcing.
To believe that equation, you have to, must, need to believe that (as you strongly imply in your post) only a change in temperature can rebalance the system … sorry, not true in the slightest.
===
There are a couple of other ways of restoring the balance. The biggest one, of course is a slight change in the time of onset of tropical clouds.
====
You seem to be implying that ∆T = λ ∆F only refers to Plank feedback, it does not. It includes anything , including cloud formation and tropical storms that is a reaction surface temperature.
It implies that if there is a change in radiative forcing this will result in a change (leaving the linearity to one side) in the equilibrium temperature. It does not dictate that the radiative response to temperature is the only thing causing this result.
For example, if there is a strong negative feedback in the tropics, that we both consider to be the case, that feedback has to be a reaction to something and it is not directly reacting to the presence of more or less radiation. As your explanation would have it, it is a local response to higher SST changing the frequency and timing of tropical storms.
Now as with steam-engine centrifugal governess and the rest, even a strong negative feedback will not restore the non forced state of the system, it will settle at a much reduced but finite change in the controlled variable. SST in this case.
A strong negative feedback will thus give a small lambda, not zero. A new equilibrium is reached at a slightly higher temperature that maintains the required frequency / timing of TS and cloud cover.
The fact that TS have internal +ve f/b and are highly non-linear , does not prevent the averaged f/b effect of the change in timing from being approximately linear and being part of “lambda”.
My draft article shows that a volcanic forcing 50% stronger than currently used values causes a feedback that peaks about 12 mo after the eruption when AOD is still at 50% of its peak value.
http://climategrog.wordpress.com/?attachment_id=884
That is presumably the minimum in the induced drop in SST and the latest onset of TS, if that is the principal f/b. Since the feedback is strong, the temperature change is small. Roy Spencer got reasonable results trying to correlate the change in TAO and SST but in view of size of the change in relation to the variability in the rest of the tropical SST record, attribution seems seems speculative (unless I’m missing the means to do that). It may be corroborative but I don’t see it as conclusive.
That model can explain the initial few years. It does not explain the definitive offset in TLS, and the likely warming of the troposphere that this implies.
http://climategrog.wordpress.com/?attachment_id=902
Whether that can also be shown to be shown to be a persistent negative feedback mechanism or simply a one-off counter effect seems beyond currently available data.
In short, I don’t see why your tropical feedback hypothesis cannot fit the equation you cited. At least as a first approximation.

Bart
April 29, 2014 12:11 pm

Willis Eschenbach says:
April 29, 2014 at 9:29 am
It’s not that hard to see. Very regular. Same amplitude. Same rise time. You have to not want to see it to miss it.

April 29, 2014 12:48 pm

@bart
http://www.woodfortrees.org/plot/hadcrut4gl/from:1900/detrend:0.75/plot/hadsst2gl/from:1900/detrend:0.75/plot/hadsst3gl/from:1900/detrend:0.75
the SST 2 (green) seems a bit strange around the WWII area, perhaps it (the cooling) is a bit anomalous there ?\
so it (the bending point) could run a bit further naturally to around 1950
The on-going decline towards (current) global cooling seems inevitable
I am not against a mixture of solar/earth-lunar cycle, setting the earth’s temperature.
However, the energy coming in is what will set the tone, in the end, I am sure.
Back in 1985, William Arnold had it all figured out that the Hale-Nicholson cycle of 21-22 years is steered by the motion of the planets. My own results merely confirmed his findings plus I was able to get the turning dates figured out, give or take a year.
The Hale-Nicholson cycle is exactly a quarter of the Gleissberg, 87 years
You will all figure it out if you study my final report on it. Take out some time for that some day and let me know what you think?
http://blogs.24.com/henryp/2013/04/29/the-climate-is-changing/

Greg
April 29, 2014 1:11 pm

Bart says: “It’s not that hard to see. Very regular. Same amplitude. Same rise time. You have to not want to see it to miss it.”
Bart, if it’s so easy to see why do you link yet again to SST ? Tell me about GMSL , I want to see it.
I see indications of it spectral analysis but there’s a lot else in there, and Jevrejava’s graph, which is also a spectral technique seems to show it (whatever that is in numbers is anyone’s guess).
I see frequency components in Willis’ Amsterdam plot that will result in a 57y component but again there’s a lot else in there.
My conclusion is that there is a circa 60y signal buried in there but there’s so much else going on it is not readily seen in the time series.
If, as Chambers suggests, there is different phase geographically, global averaging will lose it.
“It’s not that hard to see. Very regular. Same amplitude. ”
Let’s see it !

Bart
April 29, 2014 1:19 pm

Greg says:
April 29, 2014 at 1:11 pm
But, I don’t expect to see it in GMSL, as I explained above.

Bart
April 29, 2014 1:24 pm

HenryP says:
April 29, 2014 at 12:48 pm
Might we suppose the WWII glitch could be related to disruption of regular measurements during that time?
I will bookmark your page and try to take a look when I have time. I’m skeptical, in general, of planetary influences, because gravitational coupling is so weak, but… well, I’ll take a look.

Reply to  Bart
April 29, 2014 1:40 pm

@bart
Thx!
It is the planets that affect the sun. I am sure we will see another polar switch on the sun in or around 2016.
Do understand that there is quite a lag between energy in (maxima) and energy out (mean earth temp.)

Greg
April 29, 2014 4:11 pm

“the SST 2 (green) seems a bit strange around the WWII area”
This is hardly news to anyone. McIntyre was onto this about a decade ago. I call it Folland’ Folly. A pretty ridiculous 0.5 step adjustment to SST was made at 1945. It now get blended to it does not stick out like a sore thumb but I doubt where that makes it more justified.
http://judithcurry.com/2012/03/15/on-the-adjustments-to-the-hadsst3-data-set-2/

Greg Goodman
April 29, 2014 4:56 pm

Bart says: “But, I don’t expect to see it in GMSL, as I explained above.”
OK, I don’t know what you have on this. My hypothesis is that it is basin-wide, long period tides in the thermocline. They have the same origin as surface tides but the interface at the thermocline has a density difference about a thousand times less that the air/water surface. This means that the typical period of the oscillations will be about 1000 times longer.
Compared to a 12h tide that is the stimulus that the surface tides respond most strongly too, that is about 1.4 years. ie we are looking for a response measured in a few years. I suspect this is the origin of El Nino. Look at 3D animations of the thermocline depth and it is quite simply a slow acting wave.
These “pseudo periodic” phenomena are just several harmonic responses added to each other, similar to the complex variations in surface tidal amplitudes. From time to time there’s “spring tide” and we call it El Nino.
If you look at what is currently happening in the equatorial depth profile of temp, you see an El Nino like formation in the Pacific that is not coming from the surface waters as usual “slosh” myth would have it. It must be coming from non equatorial latitudes.
Consider that the recent lunar eclipse was just about 10d after the equinox and you have maximum tidal forces focused on the equator thus drawing water in bulk form both N and S Is suspect we will see a stronger El Nino build up next year as the eclipse will be within days of the equinox. Such a resonant tidal pattern does not have to be in phase with the driving force, bit it’s the first thing to look for.
The whole Pacific seems to have regions both in-phase and anti-phase with PDO. That again suggests basin-wide tidal oscillations.
These are just qualitative observations, I don’t have numbers and wave equations !
There is a 15% difference in max apogee and min perigee. That implies a 45% change in lunar tidal at the most extreme. That is one hell of change in 14 days. How that cycle ties in with lunar declination angle means the whole thing will look “chaotic” unless some serious analysis is performed.
This is why many are tempted to jump to the easy conclusion and attempt to sound learned in their ignorance by using fancy words like “stochastic” to mask their failure to analyse the system.
Hopefully some of that will key in with what you are doing.
regards, Greg.

Greg Goodman
April 29, 2014 5:01 pm

“Dear heavens, you are seriously claiming that you can diagnose is an ~70 year cycle in 115 years of data? That’s Nostradamus level madness …”
Hell, mainstream manage to predict 100 into the future with a 95% certainty, based on a sloppy match to 1960-1990 hindcasts, . Why can’t we play too ? 😉

Greg Goodman
April 29, 2014 5:27 pm

http://www.woodfortrees.org/plot/hadsst3nh/detrend:0.8
I’m more inclined to see a folded (rectified) cosine than a pure harmonic.
Same abs(cos(2.pi.x/135)) idea seems to match Arctic ice
http://climategrog.wordpress.com/2013/09/16/on-identifying-inter-decadal-variation-in-nh-sea-ice/

Greg Goodman
April 29, 2014 5:28 pm
1sky1
April 29, 2014 7:03 pm

Chambers et al. use”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.” The means by which they reach their conclusion that there is such an oscillation remains behind the paywall. I merely provide the heads-up that “periodicity analysis” is not suitable for finding such a quasi-periodic oscillation, whose amplitude, phase, and frequency can vary widely. On the basis of PSMSL’s averaging of tide-gauge data over calendar (not lunar) months and your removal of a linear trend and annual cycle, I simply conclude that “nothing truly periodic is left in the sea-level data to analyze with this simplistic technique.” Signal components can be obscured or destroyed by inept data handling, in the direct converse of the Slutsky effect.
You respond with: “Instead of doing even a scrap of actual work, you want to stand around and tell me how smart you are. Here’s a protip, 1sky1. You’ll look smart when you find the cycles. Until then, you just look unpleasant. Those that can, do. Those that can’t, stand around and bitch. So far, you’re in Group B. If you’re so damn smart, then where are your results?”
I make no claim, one way or another, on the open question of a ~60yr component in GLOBAL sea-level variations. You’re the one who does that! Your personal attack is a hilarious attempt to turn the tables. It’s solely YOUR responsibility to provide a scientifically CREDIBLE analysis.

Bart
April 29, 2014 7:38 pm

Willis Eschenbach says:
April 29, 2014 at 4:46 pm
Oh, come off it, Willis. Nothing before 1900 is reliable. The error bars are as large as the variation. There is no scientific precept which says you have to fit all the data you have, no matter how unreliable or unrepresentative it may be. Science would never advance under such a rule.
As for how long the mode has been excited in this way anyway, who can say? This is NOT a wholly deterministic system we are dealing with. The cycles can ebb and flow. This is normal when you are dealing with highly nonlinear and complex, natural systems.
Here, we have two whole, very regular, cycles. It is meaningful. It is not coincidence or, rather, if it is, it is one helluva big one.
I wish I could find the conversations I had with, I think it was Pat Frank, on these pages when we were trying to determine if there had been a turnaround in the mid-2000’s as you would expect of an at-least quasi-cyclical phenomenon with ~60 year period. I remember stating quite clearly that I did not think we could say so yet. The idea was gaining currency in many corners. SkS even had a page dedicated to debunking any notion of a ~60 year periodicity.
By 2009, I think it was, it had become evident that the turnaround had arrived in about 2005, right on time. You can wait around for the next one if you like. It should happen sometime in the 2030’s. The rest of us are moving on.
Greg Goodman says:
April 29, 2014 at 4:56 pm
We may be heading down similar paths. I have been pursuing a lead based on the recognition of this phenomenon. I believe there is possibly, if not likely, a beat phenomenon of the tides with the solar cycle alternately storing and releasing heat which leads to the ~60 year quasi-cycle.
“This is why many are tempted to jump to the easy conclusion and attempt to sound learned in their ignorance by using fancy words like “stochastic” to mask their failure to analyse the system. “
Depends on what they mean by “stochastic.” If they mean, “it’s totally random or chaotic, and we can’t do anything with it,” then it is a cop out.
Stochastic does not generally mean unpredictable. There is structure here, along with processes which are so complicated or chaotic that a probabilistic model is needed to make it all tractable. We have fairly deterministic forcing from lunar and solar tides, but very complex fluid dynamics and variable solar activity.

April 29, 2014 11:01 pm

bart says
By 2009, I think it was, it had become evident that the turnaround had arrived in about 2005, right on time. You can wait around for the next one if you like. It should happen sometime in the 2030′s. The rest of us are moving on.
henry says
you can see it clearly from 2002 onward
http://www.woodfortrees.org/plot/hadcrut4gl/from:1987/to:2015/plot/hadcrut4gl/from:2002/to:2015/trend/plot/hadcrut3gl/from:1987/to:2015/plot/hadcrut3gl/from:2002/to:2015/trend/plot/rss/from:1987/to:2015/plot/rss/from:2002/to:2015/trend/plot/hadsst2gl/from:1987/to:2015/plot/hadsst2gl/from:2002/to:2015/trend/plot/hadcrut4gl/from:1987/to:2002/trend/plot/hadcrut3gl/from:1987/to:2002/trend/plot/hadsst2gl/from:1987/to:2002/trend/plot/rss/from:1987/to:2002/trend
Strangely enough, from my own data, especially on maxima, I could already see it coming from 2000 and you can calculate from the change in the warming speed that the original change at the sun took place in 1995. So, it takes 7 to 10 years to notice the change…..
http://blogs.24.com/henryp/2013/02/21/henrys-pool-tables-on-global-warmingcooling/
Bart, in the end for that graph for the drop in the speed of maximum temperatures I decided it must be sinusoidal, as otherwise we would end up in an ice age?
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
Do you agree?
So, whatever is coming out on earth (means) is also a bit like a wave, although not necessarily having to look exactly like that of the energy being allowed through the atmosphere. Hence, my prediction that arctic ice will only start increasing again from 2020-2040 (corresponding with 1930-1950 in the Gleissberg)
The fiddling with the data in the past does not make it any easier for us. Also, I have challenged anyone to show me a re-calibration certificate of a thermometer before 1940. Nobody has been able to show me one yet. That makes me very skeptical of all the data before 1950. I would trust my own data more than any other data set. Also, all global data sets are not properly globally balanced, see here,
http://wattsupwiththat.com/2014/04/25/the-elusive-60-year-sea-level-cycle/#comment-1622942
My own data set tells me that we already dropped by -0.2 K since 2000. I am busy updating my tables and adding 2012 and 2013 to my data set and it makes it even looking worse than that……
Note that we are globally cooling from the top latitudes downward. For example, it has been cooling significantly in Alaska, at a rate of -0.55K per decade since 1998 (Average of ten weather stations).
http://oi40.tinypic.com/2ql5zq8.jpg
That is almost one whole degree C since 1998.
And then you have people like Steven Mosher who tried to twist and turn these data (from Alaska).
Instead, we should warn the farmers in Alaska that it is not going to get any better there for the next 3 decades.

Greg
April 30, 2014 5:29 am

Bart: “We may be heading down similar paths. I have been pursuing a lead based on the recognition of this phenomenon. I believe there is possibly, if not likely, a beat phenomenon of the tides with the solar cycle alternately storing and releasing heat which leads to the ~60 year quasi-cycle.”
I did an article about this time last year that showed that there was a signficant circa 9y signal in many SST ocean basins. I pointed out that would disrupt any solar signal leading to just the kind of “phase crisis” that is used to refute the presence of a solar ( Schwabe cycle ) infulence on climate.
http://climategrog.wordpress.com/2013/03/01/61/
Recent attempts to explain the beats phenomenon to Willis ended in tears.
There is strong 9.1 in cross-correlation of N.Atl and N.Pac SST. In fact I’m fairly sure that this period ( also reported by Scaffeta ) is itself a combination of 8.85 (perigee) and 9.3 ( 18.6/2 ) . The mean freq of those two being 9.04, usually reported as 9.1 +/- 0.1 . That gives a modulation of 365 _years_ . I won’t go into that now but you may like to reflect that its a one day per year drift.
Since the solar cycle if far from being this regular the result is not so nice and simple but does produce variations of around 60 years.
There’s also 8.83 in the power spect. of Church & White’s GMSL that I linked above.
http://climategrog.wordpress.com/?attachment_id=935
I think one of the major causes of the lunar signal is water mass being attracted in and out of the equatorial regions. The leads to variations between tropics and temperate latitudes that get neatly average away in the usual : one-size-fits-all global means. There’s a residual but it causes get lost due to phase difference.
Once we start to regional analysis, and apply normal systems engineer approach there is a chance we may start to learn a little about what drives climate.

Greg
April 30, 2014 5:43 am

I think you have a mistake in your link:
T1 = 11*9.3/(11+9.3) = 5 years
It is the mean freq 11*9.3/(11+9.3)*2 , ie 10.1 y with those figures, that gets a 120 y modulation ( ie 60y beats).

Greg
April 30, 2014 5:47 am

That’s the problem, people see a circa 10y seems to ‘roughly match’ SSN for a while , but then gradually drifts out of phase, ending up completely in anti-phase. Those will little understanding of interference patterns take this as definitive proof that there is NO solar signal and it’s all wishful thinking and cherry-picking. And there is a lot of cherry-picking going on by those who don’t understand the phase shift and just choose to look at the bits which fit !

Greg
April 30, 2014 6:03 am

The modulation profile of 120 y modulation is the 60y “beats” that have a folded cosine amplitude ( ie not sinusoidal ) this is what I think we see in NH SST and cyclone energy.
http://climategrog.wordpress.com/?attachment_id=215
This is one area where the P.A. technique Willis favours may be helpful. Fourier techniques lead a lot of people to assume harmonic variation when it is not the case.
For example you look a spectra of NH SST it will tell you about 60y , not 120, unless you are skilled enough to look for the other harmonics the build up the true profile. This is why we need engineers on the job not environmental activists.

Greg
April 30, 2014 6:13 am

For the modulation envelop of “beats” to be visible after it has all been smoothed by natural processes or filtered in data processing requires either some process to “rectify” the signal ( like is done in radio demodulation) or some non linearity in the system.
One possible ‘rectifier’ is wind speed , which affects many variable with it’s magnitude and thus looses the sign or direction. There is also plenty of scope for non linearities ( again wind for ex. ) that will also lead to a residual of the 60y envelop.
Some try to dismiss this kind of analysis as “cyclomania” without realising that this is exactly the kind of interaction that leads to chaotic nature of climate.
Yes it is complicated, as are many engineering problems. Saying it random is a cop out.

Bart
April 30, 2014 7:46 am

Greg says:
April 30, 2014 at 5:29 am
Interesting. Thanks. In looking at a few tide gauges via PSD analysis, I have not been able to tease out a 9.3 year signal. But, I have seen specific formations repeating at a 1/9.3 years^-1 interval, which suggests further modulation, which I have thought might be indicative of forcing at 1/9.3 years^-1 modulated by reflections off the shoreline due to the physical limits of the basins. But, I have not had time to delve into this very far, and this is just my first impression.
I will have to review your findings to see where they lead.
Greg says:
April 30, 2014 at 5:43 am
No, it’s the correct formula, because
cos((2*pi/T1)*t) * cos((2*pi/T2)*t) = 0.5* ( cos((2*pi*(1/T1+1/T2))*t) + cos((2*pi*(1/T1-1/T2))*t) )
You are going the other way:
cos((2*pi/T1)*t) + cos((2*pi/T2)*t) = 2*cos(pi*(1/T1+1/T2)*t) * cos(pi*(1/T1-1/T2)*t)
This idea is that the intensity of the Sun is “gated”, if you will, by the physical state of the oceans, whether they are extended beyond their basins to receive more radiant energy, or settled in them to consolidate what they have received. That produces a modulation, as in the first formula.
Greg says:
April 30, 2014 at 6:03 am
Yes, it’s not really a “beat”. Because the periods are so close together, you really cannot designate one the carrier and one the signal. It looks like this. Which looks not unlike this.

April 30, 2014 10:57 am

henry@bart
I see you did some work on SSN finding a 20 and 23.6
That seems a lot like the Hale-Nicholson cycle to me.
Last time I looked at SSN I was sure that the way they recorded SSN has changed over time.
Anyway, since then I keep a look at this graph:
http://ice-period.com/wp-content/uploads/2013/03/sun2013.png
Clearly, you can see that the polar field strengths of the sun are dropping?
In fact, even without having the original data, I can see a binomial best fit, hyperbolic, coming from the top down and reaching its lowest point at around 2015 or 2016. From the bottom, parabolic, reaching its highest point around 2015 or 2016.
You agree?
All of that makes my theory very simple:
I figure that there must be a small window at the top of the atmosphere (TOA) that gets opened and closed a bit, every so often. Chemists know that a lot of incoming radiation is deflected to space by the ozone and the peroxides and nitrous oxides lying at the TOA. These chemicals are manufactured from the UV coming from the sun. Luckily we do have measurements on ozone, from stations in both hemispheres. I looked at these results. Incredibly, I found that ozone started going down around 1951 and started going up again in 1995, both on the NH and the SH. Percentage wise the increase in ozone in the SH since 1995 is much more spectacular.
The mechanism? We know that there is not much variation in the total solar irradiation (TSI) measured at the TOA. However, there is some variation within TSI, mainly to do with the E-UV. It appears (to me) that as the solar polar fields are weakening, generally a larger amount of more energetic particles are able to escape from the sun to form more ozone, peroxides and nitrogenous oxides at the TOA of earth/.
You concur?

Bart
April 30, 2014 11:55 am

HenryP says:
April 30, 2014 at 10:57 am
Yes, it is very clear that the approximately 10, 10.8, 11.8, and 134 year components evident in the SSN data are coming from rectification of processes centered at approximately 20 and 23.6 years.
As for solar UV, I do not know of any source where that has been tracked. I supposed it couldn’t have been tracked for very long.
Your idea is not the one I am pursuing, so of course I cannot concur with it 😉 But, it would be very interesting to see long term data on UV variation if it exists anywhere.

April 30, 2014 12:42 pm

@bart
thx
if you read william arnold’s report,
you will find that he puts 4 cycles (Hale-Nicholson) in an a-c wave (4 quadrants) , which gave me the idea of putting the drop in the speed of maximum temperatures in an a-c wave.
he is not in favor of the 11 year Schwabe
but prefers the 22 year Hale-Nicholson
which seems a lot like an average of the 20 an 23.6 that you found…….
it might be a good idea to go back to his (ancient?) report as my own findings support exactly what he found, albeit that his dates might be a bit out.
http://www.cyclesresearchinstitute.org/cycles-astronomy/arnold_theory_order.pdf
It is not solar UV TOA that is important
we are looking beyond UV, at X-ray and further towards zero um coming from the sun
that is what is making Ox, HxOx and NxOx at the TOA.
In a way these chemical reactions TOA protect us from certain death due to radiation.
They absorb or deflect harmful UV and non-harmful UV to space.
If there is more of it they deflect more of it
but it is exactly the UV which is what mostly heats up our oceans……
That is what is causing cooling and warming periods.

Greg
April 30, 2014 2:17 pm

Bart: “Yes, it’s not really a “beat”. Because the periods are so close together, you really cannot designate one the carrier and one the signal. It looks like this. Which looks not unlike this.”
Well if it’s not a beat don’t call it a beat. No reason not to suggest one of two close frequencies modulating the other , just don’t confuse things by calling it “beats” which has a well established meaning.
Having two additive frequencies is more relevant to SPD since that is unfailingly what fourier linke techniques do. They have no way to express a modulated signal so always give additive components. If there is a physical modulation, FFT will always give the lefthand side of you second expression which is identical to the real modulaiton on the RHS.
Half the sum of the frequencies ( aka the average ) is what you see in the time series. It is amplitude modulated by half the difference. Since the eye (like the ear) usually missed the fact that the phase inverts we tend to see the repetition as being twice as fast as it is mathematically. This gets called beats. So thiat is simply the freq difference.
>>
No, it’s the correct formula, because
cos((2*pi/T1)*t) * cos((2*pi/T2)*t) = 0.5* ( cos((2*pi*(1/T1+1/T2))*t) + cos((2*pi*(1/T1-1/T2))*t) )
>>
That’s a bit of a special case because the both amplitudes are the same on the LHS. Physically things are not often modulated right down to zero amplitude like that. Usually the higher frequency (carrier in the radio analogy) is greater in amplutude and does not totally disappear at any stage. This leaves a symmetic “triplet” of frequencies. In radio, modulation depth is cnosen to be less than half ( which is confusingl called 100% modulation 😉 ) . This leaves the central peak at least twice the size of the side bands. There is no reason that limitation will be present in a natural modulation.
An example of the a triplet in arctic ice coverage:
http://climategrog.wordpress.com/?attachment_id=757

April 30, 2014 2:21 pm

Alaska.
Instead of cheery picking 10 stations, use them all
http://berkeleyearth.lbl.gov/regions/alaska
The problem with picking 10 stations is that your error of prediction is large.
Remember an “average” of temperatures is really not a physical thing. What it is is this: a prediction.
Its a prediction of what the temperature would be at locations where you didnt measure.
And its easy to test. You take your stations ( there are 300 ) you build the average with 150
That allows you predict what you are likely to see at other locations. You then test that by
using the out of sample data.
When you show your method minimizes error and is BLUE then your estimate using all the data
is BLUE and minimizes error.
Until you do this analytic test your method is just garbage. worse than HADCRUT

Greg
April 30, 2014 2:31 pm

“It looks like this: http://s1136.photobucket.com/user/Bartemis/media/60yearcycle_zps994247be.jpg.html?sort=3&o=0 which looks like this http://www.woodfortrees.org/plot/hadcrut4gl/from:1880/detrend:0.75/mean:15/mean:15
Well this is what I mean about muddying the waters. NH and SH behave differently. I suggest keeping them separate. Land changes twice as fast as SST and with slightly different phase. Mixing the two again muddles the signal and impedes analysis.

Greg
April 30, 2014 2:38 pm

http://www.woodfortrees.org/plot/hadsst3nh/from:1880/detrend:0.6
To me the bottoms look pointed and the tops round. That’s why I’m inclined to see a folded cosine.
Whether this dataset resembles real climate and whether the face I see in the clouds is really the face of God, is another question. 😉

April 30, 2014 2:39 pm

Henry P
‘The fiddling with the data in the past does not make it any easier for us. Also, I have challenged anyone to show me a re-calibration certificate of a thermometer before 1940. Nobody has been able to show me one yet. That makes me very skeptical of all the data before 1950.”
Well
1. you should be skeptical of all data.
2. A calibration document tells you nothing because.
A) you have to trust the document
B) you have to trust that the device did not go out of calibration
3. Mis calibration, sensor drift, sensor change, is all grouped under the nugget effect
You and others are used to doing bottoms up error estimates. Kriging works the other
way around. What you end up with after minimizing the error is a correlation at distance
zero which is translated into an error due to ALL SOURCES of error. For example,
if you have 10 stations and you fit the field to these stations by minimizing the fit error
your residual tells you something.
4. The earliest US records I have seen for which there is a calibration record is 1804.
Guess who created these records?
The really cool thing is you can hold out these calibrated records and use the uncalibrated
records to create an expectation. Then test your prediction.

Greg
April 30, 2014 2:49 pm

Bart : “Yes, it is very clear that the approximately 10, 10.8, 11.8, and 134 year components evident in the SSN data are coming from rectification of processes centered at approximately 20 and 23.6 years.”
Could you elaborate ? Link ?
thx

Latitude
April 30, 2014 2:53 pm

Don’t want to interrupt….just thank you guys for giving us/me an incredible education

1sky1
April 30, 2014 6:46 pm

Willis:
There you go ad hominem again, with your put or shut up meme! Meanwhile, you
remain clueless as to what’s involved in analyzing tidal data for major
constituents. You need HOURLY data for at least a month for LS analysis
(see http://drs.nio.org/drs/bitstream/2264/59/4/Mahasagar_24_1.pdf). And
for a fuller set of tidal constituents, in accordance with Doodson’s
time-honored method, you need at least a year’s worth of hourly data. (see ftp://canuck.seos.uvic.ca/docs/MFTides/heights.pdf)
Nor is your comprehension any better about analyzing MONTHLY sea-level data,
which is a can of worms with all sorts of factors (eustatic and steric
variations, wind set-up, rainfall runoff, etc.) affecting the record even
in geologically stable locations. As your LS fitting of pure sinusoids
to the Cascais record shows, you fail to realize that it’s the presence of a
strong trend that produces your rising values as period increases. And, of
course, the well-established Rayleigh criterion for resolving sinusoids in
a record of finite length remains terra icognita for you. (It specifies
that two sinusoids can be resolved when the spectral peak of one
sinusoidal component falls on the first null of the second frequency in the
record-length dependent spectral window)
As disappointing as the Chambers et al. paper turned out to be (with it’s
simplistic bias + trend + sinusoid conception), at least they had sense
enough to remove the trend in their analysis and use the mean of
the best-fit period to the GMSL. And little is gained by removing the
annual cycle by monthly anomalization, as you do, rather than by their yearly averaging when looking for multidecadal oscillations, which no experienced geophycist would expect to be periodic.

Bart
April 30, 2014 7:27 pm

Greg says:
April 30, 2014 at 2:49 pm
See here.

April 30, 2014 9:16 pm

Steven Mosher says
Instead of cheery picking 10 stations, use them all
http://berkeleyearth.lbl.gov/regions/alaska
Henry says
FCirst, I don’t do “cheery” picking
I selected 10 stations, randomly, inland.
I was not interested in looking @sea, now, and I am not interested in results before 1998
(your Berkeley seems to report only from 1990).
If you had followed the whole thread you would know why.
but here is a good method to get a global representative sample:
http://wattsupwiththat.com/2014/04/25/the-elusive-60-year-sea-level-cycle/#comment-1622942
Clearly the Berkeley global data set lacks that balancing,as it reports a (global) warming rate of almost double that of other global data sets, including my own, from 1990.
Otherwise, why don’t you do an anlysis of all the data available from the Elmendorff Army base in Anchorage. It has data from 1942, If you analyse the maximum temperature record there and look at the average change in K/annum from 1972-2014 and from 1942-1972 you should get a part of an a-c wave that looks like the second graph shown here:
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
Clearly there is still some serious cooling coming up in Alaska, Note the difference in the sine wave from Anchorage and the global a-c wave.

April 30, 2014 9:53 pm

@steven mosher
I am interested in seeing that calibration record? That must be of a new thermometer? I was talking about re-calibration.
As to error, I have deliberately chosen to look only at the average change from the average over periods of time, i.e. linear regression, in K/annum, which excludes a lot of error, especially calibration and differences between stations. Also, in older records, I trust maximum and minimum temps. more than means as the latter required presence of people and physical work, taking readings during the day.

April 30, 2014 11:33 pm

Henry.
Ur method is not BLUE. Its not proven. Its not tested.
Its wrong. Its so bad its not even wrong.
The simplest out of sample test would show you that.
Its an amateur untested flawed unreviewed piece of garbage.
Here is a simple test. Use your 10 stations to predict the 100s you ignore. Then measure your error of prediction.
It will suck. Then use the 100s you ignore to predict the ,10 you “randomly” selected. Note the improvement over
Your boneheaded approach.

Greg
May 1, 2014 12:42 am

1sky1: “As your LS fitting of pure sinusoids
to the Cascais record shows, you fail to realize that it’s the presence of a
strong trend that produces your rising values as period increases.”
The periodic analysis W used fits non harmonic patterns. It’s basically like finding the mean annual “climatology” but with varying window lengths , not just 12mo.
However, your criticism is still valid, It is the upward trend that produces what W showed and reflects his lack of experience and understanding of periodic analysis.
One of the first things to do is to remove the auto-regression and the non stationary mean, which is why the first thing I usually do with this kind of data is work with the first difference not the time-series itself.

Greg
May 1, 2014 2:03 am

Bart says:
April 30, 2014 at 7:27 pm
See here.
http://s1136.photobucket.com/user/Bartemis/media/ssn2.jpg.html?sort=3&o=22
Yes, Isn’t that something I linked you to about six months ago 🙂
I was wondering whether you had found a separate source or had reproduced it.
Oddly that links into the Stockholm temp record that our host has just published about ( comment published in Nature CS). That got me to look at SPD of Stockholm and look what I found:
http://tinypic.com/view.php?pic=lfq5g&s=8#.U2ILc6KBwrQ
I should stress that is hot off the press and unchecked, so caveat emptor.

Greg
May 1, 2014 2:11 am

Sorry is that your reworking of what the other Bart did that was produced on Talkshop?
I think you may have just explained the self convolution, that was one thing I did not get in the original. Nice one.

Greg
May 1, 2014 2:24 am

http://i1136.photobucket.com/albums/n488/Bartemis/PowerAttenuation_zpsb499835e.jpg~original
This is interesting and ties in with something else I’m doing but it’s drifting away from GMSL
Would you like to drop me a comment on my about page and I’ll get back to you?
http://climategrog.wordpress.com/about/

May 1, 2014 2:50 am

@steven mosher
why don’t you give me all your Alaska data from Berkeley from 1998, or from 2000, is also OK, if that is more readily available, and we compare that result with the -0.55K/decade I get for Alaska
(I chose 1998 because that was when earth was at its warmest)
Clearly, it is people like you standing in the way of progress,
Progress would be for you to tell the world that we are globally cooling.
.http://www.woodfortrees.org/plot/hadcrut4gl/from:1987/to:2015/plot/hadcrut4gl/from:2002/to:2015/trend/plot/hadcrut3gl/from:1987/to:2015/plot/hadcrut3gl/from:2002/to:2015/trend/plot/rss/from:1987/to:2015/plot/rss/from:2002/to:2015/trend/plot/hadsst2gl/from:1987/to:2015/plot/hadsst2gl/from:2002/to:2015/trend/plot/hadcrut4gl/from:1987/to:2002/trend/plot/hadcrut3gl/from:1987/to:2002/trend/plot/hadsst2gl/from:1987/to:2002/trend/plot/rss/from:1987/to:2002/trend

May 1, 2014 7:08 am

@Mr. Mosher
we are all waiting for you to tell us your (berkeley) result of the amount of cooling taking place in Alaska since 1998 or 2000 in K per decade
If you do not reply we will all know or notice that you are a fake and a fraud, always trying to defend AGW

Bart
May 1, 2014 9:45 am

Greg says:
May 1, 2014 at 2:11 am
There can be only one, true Bart, and that is I.

May 1, 2014 10:58 am

Willis says
Again according to Berkeley Earth, the trend 1998-present is on average -.47°C/decade, and the trend 2000-present is -1.27°C/decade.
henry says
thanks Willis. I appreciate. I am not that much interested in before. Clearly they (berkeley) are a bunch of uninformed government employees, following the masterplan, an orgaisation that has employed or engaged people like Mosher. This helps!! It proves that my estimate of cooling in Alaska of -.55K per decade since 1998 is spot on.
The acceleration to -1.27K/decade from 2000 is somewhat worrying to me. Can it be that much difference? I will check that.

May 1, 2014 11:50 am

I checked,
according to my ten sample stations , Alaska cooled by -1.05K/decade since 2000.
That worries me, as it proves my theory that we are cooling from the top, and it is accelerating as times moves on. I can see it from my global tables as well, just adding the results of 2012 and 2013. The cooling is accelerating.Exactly as predicted.
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
Pity that Mr Mosher does not care.

1sky1
May 1, 2014 5:25 pm

Greg:
What W. does with the gap-filled Casais data is LS curve fitting of sinusoids of different periods, not the simple data averaging over different bin-lengths that you presume. What mislead me into thinking that the trend, which always consists of low-frequency components, was not removed was his reference to the previous chart in his write-up. Notwithstanding this mistake, which he conveniently seizes upon to call us both idiots, what he fails to grasp is the irrelevance of such curve fitting to detecting irregular multidecadal oscillations in geophysical data. And he fails to show what happens for periods longer than 80yrs.
BTW, first differencing of data is an effective mean-and-trend-suppressing stratagem, but it also severely attenuates the lowest frequencies. I’m under the gun to finish a technical report this week; I’ll have more to say when I’m finished.

May 2, 2014 1:42 pm

To Willis (and Anthony)
“Scafetta’s work has been uniformly irreproducible. Unfortunately, he doesn’t give enough information to redo his work, and he has consistently refused to show his data and code.
As a result, what Scafetta does is merely anecdote, not science in any form, and I ignore it completely.”
Anthony, when will you start to correct your guests (Willis and Mosher in primis) about this incorrect statement that my work cannot be reproducible? Holm already let you know that it can be easily reproduced with due scientific knowledge which Willis evidently does not have. Do you understand that the statement has been demonstrated to be false and constitute “defamation” under the civil code?
Said this, about the topic addressed by Willis, as usually he does not seem to understand the issue. In the case of sea level it is caused locally by different phenomena which couple climatic effects such as a changes of the volume of the glaciers, changes in the Earth rotations and changes in the ocean currents.
The phenomenon is quite complex. Let us discuss changes in water current. Water can move from one region to another. This means that in one location the sea level can rise and in another it can decrease and the phenomenon get quite complex depending where you are. Thus the 60-year oscillation is not in phase everywhere nor it is expected to be see everywhere.
In some record it is quite evident in other it is less evident.
As Mosher noted above in my paper
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.
http://www.pattern-recogn-phys.net/1/37/2013/prp-1-37-2013.pdf
I analyze the record from New York and this long record (since 1860) show it quite clearly.
See my figure 3.
However, Mosher did not noticed that In my paper I have not analyzed only the record from NY but in Figure 2 I have analyzed the global sea level reconstruction by
Jevrejeva, S., Moore, J. C., Grinsted, A., andWoodworth, P. L.: Recent global sea level acceleration started over 200 years ago?, Geophys. Res. Lett., 35, L08715, doi:10.1029/2008GL033611, 2008.
ftp://soest.hawaii.edu/coastal/Climate%20Articles/Jevrejeva_2008%20Sea%20level%20acceleration%20200yrs%20ago.pdf
This global reconstruction of sea level does show a quasi 60 year oscillation. since 1700.
Note that in their paper Jevrejeva et al wrote:
“Superimposed on the long-term acceleration are quasiperiodic fluctuations with a period of about 60 years. ”
The issue, now, is to see whether the patter is an artifacts of the data. To show this one needs to compare with other records since 1700.
This was done in
Scafetta N., 2013. Multi-scale dynamical analysis (MSDA) of sea level records versus PDO, AMO, and NAO indexes. Climate Dynamics. in press.
http://people.duke.edu/~ns2002/pdf/10.1007_s00382-013-1771-3.pdf
See figure 10 where the there is comparison with the NAO index since 1700, and this index shows the same quasi 60-year oscillation.
This is enough to respond to Willis both about the merit of the 60-year oscillation in the SL and the reproducibility of my work.