Guest Essay by Dr. Alan Welch FBIS FRAS — 5 April 2024 — 1900 words/8 minutes
Abstract In part 1, it was proposed that the sea level rise was basically linear with a small sinusoidal variation added. Part 2 investigates whether this variation is caused because the satellites orbit at 66 degrees inclination and a decadal oscillation in the seas spanning this latitude creates a lack of some data. Tidal gauge readings at locations around the Greenland and Norwegian Seas and the Arctic Ocean are analysed to see if there is any evidence of a decadal oscillation.
The main premise of part one in studying the 2023 satellite sea level data (Ref 1) was that the increase generally followed a linear line of about 3.3mm/year on which is superimposed a sinusoidal variation of about +/-4.2mm over a 26-year cycle. In reality the linear trend could be a small acceleration commensurate with those found in the longer-term Tidal Gauge data sets. This difference is sufficiently small as not to affect any conclusions. Figure 1 is reproduced from Part 1 to show this behaviour as of November 2023.
Figure 1
The differences between the actual reading and the linear line are called residuals and Figures 2 and 3 show these together with a quadratic fit and the sinusoidal curve as of December 2023. The latter was fitted by eye and has no mathematical basis for its parameters. Also shown are the standard deviations for the two curves which are 3.15 and 3.01 respectively compared with the standard deviation of the actual residuals of 4.20.
Figure 2
Figure 3
In the comments to Part 1 questions were rightly asked about this sinusoidal component and to why it may be occurring. A suggested answer was that as the satellites were at an inclination of 66 degrees areas of the Earth around each pole were not being monitored. It may therefore be what was not measured that creates the sinusoidal variation. So, what might that be? One suggestion is that there may be Ocean Decadal Oscillation that spans the latitude at which the satellites stop measuring. Sea level changes one side of that latitude will be measured but the related variations on the other side will be missed resulting in a sinusoidal variation.
This process is very similar to the sinusoidal variation that is evident in the long-term Tidal Gauge measurements. This was shown in the paper “Sea Level Rise Acceleration – An Alternative Hypothesis – Part 2” (Ref 2) and Figure 4 shows this behaviour. The underlying trend in this case is a low acceleration of 0.0126mm/year2. On top of this is superimposed a sinusoidal variation of +/- 6mm over a 57-year cycle.
Figure 4
A small diversion at this stage is to refer to a 2012 paper by Chambers, Merrifield and Nerem (Ref 3) in which they propose a 60-year Global Ocean Decadal Oscillation. It is worth quoting their final sentences.
“Until we understand whether the multi decadal variations in sea level reflect distinct inflexion points or a 60-year oscillation and whether there is a GMSL signature, one should be cautious about computations of acceleration in sea level records unless they are longer than two cycles of the oscillation or at least account for the possibility of a 60-year oscillation in their model. This especially applies to interpretation of acceleration in GMSL using only the 20-year record of from satellite altimetry and to evaluations of short records of mean sea level from individual gauges.”
How quickly the thinking process changed when in only 6 years the paper by Nerem et al appeared advocating the use of a quadratic interpretation in the calculation of accelerations as high as 0.1 mm/year2. Soon extrapolations up to 2100 followed with alarming graphs that caused fear amongst the population. If Moses could add an eleventh commandment he could add “Thou shalt not extrapolate polynomial regression curves”.
In the Chambers et al paper they show that there might be a Global Ocean Decadal Oscillation with a period of 60 years. Figure 5 below shows plots of sea level variation and how a 60-year curve may be envisaged. It is not an exact science and there are much shorter periods of behaviour that complicates the process, but it points to what difficulties may lie ahead in trying this with the satellite data.
Figure 5
Back to the satellite readings. A look at the coverage of the satellites may help. Figure 6 shows the limits to the satellite coverage. It is very difficult to visualise the polar regions from full global projections but it can be seen that there is less ocean below the Antarctic Circle than above the Arctic Circle and what there is in the Antarctic are parts of very large portions of the Earth’s oceans and so probably part of longer decadal Oscillations.
Figure 6
Views from above and below, Figure 7, are more informative and whilst the Arctic Sea is fully contained within the Arctic Circle there is a sizeable amount of sea between it and the North Atlantic Ocean, formed in main by the Greenland and Norwegian Seas, which will be subject to possible decadal oscillations.
Figure 7
To investigate several Tidal Gauge locations around the Arctic Ocean, the Greenland Sea and Norwegian Sea will be investigated. They were all processed in a common manner starting with the NOAA graph of sea levels then Excel graphs of sea levels with a quadratic fitting curve, of the sea levels with 100 month moving average of residuals from quadratic curve and of the 100-month moving average of the residuals.
The chosen locations have a reasonably long period of measurement with none or only short breaks in readings. Figure 8 shows the chosen locations. These are listed below in order of increasing longitude East. Hence the first few are more associated with the Greenland Sea/Norwegian Sea/ Arctic Ocean combined area.
Reykjavik – Iceland
Torshavn – Faroe Islands
Aberdeen – Scotland
Lerwick – Scotland
Bergen – Norway
Barentsberg – Svalbard
Narvik – Norway
Murmansk – Russia
Tiksi – Russia
If any Decadal Oscillations occur with the required periods it is only half of the solution. There is no way of knowing the direction the oscillations follow but there might be a good chance that they occur in a more northerly direction looking at the topography of the areas involved which does extend into the North Atlantic.
Figure 8
[Some Excel warnings. When unloading the NOAA Data it uses a CSV file. If an Excel file is produced and work is done on this with pictures created it is necessary to save as a XLS file otherwise much of the additional work will be lost. Also, when plotting moving averages do not use the Excel to plot the Trend Line as this is displaced relevant to any plots of the original data. Always calculate the moving values within the spreadsheet.]
Reykjavik
The NOAA Tidal Gauge data were extracted and are shown in Figure 9. Note there is a small gap in data around 1984 but not large enough to affect any processing. In other locations there are larger gaps in data occur and so some data is ignored. Figure 10 processes this data and produces a quadratic fit. The acceleration is low at -0. 021 mm/year2. Figure 11 shows the residuals between the 100-month average and the quadratic curve superimposed on the data with Figure 12 plotting just the residuals. Superimposed on the latter is a Sinusoidal curve with a 26-year cycle. In judging this the amplitude and phase shift are irrelevant.
Figures 9 to 12 show the process followed but for subsequent locations only the first (NOAA Graph) and last (Residuals) will be presented.
Figure 9
Figure 10
Figure 11
Figure 12
The period covered is quite short and whilst the correlation is poor the actual readings show approximately 2 cycles covering about 60 years.
Torshavn
Figure 13
Figure 14
There is a high degree of correlation between the 2 curves with the actual readings having a slightly shorter period.
Aberdeen
Figure 15
Figure 16
This location has the longest period of readings at nearly 160 years. This allows sufficient time for longer periods of oscillation to occur and it can be seen that there might be larger 90-year period superimposed. There sems to be a number of shorter periods of about 20 years throughout the period and especially after 1900.
Lerwick
Figure 17
Figure 18
Again, there is a good correlation between the 2 curves.
Bergen
Figure 19
Figure 20
Some correlation exists between the 2 curves except for around 1970.
Barentsburg
Figure 21
Figure 22
No reasonable correlation exists but some 20-year oscillations can be perceived.
Narvik
Figure 23
Figure 24
Two good periods of correlation exist at each end with an extra dip in-between.
Murmansk
Figure 25
Figure 26
This graph of the actual readings is dominated by a much longer cycle of about 70 to 80 years, but this site is more on the fringes of the Arctic Ocean.
Tiksi
Figure 27
Figure 28
This site is also on the Arctic Ocean and not expected to show the periodicity of the others although there are about 3 20-year cycles.
It was stated above that the amplitude and phase shift were of lesser importance but for completeness these are listed below together with the acceleration derived from the quadratic curve. The phase shift is calculated relevant to the sinusoidal curve given in Part 1 of this paper.
| Location | Acceleration mm/year2 | Amplitude mm | Phase degrees |
| Reykjvik | -0.021 | 15 | -124 |
| Torshavn | 0.053 | 12 | -28 |
| Aberdeen | 0.013 | 12 | -28 |
| Lerwick | 0.114 | 12 | -124 |
| Bergen | 0.021 | 15 | 152 |
| Barentsburg | 0.007 | 15 | -97 |
| Narvik | 0.079 | 17 | 55 |
Notes
The accelerations, or so called accelerations, are high because of the relative short (less than 100 years) periods involved. Only Aberdeen (started 1862) and Bergen (started 1915) cover more than 100 years.
Interestingly all the amplitudes fall between 12 and 17 mm. Figure 29 shows all 7 locations plotted over the period 1990 to 2024.
Figure 29
The 7 sets of results were combined and averaged to produce Figure 30 which shows the averaged variation compared with the 26-year perceived variation. The averaged results peak at +/-5.3mm, not too different from the perceived value of +/-4.2mm. The phase shift between the 2 curves is approximately 120 degrees. If the perceived variation is due to a partial lack in measuring the more northerly levels, there would be a discrepancy in value of the phase shift.
Figure 30
What conclusions can be drawn?
All the graphs show some form of decadal oscillation. In the areas away from the Arctic Ocean there is evidence of cycles in the range of 20-to-30-year periods.
The averaged graph shows an amplitude close to that found when analysing the satellite data.
The 26 year cycle proposed is sufficient to generate “accelerations” when analysed over periods as small as 30 years.
The decadal oscillations envisaged are capable of creating a 26 year, +/-4.2mm variation about the linear sea level rise of about 3.3mm/year.
It all points to the fact that the Tidal Gauge and Satellite data is of a remarkable high quality with coherent patterns of behaviour being displayed when processing it.
References
2 https://wattsupwiththat.com/2022/06/28/sea-level-rise-acceleration-an-alternative-hypothesis-part-2/
3 Chambers, Merrifield and Nerem (2012). “Is there a 60-year oscillation in global mean sea level?” https://acp.copernicus.org/preprints/15/20059/2015/acpd-15-20059-2015.pdf
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It didn’t take long for the NJ earthquake to be blamed on climate change. Anything and everything is a result of your sin of using energy.
and?
And sea level rise is blamed on you despite it having begun in earnest around ten thousand years ago.
I seem to be losing 4 to -4!! You must have more followers than me!!
The reason for my short reply was that you didn’t address what I was talking about. More a Open Thread topic.
If you have any comments on the contents of my paper I would be pleased to read them,
I liked your quite good comprehensive post.
There are cycles everywhere in nature and it makes sense to look for their occurrence and mechanisms that explain them. Fundamentally, the universe and everything in it is spinning.
Tides are due to alignment of the earth, moon and sun and large sea level glacial oscillations are due to orbital mechanics and cosmic effects. CO2 is nothing to angular momentum.
Thanks for coming back
My steps were
Perceive a small sinusoidal variation
Then look at Tidal Gauges
Find Decadal Oscillation of similar magnitude
Shout Eureka
Maybe coincident but if if knocks a hole in the quadratic curve acceleration brigade job done
Thank you, Alan. I mentioned a couple of weeks ago that most tide gauge data was essentially linear but with an overlying oscillation, but I hadn’t ever bother to do any analysis.
Thanks for confirming…
Of course, AGW-cult trendologists use that oscillation to try to prove an acceleration….. which is just mathematically stupid.
The trouble with the satellite sea level data is that it also contains ad hoc agenda-driven “adjustments” which sort of makes any analysis not worth the bother.
Seriously? “and?” Why are you being obtuse?
My brief reply was I thought the comment had no relationship to what I had presented and I was basically asking for some more constructive comments, suggestions or criticisms.
Alan, that happens quite often here.
Didn’t Marjorie TG say it was the wrath of God… ““God is sending America strong signs to tell us to repent….” Now that is crazy.
So it’s okay for climate alarmists (like you) to say repent, but no one else can? However, MTG gets to do her thing–just like you. It’s just that your thing is more ridiculous and dangerous.
“Thou shalt not extrapolate polynomial regression curves”
Words to live by…
You’ve just disarmed the IPCC of their one and only tool.
So, how would you describe the white coats who put their names to IPCC reports?
Inmates?
Tools
This “acceleration” stuff that comes out of quadratic curve fitting is nonsense.
Agreed. That is why I found the earlier Chambers, Merrifield and Nerem quote revealing. At that stage they recognized the need for longer sets of data and if it showed cyclic to cover at least 2 cycles. But come 2018 it all changed and extrapolation raised its ugly head.
The air temperature trendologists are now doing quadratic curve fits to UAH data and claiming that global warming is accelerating.
The author seems to be claiming satellite sea level are accurate without the knowledge of exactly how raw measurements are adjusted before presentation to the general public.
I think that is baloney
Satellite data measures absolute sea level and tide gages measure relative sea level. They are not expected to be the same
There are random variations not a very steady straight line long term rise rate
The author is trying to fit curves to random variations and falsely implying there are global sea level cycles.
The author seems to be desperate to fit a sine wave cycle to random variations, to prove a cycle that obviously does not exist at every location. And each tide gauge is measuring sea level and vertical land movement, not only sea level.
My theory is sea level rise is slightly faster during a period of global warming and slightly slower during global cooling. When millionnaires stop buying oceanfront homes, we may have a sea level problem.
What I set out to do was having perceived (rightly or wrongly) a sinusoidal response over 26 years with an amplitude of 4.2mm to see if there were any mechanisms that might account for this.
Not aware of any decadal oscillations in the northern seas I just went through a process of looking at several Tidal Gauges. I was surprised (and excited) to see some actual results appearing that might back up the perceived behaviour. I know you can’t accept it as gospel but it shouldn’t be ignored. Anything that might negate the quadratic curve fitting and the unjustifiable extrapolation, in my mind, is worth pursuing.
There is an oscillation of about 30 years called the IPO interdecal Pacific oscillation. There is evidence that in Australia in combination with the SOI indicating El Nino causing droughts eg the Federation drought 1896 to 1913 and with the SOI indicating a La Nina causing floods eg Brisbane 1974 and 2011. The IPO and SOI have nothing to do with CO2.
No sea level problem: Why Jeff Bezos bought three homes in Florida’s ‘billionaire bunker’(Indian Creel Island).
https://www.thetimes.co.uk/article/0122c9b3-d0ca-4141-895e-568469ada678?shareToken=f46dbd049390e17177b2e5add51f00b5
If only Bill Gates lived there, I might be persuaded to root for the Hurricanes.
These hurricanes?
https://miamihurricanes.com/
Richard ==> Dr. Welch is analyzing the standard satellite data sets — just taking them as they come. Mostly all this is in response to Nerem et al (many iterations) trying to make a short record into an acceleration graph. as you know, I have written about Nerem’s acceleration work many times here at WUWT.
This type of work ix “exploratory” science — you fiddle with the existing data to see what it says, look at it a couple of ways.
There may be a cyclical signal in there….and maybe not.
Dr. Welch’s work is interesting if nothing else. Wish we had a century-worth of data to work with. Tide gauge data is too compromised by VLM and local/regional effects to tell us much, if anything, about Global SLR.
Local tide gauges tell people what they need to know when considering flooding risks of local infrastructure built near the shoreline
For satellite sea level numbers
— Are satellites capable of the accuracy claimed for them, considering they could drift ten feet in orbit?
Do we trust NASA when they process the raw data?
There are certainly adjustments before a number is released to the public.
Is the sea level rise whatever NASA wants to tell us or is it an honest number with no bias?
After 26 years of climate reading, I have no logical reason to trust NASA or NOAA.
It is my opinion that satellites are not accurate
And NASA can not be trusted
Assuming there are adjustments to the original raw measurements, we no longer have data, or even know what the adjustments were.
We have adjusted numbers some people in the GOVERNMENT think REPRESENT the “right” data if the measurements had been accurate in the first place.
Relative sea level for tide gauges is more important than absolute sea level from satellites
And sine wave curve fitting random variations is just mental exercise with no obvious value for predicting future sea level rise.
Same reply as for Scissors
Thanks for coming back
My steps were
Perceive a small sinusoidal variation
Then look at Tidal Gauges
Find Decadal Oscillation of similar magnitude
Shout Eureka
Maybe coincident but if if knocks a hole in the quadratic curve acceleration brigade job done
Richard ==> I agree with much of what you say, and you would know this if you had been reading regularly here. See my SEA LEVEL Rise and Fall series.
Not only have I read all yur sea level articles here but I recently asked for an index of them when the search engine went berserk and gave me a crazy list not in chronological order. It worked properly the second time
Keep up the good work on sea level and other high quality articles here.
Based on prior adjustments to temperature data by NASA and NOAA I just don’t trust either organization.
That satellite sea level just happens to show acceleration is just what NASA wants to tell the public. I am immediately suspicious.
Climate data from a government promoting rapid global warming is whatever THEY want to tell you and there’s no way to check the adjustments, infilling and fudge factors.
Antarctica is NOT melting from CO2 because of the permanent temperature inversion over almost all of the continent. Antarctica has up to 90% of ice on land. That tells me rising sea level will NEVER be a problem in the next century.
Other causes of sea level rise could be more important than ice on land melting:
— Warming of the oceans
— Groundwater draining into the oceans
–Tectonic plate movement that changed the volume of the oceans
Here is a presentation that says accuracy from ±2 cm to ±5 cm.
01_Tuesday_OCT2013_Cipollini_Altimetry_1.pdf (esa.int)
Older satellites had up to ±10 cm
https://secwww.jhuapl.edu/techdigest/Content/techdigest/pdf/V05-N04/05-04-Kilgus.pdf
Not sure how anyone could make an adequate projection from these uncertainties. We are talking from ±1 inch to ± 4 inches.
Close enough for “government work”
I tend to agree with you but the process was
1 Download the data
2 plot and fit a curve
3 calculate residuals between actual results and curve
4 make a judgement on this curve mine was sinusoidal Nerem et al were quadratic
5 publish
6 read comments and one was how do you account for this
7 At this stage all I had was a perceived curve period 26 years amplitude 4.2 mm (excuse the unbelievable accuracy)
8 answer comment in that I thought the 95% satellite coverage and possible decadal oscillations might be involved
9 study a number of Tidal Gauges in the Northern Seas
10 publish these results. I was amazed that there were some decadal oscillations appearing with the right period and combining a number of these gave a good measure of amplitude
It may all be coincidental but I felt it was worth publishing
That’s the way science progresses – think up a theory then test it
If my work is all pie in the sky lets at least put the quadratic variation and its unbelievable extrapolation scaremongering to bed.
Alan, I don’t agree with anything you have done other than items 2 and 3. As I showed, I researched satellite measures of sea level to find their uncertainty. What this means is that your data has, let’s call them error bars or uncertainty intervals. In other words, you don’t know where the actual data lies within that range and each point can lie anywhere.
The uncertainty of the data should be propagated onto the residuals which will need to be analyzed further as to the effect on your conclusion.
A good example are the accelerations. If I am reading the table that shows acceleration correctly, you show values in the hundredths to thousandsth of a mm. These are obviously within the uncertainty bounds and therefore unreliable.
Again I am not arguing with your results, they make intuitive sense. I just wanted to point out that measurement uncertainty is an issue and should be addressed in your conclusions.
I am aware of the error bars and uncertainty in satellite readings but can I address each step.
step 1 obviously the start of any analyzing. The next choice, knowing the uncertainties, is to stop or try something. Stopping gets you nowhere so lets go on.
Step 2 you agree with. The obvious choice is a straight line.
Step 3 you agree with.The residuals may be due to a 2nd at this stage unknown physical process.
Step 4 The choice is what curve. To me there were 2 choices, quadratic (which as an engineer I am wary of), or sinusoidal which is more natural. I find it remarkable that the fit to the sinusoidal is so good the main excursions generally El Nino and La Nina events.
Step 5 No good sitting on this work so I published earlier together with thoughts of why the quadratic fit gave alarmingly high figures of acceleration.
Step 6 was to study the feed back and try to answer why that particular curve may be meaningful.
So at step 7 all I had was an inkling of a small (unbelievable small) sinusoidal variation.
Step 8 was to try to suggest a mechanism. I was not aware of any decadal oscillations but was aware of the limited (95%) satellite coverage.
So in step 9 I dived into studying the oscillations of the northern seas not knowing whether I would find anything revealing. Nothing ventured nothing gained,
Step 10 Having found some, to me exciting, results I published. No good sitting on it. Science would not progress that way.
Were the error bars too pessimistic and precision of satellite readings set too high?
I found figures like Figures 14 and 18 remarkable. How would you account for these? Or would you throw the baby out with the bath water and just ignore it all?
Many thanks for your feed back.
Interesting what the next 10 years will reveal. Pity the process happens so slowly.
Just so we are on the same page. I think your discovery of an oscillation is a good job. Everything in this solar system is cyclical. There is no good reason that tide changes shouldn’t also be cyclical. I just wanted to insure that the uncertainties weren’t skewing what you were seeing.
Sadly, I agree with Richard. Much of the climate data cannot be trusted. The same distrust extends to government healthcare reporting, government-reported election voting data, government-reported economic data, etc.
All climates are local. The errors involved with constructing global measures of climate-related variables such as global temperature, global sea level rise, global rainfall, etc are such that detailed analysis offers little insight. GIGO as they say.
It always amazes me that sea level is “corrected” for telemetry and satellite orbital variations by considering the elevations of the DORIS ground stations. We correct those elevations with comparisons to sea level at various tide gauges…again correcting for glacial isostatic rebound of the crust due to the weight of the glaciers 15,000 years ago.
Yet we have very little idea how much to correct for changes in sea bottom elevation….70% of the planet…
…not to mention another 9.5% of the planet under monthly varying depths of Greenland and Antarctica snowfall…
…not to mention a foot or so daily upheaval in crustal elevation due to the Moon’s gravity…
….not to mention about 4 times the water that exists in the ocean that is contained in the crust and mantle with little knowledge of the heat transfer that causes it to move inwards or outwards.
But when we study occasional “surprises” such as the Banda Aceh tsunami, we find parts of the sea floor suddenly “jumped” 15 cm.
So when I read about sea level rise, I marvel at all the work intelligent people have put into evaluating data that is simply slow moving bullshit. Sorry to mention so many “not to mention” items…..
https://www.geologie.ens.fr/~vigny/aceh-e.html
It really doesn’t matter if relative or absolute levels are used as long as the data is consistent. If an oscillation is occurring, there is the possibility that both show it. If one shows and the other doesn’t, it won’t mean either is wrong, it just means that any explanation should show why.
You assertion is meaningless without data to show that the conclusion is in error.
Remember, a sine wave is a time function. Random values could be represented by a since curve for a cycle perhaps, but it is highly unlikely that random values would repeat at following similar points in a sine wave over several periods.
The charts in the article are not very persuasive if the goal is to prove there is a regular global absolute sea level cycle
And even if such a regular global cycle existed, rather than random variations, it would still be small variations of a very long term uptrend. Just noise.
Sea level rise…. think Antarctica
“”Essentially, it is a vicious circle of warming oceans and melting of sea ice, though the root cause is humanity and its continuing burning of fossil fuels and its production of greenhouse gases””
https://www.theguardian.com/environment/2024/apr/06/simply-mind-boggling-world-record-temperature-jump-in-antarctic-raises-fears-of-catastrophe
We’re doomed as usual
They are the Guardians of TRVTH, after all.
But worse than originally thought
The Guardian is so bad they would publish a climate chart upside down if that would better support the narrative.
The East Antarctic Ice Sheet forms the largest part of the ice in Antarctica and is based on land. It has mountains buried under 3kms of ice. Some of the ice in the dry valleys of East Antarctica is thought to be millions of years old. Can’t see that ice sheet melting any time soon.
There is a little melting of Antarctica ice shelves and the tiny peninsula, both affected by sea tide changes an underseas volcanoes
Even with that melting, the estimated ice loss of 150 gigatons a year is below the likely margin of error in the ice mass loss estimates.
But even if 150 gigatons melting is correct, that rate of melting would take 1.6 million years to melt al; Antarctica ice
And that would REQUIRE the current interglacial to last 1.6 million years, when it is unlikely to last 8,000 more years.
Melting of Antarctica ice and Florida, etc. underwater, is the
biggest hoax of the entire coming climate crisis hoax.
The extinction hoax seems worse, but I doubt (hope) most leftists don’t really believe it, like they all believe the Antarctica melting hoax.
My take on these studies is that seas are probably rising as we slowly put the Little Ice Age behind us, but not so much that anyone could notice.
Also, the planet’s water has to live somewhere, so why not the oceans?
Many of the sites you analyze have GPS elevation gauges at or near the site of sea level gauge. Is there no cyclic component to the available GPS data? Clearly, relative tide gauge data is hardly representative of actual sea level changes at the level of precision you seek. Also, are observed changes in sea level a consequence of more water, hotter water, or changes in the configuration of ocean basins leading to water level changes? Data from Larson et. al (A Search for scale in Sea-Level Studies, Journal of Coastal Research, July 2006) concludes that sea level has been slowly and steadily increasing for the past 6,000 years suggesting that geologic changes may be responsible. Which is it?
On the subject of long period oscillation, I had a post 15 years ago on the Wilkins ice shelf breakup, which was followed by a Scripps study on long period waves.
https://wattsupwiththat.com/2009/04/30/watch-the-wilkins-ice-shelf-collapse-looks-like-current-events-to-me/
https://wattsupwiththat.com/2010/02/13/antarctic-ice-shelf-collapse-possibly-triggered-by-ocean-waves/
I found the nearest sea level record to Wilkins, the Rothera base some 240 miles up the Antarctic peninsula. My plot showed fairly regular ups and downs until three months before the breakup, then some wide swings that could easily be blamed for the collapse. How this compares with the oscillations in the current article I don’t know, but it’s southern hemisphere data outside the 66° satellite coverage.
Thanks for your comments.
Your graph shows very large but fast oscillations.
I’m not an expert on the topic just an inquisitive engineer digging into the data.
From what I recall of decadal oscillations they are multi decades in period and tens of mm in amplitude but when combined over a large area or averaged at many sites tend to result in similar periods but only mms amplitude. This is what I perceived in the satellite data and in the combined northern seas data.
Is it possible to state a rationale for putting any credence onto calculated values so much smaller than measurements that can possibly be made?
Check out the Metonic Cycle:
https://tidesandcurrents.noaa.gov › publications › Understanding_Sea_Level_Change.pdf
American Council on Surveying and Mapping considers the ~19 year cycle when measuring sea level for purposes of establishing a property boundary with the sea. It is a lunar-solar cycle with predictable sine wave periodicity.
Correct link address is..
https://tidesandcurrents.noaa.gov/publications/Understanding_Sea_Level_Change.pdf
Alan,
This is a rather good examination of a much-needed topic, thank you.
Problems of measurement uncertainty continue to exist. There is no valid theory that error magnitudes should follow a straight line over time (they can be sinusoidal), or that their positive excursions are invariably balanced out by negatives. There continue to be single point estimates of satellite distance measurement uncertainty of a few cm, yet these graphs of yours like Figs 2 and 3 display points separated by a mm or so.
While your aim was directed at matters around the Poles, there remains a need to show error envelopes, so readers can see if the graphed data points are merely swimming in a big sea of uncertainty or are valid representations of what is happening.
Geoff S
Geoff, I posted a little earlier about what I found for uncertainty in satellites. Not sure if anyone can make an accurate projection that isn’t within the uncertainty interval.
So many graphs with an unlabelled y-axis. How does such laziness get past even self-review ?
Sorry I can’t see any axes unlabelled’ Which graphs do you refer to.
DMac ==> Good observation. I’m sure the author (Dr. Welch) will correct this oversight in the future. It is probably a function of the software used to create the graphs — if Excel, it means that the year-month-day data is in separate columns, which is standard for NOAA tide data downloads, and it takes a clever trick to fix it — took me a long time to search out the answer.
I’ll mention to Dr. Welch.
For his purposes, fitting curves, the y-axis is an “also ran”.
Downloaded data had 2 column such as 1950 and 01 in A1 and B1 etc. In this case just seed say G1 with =A1+(B1*1/12 -1/24)-1900 to get dates in years after 1900. Copy that all down column G. If dates are missing this will work fine.
Using full dates such as 1950 will have ramifications when it comes to the equations of trendlines.
Alan, always a good idea to move the x-axis labelling/values to the bottom of the graph.
In Excel, format the y-axis and tell it where you want the x- axis to be positioned..
As far as I can see, just Figure 10 has no values on horizontal axis.
You are right – not too bad – 1 out of 30. I’ve been in touch with Kip and will try other axis choices. I wanted the x axis to have a thicker line from the grid lines and pass through the y=0. Might have to lower the axis and add a thicker line on top of y = 0 grid line. Or have I missed a trick? Thanks for your feed back.
Is it even possible to measure sea level to a tenth of a millimeter from orbit? These measurements have not been calibrated to tide gauges. Who cares if curve-fitting does or does not show an acceleration? What a crock
It matters when Climate Scientists extrapolate it to 2100, the BBC and Guardian pick it up and scare the day lights out of their listeners and readers. The short period of 30 years is much too short and produces artificially high “acceleration” which compared with 100 year values and they may be an order too large.
Also I resent your last sentence. Read my earlier papers and try to see what I am getting at. Especially my second one
https://wattsupwiththat.com/2022/06/28/sea-level-rise-acceleration-an-alternative-hypothesis-part-2/
which shows the effect of too short a time period.
Dr. Welch,
I believe you misunderstand. My criticism is of the technology. Measuring tenths of millimeters, from orbit, with all the variables such as gravity, waves, sea foam etc. strikes me as inaccurate. Your work is not in question, just NOAA/NASA claiming skill they clearly do not have with their satellites.
Sorry sorry.
Moon
Thanks for your reply and clearing that up. I must admit that at 86 I’m feeling a bit of an “old crock”!!!
A casual observation: It looks to the naked eye that some areas show a lowering sea level while others are increasing. This leads to the question of water displacement from area to area being part of the puzzle?