Technical Note on the Possible Variation in Sea Level Rise “Accelerations” over the Next 5 Years

by Dr. Alan Welch FBIS FRAS

(WARNING – this paper contains images of 5-year projections in sea levels that some readers may find disturbing.)

The next 5 years may be a good opportunity to judge how the “global” sea level rises are changing, especially with respect to the perceived “accelerations”.  The terms “global” and “accelerations” are in quotes to infer that that these terms may not be totally appropriate.  The satellite coverage is only 95% and the “accelerations” may be caused by the methodology used and not a true physical attribute.

The two papers by Nerem et al have had a major influence about sea level rises.  The paper, Nerem et al (2018), introduced the concept of an “acceleration” stemming from the fitting of a quadratic curve.  This paper has had over 1500 citations and has greatly influenced the media and frightened all the kids from Boca Chica to Timbuctoo.  The second paper, Nerem et al (2022), stated that the “acceleration  coefficient becomes stable after 2017”, this being shown  in figure 0 below of the paper which reproduces their figure 2.

Figure 0

Contact was made with one of the co-authors, (B. D H), saying that the graph was a very interesting presentation and that it would be informative to keep it up-dated.  No reply was received, no update has been seen and no other form of this graph has appeared anywhere else except, I think, in my various papers on WUWT. 

Before proceeding a small diversion.  I asked the new kid on the block, AI, two questions.  The AI used was Google AI.

Question 1

I have 25 years of sea level data to which I fit a quadratic curve. That curve is then extrapolated for another 80 years. Is this acceptable?

AI answered“In general, this approach is highly discouraged. Extrapolating a quadratic curve fitted to just 25 years of data over an 80-year period is statistically problematic, as sea level rise is highly complex and not strictly governed by a simple mathematical parabola.”

Question 2  (Almost the same as question 1 except replacing me with Nerem et al).

In their 2018 paper Nerem et al used 25 years of sea level data to which they fitted a quadratic curve. That curve was then extrapolated for another 80 years. Is this acceptable?

AI answered (although AI seems to have now donned rose tinted glasses) “The quadratic extrapolation used in the 2018 Nerem et al. paper is considered scientifically acceptable as a descriptive diagnostic to detect current acceleration, but it is not intended to be a definitive physical projection of future sea levels.

While fitting a curve to 25 years and extending it for 80 is often criticized in statistics, the authors used it primarily as a ““thought experiment”” to demonstrate that observed satellite data is already tracking with high-end climate models.”

My updated graph based on the NASA data for the end of May 2026, showing how “acceleration” changed with time,  is reproduced below (figure 1).

Figure 1

It should be noted that the historic NASA data (as well as the historic University of Colorado data) have changed many times since 2018.  The 5-year projections use the NASA data for December 2025 which was slightly different as shown in the “acceleration” plot below (figure 2).  The topic of changes in the data over the last 8 years will be addressed in a separate paper.  The historic data sets are not readily available, but having retained most of this data it can revisited or reanalysed at any stage.  The differences between the December 2025 and May 2026 NASA data have pulled the “accelerations” between 2018 and 2025 generally back up towards the 0.08 mm/year2, which may be just coincidental, but from 2025 there is still a change to a rapidly decreasing “acceleration” values, which in May 2026 are now already below 0.06 mm/year2 as can be seen in Figure 1.

Figure 2

It can be seen that the “acceleration” remains basically constant over 2017 to 2022 then starts to drop and after the beginning of 2025 starts to drop more rapidly.  The “red” line is a theoretical line based on the sea levels varying about the best straight line fit in a sinusoidal manner with a period of 29 years.  This red curve continues over the next 15 years decaying to near zero values commensurate with those seen in long term Tidal Gauges.  

To extend the data to cover the years 2026 to 2030 the following steps were taken.

  1. Use the annual variation through 2025 to generate data for each subsequent year.  Due to the small changes during 2025 this generates quite a small increase over the 5 years, and this is deemed to be too low to be meaningful.
  2. Add an extra 2 mm rise per year each year this being deemed a lower bound (data set 1).
  3. Add an extra 3 mm rise per year each year this being deemed an upper bound (data set 2).
  4. To each of the above add a large El Niño set of data based on a rise of 10 mm over 2027 and a following decrease over 2028 (data sets 3 and 4).

The definition of data sets 1 and 2 as lower and upper bounds is only used to give a pair of data sets that are in the right ballpark.  Plots of the data are shown below (figures 3 to 6).

Figure 3

Figure 4

Figure 5

Figure 6

The slopes of the best fit straight line for the December 2025 and the 4 simulated data sets were obtained and are listed below.

December 2025   3.09 mm/year

Data set 1               3.07 mm/year    Lower Band

Data set 2               3.12 mm/year    Upper Band

Data set 3               3.10 mm/year    Lower Band plus El Niño

Data set 4               3.15 mm/year    Upper Band plus El Niño

The slope for December 2025 falls between data sets 1 and 2 with the slopes involving an El Niño being both higher.  The slopes at this period are only increasing at about 0.02mm/year so the simulated data sets are considered to be reasonable or even slightly high.

The “accelerations” for all 4 cases were calculated between 2012 (when the NASA data started to give less erratic values) and 2031and are shown below in figures 7 to 10.

Figure 7

Figure 8

Figure 9

Figure 10

The “accelerations” fall  to values of approximately 0.025, 0.035, 0.030 and 0.040 mm/year2.

This assumes there are no major changes to the historic data.  Judged on these plots the long term “acceleration” will reach about 0.0 mm/year2 by2040. although in reality the decay may be more asymptotic to about 0.01mm/year2 in line with tidal gauge data.  The sea level curve created by an acceleration of 0.01mm/year2 can also be matched by long term (1000 year) sinusoidal variation as has been shown in my paper “Does the Global Sea-Level rise have a Sinusoidal variation. An Investigation using Tidal Gauge Data. Part 1 – Preliminary Analysis”, published on WUWT as https://wattsupwiththat.com/2025/12/02/does-the-global-sea-level-rise-have-a-sinusoidal-variation/

The conclusion reached is that generally the “acceleration” will continue to fall over the next 10 to 15 years or will reach values commensurate with the Tidal Gauge estimates.

Appendix – Most of the analyses and graphs have involved the perceived “accelerations”.  Figure 11 shows the variation of the slope as calculated over the period from 1993 to the year indicated.  The 3 curves show the slopes calculated using the actual data, a quadratic variation and a sinusoidal variation.  It can be seen that the sinusoidal curve matches the actual data more closely adding more evidence negating the use of a quadratic curve and the associated “acceleration”. The quadratic variation is basically a straight line, whereas the sinusoidal variation shows the drop to about 2008, a climb up to an inflection point at about 2017 at which stage the growth in the curve begins to slow down.

Figure 11

Mission Statement – Being an 88-year OAP a 5-year projection seems overly ambitious, but I hope to make 2031 to see how right (or wrong) I have been.

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21 Comments
July 2, 2026 10:10 am

The second paper, Nerem et al (2022), stated that the “acceleration coefficient becomes stable after 2017

Nerem isn’t to be trusted for anything.

comment image

All of those plots should fall on top of one another. They don’t someone, Dr. R. S Nerem and his assistant Dallas Masters rewrote the historical data every time they updated their Chart:

https://sealevel.colorado.edu/

Over the long haul, sea level acceleration is very close to zero at 0.01 mm/yr²

comment image

Alan Welch
Reply to  Steve Case
July 2, 2026 1:29 pm

Agree with your remarks. The UOC now only publish their latest data and sometimes data up to 2020 so unless you capture other years it is difficult to track what they are up to.

It is revealing how my red line on figs 7 to 10 tends to values found for long term tidal gauges. Being derived from a sinusoidal curve it tends to zero but is more likely to tend to the order of 0.01mm/year2 found for tidal gauges.

Scissor
Reply to  Steve Case
July 2, 2026 4:15 pm

Just for information purposes, the proper name is University of Colorado Boulder. Its official acronyms are CU (no periods) and CU Boulder. In athletic contexts, it is commonly referred to as Colorado or CU.

Reply to  Steve Case
July 2, 2026 4:40 pm

“rewrote the historical data every time”

There certainly “rewrote” the data when they changed from Topex to Jason.

The chart shows a graphical overlay with axes matched as well as possible, in red, of the Topex data, on top ofthe Jason data..

Its not precise, but the changes are very obvious.

sea-level-changes
suffolkboy
Reply to  bnice2000
July 4, 2026 11:52 am

I have two nagging questions.

  1. With the switch from Topex to Jason, was there a “splice” adjustment so that the end of Topex was compatible with the start of Topex in (a) value (b) slope (i.e.)
  2. In both cases, is there a non-zero adjustment to the raw time-of-flight data, necessitated by the *change* in atmospheric composition and depth (if any) over the measurement period. If so, what formula is used to estimate the adjustment, and how does this affect the above figure?
July 2, 2026 11:30 am

As for the repeated references in the above article to “25 years of data”, I find it interesting that Figures 1, 2, and 7 thru 10 show the “sinusoidal fits” starting in 2012, thus actually cover only about 14 years leading up to May 2026. Is the fit of that “sinusoidal function” (red curve) so bad from 2000 to 2012 that it dare not be shown?

Hence, it’s just not credible that extending that red “sinusoidal” curve out to 2063 (as shown in those same graphs) has any scientific credibility, especially with the predicted inflection points around 2039 and 2051.

Beyond this, a quadratic curve (a parabola) is really NOT approximated mathematically by a sinusoidal curve, a least if more than a half cycle is shown for the sinusoidal approximation as was done in the above article.

Finally, as for the article’s Figures 3, 4, 5 and 6 each showing plots of “simulated data from 2026 to 2030” . . . well, I have never considered simulated data to be anything more than a playtoy.

Alan Welch
Reply to  ToldYouSo
July 2, 2026 1:55 pm

The plots 7 to 10 start at 2022 as the “acceleration” calculated by Nerem et al is more erratic for shorter time scales. That a sinusoidal fit is worth considering can be seen in plots of residuals – actual value minus value on straight line. I have shown these many times in my other papers which you can find by using the search feature.
Also the final figure 11 is also very revealing.
The red line is what would be obtained if “accelerations” were calculated if the variation had been a sinusoidal curve. Nerem says the “acceleration” is constant, I’m saying it varies as a damped oscillation and the figures point that way. Why you refer to inflection points as being bad confuses me. I’m not implying a sinusoidal curve is approximating a quadratic curve. I am saying a sinusoidal curve is better than a quadratic curve. If I had used a quadratic curve as cavalier as Nerem et al in my 40 years in engineering I would have been shown the door.
You seem to dislike simulated data. Surely science is derive data – formulate a theory – predict future outcomes – compare data and theory -repeat.
The main essence of my work is to show that a quadratic fit is a complete no go and in this last paper to show that the next 5 years should show its complete breakdown as a viable theory. Changes to the data – of which there are many – have kept the “acceleration” level high but in all recent releases of data the “accelerations” are all tending to enter a rapid decrease phase.

Reply to  Alan Welch
July 2, 2026 5:52 pm

Nerem says the “acceleration” is constant,”

Nerem is an idiot / climate zealot..

See the graphs posted further down.!

Rate of change of linear trends is a mess before about 1970, but has strong cycles since 1970.. Trend from 2010 to 2017 was downwards at Battery Park (see chart)

None of this is simple curves, but sinusoidal is obviously more realistic than quadratic in this case…

.. but is also not appropriate for any predictive work.

battery-tide
Reply to  Alan Welch
July 3, 2026 10:49 am

First, thank you for addressing the points that I raised in my comment.

You say,
“That a sinusoidal fit is worth considering can be seen in plots of residuals . . . Nerem says the “acceleration” is constant, I’m saying it varies as a damped oscillation and the figures point that way.”

IMHO, the choice of which mathematical function should be used to obtain a best fit to a given data set—and especially if one wants to make predictions based on that chosen mathematical function—should be consistent with the character of physics associated with that data.

I assert there is no physical basis to believe sea level acceleration has a underlying process that can be modeled as a damped sinusoidal oscillation with an asserted period of about 30 years as reflected in your plotted red curves. (Incidentally, this is the reason I previously pointed out the inflection points in those curves.)

Fundamentally, did something happen affecting sea level about 30 years ago (or more recently) to “kick off” this damped oscillation? . . . not that I know of. Is there some currently known physical process associated with sea level acceleration “forcing” that has a damped sinusoidal period of about 30 years? . . . not that I know of. If there was a underlying 30 year cyclic driver, what is it and what would cause it to dampen out so quickly (i.e., within less than 4 full cycles, or in less than 150 years)?

If Earth had had a recent meteor/asteroid impact, or a gravitational disruption from a passing large celestial object, or a major tectonic event, or perhaps just a large land-based water dam or glacier breaking with resulting flooding into a major ocean, I could see something along these lines as setting off sea-level oscillations (aka accelerations), but none of these have happened recently AFAIK.

Alan Welch
Reply to  ToldYouSo
July 3, 2026 1:19 pm

The “accelerations” derived by Nerem are not real but an outcome of the process in forcing a quadratic curve. Should the overall behaviour of the actual sea level data (not the global sea levels as 5% not measured) follows a sinusoidal curve then the “accelerations” for this sinusoidal curve will decay in the form of a damped sinusoidal curve.
If Nerem et al had not forced a constant “acceleration” on the world, life and the mathematics would have been a lot more simple.
The so called damped sinusoidal curve is not physical but follows the action of applying a quadratic fit to the sinusoidal data and calling it “acceleration”.

Reply to  Alan Welch
July 4, 2026 8:38 am

The apparently-intractable difference between us is given in your last sentence: you claim the data is “sinusoidal” and I assert there is no objective sea level data over the last 30 years (or longer) that supports that claim for SL accelerations.

Let’s just let it rest there.

Curious George
July 2, 2026 1:40 pm

I am offended by an article using AI as a scientific arbiter, and by graphs with a time axis labeled “years since 1993”. Please use AI here.

Alan Welch
Reply to  Curious George
July 2, 2026 2:08 pm

Not sure what offends you. I’m not a great fan of AI but here I asked two almost identical questions. In one I did the work in the other Nerem et al did the work. Resulted in two very different responses. For a paper that has had so much influence I feel it is based on a unacceptable approach, that is using a quadratic fit and excessive extrapolation.

What is wrong with a graph labelled “years since 1993”. Nerem et al submitted their paper in 1993 so all data sets start from 1993.

Curious George
Reply to  Alan Welch
July 3, 2026 10:42 am

I prefer labels like 1994, 1994, etc., not 1, 2, 3. I know that we live in 2026, not in 33.

Alan Welch
Reply to  Curious George
July 3, 2026 1:23 pm

Everyone to their own choice. I prefer 33 instead of 2026 as I know how far into the mathematical process I am. Other graphs do benefit from real dates and I change it then.

July 2, 2026 2:20 pm

Analysis shows there are cycles within sea level trend data.

For example.. Back calculated linear trends for Battery Park suggests a cycle of around 12-14 years since the 1970s… and maybe another cycle of about 60-70 year

If you only use 25 years of data, the starting point in relation to either cycle will make a very large difference to any trend or acceleration calculation.

Battery-7-and-30-year-linear
Alan Welch
Reply to  bnice2000
July 3, 2026 1:19 am

Starting date and length of readings are very significant. If Nerem had started about 15 years later he might have had a negative quadratic term and written a paper about deceleration and the coming ice age!!

Kevin Kilty
July 2, 2026 2:52 pm

Lots and lots of effort goes into figuring sea level rise, but a very basic consideration remains unanswered.

Generally speaking, and possibly always, the shoreline slopes away from the ocean. This means that as sea level rises there is more room per unit of rise at the interface of ocean to overlying atmosphere to hold water. As sea level rises the form of this hypsometric curve changes because the region within the tidal range undergoes erosion if nothing else.

Thus we are faced with trying to devine what is going on with regard to fluid input to the oceans when not only is the level change extremely small and subject to noisy influences, but the shape of the container, the ocean basins, changes in unknown ways.

The hypsometric curve is shown as a straight sloping line between ten meters below sea level and ten meters above, with a bit of a kink at zero. Yet, what really goes on in detail in the tiny range right at sea level is anyone’s guess and subject to, well, let’s say convenient narratives.

don k
July 2, 2026 3:04 pm

A few OPINIONS. Which is to say that it’s certainly fair to differ.

  1. IMO, fitting a quadratic to lousy data is then extracting the X^2 term as acceleration is probably a waste of time. True, the term has the proper dimension for acceleration (mm/yr/yr). But that’s pretty much the only positive thing one can say about it. First of all, there’s no reason to believe that the acceleration is quadratic. (Exponential — a constant rate of increase — seems to me more likely.) Second, one always gets an answer, but unlike statistical criteria, there’s no figure-of-merit for the quality of the fit. And finally, eyeballing the data says indicates that it’s not remotely quadratic. To quote Gavin Schmidt — about as confirmed a climate change believer as is possible. “If it doesn’t look like a quadratic, don’t fit a quadratic to it”
  2. Were the data less ghastly, I’d probably try an exponential fit rather than a quadratic fit. Here is a link to a discussion of how to do that: https://openbooks.library.umass.edu/p132-lab-manual/chapter/introduction-to-linearizing-with-logarithms/ Works well for computing compound interest, I’ve had some luck in the past using it to predict future values of real world variables.
  3. Oddly, a subset of tidal gauges, while dubious for computing sea level rise MIGHT be more suitable for computing sea level rise acceleration than the satellite data. The tidal gauges data covers a much longer time span. Sea level rise is a worldwide factor added on top of every local variation. So even if the gauge is sinking or rising due to tectonics, the acceleration would theoretically be the same at all sites. You’d need long term data from a number of sites with worldwide physical distribution. And you’d need to at least screen the data for sudden jumps due to earthquakes or undocumented site changes. For an example, of what needs to be looked at, see the https://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?id=9414290. Note the sudden (unexplained) drop near the end of the nineteenth century. I have no idea what caused that, but it has to be corrected for or the site needs to be rejected.
  4. In my OPINION, Sea Level rise acceleration computation in its current state is somewhere between faith based science, and utter nonsense.
Reply to  don k
July 2, 2026 4:28 pm

” So even if the gauge is sinking or rising due to tectonics, the acceleration would theoretically be the same at all sites.”

There was discussion recently about Battery Park… The surveying/geo people have done a major examination.

Turns out that while the measure tide gauge shows about 2.9mm/yr, there is significant subsidence, and the actual sea level rise is about 0.7mm/yr.. (they also calculated an acceleration of 0.008mm/yr².. but that may also come from changes in the rate of subsidence, which they didn’t have the long term data to calculate)

That 0.7mm/yr is not dissimilar to the to the 0.75mm/yr in the high tide measured at Fort Denison in Sydney Australia (very stable but maybe moving very slightly).
I don’t know if there is any calculatable “acceleration” in the Fort Denison data.

fort-denison
Alan Welch
Reply to  don k
July 3, 2026 1:43 am

Thanks for your detailed response.

Great to see quadratic fitting rubbished. When I use the calculated “accelerations” and show how they change with time is not that I accept them as accelerations but comparing how they change with time compared with “accelerations” for some other curves (sinusoidal?) can be informative. Not so sure of exponential over long periods. In some of my other papers I calculate residuals as the difference between the actual listed values and the value on the best linear line. Fitting a sinusoidal and quadratic curve and calculating standard deviation of the errors shows the sinusoidal is much more accurate and tends to become even more accurate with each new set of additional data.
When studying the Brest tidal gauge data it can be fitted with the usual very low acceleration but equally a spectral analysis pointed to a 1000+ year sinusoidal fit and several curves with periods around 1000 years can be fitted just as accurately.
The data may be nonsense but that is not an excuse for not trying to understand. You just don’t know. Nothing ventured nothing gained.