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How much is sea level rising?

What the science says...

Select a level... Basic Intermediate

A variety of different measurements find steadily rising sea levels over the past century.

Climate Myth...

Sea level rise is exaggerated

"We are told sea level is rising and will soon swamp all of our cities. Everybody knows that the Pacific island of Tuvalu is sinking. ...

Around 1990 it became obvious the local tide-gauge did not agree - there was no evidence of 'sinking.' So scientists at Flinders University, Adelaide, set up new, modern, tide-gauges in 12 Pacific islands.

Recently, the whole project was abandoned as there was no sign of a change in sea level at any of the 12 islands for the past 16 years." Vincent Gray).

Gavin Schmidt investigated the claim that tide gauges on islands in the Pacific Ocean show no sea level rise and found that the data show a rising sea level trend at every single station.  But what about global sea level rise?

Sea level rises as ice on land melts and as warming ocean waters expand. As well as being a threat to coastal habitation and environments, sea level rise corroborates other evidence of global warming 

The blue line in the graph below clearly shows sea level as rising, while the upward curve suggests sea level is rising faster as time goes on. The upward curve agrees with global temperature trends and with the accelerating melting of ice in Greenland and other places.

Because sea level behavior is such an important signal for tracking climate change, skeptics seize on the sea level record in an effort to cast doubt on this evidence. Sea level bounces up and down slightly from year to year so it's possible to cherry-pick data falsely suggesting the overall trend is flat, falling or linear. You can try this yourself. Starting with two closely spaced data points on the graph below, lay a straight-edge between them and notice how for a short period of time you can create almost any slope you prefer, simply by being selective about what data points you use. Now choose data points farther apart. Notice that as your selected data points cover more time, the more your mini-graph reflects the big picture. The lesson? Always look at all the data, don't be fooled by selective presentations.

graph from Church et al. (2008)

Other skeptic arguments about sea level concern the validity of observations, obtained via tide gauges and more recently satellite altimeter observations.

Tide gauges must take into account changes in the height of land itself caused by local geologic processes, a favorite distraction for skeptics to highlight. Not surprisingly, scientists measuring sea level with tide gauges are aware of and compensate for these factors. Confounding influences are accounted for in measurements and while they leave some noise in the record they cannot account for the observed upward trend.

Various technical criticisms are mounted against satellite altimeter measurements by skeptics. Indeed, deriving millimeter-level accuracy from orbit is a stunning technical feat so it's not hard to understand why some people find such an accomplishment unbelievable. In reality, researchers demonstrate this height measurement technique's accuracy to be within 1mm/year. Most importantly there is no form of residual error that could falsely produce the upward trend in observations. 

As can be seen in an inset of the graph above, tide gauge and satellite altimeter measurements track each other with remarkable similarity. These two independent systems mutually support the observed trend in sea level. If an argument depends on skipping certain observations or emphasizes uncertainty while ignoring an obvious trend, that's a clue you're being steered as opposed to informed. Don't be mislead by only a carefully-selected portion of the available evidence being disclosed.

Current sea level rise is after all not exaggerated, in fact the opposite case is more plausible. Observational data and changing conditions in such places as Greenland suggest if there's a real problem here it's underestimation of future sea level rise. IPCC synthesis reports offer conservative projections of sea level increase based on assumptions about future behavior of ice sheets and glaciers, leading to estimates of sea level roughly following a linear upward trend mimicking that of recent decades. In point of fact, observed sea level rise is already above IPCC projections and strongly hints at acceleration while at the same time it appears the mass balance of continental ice envisioned by the IPCC is overly optimistic (Rahmstorf 2010).

Basic rebuttal written by doug_bostrom


Update July 2015:

Here is a related lecture-video from Denial101x - Making Sense of Climate Science Denial

This rebuttal was updated by Judith Matz on September 13, 2021 to replace broken links. The updates are a result of our call for help published in May 2021.

Last updated on 5 July 2015 by pattimer. View Archives

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Further viewing

From Peter Hadfield (potholer54 on YouTube) published on Dec 5, 2021

Compare two photos 130 years apart and it looks as though sea levels haven't moved. So why all the fuss about rising sea levels and evacuating islands? This video closes the yawning gap between internet myths and science.


 

From Peter Sinclair (greenman3610 on YouTube) published on Sep 24, 2009

Comments

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Comments 76 to 100 out of 171:

  1. daniel at 14:18 PM on 10 July, 2010 A quick chart with all of the data used by Donnelly 2004, except the tide gauge data (NY) uses monthly mean values and extends to today. The tide gauge data consists of very frequent samples (modern readings are every six minutes or so) averaged over each month. As such errors are extremely low. The seasonal MSL variations are retained in this chart and represent measured mean sea level. The overall long term linear trend is 2.8mm/year, however in this tide gauge data the trend has gradually accelerated over the measurement period. The sediment, pollution and pollen derived data is shown with approximate two sigma and one sigma error envelopes. However it should be noted that the variance from a straight line fit for all points is very low, and in addition a smooth curve fit is further suggested by the relatively low level of decadal and inter-annual trend variation in the 150 year tide gauge record. The accelerating trend in sea level rise is evident in the overall data set. The error bars on the sediment data overlap the actual tide measurements even when an annual MSL average or overall fitted linear trend for tide gauge data is used.
  2. KR at 14:34 PM on 11 July, 2010 "you look at the larger gaps in the paleo data from this (and only this) paper, and assert that large SLR rates could occur in the spaces between the data points?" But also the large error limits of the points which indicate a high uncertainty as to where the true sea level was. "I point out between, because the slope between 9/11 and 7/8 that you use as an example shows an average slope of ~0.9-1.0mm/year" Well you clearly misunderstood me. I was saying within the small group 9-11 and also within a small group of 3-4 data points which include 7-8 either 7-10 or 5-8. "for such a large value of SLR (derivative) to occur in that period, there would have to be a corresponding low/negative SLR in that same period in order for the integral over that period to still yield ~1mm/yr?" Yeah, so, why is that so unlikely? I don't think we have to evoke negative trends to support my analysis.
  3. daniel, could you please explain this sentence: "It clearly shows that modern swings in SLR fit inside the error envelope of a shallow, linear long term trend in paleo data". As I understand it, you're saying that the tide gauge seas level data (not trend) are within the trend error of paleo data. Comparing trends is to compare 1.0 mm/yr (+/- 0.2 mm/yr) with 2.4 mm/yr. Comparing sea level, instead, is to see if tide gauge data are within the limit of variability of sedimentary data. You're doing the latter, so you're not comparing trends. Is it possible, at least in principle, that there has been similar up swings at 2.4 mm/yr in the past? Yes, but putting physics aside. If you take the lower error bar of a point and the higher of another you might get such trends. But it's unlikely, there's nothing that make us think it's actually happened and it's hard to immagine a mechanism producing such up swings. Are you aware of a sudden increase in temperature or large land ice melt between 1300 and 1800 A.D.? Are you aware of other, higher resolution, datasets showing this swings?
  4. Riccardo at 18:04 PM on 11 July, 2010 No you see the error envelope on Peter's graph. They are continuous lines that extend along either side of the paleo trend. What I am saying is that the tide gauge data points fit inside of that if it were extended over sample 1. The MSL does anyway. You can see this more clearly in Donnely which uses averaged tide gauge data which lie over the sample 1 uncertainty box. Donnelly and Peter seem to think that this overlap supports their case but actually it supports mine. You can see that paleo samples do not adequately show us where the true sea level is because they have such high uncertainties. A big deal is made about the centres of the boxes but clearly the tide gauge data shows the centres aren't that important because the centre of sample box 1 does not lie directly on the averaged data point trend of the tide gauge data. The mean height of sample 1 fits the tide gauge data at 1950 rather than the center of the assigned date range which is 1975. That's directly measured data lying on the very extreme of the 95% confidence interval for the mean height estimate of sample 1 and then I'm told tbat short term deviations in the older data are unlikely to be far from the centres of the boxes or the linear model. For at least three samples 8, 10 & 11 the linear model is far from the box centres. You guys can't have it both ways.
  5. daniel at 13:42 PM on 11 July, 2010 "Understatement of the year" "overstatement of the year" etc. Histrionics does not make up for lack of knowledge, nor does it engender respect. To put these sea level numbers into context, the sea level varies by around 1m every day close to this site, and through year seasonal and tidal variations add to this. I believe I have shown from the data that your argument (that large intersample variations containing trends similar to those of the past 150 years are "likely") is weak.
  6. read above pete
  7. daniel at 23:20 PM on 11 July, 2010 No, you have not said this until now. What you have argued is that extending the approx 1mm/year long term linear trend from pre-tide gauge data beyond 1856 by including point 1 gives a 1.2mm trend and error bars which can fully accomodate the total tide gauge data record anywhere inside this trends error envelope, therefore you argue this paper should not be used as evidence that the recent 2.8mm/year trend is unusual. Your case for including point 1 in an overall 1.2mm trend is invalid. Clearly, the density of tide gauge data makes any influence of point 1 marginal on the measured 2.8mm/yr trend since 1856, clearly, the recent measured trend is diverging away from the long term paleo trend. That point 1 error bars overlap the tide data possibly validates point 1, but the fact that the tide gauge data overlaps point 1 does not validate extending the pre-1856 trend. The post 1856 trend is already determined as measured fact by the tide gauge data. Point 1, statistically speaking, is on this trend. The question you are asking really, is: Can the 150 year tide gauge data trend be accomodated inside the pre 1856 error envelope, and show that the longer term trend could most likely have missed similar episodes of acceleration in the past? This is the question I address in my chart. The chart I have given shows the error envelopes based on the statistics given for each point, up to the start of the tide gauge data, which has much lower standard deviation and represents the measured data. It is not the same as a linear trend. It is likely that the envelope will follow or at least accomodate whatever the true trend was. We can only ascribe a probability to this. It is barely possible to fit the tide gauge data into the 2 sigma envelope in one pre 1800 place, but it is not a "good" statistical fit anywhere over any approx 150 year period except after 1800 (by comparing with at least three paleo points, though this is not a strong test). It is not possible to fit inside the 1 sigma envelope anywhere, and the data series deviates away in opposite directions above and below the envelope, indicating significant systematic trend error. I repeat that your suggestion is possible, but not "likely" from this data. Of course we need a reality check, and the temperature record and other work I referenced strengthens the case presented in the paper, and further weakens your hypothesis.
  8. daniel at 23:20 PM on 11 July, 2010 One thing slightly bugged me about my chart, the slight offset between the tide gauge data and the "centre" of the error envelopes, where we would expect the real trend to probably be. I checked the tide stations closer to the site. One (New London, CT, with a shorter record from 1938) is very local, but the other (from 1856, NY) has the longest record. I charted the NY record for this reason. I've now noticed there is a small vertical offset (not unusual between stations) between the two that (subjectively at least) neatly resolves the visible offset in the chart.
  9. In order to also start some fresh productive discussion, hot off the press is the following from Llovel 2010 This is a new measured result from GRACE which goes at least some way to confirm explanations of seasonal variations in mean sea level, and partially answers previous points on this post and also answers some questions on the visualizing sea level post. The further relevance is that land storage contribution to mean sea level trend and budget is slightly negative, giving -0.22 +/-0.05 mm/year, confirming modeling results for this with direct measurements for the first time.
  10. Peter Hogarth at 16:21 PM, Peter, the comment you make about modern tide gauges taking measurements every 6 minutes or so interests me. Given that at some locations the time it takes for the tide to rise can be considerably longer than it takes for it to fall, just a quick look at one site showed over 15 hours rising, 9 hours falling, would taking such regular measurements introduce a bias into the average when comparing against those records where the average is that of the high and low tide measurements?
  11. daniel, "What I am saying is that the tide gauge data points fit inside of that if it were extended over sample 1." They are inside the sedimentary data uncertainty and we expect them to stay there for a while given the difference in the slopes. Ok, but they do have a different slope. Does this tell you something?
  12. Riccardo at 06:08 AM on 12 July, 2010 Yes, it tells me that short term variations are quite possible within the paleo data set. It is verified by the highly deviant tide gauge results still lying within the uncertainties of the modern sedimentary data.
  13. Peter Hogarth at 02:15 AM on 12 July, 2010 "No, you have not said this until now." Pretty much what I've been saying the whole time Pete. Sure it's a different approach but what I'm saying should have been obvious from the very beginning. "What you have argued is that extending the approx 1mm/year long term linear trend from pre-tide gauge data beyond 1856 by including point 1 gives a 1.2mm trend and error bars which can fully accomodate the total tide gauge data record anywhere inside this trends error envelope," No not anywhere. For instance it is unlikely to have occurred between 1700-1850 but there is no evidence to suggest it couldn't have occurred between 1300-1700. "Your case for including point 1 in an overall 1.2mm trend is invalid. Clearly, the density of tide gauge data makes any influence of point 1 marginal on the measured 2.8mm/yr trend since 1856, clearly, the recent measured trend is diverging away from the long term paleo trend." Uh huh.... but the divergence is covered by the uncertainty of modern sedimentary data. Sedimentary data that lies on a 1.2mm/yr 700 year trend. Hmmmmm.....invalid? Maybe, I dunno, highly relevant? "That point 1 error bars overlap the tide data possibly validates point 1, but the fact that the tide gauge data overlaps point 1 does not validate extending the pre-1856 trend." Why? Too inconvenient a fact for you? "Point 1, statistically speaking, is on this trend." It is also.... statistically speaking...... on the 1.2mm/yr trend. Therefore so is the tide gauge data. Statistically speaking of course...... "It is not the same as a linear trend. It is likely that the envelope will follow or at least accomodate whatever the true trend was. We can only ascribe a probability to this." Amen brother, finally we agree on something. "It is barely possible to fit the tide gauge data into the 2 sigma envelopein one pre 1800 place,...." Mere opinion, show it with an overlay. "...but it is not a "good" statistical fit anywhere over any approx 150 year period except after 1800 (by comparing with at least three paleo points, though this is not a strong test)." Which is why Donnelly's paleo data is insufficient for a valid comparison to tide tide gauge. He doesn't have the resolution let alone the certainty. "It is not possible to fit inside the 1 sigma envelope anywhere,..." Mean height of paleo sample 1 has tide gauge lying over 95% (2 sigma) confidence interval extreme. Care to retract? "...and the data series deviates away in opposite directions above and below the envelope, indicating significant systematic trend error." Perhaps only if compared to an irrelevant long term trend on the short term scale. An overlay to help make your point? "I repeat that your suggestion is possible, but not "likely" from this data." Simply not shown at all. On the short term, with the data we have, it's just as likely. "Of course we need a reality check, and the temperature record and other work I referenced strengthens the case presented in the paper, and further weakens your hypothesis" I think what you'll find pete is that if you apply my kind of reality check to all that supportive evidence you will find the AGW hypothesis severely weakened. You can't support poor data and conclusions with more poor data and conclusions. If you can't see the error here you can't thoroughly critique the mass body of evidence you claim is out there. Peter Hogarth at 03:52 AM on 12 July, 2010 Please provide the graph with the relevant data then and provide me with your source so I can also provide graphs of a similar nature.
  14. daniel, here the discussion becames circular and I can only repeate what i wrote in #78. Do we have any evidence of such "short" (one century and a half) term variations in the past or are they just hypothetical? What should have produced these accelarations? What do other datasets say?
  15. Riccardo at 16:26 PM on 12 July, 2010 You tell me. Donnelly can't.
  16. To Riccardo #89 Ok Riccardo again I'l answer a bit more directly. Do we have any real evidence that the 1mm/yr trend existed without short term variations from the paleo data? How can we know if drivers existed or not when the links of SLR to temperature fluctuations are so poorly achieved using paleo data? What do other data sets say Riccardo? Post some links we can discuss it. Here's a graph of Donnelly's data with sample 11 reassigned to the younger date range which was never adequately constrained by Donnelly in the first place. (But he was happy to fit the older date range to suit his trend). Are you sure it's not possible for the recent sea level trends, or very similar slightly less severe uptrends, to have existed in the past given the uncertainty in the paleo data? Does this make the recent uptrend look less alarming? Is all of pro AGW science done this way? You wanna discuss drivers? Post some links.
  17. daniel, step by step things are getting clearer in my opinion and your last graph is very helpful. Now, in light of this new graph, could you tell what should drive these sudden accelerations in the past? Known science can tell just for the last one, the one in the last century, it's mainly ocean thermal expansion and land ice melting. It's up to who's trying to cast doubts on the accepted explanation to provide evidence and reconcile it with other data that support his hypothesis.
  18. Riccardo at 00:00 AM on 13 July, 2010 Well actually I would question whether your claim that SLR is so strongly linked to the percieved warming of the 20th century or if the temperature record is so reliable into the past, both over this period and beyond. But since this is a pro AGW website it is up to people like myself to disprove the unproven. Are there any papers you rely on Riccardo to undoubtedly satisfy yourself of SLR driven strongly by climatic factors and also the reliability of the reconstructed temperature record? Post a link and we'll discuss it. I've only just started to find some time to read some of Peter's links throughout the above discussion.
    Response: Might I suggest starting with Vermeer 2009 that examines the link between sea level rise and temperature, finding the two are closely linked:


    Observed rate of sea-level rise (red) compared with reconstructed sea level calculated from global temperature (dark blue with light blue uncertainty range). Grey line is reconstructed sea level from an earlier, simpler relationship between sea level and temperature (Vermeer 2009).

    Of course, where the paper gets really interesting is when it uses these results to predict future sea level rise which we examine here...
  19. daniel, I'd not look for cutting edge research paper, it's just simple physics. Global sea level may rise due to thermal expantion of the ocean or to the melting of land ice; locally it may rise for a change in the ocean circulation pattern. It has nothing to do with AGW and the like. Add to this that even simple statistics would tell you that going from the lower to the higest end of the uncertainty range is statistically very unlikely. Beyond this, I might we willing to say that global sea level rose because of a rise of the ocean floor with respect to the continental crust or because of a giant movent of masses that locally produced an increased gravitational pull. In principle they are both possible, in practice they're both untenable. And this is also the line we should never cross if we want to talk about the science of any phenomenon instead of producing pseudo-scientific hypothesis.
  20. daniel at 12:31 PM on 12 July, 2010 I suggested the tidal data barely fits into the 2 sigma envelope and does not fit anywhere except where it is using the 1 sigma curves. I have extended these up to point 1 for sake of argument only. You state “Mere opinion, show it with an overlay”. My statement stands.
  21. daniel at 12:31 PM on 12 July, 2010 On data point 1, you state “It is also.... statistically speaking...... on the 1.2mm/yr trend” if we are talking just the non-tide gauge data, I agree, but we are not. “Therefore so is the tide gauge data”. This is incorrect. I have included error bars on the tide gauge data. Do the error bars on the paleo data overlap the tide gauge trend? Yes. Do they overlap the paleo trend? Yes. Could this point be on both trends, Yes. Do the error bars on the tide gauge data overlap the extended paleo trend? No. Could they be on this paleo trend? No. Clearly the trends diverge (and continue to do so). We must accept that the tide gauge record from close to the site in question shows a 150 year relative sea level trend which is in excess of 2 mm/yr. It is important to see that this trend is smooth at decadal timescales over the entire 150 year period. There is no inconvenience to me here, perhaps a basic misunderstanding on your part? The light grey line is the paleo trend. Red is NY tide gauge MWL. Blue is New London tide gauge MWL. New London is relatively local to site. Next I will look at the paleo trends in more detail.
  22. daniel at 12:31 PM on 12 July, 2010 I have also looked at what we can say about short term trends from the paleo data. If your hypothesis was “likely” we should see random or high variations in trend away from the overall trend when looking at any approximate 150 year period in the overall time period. These variations are not random and not large. These are trends from every four consecutive paleo points. I have also taken gradients from three consecutive points, as a three or four point record from this data encompasses a period most similar to the tide gauge data (roughly 150 years). I have also added the shorter New London tidal series (running annual average) for comparison. We should be cautious with this crude approach, but it’s not a “trick”, we treat all paleo data consistently. We allocate a “centre” date for these mini-series, then finally add the measured trends from the two tide gauge series with a centre date for these (solid points below). I am aware I have argued against this breaking up of time series elsewhere, but on this occasion we are actually looking for any evidence of short term changes in gradient - whilst still honouring all of the points in the overall analysis by generating a series of overlapping trends. If deviation of the points from mean trend was high, we would expect inconsistent or noisy results. If large variations had occurred, we would expect to see some significant changes in gradient, especially on such short series. If there was no acceleration in trend, we would see a flat line, or an insignificant trend. The results are surprisingly consistent, all linear fit trends are significantly positive. The derived rate of increase in trend (just from the paleo data) is clear and consistently positive. The addition of the tidal data confirms and increases this trend, showing late period acceleration and giving strong evidence that the most likely earlier and later trends are close to those suggested by Donnelly, whilst also suggesting short and medium term variability similar to the tide gauge data, (which is intuitive). The second order fits are not meant to represent possible variation, but simply to indicate the significant positive second order component, ie acceleration. This analysis supports the conclusions of the paper, and does not support your suggestion.
  23. Surprisingly consistent, indeed. Good job Peter.
  24. Peter Hogarth at 02:45 AM on 13 July, 2010 The 1 sigma bounds are irrelevant Peter. I've already commented on this. Do you see the overlay of the tide gauge data on sample 1? That's right, it crosses the uncertainty box at the mean height and date range extreme. That is the most probable height of sample 1 has a date at the 2 sigma extreme in the date range, the least probable according to you. On this one Donnelly sees it my way since his linear fit does this also at samples 11, 10, 5 and 4 not to mention the extra paleo data used to constrain the C14 ranges.
  25. daniel - or more, properly for those reading daniel's comments, since he's apparently missed the point: The data referred to comes from two different data sources measuring the same quantity. The first is recent tide gauge data (last 150 years), indicating a sea level rise (SLR) of 2.4 mm/yr. The second data set comes from a fairly sparsely but well distributed sampled set of paleo data, based on core sample species abundance, indicating sea levels at various points over the last 1000 years, with a statistically tight best fit of ~1 +/- 0.2 mm/year. The Donnelly paper (single paper) daniel has been discussing therefore concludes that SLR increased from ~1 to 2.4 mm/year starting ~150 years ago, a conclusion completely in agreement with all other data sets (which daniel does not discuss). Daniels argument appears to be that natural variation could account for the last 150 years of 2.4 mm/year SLR. In other words, the ocean isn't warming (contradicts the data), icecaps aren't melting (contradicts the data), it's variability, not global warming. Any similar 2.4 mm/year rise extending over 100+ years in the past would have greatly offset later paleo data points. It's barely statistically possible (but certainly not the statistically justified hypothesis!) that such a rise could have occurred, if a corresponding <1.0 or even negative SLR trend balanced it out, returning later paleo samples to the ~1 mm/year trend. If there was a situation of high variability, that would have to cycle +/- around the 1.0 mm/year level to still show that on the long term averages. This is exceedingly physically unlikely, however, as sea level is driven by steric expansion and icecap/glacial melt, rather low variability processes. In addition, no records, evidence, or data supports sufficient temperature drops or increased icecap/glaciation in the past 1000 years. Additional data sets for paleo sea level also fall on the ~1.0 mm/year slope, with a total sample spacing much closer than the 11 samples in the Donnelly paper, thus leaving no room for such high variability periods. Claiming extreme variability that is somehow missed in the paleo data for even this single paper under discussion is not justified by the evidence. And opening your view to additional data clearly eliminates such variability in the time period under discussion. Asserting that it somehow snuck in between the data points is simply wishful thinking, not science.

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