Sea Smoke and Mirrors

There’s a new post at WUWT by none other than Albert Parker (of “making stuff up” infamy), a.k.a. Alberto Boretti. It’s about sea level rise.


No doubt about it, the sea is rising. Fast. It’s already high enough that coastal cities flood even without storms or torrential rainfall, they can flood from extemely high tide alone. This is a huge problem, already costing hundreds of millions of dollars for cities like Miami. It will cost even more, a lot more, in the future — the near future.

It’s also high enough that when storms come, especially those that bring big “storm surge” which leads to flooding, the sea is already higher than it used to be so that makes the flooding far worse. Ask the folks in New York and New Jersey. They know.

But Albert Parker/Boretti just wants to talk about one thing. He’s not denying that sea level is rising (very few are that stupid). He wants to tell us that sea level isn’t accelerating, i.e. that the rate of rise itself isn’t increasing. But he can’t back that up with anything but smoke and mirrors.

What evidence does he present? He urges you to visit the trends page at PSMSL (Permanent Service for Mean Sea Level). There, you can view a map of sea level trends for a variety of time spans, and you can choose the time span yourself (there’s a slider below the map). Only locations with enough data are included (at least 70% of years within the specified time span).

Parker begins with European stations and a time range from 1900 to 1975. That gives this:

Parker1

Then he extends the time range to 1900 through 2014, which gives this:

Parker2

Then he says this:


· Surprise, surprise, no major changes …..

· Do you spot any significant change?

· Those that are claiming the sea levels are rising sharply than ever before at an accelerating rate are simply not telling the truth.

· This may realize (for now) downloading and analyzing the PSMSL data, or even analyzing the data online.

· In a few years’ time, also this data base will be corrupted and the truly measured data will be replaced by computations or reconstructions.

There are fascinating aspects to his “analysis.” Foremost is that fact that there isn’t any.

It’s just “look at this” followed by “look at this” followed by “Surprise, surprise, no major changes.” Then comes the inevitable “Do you spot any significant change?” Yes, I do. But then, I looked closely and I know what I’m looking for. Most readers don’t, and don’t.

Also interesting is the comparison of 1900-1975 with 1900-2014. If you’re looking for changes, why compare two time spans that overlap (in fact, the 2nd time span includes all of the 1st). Why not just compare the separate time spans 1900-1975 and 1976-2014. Even better, make that later one 1976-2015 (since there’s another year in the PSMSL database).

Of course, including 2015 would require downloading the data and anlyzing it yourself, because their “trends” tool doesn’t include it yet. Downloading data and analyzing it yourself … what kind of blog would do such a thing?

We would. We’ll take every station in the PSMSL, extract the data from 1900 onward, and select only those which have more than 80 complete years of data (that’s 69% of the time span). Then we’ll remove the seasonal cycle and fit a continuous piecewise linear trend, allowing a trend change in 1976. That will estimate the rate of sea level rise in the two separate time spans. We can even estimate the change in the rate of sea level rise.

Station #1, for instance, is Brest in the northwest of France, and has 102 complete years since 1900 — plenty to meet the selection criteria. It gives this:

Brest

Here’s a close-up on the trend fit alone:

Brest2

But we don’t just want to do a single station. There are 89 which meet the selection criteria. Here’s a histogram of their changes in sea level rise rate:

histo

A couple of those are way out there — I don’t trust ’em. So let’s remove those:

histo2

Either way, removing outliers or not, the bulk of them show positive increases in sea level rise rate. The vast majority, in fact. If we test whether or not they are, en mass, positive or negative, we can’t rely on the super-strong statistical significance of a t test because they’re obviously not following the normal distribution. Rather, we should rely on the super-strong statistical significance of the non-parametric Wilcoxon rank sum test.

We can also make a little map of the change in sea level rise rate for European stations. It won’t have the coastal borders like that from the PSMSL trends page, but it will show how sea level rates have changed rather than just what they are (up arrows for increasing sea level rise, down arrows for decreasing):

Europe

Somehow, Albert Parker/Boretti managed to take these data and claim “no major changes.” Perhaps more amazing is that he probably actually believes it.

Sea level rise is one of the biggest problems we’ll face in upcoming decades, in fact it’s a problem now. How bad it’s going to get is highly uncertain. But as recent research shows, we could be in for a truly terrible century. Of course there’s tremendous uncertainty … but uncertainty is not your friend.


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17 responses to “Sea Smoke and Mirrors

  1. Nice analysis. One question: what does “dd” stand for?

    [Response: It’s the difference in sea level rise rate from before to after 1976. It’s also sloppy axis labeling on my part.]

  2. Scientists really are incompetent…they spent so much time ‘fudging’ temp and satellite data they forgot the sea level rise data. sigh. /sarc

    I’m curious about the effects of sea level rise in the BC lower mainland. A few times now in the past few years (twice since November) storm surges have washed debris up onto the walking paths and train tracks, something that has happened in the past but was a rarity.

    One of the storms last year came in so high it moved a huge log (was about 4 feet/1.5m in diameter, around 25-30 feet long) that had been sitting on the shoreline for decades (washed there by a previous high tide storm). That log is now sitting 70 m further inland on land I’ve never seen under water. It boggles my mind at how high that storm surge must have been to have move a log that size that distance (I have pictures of it that I should throw on-line along with pics of its new location).

  3. As one of my geology profs always said “all sea level is local.”

    Scandanavian crust is still undergoing isostatic rebound from the loss of ice since the last ice age, which explains that cluster. It looks like the two large down-arrows in the south are near the Po River delta (which I would have thought would be slumping) and somewhere near the Crimean Peninsula. Tectonics mishegas?

  4. As pointed out over at Richard Telford’s place, it’s bad enough that Parker does his tricks on WUWT, but he actually got some of this stuff published:
    http://www.sciencedirect.com/science/article/pii/S0964569116300205

    Very aptly named an “opinion” by the journal, so they have plausible deniability that they led nonsense through…after all, it is just an opinion.

    • And, it appears that this is the same Parker behind this recent paper on AMOC that is currently being touted at WUWT: http://www.sciencedirect.com/science/article/pii/S246801331500008X He seems fond of some of these somewhat dubious open access journals.

      • Yes, that one was brought up at Climate Etc. Parker argues that a small area of cooling in Central Africa disproves the notion that freshwater from Greenland could be causing the cold blob south of Greenland. It’s an assertion with nothing to back it up. His papers appear to contain many unsupported assertions.

      • Well, after all, all that data merely serves to inhibit your creativity! If you manage to keep yourself completely divorced from empirical data, you can believe what ever you want.

  5. I assume the linear line for the data gap in the first Brest plot is a plotting artifact and not interpolation. Correct? (I constantly have to remind myself to be careful what other people see when plotting gappy data).

    [Response: Yes.]

  6. And we notice that all of the locations seeing decreasing sea levels in his map are in Scandinavia. There’s a simple reason for this; they’re facing post-glacial rebound, as happens when you remove billions of tonnes of ice. This is very well known, and has been established over more than a century.

    For *any* person to posit themselves as a ‘sea level’ expert and leave this out betrays either their complete ignorance, or their complete mendacity.

  7. I’ve been wondering and reading on the statistics of sea level rise and acceleration.

    One of the lessons I’ve learned here is that it’s important to factor uncertainty in trend analysis. The histograms above presents very strong evidence of increasing rate of sea level rise around Europe. But is it statistically significant? I would guess ‘no’, owing to the larger variability we get in regional data, but I don’t have the skill to assess uncertainty myself. But I’m curious about the broader perspective.

    For global sea level rise and acceleration, the impression I’ve gleaned from reading about it is that while the mean trend estimates show recent acceleration, it is not so certain statistically/structurally for the centennial record. A post I read on the statistical question at Open Mind suggested to me that the answer is uncertain.

    https://tamino.wordpress.com/2011/03/31/so-what/

    The final curve in that post approximates global surface temperature. Stefan Rahmstorf posted about that linkage at RealClimate, referencing studies that include that point there, eg, Rahmstorf et al (2011). That study argues that large observational uncertainties and interannual/interdacadal variation in acceleration are challenging factors in determining acceleration for the 20th century.

    The questions I have in mind are:

    1) Does ‘aliasing’ of global temp/SLR have to be accounted in assessing acceleration since 1900?

    2) Are we able to say with any confidence that global sea level rise has accelerated since 1900?

    Those questions may have been dealt with in the Rahmstorf paper. Acceleration since 1930 (not statistically significant) was easy enough to glean, but the language was a little too technical for my skill level to understand if the result is different if the period is the whole century (long-term rate changes being an important part of the mix for future projections).

    Any pointers gratefully received.

    • No, I haven’t. Been making my way through Ch 13 AR5. I’ll read these, thanks, JCH.

      • To me, I have confidence reality is pretty close to Hay’s ~1.2mm pyr from 1900 to 1990; Watson’s 2.6mm to 2.9mm pyr from 1993 to 2014, and AVISO’s ~4.3mm! since 2008.

  8. CSIRO’s global mean sea level data (based on Church & White 2011) certainly show acceleration:

    1.1 mm/yr before 1940
    1.7 mm/yr from 1930 to ca. 1998,
    3.9 mm/yr from 1998 to 2013.

    The annual data from here http://www.cmar.csiro.au/sealevel/sl_data_cmar.html are available for exploration here https://tanytarsus.shinyapps.io/changepoint/

    • I’ve not seen that app before. Thanks. Structural uncertainty will not be accounted for. I notice the Bayes factor is infinite. How do you interpret that?

      • The infinite BF arises from dividing by zero, which arises from rounding a tiny number. Basically it means the observed data would be very much (effectively infinitely) more likely to arise from a non-linear model than from a constant slope model.