Dave Burton has visited, and commented extensively on this post. He takes exception to the sea level data I used, and suggests that sea level has been rising at a steady, unchanging rate “since the late 1920s.” To quote him:
Neil, many locations have seen a little bit of acceleration “since the 1800s” — but not since the late 1920s.
Is that true? I’m skeptical.
I’ll make it even harder to find acceleration: I’ll use only data “since 1950.” If Dave Burton is right, it should be quite hard to find any tide gauge stations which show acceleration. I’ll start with San Diego. I could plot it in a way which makes the changes harder to see:
Or I could plot just the data since 1950, in a way which makes the changes easier to see:
The red line shows a lowess smooth fit to the data (with pink shading the 2σ uncertainty range). The smooth enables me to estimate the rate at which sea level is changing; quite useful, although it doesn’t provide a statistical test of whether or not the rate shows any change. To that end, I applied changepoint analysis to identify when the rate might have changed and test its statistical significance. That enables me to estimate the rate during two different time spans since 1950 — if the rate changed, then the “before” and “after” rates should be significantly different. Here are the results for San Diego:
The red line shows the rate estimated from the lowess smooth; the blue line the rate estimated from a piecewise linear fit. Note that after 2011 it seems to have sped up. Pink shading shows the uncertainty range (2σ) for the lowess smooth, dashed blue lines show the uncertainty range (2σ) for the piecewise linear fit.
I strongly suspect that the extremity of the recent rise at San Diego is largely due to local factors, not entirely due to global sea level acceleration. As for the issue at hand — is there acceleration (statistically significant) in tide gauge records after the “late 1920s”? — at San Diego, yes there is.
The same is true for the data from Key West, FL:
Likewise for Boston:
Likewise for St. Petersburg, FL:
Of course, not all tide gauge data sets show acceleration. You might think Honolulu does if you only look at the graphs:
But not so. The very recent rate might seem to be “significantly” higher than the rate before, but that’s an illusion caused by the fact that we get to choose the “changepoint time” to give us the biggest before/after rate difference. That’s the root of the “selection bias” problem; a proper statistical test says no, the Honolulu data don’t show statistically significant acceleration after 1950. It might look like it — but the numbers don’t provide real evidence.
As it turns out, it’s easy to find tide gauge stations which show statistically significant acceleration after 1950 (which means of course, they show it after the “late 1920s”). It didn’t search hard for them, I just looked at the first half-dozen tide gauge records I knew off the top of my head had plenty of data, and there they were. It might be harder to find a record which does not show acceleration, than to find one which does.
Why, then, does Dave Burton find it so hard to identify them?
A few possibilities suggest themselves. First: after the “late 1920s” many stations show both acceleration and deceleration (negative acceleration). If you test the post-“late 1920s” data, and you do so only using a quadratic fit to test for rate change, often the negative acceleration early and positive acceleration late will “cancel out each other” in that particular statistical test, giving the incorrect result.
There’s also the fact that the pattern of change at most tide gauge stations does not resemble a parabola. That makes a quadratic fit a weak test for finding acceleration/deceleration. The piecewise linear fit, for the data post-1950, seems to have good statistical power for detecting acceleration — but it does require the “changepoint analysis” approach to overcome the selection bias problem.
One last possibility: I get the impression that Dave Burton very strongly wants sea level to show no acceleration. This might make him tend to see only what he wants to see (or, not to see what he doesn’t want to see). It’s the age-old problem of “confirmation bias” that we can all fall prey to.
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