Rasha Kamel of the Azimuth Project pointed us to a report in Science Daily which says:

Planet Earth experienced a global climate shift in the late 1980s on an unprecedented scale, fueled by anthropogenic warming and a volcanic eruption, according to new research. Scientists say that a major step change, or ‘regime shift,’ in Earth’s biophysical systems, from the upper atmosphere to the depths of the ocean and from the Arctic to Antarctica, was centered around 1987, and was sparked by the El Chichón volcanic eruption in Mexico five years earlier.

As always, it’s good to drill down through the science reporters’ summaries to the actual papers.  So I read this one:

• Philip C. Reid et al, Global impacts of the 1980s regime shift on the Earth’s climate and systems, Global Change Biology, 2015.

The authors of this paper analyzed 72 time series of climate and ecological data to search for such a regime shift, and found one around 1987. If such a thing really happened, this could be very important.

Here are some of the data they looked at:

Click to enlarge them—they’re pretty interesting! Vertical lines denote regime shift years, colored in different ways: 1984 blue, 1985 green, 1986 orange, 1987 red, 1988 brown, 1989 purple and so on. You can see that lots are red.

The paper has a lot of interesting and informed speculations about the cause of this shift—so give it a look.  For now I just want to tackle an important question of a more technical nature: how did they search for regime shifts?

They used the ‘STARS’ method, which stands for Sequential t-Test Analysis of Regime Shifts. They explain:

The STARS method (Rodionov, 2004; Rodionov & Overland, 2005) tests whether the end of one period (regime) of a certain length is different from a subsequent period (new regime). The cumulative sum of normalized deviations from the hypothetical mean level of the new regime is calculated, and then compared with the mean level of the preceding regime. A shift year is detected if the difference in the mean levels is statistically significant according to a Student’s t-test.

In his third paper, Rodionov (2006) shows how autocorrelation can be accounted for. From each year of the time series (except edge years), the rules are applied backwards and forwards to test that year as a potential shift year. The method is, therefore, a running procedure applied on sequences of years within the time series. The multiple STARS method used here repeats the procedure for 20 test-period lengths ranging from 6 to 25 years that are, for simplicity (after testing many variations), of the same length on either side of the regime shift.

Elsewhere I read that the STARS method is ‘too sensitive’. Could it be due to limitations of the ‘statistical significance’ idea involved in Student’s t-test?

You can download software that implements the STARS method here. The method is explained in the papers by Rodionov.

Do you know about this stuff?  If so, I’d like to hear your views on this paper and the STARS method.