Short term trends: Another proxy fight

There are two main responses to complexity in science. One is to give up studying that subject and retreat to simpler systems that are more tractable (the ‘imagine a spherical cow’ approach), and the second is to try and peel away the layers of complexity slowly to see if, nonetheless, robust conclusions can be drawn. Both techniques have their advantages, and often it is the synthesis of the two approaches that in the end provides the most enlightenment. For some topics, the two paths have not yet met in the middle (neuroscience for instance), while for others they almost have (molecular spectrometry). The climate system as a whole is one of those topics where complexity is intrinsic, and while the behaviour of simpler systems or subsystems is fascinating, one can’t avoid looking directly at the emergent properties of the whole system – of which the actual temperature changes from month to month are but one.

We have found some ways to peel back the curtain though. For instance, we know that the shifts in equatorial conditions associated with El Niño/Southern Oscillation (ENSO) in the Pacific have a large impact on year-to-year temperature anomalies. So do volcanoes. Accounting for these factors can remove some of the year-to-year noise and make it easier to see the underlying trends. This is what Foster and Rahmstorf (2011) did, and the result shows that the underlying trends (once the effects of ENSO are subtracted) are remarkably constant:

Another way one might deal with the seemingly contradictory tangle of linear trends is to impose a constraint that any linear fits must be piecewise continuous i.e. every trend segment has to start from the end of the last trend segment. Many of you will have seen the SkepticalScience ‘Down the up escalator’ figure (a version of which featured in the PBS documentary last month) – which indicates that in a noisy series you can almost always find a series of negative trends regardless of the long term rise in temperatures. You will have noted that the negative trends always start at a warmer point than where the previous trend ended. This is designed to make the warming periods disappear (and sometimes this is done quite consciously in some ‘skeptic’ analyses). The model they are actually imposing is a linear trend, followed by an instantaneous jump and then another linear trend – a model rather lacking in physical basis!

However, if one imposes the piecewise continuous constraint, there are no hidden either warming or cooling jumps, and it is often a reasonable way to characterise the temperature evolution. If you looked for a single breakpoint in the whole timeseries i.e. places where the piecewise linear trend actually improves the fit the most, you would pick Apr 1910, or Feb 1976. There are no reasons either statistically or physically to think that the climate system response to greenhouse gases actually changed in August 1997. But despite the fact that August 1997 was shamelessly cherry-picked by David Rose because it gives the lowest warming trend to the present of any point before 2000, we can still see what would happen if we imposed the constraint that any fit needs to be continuous:

A different view, no?

But let’s go back to the fundamental issue – what do all these statistical measures suggest for future trends?

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References

  1. G. Foster, and S. Rahmstorf, "Global temperature evolution 1979–2010", Environ. Res. Lett., vol. 6, pp. 044022, 2011. http://dx.doi.org/10.1088/1748-9326/6/4/044022