An interesting new paper (behind paywall) has been accepted for publication in the Journal of the Atmospheric Sciences. The paper by Jiansong Zhou and Ka-Kit Tung of the University of Washington, Seattle is titled “Deducing Multi-decadal Anthropogenic Global Warming Trends Using Multiple Regression Analysis”. This paper will add fuel to the recent discussions about the nature of the global warming trend and whether it recently has stabilized or not. The authors by the way conclude it has not. Their main conclusions however is:

When the AMO is included, in addition to the other explanatory variables such as ENSO, volcano and solar influences commonly included in the multiple linear regression analysis, the recent 50-year and 32-year anthropogenic warming trends are reduced by a factor of at least two. There is no statistical evidence of a recent slow-down of global warming, nor is there evidence of accelerated warming since the mid-20th century.

This study is following the same approach as Foster/Rahmstorf 2011 and Lean/Rind 2008 (trying to correct the global temperature for ENSO, solar and volcanoes) but adds the Atlantic Multidecadal Oscillation to their multiple linear regression analysis. This leads to their figure 1b above. What we see is a longterm trend that has hardly changed during the past century.

Now as always this result can be interpreted in many different ways. The century scale trend is still 0.68 degrees Celsius suggesting little of the total trend of 0.8 degrees C can be attributed to solar, volcanic, ENSO and AMO. That’s what the authors seem to suggest as well when they write (bold mine):

The conclusion that we can draw is that for the past 100 years, the net anthropogenic trend has been steady at approximately 0.08 °C/decade.

So for them anything that’s left after filtering out the natural forcings and natural variability is just ‘anthropogenic’. For me this conclusion is rather premature. But before I explain why let’s focus on the other trend lines that the authors show. Just like Foster/Rahmstorf they conclude that there is no slowdown recently:

There is no statistical evidence of a recent slow-down of global warming

However the trend they find for the recent 32 years (0.07ºC/decade) is far lower than that of Foster/Rahmstorf (0.17ºC/decade). If the approach has any validity at all this would suggest that the AMO alone explains the difference between the Zhou/Tung and Foster/Rahmstorf trend.

The paper by Zhou claims that in the last 32 years, the period in which greenhouse gases are supposed to be the dominant forcings, in fact some 60% (0.1ºC of the total 0.17ºC/decade) of the trend can be ‘explained’ by a combination of ENSO, AMO, solar and volcanic forcing). Ergo, only 40% of the trend could be attributed to other factors among which greenhouse gases are of course a logical candidate.

However there are other candidates as well of course. There is ongoing debate about the influence of siting issues on the temperature measurements on land as well as the Urban Heat Island effect and other socio-economic influences. In a controversial and well known paper Michaels/McKitrick estimated that “Using the regression model to filter the extraneous, nonclimatic effects reduces the estimated 1980–2002 global average temperature trend over land by about half.” If true even less of the remaining trend can be attributed to greenhouse gases.

The Zhou study could therefore have serious implications for our estimates of climate sensitivity. The paper though is completely silent about these potential implications, something that reviewers could have raised.

As said above Zhou and Tung call the remaining century long ‘underlying’ trend ‘anthropogenic’. Whether this is ‘right’ could be questioned with their figure 2 (see below). Here one sees that the anthropogenic forcing (green line) seems to underestimate the adjusted trend in the period (1889-1970) while it seems to overestimate the trend thereafter. This suggests that still not all the relevant factors (either natural or anthropogenic forcings or natural variability) are included in the regression analysis. The residuals in figure 2b still show trends which would not be the case, Zhou and Tung write, if the regression analysis would be perfect.

This leaves enough room for all to bend the paper in one’s preferred direction.