“Our results also serve to highlight the importance of Atlantic multidecadal variability in mediating the rate of global warming, and they suggest that these variations deserve more explicit consideration in twentieth century climate simulations and in attribution studies based on recent observations of the rate of change of [global mean surface temperature]. — Wu et al. (2012)
On the time-varying trend in global mean surface temperature
Zhaohua Wu, Norden E. Huang, John M. Wallace3, Brian V. Smoliak and Xianyao Chen
Abstract. The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s. In Wu et al. (2007) we showed that the rapidity of the warming in the late twentieth century was a result of concurrence of a secular warming trend and the warming phase of a multidecadal (~65-year period) oscillatory variation and we estimated the contribution of the former to be about 0.08°C per decade since ~1980. Here we demonstrate the robustness of those results and discuss their physical links, considering in particular the shape of the secular trend and the spatial patterns associated with the secular trend and the multidecadal variability. The shape of the secular trend and rather globally-uniform spatial pattern associated with it are both suggestive of a response to the buildup of well-mixed greenhouse gases. In contrast, the multidecadal variability tends to be concentrated over the extratropical Northern Hemisphere and particularly over the North Atlantic, suggestive of a possible link to low frequency variations in the strength of the thermohaline circulation. Depending upon the assumed importance of the contributions of ocean dynamics and the time-varying aerosol emissions to the observed trends in global-mean surface temperature, we estimate that up to one third of the late twentieth century warming could have been a consequence of natural variability.
Full manuscript available online [here].
Excerpts from the Summary and Discussion:
In the previous sections, we have presented the results of EEMD analysis, which indicate that the secular warming trend during the 1980s and 1990s was not as large as the linear trends of the observation-based global-mean surface temperature (GST) estimated in AR4 (IPCC 2007); and that the unprecedented rate of warming in the late twentieth century was a consequence of the concurrence of the upward swing of the multidecadal variability, quite possibly caused at least in part by an increase in the strength of the thermohaline circulation, and a secular warming trend due to the buildup of greenhouse gases. We estimate that as much as one third the warming of the past few decades as reported in Fig. TS.6 of the Summary for Policymakers of AR4 (IPCC 2007) may have been due to the speeding up of the thermohaline circulation. Other researchers have reached a similar conclusion: Keenlyside et al. (2008), Semenov et al. (2010) and DelSole et al. (2011) on the basis of numerical experiments with a climate model capable of representing the variability of the Atlantic meridional overturning circulation; Wild et al. (2007) on the basis of long term trends in the character of the diurnal temperature cycle at the Earth’s surface; and Swanson et al. (2009) based on an analysis of the partitioning of the GST trends using linear discriminant analysis. Furthermore, by analyzing the temporal derivatives of ST, we have demonstrated that the secular warming trend in GST has not accelerated sharply in the past few decades.
In way of qualifications, we note that
The time derivative of ST of GST in the later twentieth century, as estimated by EEMD, is subject to future adjustments depending on how rapidly the atmosphere warms over the next decade or two.
The contribution of aerosol forcing to ST remains uncertain, as are the relative contributions of aerosol forcing and Atlantic MDV to the observed MDV of GST.
These caveats notwithstanding, the results presented here further substantiate the reality of human-induced global warming, as evidenced by the similarity between the secular trend curve recovered from EEMD of GST and the buildup of atmospheric greenhouse gas concentrations and by the near-global extent of the temperature increases associated with the secular trend. Our results also serve to highlight the importance of Atlantic multidecadal variability in mediating the rate of global warming, and they suggest that these variations deserve more explicit consideration in twentieth century climate simulations and in attribution studies based on recent observations of the rate of change of GST.
JC comment: On the Trends, Changepoints, and Hypotheses thread, I described three hypotheses that explain 20th century climate variability and change:
I. IPCC AGW hypothesis: 20th century climate variability/change is explained by external forcing, with natural internal variability providing high frequency ‘noise’.
II. Multi-decadal oscillations plus trend hypothesis: 20th century climate variability/change is explained by the large multidecadal oscillations (e.g NAO, PDO, AMO) with a superimposed trend of external forcing (AGW warming).
III: Climate shifts hypothesis: 20th century climate variability/change is explained by synchronized chaos arising from nonlinear oscillations of the coupled ocean/atmosphere system plus external forcing (e.g. Tsonis, Douglass).
Wu et al. fall squarely in II. Their conclusion that as much as one third of the warming in the last few decades of the 20th century provides further weight to arguments that multi-decadal natural internal variability needs to be included explicitly in attribution assessments. The error bars on the ‘one third’ need some investigating, and there are additional modes of natural internal variability beyond the Atlantic Meridional Overturning Circulation. More investigations along these lines (both II an III) are very much needed.
Roy Spencer made some early efforts at II on his blog a few years ago, and recently we have seen some blogospheric efforts by Vaughan Pratt and Girma. I personally think that III is a more robust hypothesis than II, but working on II can help us with III.