Global Temperature Trends and the IPCC

As the excitement builds about the release forthcoming IPCC report (snore), debate is underway on how to interpret previous IPCC predictions for the evolution of global surface temperature trends. The debate has been super-charged by a recent article in The Daily Mail by David Rose, leading the usual suspects to say the usual things. Such debates involve exegeses of generally inscrutable IPCC statements filtered through the imperfect process of media (social and mainstream) reporting, colored by agendas.

In this post I pass on the exegeses and have a look at the actual numbers to address several questions and raise a few of my own.

How have the IPCC’s out of sample predictions for the evolution of global average surface temperature fared against observations?

I first addressed this question in a running series of blog posts at Prometheus, back in the day. That exercise resulted in a correspondence published in Nature Climate Change in 2008 (here in PDF). Here is a quick update of that analysis.

The graph at the top of this post updates Figure 1a from Pielke (2008) through 2012. I show only the NASA GISS observational dataset (with data from the KNMI Climate Explorer), as it is the “warmest” of the four datasets.

The data shows clearly that the observations are running cooler than the out-of-sample predictions of the IPCC from each of its past 4 reports.

How much cooler?

If we simply compare rates of projected increase (1990 to 2012) the answers with respect to each previous IPCC report are:

• 47% = NASA GISS linear trend slope as percentage of IPCC 1990
• 91% = NASA GISS linear trend slope as percentage of IPCC 1995
• 80% = NASA GISS linear trend slope as percentage of IPCC 2001
• 80% = NASA GISS linear trend slope as percentage of IPCC 2007

With different rates of increase, the absolute difference in observations vs. projections will be a function of the period being looked at. Note that a comparison with the other 3 surface datasets, not shown here but which appear in Pielke (2008), would lead to larger discrepancies.

What quantitative conclusions does this exercise lead to?

1. The observations of global average surface warming are about half that predicted in the first IPCC report from 1990. Over the past 25 years, projections of rates of future surface temperature increase have clearly come down dramatically.
2. Subsequent IPCC reports reduced their projections, but global average temperature observations are still running lower than that projected in 1995, 2001 and 2007.

Are the lower observed temperatures significantly different than the projections?

Fortunately, there is a just-published peer-reviewed paper in Nature Climate Change which takes up this question, and concludes:

Recent observed global warming is significantly less than that simulated by climate models.

This won’t be a surprise to anyone who has followed the ongoing, high-quality discussions of the subject by bloggers, such as Lucia Liljegren.

Does the inconsistency between observations and models have much significance for climate policy?

Not really. The fact that some enthusiasts have over-egged the climate prediction pudding does not take away from the core understandings of climate science, namely that humans influence the climate system, via greenhouse gas emissions and other means, and such influences carry with them some risks.

Of course, the over-egging has set the stage for the discrepancy to be of political significance, as the credibility of the IPCC and its champions is what is really under siege by its critics. Had the IPCC more faithfully represented uncertainties and had its public representatives been less strident and less arrogant, then the fact that we cannot actually predict the short-term evolution of the climate system would have been expected rather than treated as a scientific failure of some sort by the IPCC.

What should scientists do?

Back when I paid more attention to such things I offered the following as a (tongue-in-cheek) suggestion to those wanting to desperately prove that models were in fact consistent with the observations, which is offered without explanation.

More seriously, rather than engaging in proxy wars over media reporting and the short-term PR spin associated with it — which may in fact just make things worse — it would be in the long-term interests of the climate science community to take a step back and consider the role of their spokespeople (official or otherwise) in aiding and abetting the skeptics, deniers and other nefarious evil-doers.

A difficult question for the climate science community is, how is it that this broad community of researchers — full of bright and thoughtful people — allowed intolerant activists who make false claims to certainty to become the public face of the field? 

It is a question with continuing relevance.