To Tell The Truth: Will the Real Global Average Temperature Trend Please Rise?
A guest post by Basil Copeland
Again, I want to thank Anthony for the kind invitation to guest blog these musings about what is going on with global average temperature metrics. It has been a most interesting, and personally rewarding, experience. My original aim was quite modest, but I fear that the passion that many feel for this issue prevented them from seeing that. So in this final part to this series, I want to try to make my aim more clear, and to show how a lively exchange of ideas can lead to new insights.
The IPCC has made the earth’s global average temperature trend a central focus in the debate over anthropogenic global warming. In the AR4 report of Working Group 1, they state:
The range (due to different data sets) of global surface warming since 1979 is 0.16°C to 0.18°C per decade compared to 0.12°C to 0.19°C per decade for MSU estimates of tropospheric temperatures. (Chapter 3, Page 237)
Similar, if not the same, estimates are reported in Table 3.3, Page 61, of the Synthesis and Assessment Product 1.1 of the U.S. Climate Change Science Program (accessible here: http://www.climatescience.gov/Library/sap/sap1-1/finalreport/sap1-1-final-all.pdf ). Presumably, these estimates provide some kind of basis for the IPCC SRES scenarios that assume 0.2C per decade warming over the next two decades.
From what I can tell in reading the representations of the sources for these estimates, they are based on a straight-line linear regression that includes corrections for serial correlation. In other words, regressions that look something like what are shown in Figure 1. The trend at the top is from Appendix A, Page 130, Figure 1, of the U.S. Climate Change Science Program report just cited. The second is taken from the RSS website (http://www.remss.com/data/msu/graphics/plots/sc_Rss_compare_TS_channel_tlt.png accessed on March 15, 2008). Both show a warming trend of 0.17C/decade since 1979.
Are these “good” estimates of the historical trend since 1979? Forgive me, but I refuse to accept them as authoritative ex cathedra, nor will any true scientist expect me to. Bear in mind, I’m taking the data for what it’s worth, and am overlooking any questions about the reliability of the surface record, such as what Anthony is looking into (or Steve Mcintyre at www.climateaudit.org), or the kind of urbanization and land use effects reported by Ross McKitrick and Patrick Michaels. My concern is solely with the technical procedures used to estimate the “trends” that are commonly cited for evidence of global warming. Bottom line? There are problems with the way those trends are computed that overestimate the degree of global warming since 1979 by 16.3% to 41.3% (based on results presented below).
In Part II I attempted a demonstration of this using what might be considered to be rather a rather blunt or brute force approach — a test of whether there was a significant “structural break” (the way we describe it in my field of study) after 2001, along with whether or not linear trends are distorted by the effect of the 1998 El Nino. Nothing in the comments that followed the posting of Part II fundamentally undermined the validity of my conclusions. The chief concerns seemed to be that my decision to test for a structural break (or “change point”) at the end of 2001 was arbitrary (it wasn’t), or whether one could say anything meaningful about a cyclical system like climate from linear trend lines. Well, with respect to the latter, that horse is out of the barn, and we’re being told — by supposed authorities — that there has been X degrees of global warming per decade since 1979 on the basis of linear trend lines. If they can use linear regression to claim that global warming is proceeding apace, well please excuse me for doing the same in questioning them.
Still, the comments were provocative, and encouraged me to dig further into my toolbox of econometric techniques to see if I might be able to come up with something that would alleviate some of the concerns commenters had about what I did. So it occurred to me that I might treat the weather like a “business cycle” and model it with Hodrick-Prescott smoothing. (If you want an explanation of what that is, look here: http://en.wikipedia.org/wiki/Hodrick-Prescott_filter ). The results are presented, for the four global average temperature metrics we are using, in Figures 2 through 5.
Figure2 – click for a larger image
Figure3 – click for a larger image
Figure4 – click for a larger image
Figure5 – click for a larger image
Those who think we should let the data tell us where the “change points” are should find this approach more appealing, as well as those who believe we should be modeling the data with non-linear techniques. But in the end, the point is the same: the “real trend” over the 29 years we are looking at is substantially less than we get using straight-line regression. With the exception of GISS, Hodrick-Prescott smoothing results in even lower estimates of the degree of global warming over the past 29 years. As shown in the following Table 1, compared to the two methods I’ve employed, the straight line regression method relied upon by IPCC and the U.S. Climate Change Science Program overstates global warming since 1979 by anywhere from 16.3% (using GISS) to 41.3% (HadCRUT).
No one should be offended by what I’ve done, or what I’m saying. True science is always open to the possibility of refutation. Given the policy implications that hang on conclusions about the degree of global warming that has occurred in recent decades, we should take a closer look at what the supposed authorities are telling us, and see if there are not perhaps some significant short-comings in the way they have calculated the degree of global warming in recent decades.