Santer et al. Catch Christy Exaggerating
Posted on 14 September 2011 by dana1981
It's been a rough few weeks for climate "skeptics." The first week of September began with the editor of Remote Sensing resigning in order to take responsibility for publishing Roy Spencer's fundamentally flawed paper. Just a few days later, Andrew Dessler's paper was published, demolishing the flawed Spencer paper, another flawed Lindzen paper, and the "internal variability" argument in general. Climate "skeptics" did not react well to the news, attacking the journal for publishing the paper at its normal pace (how dare they!?). With Spencer and Lindzen debunked by a peer-reviewed publication, it's only fitting that the other prominent "skeptic" climate scientist, John Christy, would join the party.
Debunking Christy's Congressional Testimony
On August 21st, the Journal of Geophysical Research, Atmospheres accepted a paper by Ben Santer and a number of other very prominent climate scientists (Santer et al. 2011) which, among other issues, sought to evaluate some claims made by Christy in his recent Congressional testimony (whose other errors we previously discussed). Christy argued that the temperature of the lowest layer of the atmosphere, the temperature of the lower troposphere (TLT), was not warming nearly as fast as models predicted:
"In 1994, Nature magazine published a study of mine in which we estimated the underlying rate at which the world was warming by removing the impacts of volcanoes and El Niños (Christy and McNider 1994)...The result of that study indicated the underlying trend for 1979-1993 was +0.09°C/decade which at the time was one third the rate of warming that should have been occurring according to estimates by climate model simulations."
In his written testimony, Christy updated this analysis through 2010:
"In an interesting result, the new underlying trend remains a modest +0.09 C/decade for the global tropospheric temperature, which is still only one third of the average rate the climate models project for the current era (+0.26°C/decade.)"
However, one major flaw in this analysis, noted by Santer et al., is that Christy removed the effects of ENSO and volcanoes from the observational TLT data, but not from the model data. Further, Christy did not remove the effects of human aerosol emissions, solar activity, or a number of other factors which had a net cooling effect between 1979 and 2010.
In a different approach, Santer et al. examined the data without removing any effects:
"Our comparison of ‘raw’ modeled and observed trends (Figure 6F) does not involve removal of ENSO and volcanic effects from observations alone, and is not restricted to a single period of record. We find that for the range of TLT trends considered here, there is no trend length at which the multi-model average trend, bf, is more than 1.73 times larger than bo, the average observed TLT trend (see Figure 6F). Across the 10-to 32-year range of trend lengths, the average ratio of bf /bo is 1.35 for RSS v3.2, 1.46 for RSS v3.3, and 1.55 for UAH."
Santer et al. (2011) Figures 6A and 6F, showing modeled vs. observed TLT trends.
In short, it's true that lower troposphere temperature warming trend isn't as large as models project, as illustrated in Figures 6A and 6F. Figure 6A shows the TLT trend predicted by models (green) is higher than in the RSS (red) and UAH (blue) satellite observations for the entire 32 years of data (although the trends are within the [yellow] 95% uncertainty range). Figure 6F shows that the ratio of model trend to observed trends ranges between about 1.25 and 1.73, meaning that the models predict a trend anywhere from 25 to 73% larger than the satellite data shows over those 32 years.
However, the average discrepancy is approximately 45%; not nearly as large as Christy's claimed factor of three.
Sources of Model-Data Discrepancy
Santer et al. note that the reasons behind this discrepancy will be investigated in future studies. However, they discuss a few likely contributors:
"Here, it is sufficient to note that many of the 20CEN/A1B simulations neglect negative forcings arising from stratospheric ozone depletion, volcanic dust, and indirect aerosol effects on clouds....It is likely that omission of these negative forcings contributes to the positive bias in the model average TLT trends in Figure 6F. Given the considerable technical challenges involved in adjusting satellite-based estimates of TLT changes for inhomogeneities [Mears et al., 2006, 2011b], a residual cool bias in the observations cannot be ruled out, and may also contribute to the offset between the model and observed average TLT trends."
In short, many models don't account for a number of factors which have had cooling effects over the past three decades, and it's also entirely possible that the satellite temperature data is still biased on the cool side. Christy and Spencer are somewhat infamous for claiming for the better part of a decade that the UAH satellite data proved the climate wasn't warming as fast as models projected (sound familiar?), until research by a number of scientific groups [including Christy and Spencer themselves] discovered errors in their data analysis which accounted for most of the discrepancy. A number of other papers have suggested additional changes to the satellite temperature data analysis, and these adjustments could account for yet more of the model-data discrepancy.
It's not Internal Variability
Like Dessler's paper, Santer et al. also drive another nail into the "warming due to internal variability" hypothesis by noting that although the trend may be smaller than models predict, it's still well outside the noise over the long-term:
"Our estimated signal-to-noise (S/N) ratios for global-scale TLT changes were less than 1.0 on the 10-year timescale (Figure 6C). On the 32-year timescale, however, S/N exceeded 3.9 in all three observational TLT datasets. The latter result shows that natural internal variability, as simulated by current climate models, is a highly unlikely explanation for the observed lower tropospheric warming over the satellite era"
Global Warming Continues
Santer et al. also shoot down the myth that a slowed rate of warming over a decade can prove that global warming has magically stopped:
"Because of the pronounced effect of interannual noise on decadal trends, a multi-model ensemble of anthropogenically-forced simulations displays many 10-year periods with little warming. A single decade of observational TLT data is therefore inadequate for identifying a slowly evolving anthropogenic warming signal. Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature."
In their paper, Santer et al. have caught Christy exaggerating the discrepancy between modeled and observed lower troposphere temperature trends in his testimony before U.S. Congress. In his testimony, Christy also assumed that the discrepancy was due to the climate models being too sensitive to changes in atmospheric CO2. He seems unwilling to consider the possibility that at least part of the discrepancy might be due to flaws in the data or its analysis, even though climate models have a better track record for accuracy than the UAH data analysis.
It's a bit surprising that Christy seems unwilling to consider the possibility that his and Spencer's satellite data analysis might be the source of at least some of the model-data discrepancy. Santer et al. also debunked the "skeptic" myths that global warming is just due to internal variability, and that a short-term slowing in the rate of warming means global warming has magically stopped.
More research must be done to determine the exact sources of the TLT model-data discrepancy, but Santer et al. appear up to the task, doing good investigative science rather than simply assuming the problem lies in the models, as Christy and his fellow "skeptics" have done (again). Unfortunately, this is another in the long list of instances where climate "skeptics" have made significant scientific errors, and been given the platform to misinform the public and policymakers with those errors.