Klotzbach Revisited and John Christy's response, part 2
Posted on 3 April 2013 by JosHag
John Christy wrote an extensive blog post as a response to my (translated) Dutch post called 'Klotzbach Revisited', see part 1 of this serie. This post of Christy was published on 'Staat van het Klimaat' and WUWT. Here I present a version of my response to John Christy's blog post.
The remarks I made regarding Dr. Christy's post are built upon some quotes taken from his post and these are presented here in green.
"Klotzbach et al.’s main point was that a direct comparison of the relationship of the magnitude of surface temperature trends vs. temperature trends of the troposphere revealed an inconsistency with model projections of the same quantities.
This 'main point' is not present at all in the K-2009 paper, the only reference to real data coming from a climate model in the paper is the amplification factor, which was 'sort of obtained' by Ross McKitrick from the GISS-ER model. In the abstract a short conclusion is given: "These findings strongly suggest that there remain important inconsistencies between surface and satellite records." No word about models.
In my opinion the main point of K-2009 is the suggestion that the surface temperature record is biased. One third of the paper is made up by paragraph 2 with the title: "Recent Evidence of Biases in the Surface Temperature Record”. K-2009 explicitly state:
In our current paper, we consider the possible existence of a warm bias in the surface temperature trend analyses ...
"It appears Hagelaars’ key point is that when the data from Klotzbach et al. are extended beyond 2008 to include data through 2012, the discrepancies, i.e. the observed difference between surface and tropospheric trends relative to what models project, are reduced somewhat."
My key point is that if K-2009 were correct, the absolute temperature difference between surface and troposphere would be expected to increase over time (due to the fact that the presumed bias in the surface temperature data has not magically disappeared, see e.g. this paper by Watts et al). In contrast, this temperature difference has decreased about 33% for the 'NCDC minus UAH' data (which showed the largest discrepancy).
Why this large difference with only 13% (4 years) more data? If anything, it casts doubt on the robustness of the K-2009 results.
The other point I wanted to make is that the apparent discrepancies could also, perhaps even more likely, be due to biases present in the satellite data, as indicated by Santer et al 2005. Also new biases are constantly being discovered, see this paper by Po-Chedley & Fu.
Why is there no attention given to the potential presence of biases in the satellite data in Dr. Christy's blog post?
"As noted however, several additional calculations confirm the value of 1.1 utilized by Klotzbach et al. 2010."
The K-2009 paper uses 1.2 as an amplification factor over land and the correction paper K-2010 uses 1.1. I never found this very plausible. Gavin Schmidt, responsible for the GISS-ER model gave a value by e-mail to Phil Klotzbach of 0.95, still K-2010 uses the value of 1.1 as calculated on McIntyre's blog. On the same blog Gavin Schmidt gives the following amplification factor:
“A range of [0.784,1.234]… and a mean (if you think that is sensible) of 0.9708 . Lest anyone think that volcanoes or something are affecting this, the same calculation for 2010-2100 is a range of [0.914,1.097] and a mean of 0.9897.” This 0.97 is close to his previous 0.95.
The selection of an amplification factor in K-2009 and K-2010 is arbitrarily, why use the factor 1.1 and not the factor calculated by the person responsible for the GISS-ER model?
In my opinion neither of these factors should be used in scientific papers, like the Klotzbach et al papers, since they are obtained from blogs and are not backed up by peer-reviewed science.
"It is true that these differences are a little closer to zero than shown in Klotzbach et al., but that is due to the fact that there has been no warming in the past 10 years in both types of data".
I'm glad that Dr. Christy endorses my results, but I do not agree with the 'but' part. I do not think conclusions regarding a (change in) climatologically relevant trend can be drawn based upon 10 years of data. However, since Dr. Christy explicitly refers to this very short timescale I will present some trend data regarding the last 10 years (Feb. 2003 - Jan. 2013). Values in °C/decade, first global, then over land, followed by the ocean part:
|UAH minus NCDC||-0.092||-0.111||-0.064|
It is quite clear that over the last 10 years the UAH dataset (the lower troposphere) gives a positive global warming trend and NCDC does not. Both datasets give a positive warming trend over land and that is not the same as 'no warming'. The trend over land for UAH is 3.3 times higher than the trend over land by NCDC and this certainly does not reflect the amplification factors 0.95 or 1.1 mentioned in the blog posts.
The land area on earth has warmed during the past 10 years and the relationship between the surface data and the satellite data has turned upside down, over 34 years the trend difference (NCDC minus UAH) was +0.10 °C/decade and it is reversed the last 10 years to -0.11 °C/decade. Why?
I did not use amplification factors in calculating the trend differences due to the fact that these factors over land and ocean are, as far as I can tell, not backed up by peer-reviewed science.
"Therefore models, on average, depict the last 34 years as warming about 1.5 times what actually occurred."
Dr. Christy is comparing trends based upon averages from climate models with the trend in the observations. Averaging model run will also average out natural variability as present in each model simulation. For instance, the simulated influence of ENSO will not be visible anymore in the averaged data (e.g. see this graph and note the absence of any El Nino variability in the averaged model data). It is not realistic to expect that the observations will nicely follow the model average. Comparing a trend of a model average with the observational surface temperature trend and concluding from such a (simplistic and incomplete) comparison that "the climate sensitivity of models is too high", is, in my opinion, jumping to conclusions.
In the animation below the temperature observations are compared with two simulations from a climate model. The blue simulation matches the observed trend over the most recent decade and the red does not. In the long run the expected warming is roughly the same. The original (created by Ed Hawkins) can be found here.
"Since this increased warming in the upper layers is a signature of greenhouse gas forcing in models, and it is not observed, this raises questions about the ability of models to represent the true vertical heat flux processes of the atmosphere and thus to represent the climate impact of the extra greenhouses gases we are putting into the atmosphere."
The increased warming in the upper layers of the troposphere is due to the lapse rate feedback and is not a signature restricted to the influence of greenhouse gases. Since the lapse rate feedback is a negative feedback, a smaller lapse rate feedback would in fact result in a larger climate sensitivity as obtained from models. More info regarding this subject can be found here and on RealClimate.
This statement of Dr. Christy is quite an extraordinary claim and according to Carl Sagan "extraordinary claims require extraordinary evidence". Following the blog post of Dr. Christy, the claim is based upon satellite and surface data that potentially could contain biases, on amplification factors taken from blogs and not from peer-reviewed science papers and by comparing observations with model averages. I would not classify this evidence as extraordinary, especially since many other lines of evidence contradict Dr. Christy’s claim (see e.g. here or here).
For me there are a some open questions regarding this topic, for instance:
What explains these large differences in the comparison of satellite and surface temperatures with only 13% more data?
Are there potential biases in the satellite data, e.g. due to a change in satellites or other factors?
What are the actual amplification factors for land and ocean over the satellite period?
Is it possible to make a strict division between land and ocean for the complete lower troposphere, e.g. is there some averaging out from ocean to land and vice versa at higher altitudes due to convection?
It is up to scientists to resolve the remaining scientific puzzles rather than to emphasize uncertainties on one specific item and using these to jump to preferred conclusions.