New Paper by McKitrick and Vogelsang comparing models and observations in the tropical troposphere
This is a guest post by Ross McKitrick (at Climate Audit). Tim Vogelsang and I have a new paper comparing climate models and observations over a 55-year span (1958-2012) in the tropical troposphere. Among other things we show that climate models are inconsistent with the HadAT, RICH and RAOBCORE weather balloon series. In a nutshell, the models not only predict far too much warming, but they potentially get the nature of the change wrong. The models portray a relatively smooth upward trend over the whole span, while the data exhibit a single jump in the late 1970s, with no statistically significant trend either side.
Our paper is called “HAC-Robust Trend Comparisons Among Climate Series With Possible Level Shifts.” It was published in Environmetrics, and is available with Open Access thanks to financial support from CIGI/INET. Data and code are here and in the paper’s SI.
Tropical Troposphere Revisited
The issue of models-vs-observations in the troposphere over the tropics has been much-discussed, including here at CA. Briefly to recap:
- All climate models (GCMs) predict that in response to rising CO2 levels, warming will occur rapidly and with amplified strength in the troposphere over the tropics. See AR4 Figure 9.1 and accompanying discussion; also see AR4 text accompanying Figure 10.7.
- Getting the tropical troposphere right in a model matters because that is where most solar energy enters the climate system, where there is a high concentration of water vapour, and where the strongest feedbacks operate. In simplified models, in response to uniform warming with constant relative humidity, about 55% of the total warming amplification occurs in the tropical troposphere, compared to 10% in the surface layer and 35% in the troposphere outside the tropics. And within the tropics, about two-thirds of the extra warming is in the upper layer and one-third in the lower layer. (Soden & Held p. 464).
- Neither weather satellites nor radiosondes (weather balloons) have detected much, if any, warming in the tropical troposphere, especially compared to what GCMs predict. The 2006 US Climate Change Science Program report (Karl et al 2006) noted this as a “potentially serious inconsistency” (p. 11). I suggest is now time to drop the word “potentially.”
- The missing hotspot has attracted a lot of discussion at blogs (eg http://joannenova.com.au/tag/missing-hot-spot/) and among experts (eg http://www.climatedialogue.org/the-missing-tropical-hot-spot). There are two related “hotspot” issues: amplification and sensitivity. The first refers to whether the ratio of tropospheric to surface warming is greater than 1, and the second refers to whether there is a strong tropospheric warming rate. Our analysis focused in the sensitivity issue, not the amplification one. In order to test amplification there has to have been a lot of warming aloft, which turns out not to have been the case. Sensitivity can be tested directly, which is what we do, and in any case is the more relevant question for measuring the rate of global warming.
- In 2007 Douglass et al. published a paper in the IJOC showing that models overstated warming trends at every layer of the tropical troposphere. Santer et al. (2008) replied that if you control for autocorrelation in the data the trend differences are not statistically significant. This finding was very influential. It was relied upon by the EPA when replying to critics of their climate damage projections in the Technical Support Document behind the “endangerment finding”, which was the basis for their ongoing promulgation of new GHG regulations. It was also the basis for the Thorne et al. survey’s (2011) conclusion that “there is no reasonable evidence of a fundamental disagreement between models and observations” in the tropical troposphere.
- But for some reason Santer et al truncated their data at 1999, just at the end of a strong El Nino. Steve and I sent a comment to IJOC pointing out that if they had applied their method on the full length of then-available data they’d get a very different result, namely a significant overprediction by models. The IJOC would not publish our comment.
- I later redid the analysis using the full length of available data, applying a conventional panel regression method and a newer more robust trend comparison methodology, namely the non-parametric HAC (heteroskedasticity and autocorrelation)-robust estimator developed by econometricians Tim Vogelsang and Philip Hans Franses (VF2005). I showed that over the 1979-2009 interval climate models on average predict 2-4x too much warming in the tropical lower- and mid- troposphere (LT, MT) layers and the discrepancies were statistically significant. This paper was published as MMH2010 in Atmospheric Science Letters
- In the AR5, the IPCC is reasonably forthright on the topic (pp. 772-73). They acknowledge the findings in MMH2010 (and other papers that have since confirmed the point) and conclude that models overstated tropospheric warming over the satellite interval (post-1979). However they claim that most of the bias is due to model overestimation of sea surface warming in the tropics. It’s not clear from the text where they get this from. Since the bias varies considerably among models, it seems to me likely to be something to do with faulty parameterization of feedbacks. Also the problem persists even in studies that constrain models to observed SST levels.
- Notwithstanding the failure of models to get the tropical troposphere right, when discussing fidelity to temperature trends the SPM of the AR5 declares Very High Confidence in climate models (p. 15). But they also declare low confidence in their handling of clouds (p. 16), which is very difficult to square with their claim of very high confidence in models overall. They seem to be largely untroubled by trend discrepancies over 10-15 year spans (p. 15). We’ll see what they say about 55-year discrepancies.
Conclusion –
Over the 55-years from 1958 to 2012, climate models not only significantly over-predict observed warming in the tropical troposphere, but they represent it in a fundamentally different way than is observed.
…
Read the entire story here: http://climateaudit.org/2014/07/24/new-paper-by-mckitrick-and-vogelsang-comparing-models-and-observations-in-the-tropical-troposphere/
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Say that they are “logarithmic” does not help you determine the coefficient in front of the log term, and log functions, like all other smooth functions, tend to be linear in the short run because of Our Friend the Taylor Series. In fact:
. So saying that they are logarithmic is like saying that they are linear for anything like small changes. Even if 
(the relative change from 300 to 400 ppm) the quadratic term represents only around a 5 or 6% nonlinear correction. So the only thing that matters is the constant in front of the log term.
is the cross-section of the attenuator, 
is the attenuation concentration, and 
is the mean free path of photons in the medium. The cross section 
will not change in any measurable way with CO_2 variations of the order expected. The mean free path scales like the cube root of the concentration — doubling the concentration decreases the mean free path by 
.
for all the molecular species that contribute to Beers-Lambert (where CO_2 is just one component of many contributing species).
for
I do have issues with the overall claims for CO_2 at saturation, however. One claim, for instance, is that part of the warming expected arises from additional pressure broadening as one adds more CO_2. However, pressure broadening arises from collisions between molecules and is sensitive to the absolute pressure, not the partial pressure of CO_2. Indeed, at the partial pressures at issue — less than 0.1% of the total atmosphere at a projected 600 ppm — any “variation” in pressure broadening due to alteration of CO_2 concentration is dwarfed by the real-time, substantial variation in pressure broadening due to gross atmospheric pressure changes. This is not a trivial effect and has long been studied by the telecommunications industry as it essentially alters the attenuation rate of various frequencies of electromagnetic radiation as air pressure changes with the weather. Any alteration of the pressure broadened absorptive spectrum with CO_2 concentration would be utterly indetectable noise against this general background of rapid, substantial variation.
The actual expression for the expected log variation of transmittivity is the Beers-Lambert law:
where
The really interesting question is whether or not the variation in transmittivity/absorptivity with CO_2 concentration is visible at all against the general background of:
a) Gross variations of air pressure with weather that actually do cause direct variations of
b) Gross variations of GHG concentrations with weather, particularly water vapor.
c) A wide range of nonlinear feedback mechanisms (such as the cloud/albedo link or nonlinear transport of latent heat vertically through the greenhouse layer or the variation of absorptivity with surface height or the seasonal variation of surface albedo or…).
Those processes could completely erase any expected Beers-Lambert increase with the blink of a feedback eye, drown it in noise to where it is irrelevant to the actual time evolution of climate on anything like a century time scale, amplify it beyond recognition to where we cook in our own juices, or anything in between and we cannot even speak to one outcome being more probable than any other at this point. The data, such as it is, suggests that natural variability vastly exceeds the response and that negative feedback dominates the climate response to any sort of additional forcing, not positive feedback. But we have so little useful, global data taken with adequate instrumentation and care that even the data is not a very trustworthy guide to the future, so far.
rgb
thanks Lance!…..
Terry Oldberg says:
“A model is falsified when the observed relative frequencies of the outcomes of events fail to match the model-computed relative frequencies but for these models there were no events or relative frequencies.”
++++++++
If this is true, then the models are of no value. Or said another way, they do not predict anything that can be calibrated against observations. So, if you are correct, the models are not proof of anything we can regulate. If you are wrong, they are invalid based on this paper. This paper puts the nail in the coffin.
Mario Lento:
Thanks for taking the time to respond.
It’s true that models of the type that are featured in the McKitrick and Vogelsang paper are of no scientific value in regulating the climate. This is quite significant for models of this type are the basis for all of the regulations now on the books, including the EPA’s key “endangerment” finding. The endangerment finding looks to me as though it is illegal under the Daubert standard governing the admissibility of scientific testimony in federal legal proceedings in view of the lack of falsifiability of the claims that are made by models of this type.
One should not generalize to the conclusion that all climate models are of no value for in AR5, Chapter 11 of the report of Working Group 1 reports (for the first time, I believe, in an IPCC assessment report) the existence of a model for which the underlying events exist. This report provides a comparison between the predicted and the observed relative frequencies of observed events. At this point, Working Group 1 drops the scientific ball for while this comparison provides the potential basis for falsification or validation of the model, they fail to inform their readers of whether the model has been falsified or validated. Also, their comparison seems to be based upon vastly more independent observed events than can possibly be extracted from the available global temperature time series.
It looks as though something is wrong with the argument that is made by Working Group 1 in Chapter 11. When I’ve got the time, I’ll drive over to the library of the closest research university and read some of the source material in the hope of determining what’s going on.
Great Terry… looks like you’re on to something.