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Global warming and unforced variability: Clarifications on recent Duke study

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Guest Commentary from Patrick Brown and Wenhong Li, Duke University

We recently published a study in Scientific Reports titled Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise. Our study seemed to generated a lot of interest and we have received many inquires regarding its findings. We were pleased with some of coverage of our study (e.g., here) but we were disappointed that some outlets published particularly misleading articles (e.g, here, here, and here). Since there appears to be some confusion regarding our study’s findings, we would like to clarify some points (see also MM4A’s discussion).

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References

  1. P.T. Brown, W. Li, E.C. Cordero, and S.A. Mauget, "Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise", Scientific Reports, vol. 5, 2015. http://dx.doi.org/10.1038/srep09957

The return of the iris effect?

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Guest commentary from Andy Dessler (TAMU)

When a new scientific hypothesis is published, two questions always occur to me:

  1. Did the authors convincingly show the hypothesis was correct?
  2. If not, is the hypothesis actually correct?

The answers to these two questions may not be the same. A good example is Wegener’s theory of continental drift — his idea was fundamentally correct, but he lacked the data and physical mechanisms to convince the rest of scientific community. It would take several decades before enough data were gathered that the scientific community wholeheartedly endorsed plate tectonics.

In 2001, Prof. Richard Lindzen and colleagues published his “iris hypothesis” (Lindzen et al., 2001). The hypothesis has two parts: First, in a warmer climate, enhanced precipitation efficiency will lead to less cloud being detrained into the troposphere from convection. Second, with less cloud cover, more infrared radiation can escape to space, thereby creating a strong climate-stabilizing negative cloud feedback that prevents significant warming from increasing greenhouse gases.

Within a few years, a number of analyses made clear that the evidence provided by Lindzen et al. had problems [e.g., Hartmann and Michelsen, 2002; Lin et al., 2002; Lin et al., 2004; Su et al., 2008]. Lindzen and colleagues responded to these critiques, but few were convinced by their arguments. By 2006, when I submitted an analysis of tropospheric water vapor that investigated whether there was an iris in that, one of the reviewers pointedly questioned why anyone was still working on this issue. I subsequently withdrew the paper.

Nevertheless, just because Lindzen et al. did not convincingly demonstrate their case does not mean the iris hypothesis is wrong. With that idea in mind, a new paper by Mauritsen and Stevens (2015) revisits the iris hypothesis. The most important part of their work was to simulate the iris in a climate model by artificially tweaking the model’s convective parameterization. They do this by increasing the rate of conversion of cloud water to rain as the climate warms, thereby reducing the amount of detraining condensate in a warmer climate. In effect, this imposes a tweak that mimics the iris effect – it is not a demonstration that the iris effect emerges from any physical mechanisms.

What they find is that, even though cloud cover is reduced as the climate warms, it does not generate a strong negative cloud feedback. While reducing cloud cover does indeed let more infrared energy out, it also lets more sunlight in. These two effects, while independently large, act in opposite directions. The net effect is the small residual of their difference. For runs with the strongest “iris”, the model’s climate sensitivity is reduced from 2.8°C for doubled carbon dioxide to 2.2°C — still well within the IPCC’s canonical range.

It’s also worth pointing out what this study doesn’t prove. It doesn’t validate Lindzen et al.’s original hypothesis — in fact, it does the opposite – even with an iris effect, the sensitivity does not become negligible. Additionally, there is little evidence that the rate of conversion of cloud water to rain actually changes with temperature, although Mauritsen and Stevens show that incorporating the iris into the model does improve the model’s simulations of some aspects of the climate system (even though it doesn’t change climate sensitivity much).

I view this as a what-if calculation of the impact of such a process. Future research may validate this, or it may not. This kind of calculation is one of the reasons why we like using models, of course.

Another argument against the iris comes from my work looking at the cloud feedback in response to short-term climate variability. If the iris provided a strong negative feedback, then we would expect to see it in response to short-term climate fluctuations. Analysis of observations doesn’t show anything like that (Dessler, 2013).

Overall, I think the debate over the iris hypothesis is a testament to the efforts the scientific community goes through to evaluate challenges to theories and find ways to improve our understanding of the climate (for instance, see Bill Ruddiman’s post from last week). This is one of the most important reasons I have such high confidence in the scientific process for figuring out how the universe works.

References

  1. R.S. Lindzen, M. Chou, and A.Y. Hou, "Does the Earth Have an Adaptive Infrared Iris?", Bulletin of the American Meteorological Society, vol. 82, pp. 417-432, 2001. http://dx.doi.org/10.1175/1520-0477(2001)082<0417:DTEHAA>2.3.CO;2
  2. D.L. Hartmann, and M.L. Michelsen, "No Evidence for Iris", Bulletin of the American Meteorological Society, vol. 83, pp. 249-254, 2002. http://dx.doi.org/10.1175/1520-0477(2002)083<0249:NEFI>2.3.CO;2
  3. B. Lin, B.A. Wielicki, L.H. Chambers, Y. Hu, and K. Xu, "The Iris Hypothesis: A Negative or Positive Cloud Feedback?", Journal of Climate, vol. 15, pp. 3-7, 2002. http://dx.doi.org/10.1175/1520-0442(2002)015<0003:TIHANO>2.0.CO;2
  4. B. Lin, T. Wong, B.A. Wielicki, and Y. Hu, "Examination of the Decadal Tropical MeanERBSNonscanner Radiation Data for the Iris Hypothesis", Journal of Climate, vol. 17, pp. 1239-1246, 2004. http://dx.doi.org/10.1175/1520-0442(2004)017<1239:EOTDTM>2.0.CO;2
  5. H. Su, J.H. Jiang, Y. Gu, J.D. Neelin, B.H. Kahn, D. Feldman, Y.L. Yung, J.W. Waters, N.J. Livesey, M.L. Santee, and W.G. Read, "Variations of tropical upper tropospheric clouds with sea surface temperature and implications for radiative effects", Journal of Geophysical Research: Atmospheres, vol. 113, 2008. http://dx.doi.org/10.1029/2007JD009624
  6. T. Mauritsen, and B. Stevens, "Missing iris effect as a possible cause of muted hydrological change and high climate sensitivity in models", Nature Geoscience, vol. 8, pp. 346-351, 2015. http://dx.doi.org/10.1038/ngeo2414
  7. A.E. Dessler, "Observations of Climate Feedbacks over 2000–10 and Comparisons to Climate Models*", Journal of Climate, vol. 26, pp. 333-342, 2013. http://dx.doi.org/10.1175/jcli-d-11-00640.1

Reflections on Ringberg

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As previewed last weekend, I spent most of last week at a workshop on Climate Sensitivity hosted by the Max Planck Institute at Schloss Ringberg. It was undoubtedly one of the better workshops I’ve attended – it was focussed, deep and with much new information to digest (some feel for the discussion can be seen from the #ringberg15 tweets). I’ll give a brief overview of my impressions below.

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Climate Sensitivity Week

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Some of you will be aware that there is a workshop on Climate Sensitivity this week at Schloss Ringberg in southern Germany. The topics to be covered include how sensitivity is defined (and whether it is even meaningful (Spoiler, yes it is)), what it means, how it can be constrained, what the different flavours signify etc. There is an impressive list of attendees with a very diverse range of views on just about everything, and so I am looking forward to very stimulating discussions.

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The Soon fallacy

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As many will have read, there were a number of press reports (NYT, Guardian, InsideClimate) about the non-disclosure of Willie Soon’s corporate funding (from Southern Company (an energy utility), Koch Industries, etc.) when publishing results in journals that require such disclosures. There are certainly some interesting questions to be asked (by the OIG!) about adherence to the Smithsonian’s ethics policies, and the propriety of Smithsonian managers accepting soft money with non-disclosure clauses attached.

However, a valid question is whether the science that arose from these funds is any good? It’s certainly conceivable that Soon’s work was too radical for standard federal research programs and that these energy companies were really taking a chance on blue-sky high risk research that might have the potential to shake things up. In such a case, someone might be tempted to overlook the ethical lapses and conflicts of interest for the sake of scientific advancement (though far too many similar post-hoc justifications have been used to excuse horrific unethical practices for this to be remotely defendable).

Unfortunately, the evidence from the emails and the work itself completely undermines that argument because the work and the motivation behind it are based on a scientific fallacy.
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Absolute temperatures and relative anomalies

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Most of the images showing the transient changes in global mean temperatures (GMT) over the 20th Century and projections out to the 21st C, show temperature anomalies. An anomaly is the change in temperature relative to a baseline which usually the pre-industrial period, or a more recent climatology (1951-1980, or 1980-1999 etc.). With very few exceptions the changes are almost never shown in terms of absolute temperatures. So why is that?

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Climate response estimates from Lewis & Curry

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Guest commentary from Richard Millar (U. Oxford)

The recent Lewis and Curry study of climate sensitivity estimated from the transient surface temperature record is being lauded as something of a game-changer – but how much of a game-changer is it really?

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References

  1. N. Lewis, and J.A. Curry, "The implications for climate sensitivity of AR5 forcing and heat uptake estimates", Climate Dynamics, vol. 45, pp. 1009-1023, 2014. http://dx.doi.org/10.1007/s00382-014-2342-y

IPCC attribution statements redux: A response to Judith Curry

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I have written a number of times about the procedure used to attribute recent climate change (here in 2010, in 2012 (about the AR4 statement), and again in 2013 after AR5 was released). For people who want a summary of what the attribution problem is, how we think about the human contributions and why the IPCC reaches the conclusions it does, read those posts instead of this one.

The bottom line is that multiple studies indicate with very strong confidence that human activity is the dominant component in the warming of the last 50 to 60 years, and that our best estimates are that pretty much all of the rise is anthropogenic.



The probability density function for the fraction of warming attributable to human activity (derived from Fig. 10.5 in IPCC AR5). The bulk of the probability is far to the right of the “50%” line, and the peak is around 110%.

If you are still here, I should be clear that this post is focused on a specific claim Judith Curry has recently blogged about supporting a “50-50” attribution (i.e. that trends since the middle of the 20th Century are 50% human-caused, and 50% natural, a position that would center her pdf at 0.5 in the figure above). She also commented about her puzzlement about why other scientists don’t agree with her. Reading over her arguments in detail, I find very little to recommend them, and perhaps the reasoning for this will be interesting for readers. So, here follows a line-by-line commentary on her recent post. Please excuse the length.
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Labels for climate data

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metadata-fig “These results are quite strange”, my colleague told me. He analysed some of the recent climate model results from an experiment known by the cryptic name ‘CMIP5‘. It turned out that the results were ok, but we had made an error when reading and processing the model output. The particular climate model that initially gave the strange results had used a different calendar set-up to the previous models we had examined.

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Shindell: On constraining the Transient Climate Response

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Guest commentary from Drew Shindell

There has been a lot of discussion of my recent paper in Nature Climate Change (Shindell, 2014). That study addressed a puzzle, namely that recent studies using the observed changes in Earth’s surface temperature suggested climate sensitivity is likely towards the lower end of the estimated range. However, studies evaluating model performance on key observed processes and paleoclimate evidence suggest that the higher end of sensitivity is more likely, partially conflicting with the studies based on the recent transient observed warming. The new study shows that climate sensitivity to historical changes in the abundance of aerosol particles in the atmosphere is larger than the sensitivity to CO2, primarily because the aerosols are largely located near industrialized areas in the Northern Hemisphere middle and high latitudes where they trigger more rapid land responses and strong snow & ice feedbacks. Therefore studies based on observed warming have underestimated climate sensitivity as they did not account for the greater response to aerosol forcing, and multiple lines of evidence are now consistent in showing that climate sensitivity is in fact very unlikely to be at the low end of the range in recent estimates.
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References

  1. D.T. Shindell, "Inhomogeneous forcing and transient climate sensitivity", Nature Climate Change, vol. 4, pp. 274-277, 2014. http://dx.doi.org/10.1038/nclimate2136