As per a request initiated by Bender, here is a critique of the recent Lindzen and Choi paper.

Citation: Lindzen, R. S., and Y.-S. Choi (2009), On the determination of climate feedbacks from ERBE data, Geophys. Res. Lett., 36, L16705, doi:10.1029/ 2009GL039628.

http://www.seas.harvard.edu/climate/seminars/pdfs/lindzen.choi.grl.2009.pdf

Abstract: Climate feedbacks are estimated from fluctuations in the outgoing radiation budget from the latest version of Earth Radiation Budget Experiment (ERBE) nonscanner data. It appears, for the entire tropics, the observed outgoing radiation fluxes increase with the increase in sea surface temperatures (SSTs). The observed behavior of radiation fluxes implies negative feedback processes associated with relatively low climate sensitivity. This is the opposite of the behavior of 11 atmospheric models forced by the same SSTs. Therefore, the models display much higher climate sensitivity than is inferred from ERBE, though it is difficult to pin down such high sensitivities with any precision. Results also show, the feedback in ERBE is mostly from shortwave radiation while the feedback in the models is mostly from longwave radiation. Although such a test does not distinguish the mechanisms, this is important since the inconsistency of climate feedbacks constitutes a very fundamental problem in climate prediction.

I didn’t pay much attention to this paper (hereafter referred to as LC) when it came out, but it received quite a big play in the blogosphere. It was touted by some as the “end of the AGW scam.” On the other hand, numerous aspects of methodology received serious criticism. Why is this paper important (if correct)? The two main findings of LC are that: the sensitivity of the Earth’s climate is much smaller than the conventional estimates (e.g. IPCC); and climate models substantially disagree with observations and produce a sensitivity that is far too high (and hence are producing falsely alarming projections).

Some background: The equilibrium climate sensitivity (in K) is defined as a change in the equilibrium annual global surface temperature in response to a doubling of CO2. Alternatively, the equilibrium climate sensitivity can be express (in K/Wm2) as an equilibrium temperature change per unit radiative forcing. The climate sensitivity is not prescribed in global climate models but is determined as a result of the climate model integation including parameterization of various physical processes in these models. The equilibrium climate sensitivity is a useful parameter for comparing climate models. Climate system without feedbacks would have an equilibrium climate sensitivity of 0.3 K/Wm2 corresponding to the global average warming of about 1.1 K for doubling of CO2. Mostly positive feedbacks in the climate system have been estimated to increase the climate sensitivity to 1.5 to 4.5 K. LC is one of many studies that have tried to estimate climate sensitivity from observations.

For reference, some of the more substantive critiques of LC in the blogosphere include:

http://www.drroyspencer.com/2009/11/some-comments-on-the-lindzen-and-choi-2009-feedback-study/

http://chriscolose.wordpress.com/2009/03/31/lindzen-on-climate-feedback/

http://motls.blogspot.com/2009/11/spencer-on-lindzen-choi.html

http://agwobserver.wordpress.com/2009/12/05/comments-on-lindzen-choi-2009/

Would appreciate any other good links that you know of. The most significant critiques include: using an old (uncorrected) version of the ERBE data, ignoring a known temporal aliasing effect in the ERBE data, comparing to the AMIP (atmosphere only, with specified sea surface temperatures) rather than the CMIP (coupled atmosphere ocean) climate model simulations, incorrect handling of the direct response to sea surface temperature change. Each of these issues in implementation of the methodology could easily be fixed, but I would expect that their individual and cumulative impact on the analysis results would be substantial.

My assessment of this paper is quite critical (details to follow). In addition to the critiques of the methodology and its implementation linked to above, I have further concerns with the overall methodology that I hope provides a broader framework for criticism of this paper.

1. The first thing about this paper that struck me is that LC infer global climate sensitivity from an analysis of only the tropical oceans (20N to 20S). This is clearly stated in their methodology section and explicitly in the caption for Fig 1a, although in their title, abstract, and discussion the word “tropics” isn’t mentioned and the authors clearly interpret this analysis to be germane to global climate sensitivity. Why only the tropics are analyzed is not explained, other than by a vague statement in the last paragraph that refers to the “neutral higher latitudes.” Huh? Consider a global map of observed 20th century temperature changes (Fig 1B) http://ruby.fgcu.edu/courses/twimberley/EnviroPhilo/GlobalWarmingThreatProfJamesHansenNASA.pdf and also the IPCC climate model projections: http://www.ipcc.ch/publications_and_data/ar4/wg1/en/figure-10-8.html. The warming over the tropical oceans is lower than that for the tropical land masses, and far lower than that for the higher latitudes particularly the Arctic. But somehow (Fig 3) LC manage to determine a value of climate sensitivity from AMIP models for the tropical oceans that is between 2-4.5 K, which is essentially the same you would expect for the entire globe (e.g. the IPCC range of values) and in spite of the fact that the sensitivity of the tropical oceans is arguably at least a factor of 2 lower than the global average. So something is either wrong with the AMIP models (they definitely provide a different answer than the CMIP models, see Roy Spencer’s discussion on this) or with the LC methodology for calculating climate sensitivity.

2. The time scale of the feedbacks considered here are short term processes (over the tropical oceans) associated with clouds, water vapor and lapse rate, which are assumed to have equilibrium responses on time scales from a few months to less than 2 years. Even if this assumption re the timescale of equilibrium response is correct (see #3 below), Lindzen and Choi admit that their feedback analysis is relevant only for negative feedbacks since positive feedbacks have much longer equilibrium response times. It seems that this study is motivated by trying to document a negative feedback in the tropics, to support Lindzen’s iris hypothesis that addresses upper tropospheric water vapor and cirrus cloud feedbacks associated with tropical deep convection (which has received far more substantive criticism than support). The iris hypothesis and the tropical upper tropospheric water vapor and cirrus cloud feedbacks, while arguably still open to debate, are not by any stretch of the imagination a major driver in global climate feedback. Even in the limited context of local short term feedback processes over the tropical ocean, with the combination of issues raised in #1 and #2 I would expect the local feedback factor to be essentially zero.

3. Given that LC focus their analysis on the tropical oceans, the results from their analysis of ERBE data seems very implausible: a strong negative feedback in the shortwave (SWR), with a small positive feedback in the infrared (IR). The negative SWR feedback is basically an increase in the planetary albedo with increasing temperature, without a correspondingly large decrease in outgoing IR. How could this possibly be? The possibilities are:

an increase in surface reflectivity (impossible since tropical ocean surface reflectivity doesn’t change with surface temperature)

an increase in water vapor amount (doesn’t work, since water vapor changes have a much larger signal in the IR)

increase in aerosols that are making clouds more reflective with relatively small impact on IR emission (no major volcanoes during this period, but Saharan dust and biomass burning could have the desired effect. However, no known relationship between surface temperature and dust/biomass aerosols)

increase in low cloud amount (that reflects sunlight while emitting IR at nearly the same temperature of the surface). This works only if the increase in low cloud amount is not obscured by high clouds (which dominate the radiation fluxes at the top of the atmosphere when they are present). For this to be a significant effect, we would need to see a decrease in deep convective clouds in the tropics, which to my knowledge hasn’t been observed.

So, this large negative SW feedback with small positive IR feedback is not presently associated with a likely physical mechanism; e.g. Lindzen’s iris feedback wouldn’t produce this type of SWR/IR signature. I suspect that the large negative SW feedback identified from the ERBE data is an artifact of previously cited problems with the ERBE data analysis.

4. Even with a redo of the LC calculations fixing the implementation errors (e.g. using the correct version of the ERBE data, etc.), I am not convinced that the overall methodology used by LC can give a credible result for the climate feedback factor and climate sensitivity. The issue I want to focus on here is the nature of the energy balance model used to calculate the feedback factor and climate sensitivity. LC defines the feedback parameter as the change of the top of atmospheric radiation flux with change in surface temperature. If this seems counterintuitive to you and you don’t see how this relates to climate feedback, well it is based upon a lot of simplifying assumptions. This feedback parameter is derived from a simple linear feedback analysis of a simple energy balance model. Chapter 13 of my text Thermodynamics of Atmospheres and Oceans explains this

http://curry.eas.gatech.edu/climate/pdf/Ch13_GalleyC.pdf

http://curry.eas.gatech.edu/climate/pdf/chapter13_figs.pdf

For a lucid explanation of the specific equations used by LC (based upon a simple equilibrium planetary energy balance model) and discussions of the key assumptions and uncertainties, see this paper by Steve Schwartz (which by the way is highly controversial owing the short equilibrium response time that he determined)

http://www.fysik.org/website/fragelada/resurser/schwartz.pdf

Frame et al. ( http://www-atm.physics.ox.ac.uk/user/das/pubs/constraining_forecasts.pdf ) show that any estimate of climate sensitivity is critically dependent on subjective prior assumptions of the investigators, not simply on constraints provided by actual climate observations. Further, equally plausible approaches using the same model and observations can yield very different estimates of the risk of a high climate sensitivity. Assumptions inherent in the model that LC use include:

radiative equilibrium at the top of the atmosphere. If the climate system rapidly equilibrates, then climate sensitivity can be inferred from the top of atmosphere forcing and the increase in temperature over a given time period. In contrast, if the climate response time is long, inferring climate sensitivity in this way would lead to an estimate of sensitivity that would be too low. Steve Schwartz argues that the response time is fairly rapid, whereas Hansen and others argue for a much longer response time http://ossfoundation.us/projects/environment/global-warming/summary-docs/oss-reports/slr-research-summary-2008/2005_Hansen_etal_1.pdf

Arguably, the equilibrium climate sensitivity cant be obtained directly from observations, since the Earth’s climate system is always changing. LC assume a short response time, which they say is justified for negative feedbacks.

Arguably, the equilibrium climate sensitivity cant be obtained directly from observations, since the Earth’s climate system is always changing. LC assume a short response time, which they say is justified for negative feedbacks. the model does not consider spatial variations in climate sensitivity (we have already seen evidence of much higher sensitivity in the Arctic)

the model does not consider the frequency dependence of feedbacks (in sign and magnitude)

in response to a change in external forcing (e.g. solar, CO2), the top of atmosphere fluxes (SWR, IR) can be determined by many combinations of surface temperatures and albedos, vertical distribution of temperature and humidity, cloud vertical and horizontal distributions, and aerosol particles. It is only in the context of a simplified model of radiative convective equilibrium that surface temperature provides a unique value of SWR, IR. The unusual features in Delta Flux / Delta SST identified by Roy Spencer are probably an artifact of this complexity http://wattsupwiththat.com/2009/12/17/spencer-on-his-agu-presentation-yesterday/.

Steve Schwartz concludes: “Finally, as the present analysis rests on a simple single-compartment energy balance model, the question must inevitably arise whether the rather obdurate climate system might be amenable to determination of its key properties through empirical analysis based on such a simple model. In response to that question it might have to be said that it remains to be seen. In this context it is hoped that the present study might stimulate further work along these lines with more complex models. It might also prove valuable to apply the present analysis approach to the output of global climate models to ascertain the fidelity with which these models reproduce “whole Earth” properties of the climate system such as are empirically determined here. Ultimately of course the climate models are essential to provide much more refined projections of climate change than would be available from the global mean quantities that result from an analysis of the present sort. Still it would seem that empirical examination of these global mean quantities – effective heat capacity, time constant, and sensitivity – can usefully constrain climate models and thereby help to identify means for improving the confidence in these models.”

Summary: No confidence in the analysis of LC.

Prognosis: So where do we go from here in evaluating climate sensitivity and understading feedbacks? The basic assumptions behind this type of sensitivity analysis based on top of atmosphere fluxes used by LC need to be tested by climate models. Personally, I don’t have confidence in this method. I spent the 1990’s working of the feedback problem (mainly in the Arctic). I hosted a workshop on feedbacks and sensitivity in 2003, the workshop summary contains much food for thought http://www.gewex.org/reports/workshop02.pdf

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Update: this essay was finished on Dec 26. Steve decided to wait a few weeks before posting, given all the interest in climategate. Since then, there is now a formal reply to the LC paper that is in press in GRL by Trenberth, Fasullo, O’Dell and Wong, this is dicussed at RealClimate http://www.realclimate.org/index.php/archives/2010/01/first-published-response-to-lindzen-and-choi/ and http://www.realclimate.org/index.php/archives/2010/01/lindzen-and-choi-unraveled/. See also DotEarth http://dotearth.blogs.nytimes.com/2010/01/08/a-rebuttal-to-a-cool-climate-paper/



