Wrong type of cloud, but the white whale is there
Richard “Dick” Lindzen is one of the last of the denialists with credentials impressive enough to be taken seriously by the press (and indeed, Lindzen has some done deservedly-award-winning work in tropical meteorology). Leaving aside for the moment his unfortunate cigarette-cancer denial and his fallacy-riddled op-eds in the WSJ, Lindzen is probably best known in the climate science community for his pathological belief that climate sensitivity is near zero or negative: that is to say that he believes the effect of doubling atmospheric CO2 levels will have either a trivial or cooling effect on global temperature. Lindzen’s white whale is the alleged existence of a negative feedback in the tropics that he’s termed the Iris effect- essentially, Lindzen contends that warming of the tropical ocean will result in a reduction in cirrus cloud cover, which will result in more infrared radiation making its way back out to space.
Unfortunately, neither recent paleoecological evidence nor observations and modeling bear this idea out, and of course the broader picture of climate sensitivity derived from the paleo and instrumental records as well as modern climate modeling illustrates how wildly out of touch Lindzen’s belief is.
Lindzen’s latest folly volley in his low sensitivity crusade was a recent GRL paper coauthored with Yong-Sang Choi entitled “On the determination of climate feedbacks from ERBE data” which attempted to derive climate sensitivity by examining changes in outgoing infrared radiation from ERBE (Earth Radiation Budget Experiment) data and comparing them to AMIP (Atmospheric Model Intercomparison Project) modeling, finding – surprise! – sensitivity to be negligible and models to overstate it).
Kevin Trenberth, John Fasullo, Chris O’Dell, and Takmeng Wong (henceforth TFOW10) have a rebuttal paper at GRL (in press, doi:10.1029/2009GL042314) entitled: “Relationships between tropical sea surface temperature and top-of-atmosphere radiation”, which I’ll quote from at length.
To assess climate sensitivity from Earth radiation observations of limited duration and observed sea surface temperatures (SSTs) requires a closed and therefore global domain, equilibrium between the fields, and robust methods of dealing with noise. Noise arises from natural variability in the atmosphere and observational noise in precessing satellite observations. This paper explores the meaning of results that use only the tropical region. We compute correlations and regressions between tropical SSTs and top-of-atmosphere (TOA) longwave, shortwave and net radiation using a variety of methods to test robustness of results. The main changes in SSTs throughout the tropics are associated with El Niño Southern Oscillation (ENSO) events in which the dominant changes in energy into an atmospheric column come from ocean heat exchange through evaporation, latent heat release in precipitation, and redistribution of that heat through atmospheric winds. These changes can be an order of magnitude larger than the net TOA radiation changes, and their effects are teleconnected globally, and especially into the subtropics.
[A] recent attempt to estimate sensitivity and λ [Lindzen and Choi, 2009] (LC09) notes that there are many pitfalls to be avoided in assessing climate feedbacks in models using observations of radiation at TOA. While they adopt a procedure to avoid one of these pitfalls, they fail to recognize and account for several others, they do not account for external forcings, and their use of a limited tropical domain is especially problematic. Moreover their results do not stand up to independent testing. Accordingly, one focus of this article is to carry out a more robust analysis of the tropical domain results and its implications, if any, for climate sensitivity. We also resolve why there was an apparent discrepancy between model and observed results.
TFOW10 review Lindzen and Choi’s attempt:
To summarize the approach of LC09, variability in the TOA energy budget was assessed as it relates to variability in tropical (20oN to 20oS) SSTs from 1985 to late 1999 for both nature and 11 atmospheric climate models run with specified SSTs. Fluxes from the ERBS sensor were used, excepting for gaps in 1993, 1998, and 1999. Major intervals of warming and cooling in SST were identified to quantify the change in TOA fluxes across these intervals. Owing in part to the precession of the ERBS satellite, there is considerable noise in monthly means used by LC09, although they apply a 7-month smoother to RSW to reduce this. LC09 avoid the uncertainties in trends problem by choosing short-term segments “that are long compared to the time scales associated with the feedback processes, but short compared to the response time over which the system equilibrates.” The segments range from about 4 to 18 months and mainly 6 reflect ENSO fluctuations. A serious omission in LC09 is that they did not consider the forcing F in eq. (1) in their regressions, and this is an especially grievous error when the period following the large perturbation associated with the Mount Pinatubo eruption in April 1991 is considered.
TFOW10 attempt to reproduce Lindzen and Choi’s results, finding them extremely sensitive to the methods used to achieve them:
In attempting to reproduce the LC09 results (Fig. 1a) we found extreme sensitivities to their method. Note that the “Net” radiation in LC09 is outwards and thus has the opposite sign to RT. As the dates used by LC09 are not provided, they were estimated from their Fig. 1. Sensitivity to the method was examined by allowing for a displacement of the endpoints of their warming and cooling intervals by a month or less (Fig. 1). The LC09 result (their Fig. 2) is equivalent to the m=4.55 W m-2 K-1 slope in Fig. 1b, and the higher correlation is because the noise (not the signal) is being explained. It is evident that the uncertainty is very large. As the filter employed by LC09 is not given, we used a 7-month running mean although a Gaussian and other filters were tried, and results are not a strong function of the filter used.
And find their choice of test intervals unjustified (a less charitable characterization would be “cherry picked”):
Moreover, their selection of dates for the intervals (Fig. 1 of LC09, and Fig. 1a here) is frequently not justifiable. This is evident if an objective method of identifying the intervals is employed, for example, to identify local minima and maxima exceeding 0.1°C in low-pass filtered data (see Fig. 1a). For example, for the warming event in 1997/98, the warming declared by LC09 ceases in mid-1997 rather than at the obvious SST peak in Jan 1998. Also, the warming during the 1986/87 ENSO is assumed to begin in mid-1986 when it can alternatively be proposed that warming began in 1985. Warming is declared by LC09 to end in early 1993, well prior to the peak in SST in the middle of the year.
Hence we find that the LC09 results are neither robust nor meaningful, as small sensible changes in the dates bounding their warming and cooling intervals entirely change the 7 conclusions.
TFOW next turn to Lindzen and Choi’s use of AMIP modeling:
We attempt to reproduce the results of LC09 using three different methods and 9 models available to us (excluding miroc3_2_hires and mri_cgcm2): first, using the same basic method as LC09, then repeated with more sensible dates for the period end points, and finally with monthly surface temperature and the corresponding flux anomalies; see Table 2. When revised dates are used, the RSW regression decreases in magnitude and the net radiation regression reverses sign to become the same as for observations (Table 1). Our AMIP model results (Table 2) from both valid methods are consistent with the ERBE observations for OLR, RSW, and RT to within error bars. Those of LC09 are not. The large mean slope for LC09 is removed if more appropriate dates for starting and ending of segments are used (and in particular moving the boundary for rising to falling SSTs to Jan 1998).
The eruption of Mt. Pinatubo in June 1991 is clearly evident in the ERBS nonscanner record and the TOA RSW flux response exceeds 5 W m-2 and is the largest perturbation in TOA radiation. Hence a fundamental shortcoming of LC09 is the failure to recognize that 9 of the 11 models used for comparisons during the ERBS nonscanner period did not include Pinatubo aerosol forcing. There is also no accounting of other aerosols, either anthropogenic or natural, in the AMIP runs. Hence there is no forcing F (Eq (1)) in most AMIP runs.
[T]he approach taken by LC09 is flawed, and its results are seriously in error. The LC09 choice of dates has distorted their results and underscores the defective nature of their analysis. Incidentally, LC09 incorrectly computed the climate sensitivity by not allowing for the Planck function in their feedback parameter. For their slope of -4.5 W m-2 K-1 and using the correct equations (Section 1), LC09 should obtain a feedback parameter and climate sensitivity of -0.125 and 0.82 K, respectively, rather than their values of -1.1 and 0.5 K. In contrast, the case 4 (Table 1) results yield a positive feedback parameter of 0.6 and a climate sensitivity of 2.3 K. Moreover LC09 failed to account for the forcings in estimating sensitivity.
When the Lindzen and Choi paper was first accepted, a fair number of non-denialist skeptics and even non-skeptics seemed puzzled by the lack of immediate pushback from the broader climate science community. Unlike past instances of perhaps well-intentioned but wrong papers like Schwartz ’07 or papers purporting to illustrate one (incorrect) thing being used in the press to claim another like McLean ’09, there isn’t anything particularly novel about yet another paper in which Dick Lindzen takes aim at and runs headfirst into the evidence illustrating a climate sensitivity of ~2-3°C. Although TFOW10 do take the time to correct Lindzen and Choi’s errors, they do so not simply to put out the figurative fire, but rather took the time to place Lindzen and Choi’s misguided efforts within a broader context of the role of the tropics in the global energy budget, and use the opportunity to demonstrate a larger point about the danger in trying to draw global conclusions from tropics-specific data:
However, it is not appropriate to use only tropical SSTs and TOA radiation for feedback analysis as the transports into the extratropics are substantial. Any feedback analysis must also recognize changes in ocean heat storage and atmospheric energy transport into and out of the tropics which are especially large during ENSO events. While the tropics are important in climate sensitivity, values of the latter based on only tropical results are misleading.
[UPDATE: And before I had time to hit submit, it looks like the authors themselves have a more accessible explanation of their paper up at RealClimate. The perils of procrastination…]
[UPDATE: In before Dot Earth, though. : )]