Dr. Richard Lindzen writes to me with news of this significant new paper saying “It has taken almost 2 years to get this out. “. Part of that problem appears to be hostile reviewers in earlier submissions to JGR, something we’ve seen recently with other skeptical papers, such as O’Donnell’s rebuttal to Steig et al (Antarctica is warming) where Steig himself inappropriately served as a reviewer, and a hostile one at that.
Hostile reviewers aside, the paper will now be published in an upcoming issue of the Asia-Pacific Journal of Atmospheric Sciences and I am honored to be able to be able to present it here. The authors state that:
“We have corrected the approach of Lindzen and Choi (2009), based on all the criticisms made of the earlier work (Chung et al., 2010; Murphy, 2010; Trenberth et al., 2010).”
The present paper responds to the criticism, and corrects the earlier approach where appropriate. The earlier results are not significantly altered, and we show why these results differ from what others like Trenberth et al. (2010), and Dessler (2010) obtain.
So, while that may satisfy some critics, given the hostility shown to the idea that there is a low sensitivity to forcings, I’m sure a whole new crop of critics will spring up for this paper. The response to this paper in AGW proponent circles, like the feedback posited for Earth’s climate system, will surely be negative. Let the games begin.
However, warming from a doubling of CO2 would only be about 1°C (based on simple calculations where the radiation altitude and the Planck temperature depend on wavelength in accordance with the attenuation coefficients of wellmixed CO2 molecules; a doubling of any concentration in ppmv produces the same warming because of the logarithmic dependence of CO2’s absorption on the amount of CO2) (IPCC, 2007).
This modest warming is much less than current climate models suggest for a doubling of CO2. Models predict warming of from 1.5°C to 5°C and even more for a doubling of CO2
As a result, the climate sensitivity for a doubling of CO2 is estimated to be 0.7 K (with the confidence interval 0.5K – 1.3 K at 99% levels). This observational result shows that model sensitivities indicated by the IPCC AR4 are likely greater than than the possibilities estimated from the observations.
Our analysis of the data only demands relative instrumental stability over short periods, and is largely independent of long term drift.
Willis Eschenbach will no doubt find some interesting things in this paper, as it speaks of some of the same regulation mechanisms in the tropics as Willis has opined on here at WUWT. Here’s the Abstract and Conclusion, a link to the full paper follows:
On the Observational Determination of Climate Sensitivity and Its Implications
Richard S. Lindzen1 and Yong-Sang Choi2
1Program in Atmospheres, Oceans, and Climate, Massachusetts Institute of Technology, Cambridge, U. S. A.
2Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Korea
Asia-Pacific J. Atmos. Sci., 47(4), 377-390, 2011 DOI:10.1007/s13143-011-0023-x
We estimate climate sensitivity from observations, using the deseasonalized fluctuations in sea surface temperatures (SSTs) and the concurrent fluctuations in the top-of-atmosphere (TOA) outgoing radiation from the ERBE (1985-1999) and CERES (2000-2008) satellite instruments. Distinct periods of warming and cooling in the SSTs were used to evaluate feedbacks. An earlier study (Lindzen and Choi, 2009) was subject to significant criticisms. The present paper is an expansion of the earlier paper where the various criticisms are taken into account. The present analysis accounts for the 72 day precession period for the ERBE satellite in a more appropriate manner than in the earlier paper. We develop a method to distinguish noise in the outgoing radiation as well as radiation changes that are forcing SST changes from those radiation changes that constitute feedbacks to changes in SST. We demonstrate that our new method does moderately well in distinguishing positive from negative feedbacks and in quantifying negative feedbacks. In contrast, we show that simple regression methods used by several existing papers generally exaggerate positive feedbacks and even show positive feedbacks when actual feedbacks are negative. We argue that feedbacks are largely concentrated in the tropics, and the tropical feedbacks can be adjusted to account for their impact on the globe as a whole. Indeed, we show that including all CERES data (not just from the tropics) leads to results similar to what are obtained for the tropics alone – though with more noise. We again find that the outgoing radiation resulting from SST fluctuations exceeds the zerofeedback response thus implying negative feedback. In contrast to
this, the calculated TOA outgoing radiation fluxes from 11 atmospheric models forced by the observed SST are less than the zerofeedback response, consistent with the positive feedbacks that characterize these models. The results imply that the models are
exaggerating climate sensitivity.
We have corrected the approach of Lindzen and Choi (2009), based on all the criticisms made of the earlier work (Chung et al., 2010; Murphy, 2010; Trenberth et al., 2010). First of all, to improve the statistical significance of the results, we supplemented ERBE data with CERES data, filtered out data noise with 3-month smoothing, objectively chose the intervals based on the smoothed data, and provided confidence intervals for all sensitivity estimates. These constraints helped us to more accurately obtain climate feedback factors than with the original use of monthly data. Next, our new formulas for climate feedback
and sensitivity reflect sharing of tropical feedback with the globe, so that the tropical region is now properly identified as an open system. Last, the feedback factors inferred from the atmospheric models are more consistent with IPCC-defined climate sensitivity
than those from the coupled models. This is because, in the presence of cloud-induced radiative changes altering SST, the climate feedback estimates by the present approach tends to be inaccurate. With all corrections, the conclusion still appears to be
that all current models seem to exaggerate climate sensitivity (some greatly). Moreover, we have shown why studies using simple regressions of ΔFlux on ΔSST serve poorly to determine feedbacks.
To respond to the criticism of our emphasis on the tropical domain (Murphy, 2010; Trenberth et al., 2010), we analyzed the complete record of CERES for the globe (Dessler, 2010) (Note that ERBE data is not available for the high latitudes since the field-of-view is between 60oS and 60oN). As seen in the previous section, the use of the global CERES record leads to a result that is basically similar to that from the tropical data in this
study. The global CERES record, however, contains more noise than the tropical record.
This result lends support to the argument that the water vapor feedback is primarily restricted to the tropics, and there are reasons to suppose that this is also the case for cloud feedbacks. Although, in principle, climate feedbacks may arise from any
latitude, there are substantive reasons for supposing that they are, indeed, concentrated mostly in the tropics. The most prominent model feedback is that due to water vapor, where it is commonly noted that models behave roughly as though relative humidity
were fixed. Pierrehumbert (2009) examined outgoing radiation as a function of surface temperature theoretically for atmospheres with constant relative humidity. His results are shown in Fig. 13.
Specific humidity is low in the extratropics, while it is high in the tropics. We see that for extratropical conditions, outgoing radiation closely approximates the Planck black body radiation (leading to small feedback). However, for tropical conditions, increases in outgoing radiation are suppressed, implying substantial positive feedback. There are also reasons to suppose that cloud feedbacks are largely confined to the tropics. In the
extratropics, clouds are mostly stratiform clouds that are associated with ascending air while descending regions are cloudfree. Ascent and descent are largely determined by the large scale wave motions that dominate the meteorology of the extratropics, and for these waves, we expect approximately 50% cloud cover regardless of temperature (though details may depend on temperature). On the other hand, in the tropics, upper level clouds, at least, are mostly determined by detrainment from cumulonimbus towers, and cloud coverage is observed to depend significantly on temperature (Rondanelli and Lindzen, 2008).
As noted by LCH01, with feedbacks restricted to the tropics, their contribution to global sensitivity results from sharing the feedback fluxes with the extratropics. This led to inclusion of the sharing factor c in Eq. (6). The choice of a larger factor c leads to
a smaller contribution of tropical feedback to global sensitivity, but the effect on the climate sensitivity estimated from the observation is minor. For example, with c = 3, climate sensitivity from the observation and the models is 0.8 K and a higher value
(between 1.3 K and 6.4 K), respectively. With c = 1.5, global equilibrium sensitivity from the observation and the models is 0.6 K and any value higher than 1.6 K, respectively. Note that, as in LCH01, we are not discounting the possibility of feedbacks in the extratropics, but rather we are focusing on the tropical contribution to global feedbacks. Note that, when the dynamical heat transports toward the extratropics are taken into account, the overestimation of tropical feedback by GCMs may lead to even greater overestimation of climate sensitivity (Bates, 2011).
This emphasizes the importance of the tropical domain itself. Our analysis of the data only demands relative instrumental stability over short periods, and is largely independent of long term drift. Concerning the different sampling from the ERBE and CERES instruments, Murphy et al. (2009) repeated the Forster and Gregory (2006) analysis for the CERES and found very different values than those from the ERBE. However, in this
study, the addition of CERES data to the ERBE data does little to change the results for ΔFlux/ΔSST – except that its value is raised a little (as is also true when only CERES data is used.). This may be because these previous simple regression approaches include
the distortion of feedback processes by equilibration. In distinguishing a precise feedback from the data, the simple regression method is dependent on the data period, while our method is not. The simple regression result in Fig. 7 is worse if the model
integration time is longer (probably due to the greater impact of increasing radiative forcing).
Our study also suggests that, in current coupled atmosphereocean models, the atmosphere and ocean are too weakly coupled since thermal coupling is inversely proportional to sensitivity (Lindzen and Giannitsis, 1998). It has been noted by Newman et al. (2009) that coupling is crucial to the simulation of phenomena like El Niño. Thus, corrections of the sensitivity of current climate models might well improve the behavior of coupled
models, and should be encouraged. It should be noted that there have been independent tests that also suggest sensitivities less than predicted by current models. These tests are based on the response to sequences of volcanic eruptions (Lindzen and Giannitsis, 1998), on the vertical structure of observed versus modeled temperature increase (Douglass, 2007; Lindzen, 2007), on ocean heating (Schwartz, 2007; Schwartz, 2008), and on
satellite observations (Spencer and Braswell, 2010). Most claims of greater sensitivity are based on the models that we have just shown can be highly misleading on this matter. There have also been attempts to infer sensitivity from paleoclimate data (Hansen
et al., 1993), but these are not really tests since the forcing is essentially unknown given major uncertainties in clouds, dust loading and other factors. Finally, we have shown that the attempts to obtain feedbacks from simple regressions of satellite measured outgoing radiation on SST are inappropriate.
One final point needs to be made. Low sensitivity of global mean temperature anomaly to global scale forcing does not imply that major climate change cannot occur. The earth has, of course, experienced major cool periods such as those associated with ice ages and warm periods such as the Eocene (Crowley and North, 1991). As noted, however, in Lindzen (1993), these episodes were primarily associated with changes in the equatorto-
pole temperature difference and spatially heterogeneous forcing. Changes in global mean temperature were simply the residue of such changes and not the cause.
Dr. Lindzen has the full paper on his personal website here: