A new paper is out by Foster and Rahmstorf (2011), and while I may later do a more in-depth analysis, I want to point out a rather interesting implication of this paper, if indeed one were to take it at face value — it supports Spencer and Braswell (2008, 2010, and 2011 to some degree). Allow me to explain. (Note: to avoid confusion, there is Grant Foster, a.k.a. Tamino, and Piers Forster, whose papers I reference below attempt to measure sensitivity from radiation fluxes).
As you may recall, I performed some sensitivity tests related to the multiple regression a while back . Looking that post over again, there are a few errors on my part (I believe I used actual surface T for the S-B/Planck response), but there are a few interesting tidbits: 1) leaving the adjustments for TSI/solar out affects the conclusions, and 2) the estimated solar response is around 4 times greater than the volcanic response.
Let’s take a closer look at #2, which may have changed a bit from the post to the paper. From figure #3 of the FR11 paper, we see the coefficient for TSI at around 0.1 C for the land data, which, after adjusting for planetary albedo and shadow area / surface area, results in around a 0.57 C/(W/m^2) instantaneous surface temperature response for the actual solar forcing. Note that in Tamino’s original post, he had estimated about 0.39 C/(W/m^2) for solar, but that was when the solar influence range was only 0.08 C rather than the 0.12 C mentioned in the new paper.
For Aerosol Optical Depth (volcanic), the coefficient is around 2 deg.c / tau. If we look up the approximate efficacy, we see that it is around -25 W/m^2/tau. Such an estimate would yield the instantaneous sensitivity of around 0.08 C/(W/m^2), which would put it at around 1/7 the efficacy of a solar forcing, both in W/m^2. Certainly, there are reasons to believe that the instantaneous surface temperature response to the larger forcings may be damped (thank you SteveF) by the ocean heat uptake, but it seems that a factor of 7x (or 4 times) remains far too big of a discrepancy to be considered a reasonable physical result. Furthermore, the longer-term response may be expected to manifest itself over the course of say 8-12 years, but for the FR11 paper anything beyond the instantaneous response is ignored.
Anyhow, according to FR11, the time between the solar forcing anomaly to the surface temperature response is estimated to be around 1 month. Remember that for later.
Relation to Spencer and Braswell
For more on the background of attempting to measure climate sensitivity and where the Spencer and Braswell arguments fit in, please see this page . But as a quick summary, I’ll note that in Forster and Gregory (2006), the authors comment (my insert in bold):
The X terms [radiative noise or unknown radiative forcings] are likely to contaminate the result for short datasets, but provided the X terms are uncorrelated to Ts, the regression should give the correct value for Y, if the dataset is long enough.
Spencer and Braswell argue that the unknown radiative forcing (fluctuations in cloud cover, which we know to exist AT LEAST on short timescales, per Dessler (2010)) would necessarily influence the Ts and hence lead to an underestimate of the radiative response. The counter-argument has been two-fold:
The decorrelation time of this radiative noise is shorter than the surface temperature response time. From Murphy et al. (2009), we read:
If temperature variations are changing outgoing radiation then temperature should be the independent variable whereas if radiation variations are affecting temperature then temperature should be the dependent variable. Although both are true to some extent, they can be partially separated by time response: outgoing radiation changes are mostly immediate whereas surface temperatures lag radiative forcing. Autocorrelation analyses of global temperatures suggest that the surface ocean portion of the Earth’s climate response has a time constant of about 8–12 years [Scafetta, 2008; Schwartz, 2008].
I believe this response misses the mark, as you might very well expect significant surface temperature responses to forcings on much shorter time-scales, even if the full forcing response is not realized for several more years. A better argument might be that the decorrelation time of this noise used by SB is too long, and that for cloud fluctuations it is actually on the scale of 2-3 months, whereas the temperature response is (for example) about 5 months later. However, the Fo
rster and Rahmstorf (2011) paper implies a lag in temperature response of only around 1 month for these smaller fluctuations, which, even with only intraseasonal fluctuations (such as the Madden–Julian oscillation) in cloud cover, would suggest a strong correlation between these unknown radiative fluctuations (X) and T_surface!
The second major argument against the Spencer and Braswell result, as advanced by Murphy and Forster (2010) and Dessler (2011), is that the effective heat capacity of the ocean on these timescales is too high for the unknown radiative forcing to have any significant effect on surface temperatures. They attribute almost all of the surface temperature fluctuations during this recent decade to internal, non-radiative forcings (e.g., heat exchange between the ocean layers). I have explained before why their estimates of heat capacity are inappropriate for these monthly timescales. Nonetheless, using a similar method to Dessler (2011), I’ll point out that the standard deviation in surface temperature anomaly from 2000-2010 is around 0.1 C. Dessler (2011) calculates the standard deviation of the cloud forcing/noise to be around 0.5 W/m^2. So, can this 0.5 W/m^2 cloud fluctuation force any significant amount of the 0.1 C surface temperature changes? According to Dessler (2011), the answer is a strong NO (~5%). But according to Foster and Rahmstorf (2011), with its 0.57 C/(W/m^2) instantaneous response to solar forcing, such cloud forcing fluctuations (if the response scales) could result in 0.28 C changes! Now one may argue that the responses to slower solar cycles don’t experience the same damping, but even if the cloud forcing efficacy is only 1/5 that amount, this would imply that the measurements of climate sensitivity from radiative fluxes has been greatly overestimated.
Overall, I don’t think a proper analysis will support either the high Dessler (2011) heat capacity over these short period, or the high instantaneous effect of changes in TSI from FR11 that contradicts it. Indeed, I suspect the latter is likely an artifact of fitting to an underlying linear trend, as the effect of the solar minimum is overestimated in order to counter the flattening in the early 21st century. I think this point highlights the larger problems with such a methodology. Nonetheless, if one were to take the FR11 results at face value, Spencer and Braswell could very well point out that this peer-reviewed paper suggests a short lag time for the large surface temperature response (1 month) to a small forcing, lending credence to their argument that unknown radiative forcing “noise” will correlate with surface temperature. Heck, even using a T_s response midway between the FR11 values for TSI and AOT per W/m^2 would strongly support the SB case.