Wondering Willis Eschenbach's sensitive side
Wondering Willis Eschenbach has returned from his hot but remote airports and brings great news (archived here). He has done an about face and is no longer an insensitive lout, but extremely sensitive when it comes to climate.
No more figuring out feedbacks. We no longer need to wonder what impact the disappearing Arctic sea ice will have over what time frame, or whether clouds will have a net positive or negative feedback effect. Wondering Willis has pronounced (in a convoluted post using a circular argument, in which he misses the point of a six year old paper) that climate sensitivity is as follows:
Climate Sensitivity = Climate Sensitivity
No need to worry any more. Problem solved. Willis says all the climate models can be dismantled. There is no need for climate modellers to puzzle any more. Just ask Willis. Don't ask Jeffrey Kiehl. Though Willis does give Dr Kiehl a pat on the head for effort:
Note that Kiehl’s misidentification of the cause of the variations is understandable. .... But as a first cut at solving the paradox, as well as being the first person to write about it, I give high marks to Dr. Kiehl.(Kiehl attributed differences between the models in regard to climate sensitivity to uncertainty in aerosol forcing. Willis argued Kiehl was wrong. As far as I can gather, Willis attributed the difference between those same models in regard to climate sensitivity to differences in climate sensitivity! These days differences between models in regard to climate sensitivity is attributed to uncertainty in cloud feedback.)
Kiehl, Jeffrey T. "Twentieth century climate model response and climate sensitivity." Geophysical Research Letters 34.22 (2007).
Willis is uncertain about uncertainty (very high confidence)
Despite being certain about climate sensitivity, I can say with very high confidence that Willis is uncertain about uncertainty (same article). So much so that he "laughed because crying is too depressing". He thought that when the IPCC report stated:
The model spread in equilibrium climate sensitivity ranges from 2.1°C to 4.7°C and is very similar to the assessment in the AR4. There is very high confidence that the primary factor contributing to the spread in equilibrium climate sensitivity continues to be the cloud feedback. This applies to both the modern climate and the last glacial maximum....that it contradicted the fact that there is a degree of uncertainty in cloud response. But of course he got it all wrong (again). Willis foolishly writes:
How can they have “very high confidence” (95%) that the cause is “cloud feedback”, when they admit they don’t even understand the effects of the clouds?What was meant in the report was that there was very high confidence that the difference in estimates of climate sensitivity can be attributed to different estimates of the effect clouds will have on the radiation balance. The authors have high confidence that there is large uncertainty in regard to cloud feedbacks. Higher sensitivity would mean that clouds exert a stronger positive feedback, while lower climate sensitivity would be expected if changes in clouds exerted a less positive or maybe dampen the forcing with a slightly negative feedback. This is from page TS-54 of the WG1 Technical Summary (my paras and bold italics):
The water vapour/lapse rate, albedo and cloud feedbacks are the principal determinants of equilibrium climate sensitivity (ECS, the equilibrium change in annual mean global surface temperature following a doubling of the atmospheric CO2 concentration). All of these feedbacks are assessed to be positive, but with different levels of likelihood assigned ranging from likely to extremely likely. Therefore, there is very high confidence that the net feedback is strongly positive and the black body response of the climate to a forcing will therefore be amplified.
Cloud feedbacks continue to be the largest uncertainty. The net feedback from water vapour and lapse rate changes together is extremely likely positive and approximately doubles the black body response. The mean value and spread of these two processes in climate models are essentially unchanged from AR4, but are now supported by stronger observational evidence and better process understanding of what determines relative humidity distributions.. Clouds respond to climate forcing mechanisms in multiple ways and individual cloud feedbacks can be positive or negative.
Key issues include the representation of both deep and shallow cumulus convection, microphysical processes in ice clouds, and partial cloudiness that results from small-scale variations of cloud-producing and cloud-dissipating processes. New approaches to diagnosing cloud feedback in GCMs have clarified robust cloud responses, while continuing to implicate low cloud cover as the most important source of intermodel spread in simulated cloud feedbacks.
The net radiative feedback due to all cloud types is likely positive. This conclusion is reached by considering a plausible range for unknown contributions by processes yet to be accounted for, in addition to those occurring in current climate models. Observations alone do not currently provide a robust, direct constraint, but multiple lines of evidence now indicate positive feedback contributions from changes in both the height of high clouds and the horizontal distribution of clouds. The additional feedback from low cloud amount is also positive in most climate models, but that result is not well understood, nor effectively constrained by observations, so confidence in it is low.It all goes to show that no matter how much effort one takes to clarify meaning, there will always be someone who gets it all wrong.