“”To claim that observations can tell us something about ECS, we first have to see whether it is a meaningful test by using the best info to hand – model output ”
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Or in other words ignore data. Who needs data anyway.
It is useless without models.
Now as someone once said all models are wrong.
But we can discuss a lot of physics in the models and the answers are always right.
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Further proof,
“Observations therefore are not likely to usefully constrain ECS in any Bayesian assessment”
We do not need observations or data to construct highly reliable models, especially when we know what the data will be in the future without looking at it.
“Whereas by 2095, the correlation between total warming and ECS is 0.77. Correlation over the period 2006 to 2095 is 0.81. The best way to estimate climate sensitivity is to be there, not here and now.”
In fact model data gets better and better in correlation with the models as it gets further away from actually being observed.
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“Roughly speaking, this result seems broadly consistent with the IPCC range of 1.5-4.5K (although that might be a 17-83%, rather than a 5-95%, range),”
Eyeballing the graphs roughly there appears to be little correlation with the Lewis best estimate way below the IPCC estimate.
BBD prefers 3.0 Lewis would be lucky to be 2.0.
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“What would be nice would be to maybe include more physics so as to exclude regions of parameter space that we regard virtually impossible (for example, ECS values below 1K).”
If the physics is right why do we have to include “more” physics? Surely impossible results will be excluded by the physics we have, if it is right in the first place, not more of it.