On Monday, I will have a post on the relationship of the article
McKitrick, Ross R. and Lise Tole (2012) “Evaluating Explanatory Models of the Spatial Pattern of Surface Climate Trends using Model Selection and Bayesian Averaging Methods” Climate Dynamics, 2012, DOI: 10.1007/s00382-012-1418-9
to our research, as his excellent study bolsters our findings.
However, I need to post this afternoon on a remarkable admission by Gavin Schmidt on the McKitrick and Tole paper. In a reply to a comment (#260) by someone who labels themselves as MapleLeaf in the Real Climate post
Gavin writes [highlight added]
“The basic issue is that for short time scales (in this case 1979-2000), grid point temperature trends are not a strong function of the forcings – rather they are a function of the (unique realisation of) internal variability and are thus strongly stochastic…..There are other issues, but his basic conceptual error is big one from which all other stem”
This is an amazing statement with respect to multi-decadal trends. Perhaps Gavin misspoke. Otherwise, he is stating that that multidecadal local temperature trends are dominated by non-global climate effects and not by the global annual surface temperature tend. I agree with this view, and am pleased to see recognition of the behavior of the real world climate system from Gavin.
There is also one other remarkable statement as part of this exchange (by MapleLeaf). MapleLeaf wrote that McKittrick
….also seems to be floating a red herring when he claims that the GCMs are not good at predicting regional changes. We know that, but what is his point when it comes to reducing GHG emissions? That we do nothing?”
I actually agree with this view. As my son has written on many times (e.g. see The Climate Fix), the addition of carbon dioxide and other greenhouse gases by human activity to the atmosphere is a first-order climate forcing. The science is settled on this issue. However, where MapleLeaf is missing the point is that huge amounts of research funding and time are being used to apply multi-decadal regional climate prediction results from the global models (either directly, or dynamically or statistically downscaled) by the impacts communities; e.g. see.
I am pleased to see MapleLeaf also sees this as a waste of money.
I am also glad to see Gavin Schmidt admit to what we have known for a long time - that a global annual averaged surface temperature trend tells us almost nothing of importance with respect to the risks from climate, including any changes in regional and local climate due to human activities.