from **http://dx.doi.org/10.1126/science.1203513**

P.S. I wrote more here. Reproduced below …

Practical likelihood functions are very flat-topped, so the idea that a maximum likelihood function (MLE) can be confined to a point is a theoretical mirage. See Chapter 3 of S. Konishi, G. Kitagawa, *Information Criteria and Statistical Modeling*, Springer, 2008. Even if you want to set aside Bayesian considerations, whose priors *tend* to sharpen the posteriors, the best you can do is *expected likelihoods*, because likelihoods in practice, just like *p-values*, are random variables. Accordingly, the MLE is a neighborhood, because a point has probability mass zero.

Besides, … the question of multimodality [wasn’t addressed]. Actual Expected Climate Sensitivity is a combination of the densities over oceans and land, each of which have different distributions and modes. (See https://goo.gl/pB7H24 which is from http://dx.doi.org/10.1126/science.1203513) Accordingly, their combination is (at least) bimodal. Ocean ECS has 4 modes. Land ECS has 2 modes, one slightly higher than the other, the higher being at +3.4°C and the second at about +3°C. Worse, the variance of land ECS is over twice than of oceans.

Finally, what you *should* be looking at is the ECS_{2x} *over land*, not combined. Even if granted to want to go with the location of the highest mode, that’s +3.4°C.

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About ecoquant

See https://667-per-cm.net/about. Retired data scientist and statistician. Now working projects in quantitative ecology and, specifically, phenology of Bryophyta and technical methods for their study.

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