The eminent statistician (and occasional BH reader) Radford Neal has been writing a series of posts on global temperature data at his blog. There are three so far:

What can global temperature data tell us?

Has there been a pause in global warming?

and finally

Critique of "Debunking the climate hiatus", by Rajaratnam, Romano, Tsiang and Diffenbaugh.

They are all rather technical but very well written - the clarity of thought is striking. But I particularly recommend the last one, a gloriously deadpan take on a much-trumpeted paper (one which trashes claims of a hiatus, apparently), with gems like this:

The authors are all at Stanford University, one of the world’s most prestigious academic institutions. Rajaratnam is an Assistant Professor of Statistics and of Environmental Earth System Science. Romano is a Professor of Statistics and of Economics.Diffenbaugh is an Associate Professor of Earth System Science. Tsiang is a PhD student. Climatic Change appears to be a reputable refereed journal, which is published by Springer, and which is cited in the latest IPCC report. The paper was touted in popular accounts as showing that the whole hiatus thing was mistaken — for instance, by Stanford University itself. You might therefore be surprised that, as I will discuss below, this paper is completely wrong. Nothing in it is correct. It fails in every imaginable respect.

...and this:

Rajaratnam, et al. describe [their] data as “the NASA-GISS global mean land-ocean temperature index”, which is a commonly used data set, discussed in my first post in this series. However, the data plotted above, and which they use, is not actually the GISS land-ocean temperature data set. It is the GISS land-only data set, which is less widely used, since as GISS says, it “overestimates trends, since it disregards most of the dampening effects of the oceans”. They appear to have mistakenly downloaded the wrong data set, and not noticed that the vertical scale on their plot doesn’t match plots in other papers showing the GISS land-ocean temperature anomalies.

You have to read it now, don't you?