Global warming v weather shift

[GIGObuster]

@Trinopus

Just as a point of human interest – I read the article GIGObuster linked to, with the nifty graphs and the discussion of confidence levels.

WHY is there that really grotesque data outlier in April of 2010? How did anyone manage to make a measurement that was so remarkably outside of expectations? Did somebody flub, or is it simply an unavoidable result of techniques? (i.e., by pure coincidence, it snowed near eight out of ten measuring stations, the sort of random thing that is just bound to happen?)

Just fascinated to see a data point that grabs the eye that way!

(If I saw a data outlier like that in the log I keep of my personal weight, I’d assume that the scale had got a bit of grit in it. ETA: I’d also use it as a justification for eating an extra helping of dessert!)

Whoa!!! What’s that huge spike at the end? It rises faster than a “hockey stick”!

The huge spike is the huge uncertainty level of the final two data points — April and May 2010. While the other data have uncertainty levels around 0.1 deg.C, those two months have uncertainty levels of 2.8 and 2.9 deg.C. Which makes them, plainly, unreliable.

More of what happened is in the article, appropiately called, “Baked Curry”

Baked Curry: The BEST Way to Hide the Incline

So what happened with the April and May 2010 data? While the March 2010 anomaly was based on 14,488 stations, April and May were based on only 47 stations, all in the Antarctic (h/t Nick Stokes). In other words, April and May 2010 should be excluded from BEST data analysis because they are incomplete, their uncertainties are just too large, and April 2010 is quite obviously an anomalous outlier. Frankly they should not have been published in their current state.