So with all of this discussion, and with this newly collated data-set handed to me today, it gave me an idea. I had never seen a histogram comparison done on all four data-sets simultaneously.
Well, there is a reason for that. The data sets use different baselines to compute relative anomalies, so such a histogram comparison would be worthless.
Doing so would show how well the cool and warm anomalies are distributed within the data. If there is a good balance to the distribution, one would expect that the measurement system is doing a good job of capturing the natural variance. If the distribution of the histogram is skewed significantly in either the negative or positive, it would provide clues into what bias issues might remain in the data.
Well, no it would not. It would however provide a clue that whoever was attempting the comparison didn’t know the difference between an anomaly and a trend. If for example somebody computed anomalies relative to absolute zero, then all the anomalies would be in the red. The trend would remain unaltered and it would be no less correct. Needless to say such a basic error won’t stop the usual denialists running with this and repeating it verbatim. Posts such as this one from Watts do however provide a useful function. They are wrong in such a uniquely clueless way that they are the equivalent of exploding dye packs in stacks of stolen money. Look for a lot of global warming denialists running around colored bright red before they figure out what happened here. Update: the original post seems to have been taken down. Meanwhile it is available here. Technorati Tags: globalwarming, anthony watts, histogram, anomaly, trend, temperature, agw, denialists