Extract-
"But think about what happens when we try and estimate the absolute global mean temperature for, say, 2016. The climatology for 1981-2010 is 287.4±0.5K, and the anomaly for 2016 is (from GISTEMP w.r.t. that baseline) 0.56±0.05ºC. So our estimate for the absolute value is (using the first rule shown above) is 287.96±0.502K, and then using the second, that reduces to 288.0±0.5K. The same approach for 2015 gives 287.8±0.5K, and for 2014 it is 287.7±0.5K. All of which appear to be the same within the uncertainty. Thus we lose the ability to judge which year was the warmest if we only look at the absolute numbers."

"Like the proverbial elephant, the internet never forgets. And so the world is awash with quotes of absolute global mean temperatures for single years which use different baselines giving wildly oscillating fluctuations as a function of time which are purely a function of the uncertainty of that baseline, not the actual trends."

"One example is sufficient to demonstrate the problem. In 1997, the NOAA state of the climate summary stated that the global average temperature was 62.45ºF (16.92ºC). The page now has a caveat added about the issue of the baseline, but a casual comparison to the statement in 2016 stating that the record-breaking year had a mean temperature of 58.69ºF (14.83ºC) could be mightily confusing. In reality, 2016 was warmer than 1997 by about 0.5ºC!"

http://www.realclimate.org/index.php/archives/2017/08/observations-reanalyses-an...


Hat tip to Kip Hansen.


That Gavin Schmidt can sure spin whoppers.

Note: 1997's 62.45ºF is an absolute temperature. So how do you manipulate a 62.45ºF temperature to be cooler than 2016 58.69ºF by "about 0.5C"? 16.92ºC -14.83ºC is 1.07ºC.

Moving the baseline does not alter an absolute temperature. it moves the anomaly.

If the baseline was 15.3ºC and the anomaly was +0.3ºC the absolute temperature for that year would be 15.6ºC.

If we change the baseline to 15.4ºC then the anomaly goes down to maintain the absolute temperature of 15.6ºC. Meaning the anomaly would be +0.2ºC.
And vice versa of course.

But it is interesting that he says that the uncertainties in the data are +/-0.5ºK or C, whichever you prefer.

And then magically transforms it into anomalies with an accuracy of +/- 0.05C. An order of magnitude smaller than the data.