This is a guest blog by Bill Fothergill, also known as billthefrog.
He sent it to me a couple of weeks ago, but it's still topical.
Many of the contributors to the Arctic
Sea Ice Blog have passed comment on the dangers of basing an
end-of-melt-season prediction on anything as simple as the current
area or extent values. The variables that determine the eventual
outcome of the annual melt season are truly legion, and it is sheer
folly to think that a single parameter provides anything other
than a tenuous glimpse at what eventually may transpire.
However, whilst few might disagree with the above assertion, it would obviously be better to base this claim on something a trifle more rigorous than a vague gut feeling or some unshakeable belief that the universe should conform to one’s prejudices. There are obviously many ways to perform some form of mathematical analysis on the available data, but an example of such a method would be to look at the correlation between various mean monthly values over a predetermined time frame.
In the example outlined here, the NSIDC monthly area and extent values are used to provide the data, and the CORREL function in Excel is used to calculate a type of relationship known as the correlation coefficient. The dataset(s) were read into a rectangular array with “months” along one dimension and “years” along the other such that, say, the April extent for each year from 1979-2012 could be compared in turn with its respective equivalent figure for May, June, July etc.