JoNova

The Australian Bureau of Meteorology have been struck by the most incredible bad luck. The fickle thermometers of Australia have been ruining climate records for 150 years, and the BOM have done a masterful job of recreating our “correct” climate trends, despite the data. Bob Fernley-Jones decided to help show the world how clever the BOM are. (Call them the Bureau of Magic).

Firstly there were the Horoscope-thermometers — which need adjustments that are different for each calendar month of the year — up in December, down in January, up in February… These thermometers flip on Jan 1 each year from reading nearly 1°C too warm all of December, to being more than 1°C too cold for all of January . Then come February 1, they flip again. Somehow the BOM managed to unravel this bizarre pattern (cue X-files music) and figure out exactly what anti-horoscope-adjustments to use (and they were different in every city). Modestly the BOM did not explain to the public how clever their adjustments were; despite their $300m budget, it took volunteer Bob Fernley-Jones to reverse out the Special Horoscope Cure, and find the square wave algorithm that repaired our damaged climate records. Lucky for the […]

Two out of three Australians live in our capital cities where the longest and best resourced temperature records would be found. These are the places where the weather reports matter to the most people on a daily basis — and where headlines about records and trends will be widely discussed. But these are also the sites which have been affected by the growth of concrete and skyscrapers, and potentially have the largest urban heat island (UHI) effect, so might need the largest adjustments.

Bob Fernley-Jones has been going through the BOM records for six of Australia’s state capitals, looking at the original raw data (at least, as is recorded in the BOM’s climate data online, called CDO). Bob compares the new “corrected” dataset called ACORN for these locations — that’s the all new marvelous adjusted data. He finds many step changes that can’t be explained by known site moves or the UHI effect. Many step changes occur in either minima or maxima, but not in both at the same time, which is also odd. As we already know, the adjustments usually cool the past — especially the minima (see all the blue lines on graphs below […]