One of the things making wildfire/bushfire worse, contributing to the current conflagration in Australia, is the increase of daily high temperatures. It increases the Vapor Pressure Deficit (VPD), the difference between how much water vapor the air can hold and how much it does hold. When VPD is high, it can suck the moisture right out of potential fuels big and small, which increases the frequency and severity of fire dramatically.
The data are clear, that for daily high temperature last year (2019) was the hottest on record for Australia:
It started with the summer of 2018/2019, hottest in Australia’s history (summer being December-January-February):
The new summer is off to a roaring start, December 2019 bringing another of the all-too-common record breakers, this time a giant:
Australia has been hot, hotter than ever before in history.
Jennifer Marohasy disagrees, saying that “It has been hotter, fires have burnt larger areas”. She blogged about it last March, claiming “Hottest Summer in Australia was 1938/1939”. Her evidence? This:
Retrieving data for Rutherglen (near the border between the states of Victoria and New South Wales) and computing its average high temperature each summer, I got this:
That’s definitely not the same as Jennifer Marohasy’s graph, and the hottest summer is definitely last summer (2018/2019).
The data I used are the ACORN-SAT data for Rutherglen from Australia’s Bureau of Meteorology (BoM). The BoM has, in my opinion, assembled the best national temperature data in the world because they use the most advanced methods to correct for known problems, like moving a recording station to another location or installing a new instrument. The process is called “homogenization” because its goal is to create a temperature record which reveals what happened other than those things irrelevant to climate (like moving the station or changing the instrument). They also use advanced methods to detect such discontinuities; the BoM really does an impressive job. Australians should be proud.
Some people hate homogenized data. They loathe it, maybe even fear it, often slander it; you might even think they’re homophobic. Jennifer Marohasy despises the homogenized temperature data from Australia’s BoM, and often criticizes it. She also implies that the whole process is some underhanded scheme by the BoM. My opinion: the reason she so hates the homogenized data, is that it so clearly shows the heating overtaking Australia. Just my opinion.
Anyway, she insists on using the original raw data, even when we can prove that it’s tainted by non-climate factors and the homogenized data are better. So let’s use the unadorned, unimproved raw data instead and get this:
Well, that’s embarrassing for Jennifer Marohasy. Even using the raw, unhomogenized data, the hottest summer on record is still last summer, 2018/2019.
Now a most fascinating plot twist: to make the 1938/1939 summer Rutherglen’s hottest on record, Jennifer Marohasy killed everything after the 1997/1998 summer. If last summer was too hot — just get rid of it. Fugettaboutit.
She removed it on the pretense that after the 1997/1998 summer, they changed the instrument, no longer using a mercury thermometer. My opinion: that is one of the most lame excuses for deleting the data you don’t like, that I’ve ever heard. And I’ve heard a lot. Just my opinion.
Anyway, I can make a graph very similar to hers, but it’s revealing how many hoops I have to jump through.
First, I have to limit myself to only one location. The subject (according to Jennifer Marohasy) was the hottest summer in Australia. Obviously it’s better to use a composite based on a large number of stations which cover most of the continent, like the BoM has done. But if you want to say the hottest summer in Australia wasn’t last summer you might prefer to look for a single location.
Second, I can’t use the best data. The homogenized data, from ACORN-SAT, really is the best we have. It’s not perfect, nobody claims it is, but the raw data have some obvious problems that we can improve. If you want the wrong impression, use the wrong data.
Third, I can’t show the data up to the present, or even after 1998, because even the unimproved raw stuff shows how wrong Jennifer Marohasy is. It has to be 1998 because that’s timed with the excuse Marohasy uses to whack that data, and lame though it may be, it’s the best she could come up with.
Final result: a lot like her graph:
Rutherglen makes an interesting case for the homogenization of temperature data. Let’s look at the original, raw data and see how Rutherglen compares to its neighbors.
I retrieved daily high temperature (NOT homogenized) for Rutherglen and for 25 nearby locations, which I used to form a composite average for the region. Then I computed the difference between the value at Rutherglen, and the composite regional average. Here’s what I got:
Since it’s daily data, there’s a lot of it. I looked for sudden “jump discontinuities” using changepoint analysis (it’s what changepoint analysis was designed for). I was able to identify four “change points” with such strong statistical significance that they aren’t really in doubt. Furthermore, the data show a distinctly different average in each interval between changepoints. Here they are, with changepoint times shown as dashed vertical lines, averages shown as horizontal lines, and for the data I’ve plotted monthly averages rather than daily just so the graph won’t be so crowded:
The result is that right off the bat, by the most basic and reliable of methods (compare station data to that of its neighbors), I’ve identified four times at which we really should change the data baseline to remove non-climate factors. Assuming, of course, that we want the data to be better.
What did the BoM do with the Rutherglen data? Here are yearly averages of the difference between the original raw data, and the homogenized data for Rutherglen:
Notice the vertical dashed lines?
In cases like Rutherglen, the non-climate factors introduced a false cooling trend. It should be cancelled — assuming, of course, you want the data to be better.
Few people appreciate just how advanced are the methods that the BoM uses to homogenize data, or how many tests and critiques it has withstood. When I say that in my opinion theirs is the most advanced in the world, I base that on years of experience as a scientist and statistician, and on close examination of the methods used by many organizations. The insulting, accusatory rhetoric of far too many climate deniers might not be a crime, but it is a sin.
And I really meant it when I said that when it comes to their Bureau of Meteorology, Australians should be proud.
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