In The Weekend Australian I wrote that many false claims are made about the state of our environment on an almost daily basis but because most Australians are illiterate when it comes to science and maths, they are mostly just accepted. My first example was eastern Australian rainfall and the claim that the east coast of Australia has suffered declining rainfall, a claim first made by Sir Nicholas Stern in his influential report to the British Parliament.
I explained that observational data on rainfall for the entire east coast of Australia is available from the Australian Bureau of Meteorology with yearly averages for all the sites back to 1900. But, contrary to the Stern report, this chart does not show declining rainfall; rather, it indicates that rainfall was very low in the early 1900s, that there were some very wet years in the late '50s and early '70s, and overall the trend is one of a slight increase in rainfall during the past 107 years, Chart 1.
Chart 1.
While I received many emails, phone calls and The Australian published several letters supportive of my analysis, there have been criticisms including the following comment published in The Australian, "A number of scientifically indefensible ways of presenting data are used in the “Case of the warm and fuzzy”. In each case the errors support the author’s conclusions... In two of the six graphs shown the data is fitted to a straight line which is claimed to show an upward trend in rainfall. What would happen if a non-linear fit (eg, quadratic) were used instead of linear fit.. Dennis Matthews, Ironbark, SA."
When I fit a simple quadratic equation to the data, it also shows an increase in rainfall over the 107 year period, Chart 2.
Chart 2.
But there is really no reason to assume that the rainfall data would be represented by any particular equation (linear or quadratic). These trend lines are unlikely to provide any insight into what is likely to happen next year because weather systems, like financial markets, are complex.
But interestingly, even fitting an 11 year moving average shows a trend of increasing, not decreasing, rainfall, Chart 3.
Chart 3.
My advice to those trying to interprete data presented graphically would be to use what Professor Harry Roberts, University of Chicago Graduate School of Business, has described as the world's most powerful statistical analysis tools - your eyes. What can you see from the squiggly line, Chart 4?
Chart 4.
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Hat tip to MR for the Harry Robert's advice.
[...] My Oz friend Jennifer Marohasy has this discussion of Eastern Australian rainfall from 2008 and offers this graph, not the 1974 peak. When this graph is updated with the latest rainfall data, [...]
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With thanks Michael Blundell
The most disturbing feature of this data is not the peaks and troughs, rather the length of time between the peaks and troughs. the waves are spreading out, which if these graphs represented like a heartbeat would cause someone to become lethargic and itchy due to oxygen deprivation. The earth needs water as it's lifeblood... use your quadratic on this concept and one can plainly see the earth is suffocating.
Bernard,
"You are continuing to conflate DIFFERENT parameters."
Au contraire - I know exactly the games being played by the warming crowd. They argue that 0.5C per century is going to kill us all. I say, that's garbage.
"Taking your logic to its end the scale of the graph should be -90ºC to +60ºC."
Graphed on such a scale, it would be completely apparent to everyone that there was nothing to worry about and that global mean temperature is what it is: essentially, a flat line. Why do you think the warmers continue to plot the y axis, with no reference to the daily fluctuations the earth copes with admirably?
"When we interogate a dataset of annual global mean temperatures, which is, after all, a proxy for how warm or otherwise the planet has been over each annual increment, we are interested in the change to these annual means. The various maxima and minima are irrelevant to this interogation..."
As an abstract statistical exercise, maybe. Outside of that, in the real world, where real world temperature ranges occur every single day, in no way are minima and maxima irrelevant. In fact, as I noted in my post and you studiously ignored, a rising mean temperature tells us nothing about whether that derives from increased maxima, minima, or from a change in the skewness of the distribution.
And, here's the secret, Bernard: as a committed warmer, you'll never know the answer to this question, because actual temperature ranges repel you; you are only interested in focussing your electron microscope in on the mean.
Listen to the warmers and we only have linear trends, bell-shaped distributions and zero sampling error. Were that actually the case, you might have some (and only some) argument for shining such a bright light on the mean, alone. It is not and there is no justification for removing the real world context from graphs of the mean's behaviour.
Apologies for the misplacement of TheWord's name to the authorship of the 12.07am post. My laptop's display driver is dying and the screen superimposes different part of the page as I scroll, so the first line of the message text ended up in the name box.
That post should be attributed to me.
When we interogate a dataset of annual global mean temperatures, which is, after all, a proxy for how warm or otherwise the planet has been over each annual increment, we are interested in the change to these annual means. The various maxima and minima are irrelevant to this interogation, especially as any change to the global annual means is going to come almost exclusively from values that fall between the maxima and minima anyway.
Can you not get it through your head that an instantaneous maximum LOCAL temperature or an instantaneous minimum LOCAL temperature has no direct comparable relationship with an annual GLOBAL mean temperature, and that the consideration of localised maximum or minimum is a DIFFERENT kettle of fish to the consideration of an ANNUAL GLOBAL trend?
They are different parameters. In considering mean annual global temperature trends the maxima and minima in any one year are irrelevant. They are relevant if one considers change in maximum temperature, or change in minimum temperature, and then you would construct separate graphs to display the trends in these separate paramters.
Tell me, if you were going to describe the variance in annual mean global temperature, what values would you use to do the computation? Or let me put it another way - if you were going to plot the variance in the average global anomaly, what data would you use? Do maxima and/or minima for a single location on a single day during any year come into it?
Taking your logic to its end the scale of the graph should be -90ºC to +60ºC.
And finally, you can change the scale to give you a nice flat-seeming line, but it won't alter the results of appropriate statistical analyses. The scales that I and most of the rest of the scientific world use simply best reflect the statistical characteristics of the particular parameter being considered.
You are continuing to conflate DIFFERENT parameters.