Climate Change in Australia

BC doesn’t speak for me. I highly appreciated your response, HM, both your time & the content. Looking forward to further reading. Cheers.


Sorry mate, I probably got a bit fed up with HM having to repeatedly sacrifice enormous reserves of time and thought addressing similar subjects over and over, often at the request of utter dolts. Anyone accusing him/her of ‘dodging’ a question may not have read much back into the thread. Glad you’re interested.

The most likely commercial approach for Australia with Nuclear would be to pay experienced companies to design and build the plant. The new nuclear plant planned for the UK is being designed and built by EDF (mainly state-owned French Company) and CGN (state-owned Chinese Company).

Hinkley Point is not an example the nuclear energy lobby will be pointing at as an example. Already running at double its proposed budget, currently guesstimated to be operational in 2027 which is NINETEEN years after construction started, and you can bet there’ll be further delays & cost overruns before the thing so much as turns a lightbulb on. And it’ll supply power at double the cost of renewables. And they still don’t know what they’re doing with the radioactive waste long term, despite having had since the 1950s to think about it.


Did many people watch QandA last night?

Rightio, part 2. Let’s all gird our loins (or someone’s loins, anyway…) and sally forth into the next section of Mr Macrae’s masterwork…

In part 1a of his ‘observations’ we have a graph. This graph shows that, since 1982, the rate of change over time of atmospheric co2 measurements from the Mauna Loa research station in Hawaii has closely resembled the .variation in global temperature.

A couple of red flags here. First - why only since 1982? He doesn’t say. We have data going much further back in time than that. Arbitrarily ignoring huge amounts of data with no explanation is not a good sign.

(His choice to use Mauna Loa as a proxy for global co2 is more defensible - Mauna Loa is often used in this way as it’s a long way from any significant source of artificial co2 emissions so measurements there won’t be too biased by local conditions)

Second, why is he only looking at the rate of change of co2 over time? Why not just use simple co2 measurements? He doesn’t explain (a big red flag - making decisions like this with no explanation as to why you’re doing it), but I have a suspicion as to his real motivation that I’ll go into in more depth later.

In part 1b, and 2a, 2b, 2c, he presents a series of graphs that demonstrate that, for the above data, fluctuations in temperature are followed, about 9 months later by similar-sized changes in co2. This is all a lot of graphs to make the same point. Though I will say, I wish the guy would settle on a single graphing standard! Sometimes he uses raw data, sometimes he uses a 12 or 13 months running average to smooth out seasonal variations, sometimes he goes back as far as 1960 but then he’s back to 1982 again, he uses at least three different measurment sets for global temperature at different places and switches between them with no explanation as to why … urgh)

Anyway, here’s another of our red flags. In this section he actually has two references(!) One is … himself. Modest type, isn’t he? The other is one of the very few published peer-reviewed scientific articles referred to in this paper. It is by a Norwegian by the name of Humlum, and was published in the scientific journal Global and Planetary Change, issue 100. So, back to Google! Humlum’s main source of scientific significance seems to be his papers being bad enough that they were disproportionately represented in a recent study that re-examined past climate denial scientific studies ( and found that the vast majority of them made mathematical mistakes or cherrypicked their data to predetermined solutions. The journal Global and Planetary Change seems to be a distinctly minor journal best known for a 2017 scandal in which they published a climate denialist paper even though a majority of the experts they asked to peer-review it said that it was garbage and should be rejected ( So it’s worth remembering that with all the expertise in the world available to him here, Macrae is choosing to reference himself, and a guy who is principally famous for being wrong all the time and is publishing in a journal that breaks its own rules to give climate deniers a hand up. And once again, remember our dinosaur guys yesterday? 116 references for a paper that basically said ‘i found dinosaur bones and this is the sort of dinosaur I think they belonged to’. Compare and contrast the depth of research and intellectual rigour that went into that, compared to this.

Ok, enough of that digression, let’s move on again. What Macrae wants everyone to take from this is that changes in atmospheric co2 follow temperature changes by around 9 months. Let’s remember that.

Now we have more graph spam. 3a, 3b, 4a, 4b, 5a, 5b, are all graphs that all graph the close correlation between sea surface temperatures in the Equatorial Pacific Ocean Nino34 Area (which is basically the area of mid-Pacific 5 degrees on either side of the equator), and the rate of change of co2. Triumphantly, in section 6, he announces

The sequence is Nino34 Area SST warms, seawater evaporates, Tropical atmospheric humidity increases, Tropical atmospheric temperature warms, Global atmospheric temperature warms, atmospheric CO2 increases (Figs.6a and 6b).

Picture, if you will, Galileo, the great astronomer and symbol of the brave scientist championing hard facts and observations about the world, against a hidebound an superstitious authority that persecutes him. Macrae fancies himself as a Galileo, I think (or else it suits his purposes to pretend to be one)

However, in reality, what’s happening is something like this:

Galileo(/Macrae): hark, and heed to my genius, for I have discovered that the earth revolves around the sun!
Assembled crowd: [gasps in awe and shock]
Galileo: See, my calculations, my observations, my many, many rather poorly-illustrated graphs! The truth is undeniable! What do you make of THAT, oppressive establishment?
Oppressive establishment: um, well, you see, there’s a little bit of a problem with this…
Oppressive establishment: The problem is, Mr Galileo, that it’s 2019. We’ve known the earth revolves around the sun for hundreds of years. You’re not wrong, you’re just … late.
Galileo: well also my research proves that the moon is made of green cheese and the sun is was formed when the invisible space dragon Blorblesnitch used its flaming breath to light its own farts.
Oppressive establishment: … you know, I think we’re done here.
Galileo: wHY WOn’T YOu dEbATE ME??!?

Macrae’s revelation/discovery/whatever is not revolutionary. It’s not even new. This has been commonly-accepted scientific knowledge for a long long time. When temperatures increase, seawater releases some of its stored co2 into the atmosphere. Where Macrae fundamentally gets it wrong is that having identified this fact, he decides that he’s found the One True Answer and everything else is wrong or irrelevant. I’ll talk a bit more about what he’s neglecting next episode, today I’m just going to try to get through to the end of his ‘observations’ section.

Anyway, let us plough on. In section 7, Macrae presents two tables to support his argument that the temperature at the Nino34 area varies as a sine function with a period of 3.1 years, and which causes a similar variation in atmospheric co2 about 9 months later. This really is the crux of his argument. He is arguing that global co2 fluctuations are caused entirely by the temperature conditions in the Nino34 area.

There’s so many red flags waving here that I keep wondering if it’s Stalin’s birthday or something. Here we go…

Red flag number one - if he’s being so scientifically rigorous, why does he go straight to Nino34 as the source of everything? How is he so confident that this particular area is the root cause? Why Nino34 and not Siberia, or Madagascar, or the GUIK gap, or the South China Sea? There’s no mathematical analysis as to which region’s temperatures match co2 changes most closely. He certainly doesn’t bother looking anywhere else in the world, nor does he offer any possible scientific reason as to HOW exactly this particular bit of sea wields so much influence over the rest of the world. That’s always the problem with leaving the science behind and just focusing on the maths when it comes to stuff like this. Correlation does not necessarily imply causation, as anyone who’s ever looked at the Spurious Correlation Page would know full well.

This is one of my favourites

Nino34 is a relatively well-known dataset, because in the short-term (a few months) it has some value in predicting whether there’s going to be an El nino cycle (with attendent droughts etc). It’s marginally possible that Macrae chose Nino34 for that reason I suppose (he could have mentioned it, if this were the case though!) but frankly I suspect it was chosen because it’s an equatorial data set. Global warming is affecting temperatures on the equator much slower than it is temperatures at the poles. If Macrae had chosen an arctic data set, in the 1982-2019 time window he’s chosen, he would have had to explain THREE DEGREES of warming in that time.

Ok, next red flag is the sudden introduction of the sine wave concept in section 7a. Macrae is obviously trying to express temperature variation over time as an equation here. But again, he makes a wild leap of logic straight to ‘sine wave’ without explaining HOW he decided the sine wave was relevant. Did he consider there might be a linear or polynomial component? Or a damped exponential maybe? Regression curve fitting (the creation of a mathematical formula that fits a collection of data as accurately as possible) is a much of an art as it is a science, but there ARE techniques available (basic r-scores if nothing else) to help out. Macrae uses none of them, but goes straight to his sine wave. And I suspect that it’s because he WANTS to see a sine wave, because a sine wave is cyclical - what goes up will come down again the same amount, nice and predictable if you wait long enough. See below, sample sine wave.

Next red flag for this section is table 7a (especially when you combine it with 7b!). 7a is a lesson in the hazards of averages. After going to a great deal of effort to tell us how sine waves are perfect and regular, Macrae triumphantly presents us with a sine wave with a period of 3.1. Or, if he was honest, a period of 3.1 +/- 50% A real scientist would laugh at a dataset of only ten data points having a 50% error bound, that’s basically saying ‘if these two values are related in any way, it’s only through coincidence’ There’s whole fields of maths to do with this stuff, statistical significance analysis etc. I’m no expert on them. But they’d sneer at this. And his lag data is just as bad. There’s the old joke about averages - Bill Gates and ten hobos walk into a pub. On average, everyone in the pub is a billionaire. Averages (without the qualification of expected error/uncertainty bounds, variances etc) are the bluntest and clumsiest of statistical tools, and no reputable scientist would use them like this. Even our dinosaur guys from last episode had more mathematical rigour.

Next red flag - 7b. Macrae seems to have understood how dumb 7a made him look, so now he tries to walk back on it by splitting his data set in half at 2003 and fitting different sine curves to the two halves. Again, we have his problem where he tortures the maths until it fits but pays no attention to the actual science behind what his maths is trying to describe. Back at the start of section 7 he was telling us about how all this is a natural cycle, and now he’s implying that the natural cycle changed wildly in the middle of 2003, without offering any explanation about WHY it did this? And of course, now his two different sine curves have even fewer data points, but as we’ve already established, Macrae thinks that statistical significance is something that happens to other people.

Ok, final red flag. In the spreadsheet he links to (yes, I downloaded it and read it and now my brain is in a puddle on the floor, I hate you all a little bit right now :stuck_out_tongue:) he seems to have realised how dumb both 7a and 7b made him look, and so he quietly chucks them out and has a third try. In this one he (sigh) runs a fourier transform over the input data.

Now, for those who are not aware, a fourier transform breaks down any graph, of any shape, into a combination of different sine waves. You can create a fourier transform of ANYTHING, hell, I believe the digitising/compression of music uses a fourier transform. It’s a powerful tool, and it can digitise a symphony it can certainly handle Macrae’s crappy little graph. But powerful tools are dangerous to the foolish, and Macrae with a fourier transform somewhat resembles a small child merrily playing with a chainsaw. First big mistake is that he forgets (or doesn’t know, or chooses to ignore) that fourier transforms are descriptive, not predictive. They can efficiently tell you what your graph looks like based on the data you feed them, and they can sometimes help you identify individual components within your data, but they cannot be used to predict the future (no matter how well you digitise beethoven’s 9th symphony, it’ll never tell you what his 10th is like!) Second is that fourier transforms are really bad at dealing with long-term trends, especially when you’ve got, for instance, only 36 years of climate data and are trying to use it to generalise over the next hundred. And that’s just a limitation of the method - fouriers assume that everything can be described as a combination of sines. In reality, this is not true - and most of the time it doesn’t matter, when the user is aware of this limitation. Have a look below. If the black dots are your data. and you run a fourier analysis - your fourier analysis will always give you the blue line, and never the red. But this may not be the right answer! Again you need to understand the scientific concepts behind what you’re trying to analyse before you start throwing maths at it. Or, in the case of Mr Macrae, if you know you want a relationship that’s cyclical in time, and you definitely DON’T want to see things like a long-term increasing trend in your temperature data, then a fourier transform just might suit your purposes…

Ok, I’m going to call it quits for the night there. I didn’t nearly cover everything I wanted to today, This article is an absolute proof of the old saying ‘a lie can go round the world before the truth has got its boots on’ - by the end of this, I’ll probably have spent more time analysing this crap than Macrae spent writing it. God this is tiring. Anyway, I managed to step through his observations piece by piece and address them fairly closely, but the flaws in this article are as much in the big picture and what it doesn’t say as much as the minutae of what it does say. I’ll try to have a look at that tomorrow, then start to cover the rapidly-accelerating-towards-the-horizon lunacy of the ‘Discussion’ section later in the week.


Simply awesome.

Can’t wait for the next part.

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Now, that’s the way to critique an article/paper. Brilliant stuff, HM. Looking fwd to your next installment. Cheers.

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That is as scary as ■■■■

Our kids are going to live in a world utterly unrecognisable to ours, and not in a good way :frowning:

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Oh well, … all those working hard to prevent any action will make Billions out of it, so … you know, all good. :+1:

Fantastic write up earlier, read every word.

This article has been doing the rounds on social media. Absolutely terrifying.

I didn’t read the article so I don’t know if they mentioned that permafrost melts mean that there will be huge methane emissions, especially over the entire Siberian region.

Methane is of course a worse greenhouse gas than CO2.

This could well set up runaway greenhouse.

But as BSD says, as long as rich barstards make even more billions, what is there to worry about?

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34 times more potent IIRC, however only lasts 10 years or so. Not that we have 10 years.

Time to invest in giant floating algae farms.

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Part 3 will be delayed til probably Friday, as tonight I’m having back spasms and hunching in front of a laptop is not helping, and tomorrow instead of spending time with Mr Macrae, I’m having dinner with my mum :slight_smile:

And in addition to the greenland melt article above, it’s worth mentioning that, amid a 48C heat wave, the sixth largest city in India (population a lazy 11 million) has now emptied all four of its water storages.

The future is here. We really have to start being grown up about this stuff, or in 20 years we’ll be dealing with the collapse of mass agriculture and half a billion climate refugees.


Scumo and his gang think:

Half a billion??? Great - just think what that will do to property prices!1!!1! And how much more we can give to our mates with the Kangaroo Island/Singapore/Cayman Islands companies to house all them refugees.

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Great stuff. Hope I don’t cop you as a reviewer, lol (unlikely, as we’re in very different fields)

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Thanks for your analysis HM. It’s quite eye opening. I’m very much a fence sitter on this issue and it’s great to be treated to some in depth thoughts rather than the biased extremes we see in the media.

No disrespect hambo, but what does “very much a fence sitter” mean ?

I can understand some being a tad sceptical about some of the climate change claims, but not the big picture, as it does seem beyond dispute.

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Sitting on fences is good if you have an itchy bum, maybe he’s got worms?

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