The average of a decreasing trend extrapolated as an exponential growth in the future

While writing previous post, I got intrigued by the graph representing the electricity generation forecast until 2032, especially that yellow line representing the exponential growth of solar PV and wind. To recapitulate, this is the graph I am talking about:

The authors claim that this graph represents:

Current world electricity generation trends, extrapolated to 2032

They also state that the growth rate of solar PV was 28% and that of wind was 13% between 2012 and 2016. The yellow line, being a combination of solar PV and wind, will be somewhere between those two values.

The suggestion is that this growth of solar PV and wind is somehow established between 2012 and 2016, therefor could be used to extrapolate future values that give rise to that exponentially increasing yellow graph line. I wondered whether such trend really could been found between 2012 and 2016, so I looked at the values of electricity generation that I used for previous post:

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Solar PV and wind are on track to replace all coal, oil and gas within two decades (define “all”)

Solar PV and wind are getting so cheap and more abundant that they are on track to entirely displace fossil fuels worldwide by 2032. This remarkable claim is made in The Conversation article titled Solar PV and wind are on track to replace all coal, oil and gas within two decades.

It is a remarkable claim because the last figures that I found show that solar PV plus wind generated only a tiny fraction of total energy compared to fossil fuels. So I would doubt that solar PV and wind suddenly could replace all coal, oil and gas in just a couple decades. Two decades seems like an awfully short time to go from (almost) zero to hero.

That made me really curious about the principle behind this claim. To clarify their case, the authors showed two graphs. This is the first one:

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Finding unprecedented high resolution values in a low resolution dataset

In previous post, I discussed a graph that suggested that the CO2 and CH4 levels in the atmosphere are unprecedented in the last 800,000 years and proposed that it is misleading to compare high resolution data with low resolution data. After I published that post, I wondered whether I could illustrate this with an example. It should be possible if I had some detailed dataset. Then I could make a detailed graph, see how that looks like, then sample this dataset in the same way as a proxy dataset and again make a graph. Comparing both graphs should make clear what the effect is.

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The good old times when carbon dioxide and methane levels as well as temperatures were low

The previous post was about “the most popular contrarian argument” according to skepticalscience (“climate changes before, so current climate change is natural”) and what they seem to consider a live example of such a claim. I then proposed in that post that it actually was not a good example of what they want to prove.

What I didn’t discussed yet was how skepticalscience “debunked” this most popular contrarian argument. They did this in the “Climate’s changed before” myth page that was apparently based on this example.

They “debunked” this “myth” by stating that the climate is indeed always changing, but the difference is that it is changing much faster now than in the past because of our increasing emissions. This is how it starts:

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The pitfall of Cook’s “simple” six-step critical thinking process

There is this statement in the introduction of the Cook et al 2018 paper that caught my eye:

This paper introduces key critical thinking concepts and outlines a straightforward process for identifying reasoning errors that allows for people who lack expertise in climate science to confidently reject certain denialist arguments.

In a way, I can understand what they are trying to do. Just before I started blogging, now five years ago, I had the idea to look somewhat deeper into logical fallacies. At that time I wasn’t familiar with the global warming debate and it was my hope that I could find a fast and easy way to differentiate between right arguments and wrong arguments, without having to put much effort in studying the topic. However, it didn’t take very long before I realized that for some type of fallacies this would be perfectly possible, but not for most. If I wanted to know right from wrong, then I had to dive in the arguments themselves.

So although I think that their effort is praiseworthy, in practice it is not black & white. My conclusion back then was that when one wants to confidently confirm or reject an argument, then one needs to get messy and go to the source and understand what the argument is all about. I would certainly not put my bet on the knowledge of logical fallacies alone. Without some background, it could lead to possible misinterpretations.

This became rather clear in the page on the SkepticalScience website that was devoted to the Cook et al paper. The post is titled Humans need to become smarter thinkers to beat climate denial and John Cook is a co-author. At the beginning of the post, they basically repeat the statement from the paper in a slightly different wording:

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Define “AGW”

Spread over the Cook et al 2018 paper are the terms “anthropogenic climate change” and “anthropogenic global warming”. It is also mentioned a in table S2 of the supplementary material. I assume that “anthropogenic global warming” means that global temperatures are rising and humans have an impact. This seems to be supported by the consensus claim from the paper (my emphasis):

There is an overwhelming scientific consensus that humans are causing global warming (Cook et al 2016), with a number of studies converging on 97% agreement among publishing climate scientists or relevant climate papers (Doran and Zimmerman 2009, Anderegg et al 2010, Cook et al 2013, Carlton et al 2015).

That is a far cry from the previous statement in the Alice in Wonderland paper. In that paper, the claim was made that there is a consensus that global warming “presents a global problem”. A claim that obviously was unsupported by the papers that were referenced.

At least he skipped the “dangerous” part of the claim. It is now in line with what the referenced papers researched. As explained in the link above, the referenced papers investigated the claim that global temperatures are rising and that humans have an influence in this. Not whether it is dangerous. Not whether something should be done about it.

However, I don’t think that the term “AGW” is used in this way in the paper. This sentence in the abstract makes me think that he means something different (my emphasis):

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Decreasing demand for natural gas power thanks to wind and solar?

At the beginning of this month, I found an article in a Flemish newspaper that seemed to be inspired by the gas deficit alarm from the UK National Grid. It was titled “Renewable energy gets us though the winter cold”. This is how the story goes: the very cold February of this year did not result in record natural gas consumption. We used less natural gas in February 2018 than six years ago in February 2012. The demand for natural gas from households and industry stayed more or less the same. The difference was the demand for natural gas for electricity production, which was lower in 2018 than back in 2012.

Conclusion of the article: there was no record natural gas consumption in February because renewable energy grew in the last six years and this increased share lowered the demand for natural gas power. Because of this, we currently don’t need as much natural gas than we would only six years ago and there was no shortage in our country.

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