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Climate Change – It’s Complicated, But It’s Real

I was recently invited to provide a response to an opinion article on climate change that was offered to “The Punch” website. 

It seems that many of the commenters on The Punch website thought I was being patronising or pontificating. Maybe I was, but how else to answer such a “it’s all too hard” complaint? As one of the others commenters noted: “If wishes were horses, beggars would ride”, i.e. just wanting for simple answers and consistent outcomes won’t make them so. Anyway, see what you think… The lead article can be read here: It’s just too hard to understand climate change. My response, reproduced below, should be read with this context in mind.

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Dylan Malloch laments that understanding climate change is difficult, with the forecasts sometimes appearing to be contradictory or having a bit both ways, and therefore seeming all rather confusing! It’s easy to sympathise with him. Unfortunately, this is the nature of science.

Let’s consider another example. Newton’s laws of physics work just fine for the everyday world, but if we tried to use them in the timing system of our global positioning satellites, the resulting drift error would be about 10 kilometres every day.

So, the engineers at GPS mission control need to use Einstein’s relativistic theories to make sure your iPhone tells you precisely where you are, whenever you want to know. Similarly, neither Newton’s or Einstein’s equations allow scientists to properly predict the subatomic interactions within the electronics of satellites or iPhones. For that, you need to reference the weird world of quantum mechanics.

Each of these model systems – Newtonian, Einsteinian and Quantum physics – produce some contradictory predictions, and gaps in understanding remain. The theories have not yet been unified, for instance, to the lament of Einstein and his successors.

Yet the vast majority of us – the average Joe and Josephine Public –  are not confused or worried about GPS and iPhones, for the simple matter that we don’t try too hard to understand how they work. After all, it’s plain enough to our eyes, immediately and incontrovertibly, that they do! So we just accept it, like we do for most forms of technology.

Climate science is now treated rather differently, however. This is because although the stochastic and chaotic systems involved are, in their own way, just as complex as relativity and quantum theory, many people just don’t want to take the underpinning science and evidence for granted.

They WANT to know and understand this stuff (which is good, from a science education perspective), and their motivation usually comes about because they feel threatened by it, or guilty about it, or whatever. Dylan’s example of not wanting to be responsible for suffering poor people underscores the point.

Yet, at its core, much of the maths, physics, chemistry, models, theory, and so on, which together make up the many fields of climate science, can be really difficult stuff. It takes a lot of learning time, and lots exposure to the many lines of scientific evidence and the general practice of doing science and dealing with uncertainty, to appreciate the complexities and nuances involved.

So when people don’t ‘get’ the science and are left confused by media sound bites, it’s typically because they haven’t got the time, experience or training to really grasp the interconnections, feedbacks and apparent contradictions.

The other obvious problem is that climate model forecasts are not tangible and deterministic – unlike the GPS or iPhone, there is no simple, repeatable test of whether they ‘work’ or not. Climate change is also not being painted on a ‘blank canvas’ – extreme weather has always been with us, for instance, so how to tell what can be attributed to natural versus human-caused effects?

It’s tough, no doubt about it, and there is a huge scientific effort dedicated to identifying the ‘fingerprints’ of human activity amongst the many ‘smudges’ caused by ever-present natural influences on weather and climate.

Imagine, for example, that you wanted to safely cross a busy road, and there were 20 cars going past you every minute (natural events). Then, a traffic signal somewhere up the street failed, and started to let more traffic through (climate change), such that there were now 30 cars whizzing past each minute.

You step out on the road and are unfortunately hit by a car. As you lay in hospital with your leg in traction, you wonder: was I hit by one of the original 20 cars, or one of the new 10? You decide that you can never know for sure, but having later been told about the circumstances, you realise that your risk of being struck went up by half because of the failed traffic signal that you didn’t even observe.

Analogies like this are always imperfect, but it might help you get the point.

So Dylan is left wondering how ‘global warming’ can cause more heat waves and droughts, and yet also be attributed to torrential down pours and flooding.

The simple answer is that you can have both, because more and more energy is being trapped by the Earth’s atmosphere as greenhouse gases accumulate, and the climate dynamics that result from this energy input is expressed in different ways in different parts of the world at different times. The full answer? Well, it’s complicated…

Barry Brook's picture

Thank Barry for the Post!

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Rick Engebretson's picture
Rick Engebretson on Feb 12, 2011 5:56 pm GMT

So you’re saying we’re just too stupid and lazy. Here’s some science.

One of the tools used in hydrogen exchange kinetics within protein was the gamma distribution. It fit the data nicely so others used it and they had (protein conformational fluctuation) theories galore. So I dug into the math for some real physics.

It turned out the gamma distribution was derived to calculate the result of a Poisson (improbable) distribution of improbable (Poisson) events. One application was, as military equipment became complicated with many parts, to estimate breakdown due to many possible sources. I used it to get a distribution of conformational fluctuation frequencies in the macromolecular protein. I got some hard numbers, tested EM and Ultrasound along with my assigned pressure. My goal was to figure out if protein (liquid crystal) configuration was addressable (like a computer chip on a bus). Then I got hired by an NMR lab that found the same frequency data by NMR dispersion.

My point is, human impact on the earth is real, we all see it. But to attribute it to atmospheric CO2 alone is poor science. Many improbable events can combine into large amplitude events of some frequency.

Well, I got out of that lab stuff realizing we needed more than endless theories. Pushed addressable fiber optic networking, etc. And now see liquid crystals opening eyes.

Many ways to approach a problem. Calling people stupid and lazy is least effective, and sure isn’t science.

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