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lordnacho

Would it be hard for a climate scientist to present the numerical evidence in something akin to a Jupyter notebook?

So, something that says

"Here's how we collected the data, and here it is"

"Here's some transformations on it"

"If we're right about xyz, this bunch of statistical tests will turn out like so..."

I tend to give the experts the benefit of the doubt, also on this issue. But everything I hear in the media is simply "consensus" vs "conspiracy".

I actually would like to understand how the data works, and how the models work.

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The problem with presenting data is that you have to be an expert (e.g. a climate scientist in this case) to thoroughly understand the techniques and assumptions used in the models. The average citizen, who is no doubt quite intelligent, isn't going to understand that stuff and certainly isn't going to put their life on hold to learn it. We need to look at the big picture here: society needs to trust science to get this stuff right. Or at the very least, we should all be asking ourselves "who benefits from the policy that this person is advocating?". The answer that we should accept for that question is "everyone", not "energy company shareholders".

> We need to look at the big picture here: society needs to trust science to get this stuff right.

Why do we trust in mathematical proofs? Answer: because one (theoretically) doesn't have to trust authorities, but can check the proof oneself. The same holds for results from empirical sciences: They can be falsified and lots of experiments have been done with the intention to falsify the theories and failed.

By the way: This is also a strong argument for open access (because parking scientific results behind paywalls makes this really hard).

Thus science is not about trusting authorities, but about being to verify yourself (structural sciences) and all. In other words: Science is about distrusting authorities and verifying/falsifying yourself.

That's beside the point --- the argument above is that most people do not have time to obtain the expertise and check it yourself. So the next best thing is to trust someone who has done that, where you can't do much better than to trust consensus.

If you don't have the time to obtain the expertise one can still do good checks (only not in the details). For example if we are willing to accept the correctness (in some formalized sense) of a statistical test, we can still check whether it was applied correctly (or alternatively you can accept that it was applied correctly and try to understand the proof details behind the statistical methods). This way you will surely not get a complete understanding, but neverthess can check parts of the chain of conclusions and falsification attempts.

I agree for the most part. The problem is that the science that needs to be done to verify/falsify results requires a lot of knowledge. We cannot reasonably expect every citizen to have that knowledge. If they did, we wouldn't have this problem. (We'd have other problems, like who's doing all the other jobs now that everyone is a climate scientist?)

Your point about open access is very much on the mark, though. The society I want to live in is one that trusts science, and making all research freely available would, I think, greatly improve the general public's attitude even if they themselves cannot understand that research.

It doesn't work that way. Climate change is so politicised that pretty much every source of information is biased. It is impossible to get a clear picture. Politics is absolutely toxic to science. Many people would like to establish something like a world government by leveraging issues like climate change. Even though we really have no idea about the severity and magnitude of the problems ahead of us. I personally think scientists are exaggerating massively; here we have climatologists who cannot even predict correctly whether it rains next week, yet they make predictions about how in 20 years the climate is such and such.

Climate is not weather.

"World Government" is an utterly crazy conspiracy theory.

Climate is not weather.

Clearly you have no idea how modeling works and how similar such computer models for weather and climate are (usually splitting up the area in smaller parcels or a volumetric approach and running equations on them in parallel). Unless the scientist is really dumb and just extrapolates arbitrary temperature data points with a polynomial of degree 1 (aka a line) to predict the climate.

"World Government" is an utterly crazy conspiracy theory.

Look at governmental bodies like the EU that spread and grow like cancer. It is obvious that in today's world, more than ever, there are strong forces in play that want to centralize power. It is a fact that climate change is already used to push regulations onto people by unelected governmental bodies.

> here we have climatologists who cannot even predict correctly whether it rains next week, yet they make predictions about how in 20 years the climate is such and such.

Consider observing a forest road in an area with lots of rabbits. You can't accurately predict how many rabbits will dart across the road in the next hour, but you can — based on long-term observations — predict roughly how many rabbits will cross that road in a year, and based on the empirical evidence of bunnies counted conclude that the number furry creatures moving from one side to another is increasing or decreasing.

Symptoms versus trends. The latter can be predicted with some degree of accuracy.

You raised a good example with rabbit population. Consider this:

http://fractalfoundation.org/OFCA/predatorprey.jpg

Nobody would ever dare to fit any of the two populations with a straight line, yet they do that with temperature data with barely any explanation for the choice of a linear function.

Read and understand the IPCC reports, and then we'll talk.

Thank you, I will.

For those who are interested:

https://en.wikipedia.org/wiki/IPCC_Fifth_Assessment_Report

http://ipcc.ch/report/ar5/

Averages (climate) can be much easier to predict than particular values (weather). As a mathematical analogy, we cannot predict accurately whether flipping a fair coin is going to come up head or tails, but we can predict that if you flip it 1000 times it's going to be between 450 and 550 heads with 99.8% probability.

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