Comments DeepishThought has made
Chaos & Climate
"The ocean-atmosphere climate system is certainly a complex system, and capable of some surprising behaviors, but there is no evidence that it is chaotic in the formal sense."
Interestingly, the link embedded in this comment leads to a Wikipedia article on chaos theory that actually includes the following comment:
"Everyday examples of chaotic systems include weather and climate."
The idea that the climate, "is an inherently chaotic system, and as such its behavior can not be predicted." is important and needs to be addressed, but your article could clearly use some work.
I would try something along the lines of:
The scientific term 'chaotic' has a very specific meaning. The behavior of chaotic systems are not unpredictable or random. Chaotic systems develop in a deterministic way and are therefore, in principal, totally predictable.
In practice however, chaotic systems are very difficult to predict because their behavior is extremely sensitive to their initial conditions. Make a slight error in measuring the initial conditions and observed behavior tends to depart very rapidly from predicted behavior.
The atmosphere is the classic example of a chaotic system, which is why predicting the weather more than a few days in advance is so frustratingly difficult.
However, if we were able to precisely measure the current state of the atmosphere and we fully understood all rules governing its development over time, we would be able to perfectly predict the weather.
As it happens we can only roughly measure the current state of the atmosphere and we don't fully understand all the rules that govern its operation. However, this does not mean that weather is completely unpredictable. Our approximations are good enough that we can make usably accurate predications over limited time horizons.
This leads to the obvious question, if weather predictions are next to worthless more than a couple of weeks out, how can we seriously make predict climate decades or even centuries in advance?
The answer is that 'climate' implies a much less specific prediction than 'weather'. The less specific the prediction, the longer the time horizon over which we can predict with some degree of confidence.
We can predict with reasonable accuracy the high temperature in Baltimore a few days in advance. We can also make a pretty reasonable prediction of the average summer high temperature in Baltimore in February. What can't predict in February, at least not any better than a random guess, is the high temperature on the 4th of July in Baltimore.
Average annual global temperature is about the least specific environmental measurement immaginable, so it is, unsurprisingly, something we can predict with reasonable confidence over very long timescales.
Having said that, I'm not particularly enamored with long range climate models. They inherently include all kinds of unconfirmed assumptions about how the atmosphere-ocean-ice system operates and about future economic activity (which is not famously easy to predict). It doesn't matter how much computing power you throw at the problem, a wild ass guess is still a wild ass guess.
The fact that the models can back predict historical environmental behavior proves absolutely nothing since that was exactly the data used to generate the models in the first place. You can buy any number of software packages that back predict stock prices beautifully. Unfortunately this does not make them effective predictors of future.
In my view we shouldn't be addressing global warming because the models are scary. We should address global warming because we don't know what the hell is going to happen, which is really scary. If you are driving blindfolded, taking your foot off the gas is a pretty good idea.
On 'Chaotic systems are not predictable'--Sure, but who says climate is chaotic? posted 2 years, 6 months ago 13 Responses