In University I did a fair bit of work on climate modeling and environmental processes. I quickly came to the assumption that there are far too many factors for climate models to ever be completely accurate. I figured the largest problem was that there are over 6 billion people on this planet, who’s actions can’t be predicted by anyone – except for maybe some guests on Coast to Coast AM. However, this new paper by Matthew Collins, the author alludes to the idea that combining all the world’s climate models (if all were statistically accurate) would produce the range of outcomes we can expect with climate change.
In the past, the range of different model projections has been interpreted as the bound of uncertainty in the prediction, but this is far from ideal when one is, for example, considering how big to build a reservoir. Is the collection of the world’s climate models an adequate sample of the space of all possible models (and, indeed, is it even possible to define such a space)? Should all models be considered equally probable when assessing uncertainty? These and other questions have been central in framing the development of the techniques outlined in this issue.
Or at least, that’s what I got from that passage. I don’t have access to the whole article, so I can’t really say more on the issue – but it does sound interesting. With the mathematics involved in these models, it sort of reminds me of the Foundation series by Asimov, but those were more to with human nature than environment. Still, any sort of expectation that we will soon be able to accurately predict future climate situations will lead to disappointment. We know it will be warmer, we know where it might be wetter/drier, but we can’t model the human interaction – nor do I think we ever will be. Wow, this wasn’t humorous at all.
from Green Car Congress