In case you are missing the New England Aquarium's climate talk tonight (more than 400 people are expected to go), here is a question and answer with the featured speaker, Oxford University's Timothy Palmer. His lecture is called Predicting Climate in a Chaotic World: How Certain Can We Be?
Here are a few questions and edited answers the Green Blog posed to Palmer before the talk.
Green Blog: Historically, what has been climate models' greatest obstacle and how far are scientists along in overcoming it?
Tim Palmer: I think it is simply that Earth's climate is an extraordinarily complex system. We can work out some of the basic principles of climate using simple "back-of-the-envelope" calculations. However, if we want to know what will happen to climate at a detailed quantitative level - relevant if we are to inform government policy - we have to try to represent this complexity with mathematical models which describe as comprehensively as possible all the processes that are relevant: from the atmosphere and oceans to the land surface and ice sheets. Unlike some other sciences, we have no "laboratory" where we can answer "what if" questions (what if we perturb the system this way, or that way).
To overcome the obstacles of complexity we need three things: climate observations, big computers and lots of scientific intuition and insight. The big computers are needed to actually solve the equations - the scientific intuition and insight are needed to formulate the models so that they are as close as possible to the underpinning laws of science, to design the types of computer experiments that need doing (computer time is precious), and to analyse and understand the results that come out from the computer experiments. The observations, of course, are needed to study how the real system works, and to assess whether the mathematical models are realistic simulators of current and past climate.
GB: How reliable are climate models in looking at small geographic regions, such as the Northeast U.S., and are they getting better?
TP: This is a difficult question to answer. For example, if you asked me, are the models reliable enough to inform on new infrastructure investment to adapt to future climate change, then my answer would depend on whether the investment is more about temperature or precipitation changes. I think the predictions of regional temperature change are pretty reliable and robust, but precipitation changes are less reliable and robust. But certainly the models are getting better. On the one hand the amount of detail in these models (what a climate modeller would call "resolution") is increasing and this is making the models look more and more like the real world. On the other hand, we have better ways of representing the inherent uncertainty in these computer representations of the real world. This means that we can put more realistic "error bars" around the predictions that are made.
GB: What is the one message you want the public to understand about climate prediction?
TP: Simply this. Don't treat climate change as a matter of belief or denial. When we take out house insurance, it is not because we believe our house will get burgled or burnt down. Similarly, we should be asking whether it is worth taking action now to minimise the risk of the types of climate which our best disinterested scientific estimates suggest may occur in this century and beyond. I don't think it is the job of the scientist to answer this question, but rather to ensure that those that seek their own answers have the information they need to form an opinion.
5. How confident should people be in weather - and climate predictions?
As Ed Lorenz showed, weather is chaotic - the flap of a butterfly's wings a few weeks ago could indeed have made the difference between Sandy heading inland or out to sea. Hence people should by wary of any predictions of weather and climate which come without any properly quantification of uncertainty. But in a sense this is true of any prediction. A prediction without an estimate of uncertainty is not a scientific prediction. I am not aware of Astrologers putting error bars on their predictions! As I have tried to show with the Sandy example, we can be confident in our probabilistic estimates of future weather. We are currently putting these insights into our climate prediction models and increasingly I believe people can be confident in future climate predictions, not just of the large scale temperature changes, but even of regional precipitation changes.
Ed was an inspiration to me. But I am also reminded of the great theoretical physicist Richard Feynman who, according to his biographer Gleick, "believed in the primacy of doubt, not as a blemish on our ability to know, but as the essence of knowing!".
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