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What do we mean by parameterization?
To completely describe all the dynamics of the atmosphere we would have to simulate the movements of every individual air molecule. Clearly this is impossible and larger parcels of air have to be modelled. In reality these parcels have to be quite large, larger in fact than single clouds or even storms. As a consequence equations have to be used that describe the physics of the atmosphere at these large scales and not at the scale of individual molecules. The physics is in other words an approximation and not a precise description of the way the molecules behave.
Now the numerical values we use in these equations can quite legitimately vary within certain limits and depending on the exact values used the end climate model results will vary. The problem is that when there are several such approximations, each with equations having a range of values, the combined effect of these differences is impossible to predict as they cascade through a climate model run. Therefore the only way we can explore the prediction “envelope” is to run the model over and over again with different values in each approximation and see what effect these differences have on the climate predictions.
In the past estimates of climate change have had to be made using one or, at best, a very small ensemble (tens rather than thousands!) model runs. By using participant’s computers, we are able to improve our understanding of climate change predictions far more than would ever be possible even using the supercomputers currently available to scientists. In this way we also improve our confidence in the predictions because we understand better the inherent uncertainties.
The climateprediction.net experiments will help to "improve methods to quantify uncertainties of climate projections and scenarios, including long-term ensemble simulations using complex models", identified by the Intergovernmental Panel on Climate Change (IPCC) in 2001 as a high priority. Hopefully, the experiments will give decision makers a better scientific basis for addressing one of the biggest potential global problems of the 21st century.
Within just 24 hours of launching, the project exceeded the computing capacity of the largest supercomputer dedicated to climate change issues and became the world’s largest climate modelling facility. Within three months the model had simulated one million years of atmospheric processes (not though 1 million years of climate change which is another issue entirely!). The concept of distributed computing for exploring climate change had well and truly been demonstrated, opening the way to more sophisticated experiments of the kind now being run in conjunction with the BBC.
And the ice cream? Needless to say Myles won the bet and the Nature Editor duly paid up.
Further Reading:
Discover the current state of the project
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