The world of climate modelling has to be a tricky one, to be sure. There can never be enough data to input and, to create models that are at all helpful you actually end up needing masses of data so large that it starts to boggle the mind.
However, scientists from Brown University believe that basic physics could actually offer a simple method to model key elements of the climate.
Their research was published in the journal Physical Review Letters and details a technique called direct statistical simulation. According to their research, direct statistical simulation does a very good job of modelling fast-moving flows that form naturally in the oceans and atmosphere called fluid jets.
Brad Marston, professor of physics at Brown University and one of the authors of the paper, says the findings are a key step toward bringing powerful statistical models rooted in basic physics to bear on climate science.
The method of simulation used in climate science now is useful but cumbersome, Marston said. The method, known as direct numerical simulation, amounts to taking a modified weather model and running it through long periods of time. Moment-to-moment weather — rainfall, temperatures, wind speeds at a given moment, and other variables — is averaged over time to arrive at the climate statistics of interest. Because the simulations need to account for every weather event along the way, they are mind-bogglingly complex, take a long time run, and require the world’s most powerful computers.
Direct statistical simulation, on the other hand, is a new way of looking at climate. “The approach we’re investigating,” Marston said, “is the idea that one can directly find the statistics without having to do these lengthy time integrations.”
It’s a bit like the approach physicists use to describe the behaviour of gases.
“Say you wanted to describe the air in a room,” Marston said. “One way to do it would be to run a giant supercomputer simulation of all the positions of all of the molecules bouncing off of each other. But another way would be to develop statistical mechanics and find that the gas actually obeys simple laws you can write down on a piece of paper: PV=nRT, the gas equation. That’s a much more useful description, and that’s the approach we’re trying to take with the climate.”
Simply put, direct statistical simulation focuses attention on fundamental forces driving climate, rather than focusing on ever little aspect. One obvious impact of a climate model like this is being able to model climate conditions millions of years ago without having to reconstruct every aspect of a time we no longer live in.
There are limits, naturally, to direct statistical simulation. The study found that the statistical model started to break down as the pace of adding and removing energy to the fluid system increased.
Marston and and co-author University of Leeds mathematician Steve Tobias are currently working on an expansion of their technique to deal with that problem.
Despite the limitation, Marston is upbeat about the potential for the technique. “We’re very pleased that it works as well as it did here,” he said.
Source: Brown University