New research suggests that the atmosphere can be modeled with fractal patterns and may not be as, er, complex as we thought. The benefit of the new knowledge? Perhaps more accurate forecasts and better climate models. From New Scientist:
The results point to a new view of the atmosphere as a vast collection of cascade-like processes, with large structures the size of continents breaking down to feed ever-smaller ones, right down to zephyrs of air no bigger than a fly."Tomorrow's weather: Cloudy, with a chance of fractals" (Thanks, Chris Arkenberg!)The implications promise to transform the way we predict everything from tomorrow's local weather to the changing climate of the entire planet. "We may never be able to view the atmosphere and climate in the same way again," says team member Shaun Lovejoy of McGill University in Montreal, Canada. "Rather than seeing them as so complex that only equally complex numerical models can make sense of them, we're seeing a kind of scale-by-scale simplicity."
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Interesting. So instead of weather prediction being based on processing bulk data, it's based on processing fractal equations representing bulk data. Like jumping from spreadsheet algebra to differential equations.
More interesting is that the fractal description will change with location and time. So you end up with a fractal of fractals. The spatial part will probably be very detailed. The time domain will probably converge to a climate model.
I wonder if human impact on the climate will be more easily demonstrated with such phenomenology.
We didn't have fractal clouds for this 1987 TV spot, so we interpreted the fractal mountain height data as shades of blue and white.
http://www.digitalartform.com/archives/2004/11/benoit_mandelbr.html
I was under the impression that fractals were brought to light by Mandelbrot when he was researching a way to predict weather patterns (not 100% sure)
"with large structures the size of continents breaking down to feed ever-smaller ones, right down to zephyrs of air no bigger than a fly."
do they mean fractal or turbulent? The description seems more like 70-year-old Kolmogorov stuff than a transformative change:
Big whirls have little whirls
That heed on their velocity,
And little whirls have littler whirls
And so on to viscosity.
pretty cool.
"brought to light by Mandelbrot when he was researching a way to predict weather patterns"
i always heard he was looking at the curve that defined where land meets ocean (or river maybe). dunno for sure though.
This is based on chaos theory, which was arguably "invented" by Edward Lorenz. He was working on equations to simulate weather, and ran a simulation. The state values were printed to a certain number of decimals. When he re-entered these values, he was missing the last few digits which were not printed. He was amazed that weather simulations were so drastically different if the numbers were off by even a thousandth of a percent. The butterfly effect: "A butterfly's wings can cause a tornado half way across the world."
Mandelbrot's fractals were inspired by coast lines, which are technically infinitely long, if you measure into each tiny crevice. They're based on fractional dimensions/degrees-of-freedom. They repeating, chaostic patterns.
For more information on this, look up bifurcations in population dynamics diagrams, non-linear systems of differential equations, the Lorenz' attractors (which look very much like butterfly wings), and chaos theory.
It is very related, that chaos would be related to fractals.
A funny quotation from wikipedia:
According to an apocryphal story Werner Heisenberg was asked what he would ask God, given the opportunity. His reply was: "When I meet God, I am going to ask him two questions: Why relativity? And why turbulence? I really believe he will have an answer for the first."
Why doesnt someone catch that bloody butterfly in the amazon rainforest that keeps causing all these storms!
I think it has generally been accepted that weather is "chaotic," that is, small changes create large effects. This makes it virtually impossible to model, as every assumption made, every rounding operation, affects the outcome.
By thinking of weather as Fractal, instead of as Chaotic, it makes it much simpler to model the system, as you have levels of patterned complexity instead of unpredictable noise.
get off it.
you just put those words into a gibberish generator, didn't you?