Technique could help climate models sweat the small stuff

Technique could help climate models sweat the small stuff
A new statistical technique that puts the fine details back into computer simulations of large-scale phenomena might prove useful in capturing the influence of cloud formation, a significant source of uncertainty in current climate models. Credit: Brad Marston

A team of physicists and mathematicians has come up with a statistical technique that puts the fine details back into computer simulations of large-scale phenomena like air circulation in the atmosphere and currents in the ocean.

Computer models are generally good at capturing the big picture, but they are often forced to ignore things that happen at small scales. For example, models of a planet's atmosphere capture the large-scale dynamics of jets and airflows, but they don't include small-scale dynamics created by things like clouds and localized turbulence, despite the fact that those dynamics can often influence the larger scales.

"There are simply too many numbers for the computer to simulate it at a reasonable speed," said Brad Marston, a Brown University physicist. "It might take years to simulate a day of the atmosphere, which wouldn't be good."

The traditional approach to dealing with the problem is to simply lop the small scales off of the simulation. A few ad hoc ways of putting some of that information back in exist, but they tend not to be mathematically rigorous.

"These schemes have always suffered from the criticism that they lack predictive power," Marston said. "You have to make a lot of decisions that you really shouldn't have to make but you're forced to make."

In a paper published in the journal Physical Review Letters, Marston and his colleagues show a method of averaging out those small-scale dynamics in a way that is computationally tractable, which allows those dynamics to be simulated and their effects to be captured in a rigorous way.

"We're retaining the degrees of freedom at the small scale, but treating them in a different way," Marston said. "We don't have to simulate all the little swirls, so to speak. We treat them by using their averages and the sizes of their fluctuations. It allows us to capture the contributions of these small-scale dynamics that would normally not be included."

In their paper, the researchers used the technique to model air jets forming on a round surface. They showed that the method produces results similar to brute-force numerical simulations of the same jets.

There have been prior attempts to treat small-scale disturbances statistically, Marston said, but those haven't fared very well. Prior attempts have treated disturbances as being homogeneous and assumed they were not traveling in any one particular direction.

"But that almost never happens in nature," Marston said. "Turbulence almost always has some directionality to it. That directionality is what makes these kinds of approximations work. It makes these approximations tenable."

The researchers hope that the method might make for more accurate simulations of a wide variety of natural phenomena, from how the churning interiors of planets create magnetic fields to how air flows across the surfaces of cars or airplanes.

The method could be particularly useful in modeling Earth's changing climate because the technique can more rigorously capture the influence of .

"Cloud formation is seen as the largest source of uncertainty in climate models right now," Marston said. "There are famous examples where different climate models that have different ways of dealing with the clouds give you qualitatively different results. In a warming world, one model might produce more clouds and another might produce fewer."

By averaging those cloud and then simulating them in the models, it might be possible to reduce some of that uncertainty, Marston said.

The team has already started working to incorporate the method in climate simulations, as well as simulations of ocean currents and problems in astrophysics dealing with the behavior of plasmas.

"There are a whole bunch of problems out there where we feel this could be helpful," Marston said.


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Statistical physics offers a new way to look at climate

Journal information: Physical Review Letters

Provided by Brown University
Citation: Technique could help climate models sweat the small stuff (2016, June 3) retrieved 25 April 2019 from https://phys.org/news/2016-06-technique-climate-small.html
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Jun 03, 2016
What are they gonna do when those models will no longer predict global warming?
(see the "double ITCZ problem" and you'll understand how biased models currently are)

Jun 03, 2016
There are famous examples where different climate models that have different ways of dealing with the clouds give you qualitatively different results. In a warming world, one model might produce more clouds and another might produce fewer.

And, that is what the AGW Cult calls 'settled science".

Jun 03, 2016
It seems they keep tweaking the models to match reality in the now but the models will never be able to predict the butterfly future.

Jun 03, 2016
Fascinating, and with wide applicability far beyond climate models. This could improve aircraft, turbines, propellers, interpretation of sonar, and MHD generators, just to name a few applications.

It is typical that AGW deniers fail to see these other possibilities, since they are innumerate and technologically illiterate.

Jun 04, 2016
Yikes, the BOZO brigade of deniers piles on a mathematical method? It doesn't matter what a computer models says. When the measured temp is way beyond what was typical of the past 100,000 years, the only logical conclusion is temps are increasing. That is simply being realistic. The math model simply averages smaller turbulence and adds those to the fringe or did no one read the article? This could improve computer models for all kinds of things as @Da Schneib points out. It's a new way of error correcting fluid dynamic models.

Why the Denier Trump-iacs want to deny basic math is beyond us all. Perhaps they are stupid?

Jun 04, 2016
It's a new way of error correcting fluid dynamic models.
Yeah, absolutely, and that's an enormously important piece of computation. This is a really big advance in numerical simulation of all kinds in fluid dynamics.

There are Millenium Prizes in mathematics available to anyone who can either solve or prove there is no solution to the existence and smoothness problems in the Navier-Stokes equations, which is coming at this same problem (computational intractability of turbulence) from the other end, that is, by traditional solution of these integrals as opposed to numerical simulation like that used in most physical computer models of fluid dynamics. These folks aren't up for that, but this is a big step in the same direction.

Jun 04, 2016
When the measured temp is way beyond what was typical of the past 100,000 years, the only logical conclusion is temps are increasing.


https://www.xkcd.com/605/

Jun 04, 2016
Classical climate models could benefit from concepts of quantum physics models. The presence or absence of global warming is like wave particle duality involving questions of interpretation by the observer so that there are fundamental limits to the precision of understanding both the science and the politics of climate change simultaneously. The observer's Ideology is an integral part of the investigative instrument that alters the state of what is measured.

Jun 04, 2016
A new statistical technique that puts the fine details back into computer simulations of large-scale phenomena might prove useful in capturing the influence of cloud formation, a significant source of uncertainty in current climate models.


This is absolute and utter blasphemy! There is NO uncertainty in climate science whatsoever. It's all SETTLED SCIENCE. There are no further discoveries to be made and no adjustments that can possibly show AGWism to be incorrect. The climate models are a prefect representation of reality and only the "deniers" obfuscate the obvious truth shown by the crystal ball of the soothsaying climate gods.

Jun 04, 2016
Here's hoping, with several more BILLIONS of dollars and bit of sweat, their climate models will at least be able to "predict" yesterday's weather. Not holding my breath though.

Jun 04, 2016
climate models will at least be able to "predict" yesterday's weather
Climate is not weather.

Dumb da dumb dumb. Dumb da dumb dumb duuuuhhhhh.

Jun 04, 2016
Climate change is science pornography which gets scientists aroused until a climax of verbiage is deposited on the internet. Climate change also functions as the Match.com for scientists trying to find partners for giving birth to a new world order.


Jun 05, 2016
"Climate is not weather."

Unless it's hot weather, in which case it's climate.

Jun 05, 2016
Here is the reference: Generalized Quasilinear Approximation: Application to Zonal Jets

J. B. Marston, G. P. Chini, and S. M. Tobias
Phys. Rev. Lett. 116, 214501 – Published 27 May 2016

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