Allow me to make the problem crystal clear. Mathematics can solve a problem having two objects and one controlling nonlinear variable. We call it the two body problem. Until the introduction of my work in the recently accepted paper mentioned in my profile, no other exact tools properly existed.
The climate is influenced by a number of non linear variables in a three dimensional space, not least been the daily solar cycle. If we could get them measured properly and actually put together a convincing equation, it is possible to estimate things on a continuing basis and to hope it is meaningful.
The problem is divergence.
Everything about the climate predicts a self correcting system of processes that act and react to ensure that the net result is zero. We call it weather.
This means that if you set out to prove divergence you need extraordinary proof.
It has not been forthcoming for the CO2 hypothesis and this recognition has been postponed by suppressing the data.
The computer models are estimation systems that will be right or wrong often depending on the bias of the observer.
Scientists’ use of computer models to predict climate change is under attack
Tuesday, April 6, 2010
The Washington
And, depending on how much greenhouse gas emissions increase, the world’s average temperature will rise between 2 and 11.5 degrees by 2100.
The computer models used to predict climate change are far more sophisticated than the ones that forecast the weather, elections or sporting results. They are multilayered programs in which scientists try to replicate the physics behind things such as rainfall, ocean currents and the melting of sea ice. Then, they try to estimate how emissions from smokestacks and auto tailpipes might alter those patterns in the future, as the effects of warmer temperatures echo through these complex and interrelated systems.
To check these programs’ accuracy, scientists plug in data from previous years to see if the model’s predictions match what really happened.
But these models still have the same caveat as other computer-generated futures. They are man-made, so their results are shaped by human judgment.
This year, critics have harped on that fact, attacking models of climate change that have been used to illustrate what will happen if the United States and other countries do nothing to limit greenhouse gas emissions. Climate scientists have responded that their models are imperfect, but still provide invaluable glimpses of change to come.
They have found themselves trying to persuade the public — now surrounded by computerized predictions of the future — to believe in these.
If policymakers don’t heed the models, “you’re throwing away information. And if you throw away information, then you know less about the future than we actually do,” said Gavin Schmidt, a climate scientist at NASA’s Goddard Institute for Space Studies.
“You can say, ‘You know what, I don’t trust the climate models, so I’m going to walk into the middle of the road with a blindfold on,’ ” Schmidt said. “But you know what, that’s not smart.”
Climate scientists admit that some models overestimated how much the Earth would warm in the past decade. But they say this might just be natural variation in weather, not a disproof of their methods.
As computers have become faster and cheaper, models both simple and sophisticated have proliferated across government, business and sports, appearing to offer precise answers to questions that used to be rhetorical.
How many games will the Redskins win next season?
The Web site Footballoutsiders.com, which uses computers to show fans hidden dimensions of pro football, uses a model with about 80 variables. It looks at a team’s third-down conversions, the experience of its coaches, even the age of its defensive backs.
No crystal balls
How much cleaner would the Chesapeake Bay be if it had twice as many oysters?
The Environmental Protection Agency uses a model that divides the bay into 55,000 slices, and maps how pollution progresses through them, from upstream tributaries into the deeper waters of the Chesapeake
But, some of the time, these electronic futures haven’t come true.
The Football outsiders site predicted the Redskins would win 7.8 games in 2009. The real-world team won four. The EPA’s Chesapeake Bay model has been criticized repeatedly for over-optimism, for creating a virtual bay that looked cleaner than the real one. Last month, another model’s prediction was busted: a Georgia Tech professor’s computer said Kansas
These and other models are only as smart as the scientists who build them — they rely on data that scientists have gathered about the real world, and the accuracy of estimates about how all the factors fit together (Is an experienced coach more or less important than young defensive backs?).
They also depend on the computers running them. To accurately depict how individual clouds form and disappear, for instance, the computers that model climate change would need to be a million times faster. For now, the effects of clouds have to be estimated.
But scientists say complexity doesn’t guarantee accuracy. The best test of a model is to check it against reality.
“We’re never going to perfectly model reality. We would need a system as complicated as the world around us,” said Ken Fleischmann, a professor of information studies at the University of Maryland
Scientists say they don’t need models to know that the world is warming: There is plenty of real-world evidence, gathered since the mid-1800s, to suggest that. “There’s no climate model in that conclusion,” said Christopher Field, of the Carnegie Institution for Science in California
There are more than a dozen such models running around the world: mega-computers whose job is creating a virtual Earth.
These usually combine a weather simulation with other programs that mimic effects of rain and sun on the land, currents in the ocean, and emissions of greenhouse gases. First, these models imagine all the factors interacting within a “grid box” — an imaginary cube of land, water and sky that might be 60 miles long and 60 miles wide.
Then, the computer imagines effects in one box spilling into the next, and so on.
As the model runs, imaginary cold fronts sweep over virtual oceans, simulating weather at rates such as five years per day. In some cases, the models are re-run with different weather conditions, until a pattern emerges in global temperatures.
The pattern is the point. It is man’s signature, a guide to what could happen in the real world. All the major climate models seem to show that greenhouse gases are causing warming, climate scientists say, although they don’t agree about how much. A 2007 United Nations report cited a range of estimates from 2 to 11.5 degrees over the next century.
“It’s an educated, scientifically based guess,” said Michael Winton, an oceanographer at the National Oceanic and Atmospheric Administration. “But it’s a guess nonetheless.”
Raining on their parade
But Warren Meyer, a mechanical and aerospace engineer by training who blogs at www.climate-skeptic.com, said that climate models are highly flawed. He said the scientists who build them don’t know enough about solar cycles, ocean temperatures and other things that can nudge the earth’s temperature up or down. He said that because models produce results that sound impressively exact, they can give off an air of infallibility.
But, Meyer said — if the model isn’t built correctly — its results can be both precise-sounding and wrong.
“The hubris that can be associated with a model is amazing, because suddenly you take this sketchy understanding of a process, and you embody it in a model,” and it appears more trustworthy, Meyer said. “It’s almost like money laundering.”
Last month, a Gallup Gallup
But scientists say that, during this time, they have only become more certain that their models work.
Put in the conditions on Earth more than 20,000 years ago: they produce an Ice Age, NASA’s Schmidt said. Put in the conditions from 1991, when a volcanic eruption filled the earth’s atmosphere with a sun-shade of dust. The models produce cooling temperatures and shifts in wind patterns, Schmidt said, just like the real world did.
If the models are as flawed as critics say, Schmidt said, “You have to ask yourself, ‘How come they work?’ “
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