Posted on 08/26/2005 11:11:20 AM PDT by aimhigh
State Climatologist Roger Pielke Sr. says his position on global warming was misstated in an Aug. 23 article in The New York Times.
The article reported Pielke's resignation from a panel that is preparing a study for the Bush administration on temperature trends in the atmosphere.
...My feeling is that the climate system is so complex that we can't predict, with skill, what will happen in the future," as levels of carbon dioxide and other heat-trapping gases continue to rise, Pielke told the Rocky Mountain News earlier this year.
(Excerpt) Read more at rockymountainnews.com ...
has he gotten around to talking about the newly revealed backers of Cindy Sheehan yet?
More Dan Rather type 'fake but accurate' reporting by the MSM
The prevalence of fake journalism in the mainstream media is disturbing.
It makes me wonder how much of the news I'd consumed before was the fabrication of political hacks posing as journalists.
Pielke, who bridles when he's labeled a "climate skeptic," said he is convinced that human activities are to blame for most of the climate warming that's been seen during the past 50 years.
But Pielke's skepticism surfaces when the conversation turns to the computerized climate models used to forecast future warming. The models are incomplete and unreliable, he says, especially when used to predict climate change at the regional level.
"My feeling is that the climate system is so complex that we can't predict, with skill, what will happen in the future," as levels of carbon dioxide and other heat-trapping gases continue to rise, Pielke told the Rocky Mountain News earlier this year.
The guy just states the obvious, but because he does not back in whacko belief that the world will end, he gets attacked. This is not science, this is a cult.
We can indeed predict what will happen with skill.
We just can't necessarily predict it with accuracy.
Minor nit, I know.
LOL true, but doing something with skill kind of implies you have some accuracy.
As I said, a nit.
Skill defines the process, accuracy describes the result.
"My feeling is that the climate system is so complex that we can't predict, with skill, what will happen in the future," as levels of carbon dioxide and other heat-trapping gases continue to rise, Pielke told the Rocky Mountain News earlier this year.
"I think we should probably control CO2 (carbon dioxide)," he said. "But to try to base it on these models is not solid. It's not good science."
I have said this, and said this, and said this.
Computer modeling is hard. When you get everything right, by developing a model and testing it iteratively against reality, then you have something really valuable. But that's hard, even for simple systems. I have a fair amount of experience in this.
For something as complicated as the Earth's climate over decades, it would be a Herculean task to make such a model, but it would be doable if you had enough decades-long stretches of data to check against. But we don't, and we won't.
At best, the models tell us what could potentially happen, and that's valuable. But their predictions must ultimately be treated as guesses, and not as prophecies. That makes a big difference in public policy decisions.
I love it. They claim the earth is billions of years old, but yet they can make a forecast on "what is happening" based on about 130 years of consistant weather data....rightttttttttt.
It's tough for these guys to get right what's going to happen tomorrow.
At some time in the future the earth will grow warmer and at some other time, it will grower cooler. That's clear since our geological history shows constant shifts to and from ice ages. Beyond that, accurate prediction really isn't possible.
What has one got to do with the other?
Absolutely. I agree with you 100% here.
What bothers me about the climate models is that there is almost no opportunity for that sort of feedback loop. We only have a few decades of hard data, and they are spotty. Worse still: those are the data that are being used to develop the models, so they can't honestly be used to test the models. All you really get is an empirical fit to the existing data, whether you set out to get that or not. (If you've worked with ensembles of neural networks, you know what I mean: a trained network that performs beautifully on its training set can fail infuriatingly on a new data set.)
Moreover, the Earth's climate is complicated. Hadronic shower development, by contrast, is a well-understood process governed by simple equations, but it is still challenging to model properly. There are always approximations to be made, series to be truncated, and numerical instabilities to be overcome.
If I am skeptical of the models, it's a skepticism I've earned through years of experience. I worry that most of the scientists who accept the models do so from a position of ignorance, basing their trust on some of the spectacular, public successes of computer models in other contexts. Those who made the models, while not ignorant, of course, believe the models because they have convinced themselves they're right. (It hurts to work that hard and be wrong. This I also know through experience.) Time will tell either way.
Thanks for the feedback. What I obviously forgot is that a computer model is just as prone to error or misinterpretation as any other attempt at physical modeling.
Appears to me their universe of study is very, very limited. How can you make a prediction on only 130 years of data given billions years of existence. Folly...
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