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I guess the editors of Nature, the most prestigious journal in all of science, have lower standards, and or are less knowledgeable abut the feild, than the omniscient MacFury
No. They reproduced a recent paper. If you expect that everything these journals print is either extremely important or earth shaking, you are mistaken. That their papers are peer reviewed does not make them true.
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If you expect that everything these journals print is either extremely important or earth shaking, you are mistaken.
"Important" is a matter of perspective. Nature (and Science) are the two most prestigious journals of research in the world; most scientists will spend their entire career working arduously and never publish in either of these journals simply because they never discover anything of sufficient importance. If you think papers published in Nature are "unimportant," by definition, you think the best research in the world is "unimportant."
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That their papers are peer reviewed does not make them true.
Science does not deal with Truth(tm). Science deals with data, logic and probabilities. That is why quantitative statements in science are usually accompanied by some indication of the degree of certainty with which the conclusion can be held. In this case, the research shows that the probability of the measured warming of the oceans being due to human activity is at least 99%.
If you think their methodology is in error, you're welcome to write a letter to the editors of Nature; they do publish these sorts of things when they are of academic merit. Somehow, I doubt you're knowledge of the subject is up to the task.
Science does not deal with Truth(tm). Science deals with data, logic and probabilities. That is why quantitative statements in science are usually accompanied by some indication of the degree of certainty with which the conclusion can be held. In this case, the research shows that the probability of the measured warming of the oceans being due to human activity is at least 99%.
No--it means that, given the way they chose to analyze the data, they believe their hypothesis is borne out to 99% certainty. Part of the fun of such studies is setting and resetting various experimental parameters to find the greatest significance. That is why the previous study I mentioned looked at the same data and came to a much different conclusion.
Given a complete data set, the parameters of any theory can be tweaked to create a confidence level approaching 100. Comparing other such tweaked models to each other does not allow solid conclusions to lift themselves up by their bootstraps.
Anyone interested in this phenomenon might be interested in the book Inevitable Illusions: How Mistakes of Reason Rule Our Minds, by Massimo Piattelli-Palmarini.
In discussing the excellent 1977 paper by Fischhoff, Slovic, & Lichtensteini, appearing in the Journal of Experimental Psychology Piatelli-Palmarini notes that, “...the discrepancy between correctness of response and overconfidence increases as the respondent is more knowledgeable…the level of accuracy increases, yes, but the level of overconfidence increases to a far greater degree.”
I would be more impressed if the researchers based their models on half the data only. When their model approached 99% certainty they should then be able to predict the other half of the data with a significant degree of accuracy. However, they all begin with access to the entire data set.
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Last edited by Macfury; Jun 19th, 2012 at 10:43 AM.
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I would be more impressed if the researchers based their models on half the data only. When their model approached 99% certainty they should then be able to predict the other half of the data with a significant degree of accuracy. However, they all begin with access to the entire data set.
This is model-building 101. That's how all the models have been developed, and they all succeed to various degrees within various constraints. And this is how the researchers estimate the accuracy of their models WRT predictions of future climate.
But ironically, your wish has been far exceeded by what has happened over the past 3 decades in climate research. Back in the 70's climatologists began to model the greenhouse effect with some rigour, and found their models predicting significant increases in global temperature. As more and more data has been accumulated, the models have been iteratively refined, and are now able to 'back project' with extremely good accuracy. Furthermore, as new and independent methods of measuring things that were not previously accessible have developed, researchers have found that the predictions of the models ranged from moderately accurate to seriously under-estimating the effects of anthropogenic GHG emissions.
So, while no one publishes without considering all the data available to them, the progress of time (not to mention the life work of many excellent researchers) provides us with much more than twice as much new data. And low and behold! The "alarmist" scientists of the 1970's weren't "alarmist" at all... they were conservative in their predictions (as scientists tend to be).
This is model-building 101. That's how all the models have been developed, and they all succeed to various degrees within various constraints. And this is how the researchers estimate the accuracy of their models WRT predictions of future climate.
But ironically, your wish has been far exceeded by what has happened over the past 3 decades in climate research. Back in the 70's climatologists began to model the greenhouse effect with some rigour, and found their models predicting significant increases in global temperature. As more and more data has been accumulated, the models have been iteratively refined, and are now able to 'back project' with extremely good accuracy. Furthermore, as new and independent methods of measuring things that were not previously accessible have developed, researchers have found that the predictions of the models ranged from moderately accurate to seriously under-estimating the effects of anthropogenic GHG emissions.
There are many such climate models and many can "back-project" only given the actual data. In other words, the model is created to fit the data.
Finally, the models do not finger the so-called greenhouse gases. They assume carbon-dioxide is the culprit, then make their predictions. The models themselves don't say anything about carbon dioxide.
Are the models improving? Their errors are less egregious as time passes. Are they worth basing public policy on? No, not yet, given the inability to either make accurate predictions, or free the data from their obvious AGW bias.
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Originally Posted by bryanc
So, while no one publishes without considering all the data available to them, the progress of time (not to mention the life work of many excellent researchers) provides us with much more than twice as much new data. And low and behold! The "alarmist" scientists of the 1970's weren't "alarmist" at all... they were conservative in their predictions (as scientists tend to be).
They need to test the models without considering all of the data available to them. Seeing all of the data allows them to skew the model to the data. They should publish only after completing this step.
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Originally Posted by bryanc
And low and behold! The "alarmist" scientists of the 1970's weren't "alarmist" at all... they were conservative in their predictions (as scientists tend to be).
I was in grade school when the predictions of Ice Ages came down from scientists. Many were not conservative at all.
The climate prediction models used by the IPCC, for example, are woefully inadequate and consistently fail to accurately predict what they were designed to predict. Some of these models predicting warming, not cooling, made wildly exaggerated predictions and others did not. Given enough predictions, even an astrologer is right, some of the time.
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Last edited by Macfury; Jun 19th, 2012 at 12:18 PM.
They assume carbon-dioxide is the culprit, then make their predictions.
Read the Nature paper. You are simply wrong. If you had any knowledge of this feild, you'd recognize how ludicrous your criticisms and assertions are. I can only presume that reading denier weblogs for so long has left you completely divorced from the actual science of the feild, because you're almost comically mis-informed on this topic.
Read the Nature paper. You are simply wrong. If you had any knowledge of this feild, you'd recognize how ludicrous your criticisms and assertions are. I can only presume that reading denier weblogs for so long has left you completely divorced from the actual science of the feild, because you're almost comically mis-informed on this topic.
You have stated on this forum that you're incapable of offering an informed opinion on climate science.
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You have stated on this forum that you're incapable of offering an informed opinion on climate science.
I am not capable of analyzing the data. I am capable of recognizing that the standards of academic research are being upheld*. There is a difference. You are, apparently not capable of doing either, or distinguishing the difference.
{edit: for example, I'm currently examining a Ph.D. thesis in Geology. I don't know much about geology, and I'm certainly not capable of criticizing the analysis of the data, but I am a scientist and I can assess wether the standards of academic research are being met. Part of that assessment will be my reading of the external examiner's review (i.e. I will consider the opinions of appropriately trained experts in the feild), and part of that assessment will be based on the candidate's responses to my questions about how the methodology and data eliminate alternative explanations, etc.
The point here is that anyone who has the faintest clue about how science works is capable of seeing that AGW is now so well supported scientifically that it's essentially beyond question. The questions are now "how bad is this problem" and "what can we do about it?" And the consensus of the experts who actually have a meaningful opinion on these issues is that the problem is pretty bad, and the sooner we do something about it the less it will cost us in the long run.}
Last edited by bryanc; Jun 19th, 2012 at 01:35 PM.
Reason: added clarification
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