I don't consider the other side wrong.
Just not proven to the level of an FAA audit.
In the aircraft business we design with the reqmt. of one death per 1E9 operating hours.
I think political action based on climate science should be proven to that level. After all we are talking about the potential either way of 1E8 deaths.
Until we know what we are about doing nothing (which will insure economic growth and the possibility of ameliorating anything bad) is the best way forward.
Here I discuss two peer reviewed papers:
http://powerandcontrol.blogspot.com/200 ... auses.html
One says global warming will increase sea salinity. One says it will reduce sea salinity. Both were published in the same time frame.
And that is the consensus science. Think of how much worse it would be if a sceptic was writing them.
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Did you know there were principles of forecasting? I don't mean like the positions of the planets. Which for time spans of tens of thousands of years is fairly mechanical. The kind of forecasting I'm talking about involves events that are less deterministic than the motions of the planets. And yet there are principles.
The first is to classify the methodology. Are you starting with numbers or guesses? Which is to say how good is your data base? If you have numbers, what kind of precision is attached? Do you use the numbers directly? Or do you use statistical methods to tease out "useful" information?
OK. You have some data. Now you have to select a method of analysis that is both suitable to the data and the purpose for which it will be used. Is this an investment decision? Or just a report on something to keep an eye on? Do you have a business plan in hand or just a casual "this seems like a good idea"?
The above pages are full of annotated charts with little pop-up explanation boxes to help you understand the charts.
And if that isn't enough the authors of these pages and the accompanying book will give you free help if you describe your problem(s) to them.
We have come a ways and surely it can't be just to talk about forecasting methods. Well yes and no. I want to talk about climate. Climate forecasting.
J. Scott Armstrong, of the Wharton School, University of Pennsylvania, and Kesten C. Green, of the Business and Economic Forecasting Unit, Monash University have done a short audit of IPCC climate science [pdf] based on the forecasting principles outlined above.
I think it would be good to start with the title which really gets to the heart of the matter.
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There is more at Principles of Forecasting:
http://powerandcontrol.blogspot.com/200 ... sting.html
Which makes this (finally) on topic.
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One of the principles of forecasting outlined is that if your info is not sufficiently good do nothing and wait until things become clearer.
So I like JD's suggestion. Lets wait and see what happens for a while. Will we come out of this flat period with temps rising or falling?
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Right now we are in a data dearth phase of Polywell. Some money is being spent to get better data. Good idea. No point in making a $200 million bet based on faulty or insufficient data.
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Let me also note that the scientific/engineering attitude should be similar to the proper ethos of newspaper men. "If your mother says she loves you, check it out".
BTW science is not consensus. Once upon a time 100 German scientists (in the 30s when you know who was running Germany) wrote a book refuting Einstein. Einstein's response: "One would have been enough".
Consensus is about politics not science.
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Take Polywell and the hundreds of scientific sceptics. WB-7 will be enough to refute them if the results warrant.
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I have been in engineering situations where I have had whole companies (or at least the relevant depts) tell me my analysis was wrong.
So I soldiered on. The fist ten pre-production prototypes worked perfectly and I had egg on my face. The field failure rate in production was 99%.
Consensus don't mean squat.
The only fix was a redesign. Which is what I recommended in the first place. They used a new model # to avoid the taint.
Several million down the drain when an extra $10K or $20K (plus the cost of a schedule slip) would have prevented the problem.
I am tough on bad data and bad design. Its my job.