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Originally Posted by Hornblower
Conservation of angular momentum, as I understand it, tells us nothing one way or the other about possible stresses on the Sun as it orbits the barycenter. Please enlighten us as to why you believe otherwise.
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I am not talking about stresses I am only talking about the conservation of angular momentum and the effect it has on the sun’s position. I do not want to hijack JimP’s thread but to help answer your specific questions you can check out an ATM thread I posted in Oct of last year:
A Solar Dynamo Theory
If you follow it to my site and check out section 7 near the bottom on the Maunder Minimum and if you understand the conservation of angular momentum on a gyroscope then I think you will start to see my logic.
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Originally Posted by orionjim
I see JimP’s plotting of number of sunspots to Jupiter’s distance from the sun as maybe a quick and dirty way of indirectly seeing if the sun’s poles are moving (which would have an effect on the number of sunspots we see).
If JimP does take the time to put Saturn into his charts and the R^2 number does go up then I will explain the mechanism I am thinking about. I personally think the R^2 will go up! If the R^2 number doesn’t go up then posting my idea would be a total waste of time.
My question to you (Hornblower) is if the R^2 does go up would it get your interest up?
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Originally Posted by Hornblower
Don't ask me, ask a statistician. I don't know diddlysquat about these statistical criteria.
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As far as the R^2 number goes it’s pretty simple, the closer to ‘1’ it gets the closer the correlation. If the correlation or R^2 number is ‘1’, then on the ‘Jupiter versus sunspots’: if you know where Jupiter is then you know how many sunspots there are; It’s that simple.
JimP is getting a R^2 number of .95 and most statisticians would say that’s highly correlated, but the fact he is averaging the data in four month chunks really smoothes the sunspot data out and I think these same statisticians would be less impressed with that .95 number. Then if you explained to these same statisticians that not only is the data averaged in four month chunks but there is also 22 orbits of Jupiter (meaning averaging 22 x 4 chunks of data) these statisticians wouldn’t be very impressed.
What does that .95 number really mean in JimP’s correlation chart? Well it means that if you collect four months worth of sun spot data say from January through April and averaged it together and then did the same for the next 21 years and averaged all of these data points you will have a point that will likely fall close to his polyline. Using Jupiter’s closeness to the sun as a predictor of the number of sunspots would be like trying to predict the temperature in Washington DC on March 6th using a four month average temperature based on the last 22 years. The best it can do is say something like “it will be 45 degrees +/- 30 degrees”; not very impressive.
One question a good statistician would ask when looking at these charts would be about the scaling; in this case JimP’s chart goes from 40 to 70 average number of sunspots. A statistician would want to know what we would see from day to day, what is the range? The correct answer is they go from 0 to 170. Using JimP’s chart as a predictor would fail miserably.
The question on your mind right now probably is “why does it seem that you are supporting JimP’s charts”? And the answer is simple; because to me they show the change I’ve been looking for that helps support a theory based on the model I’ve been working on.
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Originally Posted by Hornblower
As I argued before, the period analyzed in the OP is too short to rule out a periodic solar max variation whose period is not exactly that of the Jupiter pattern, but is close enough to give a false positive for two or three cycles. If it holds up over 10 or 20 such cycles I would say, "Go for it." My question: Is there forensic evidence of the strength individual solar maximums and minimums in prior centuries that can be dated exactly?
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As JimP stated in the OP he used data from all 23 solar cycles (from 1749 to present). The problem is he averaged it together and as I stated above this averaging really smoothes out the data.
Jim