This is an official NCAR News Release (National Center for Atmospheric Research) Apparently, they have solar forecasting techniques down to a “science”, as boldly demonstrated in this press release. – Anthony
Scientists Issue Unprecedented Forecast of Next Sunspot Cycle
BOULDER—The next sunspot cycle will be 30-50% stronger than the last one and begin as much as a year late, according to a breakthrough forecast using a computer model of solar dynamics developed by scientists at the National Center for Atmospheric Research (NCAR). Predicting the Sun’s cycles accurately, years in advance, will help societies plan for active bouts of solar storms, which can slow satellite orbits, disrupt communications, and bring down power systems.
The scientists have confidence in the forecast because, in a series of test runs, the newly developed model simulated the strength of the past eight solar cycles with more than 98% accuracy. The forecasts are generated, in part, by tracking the subsurface movements of the sunspot remnants of the previous two solar cycles. The team is publishing its forecast in the current issue of Geophysical Research Letters.
“Our model has demonstrated the necessary skill to be used as a forecasting tool,” says NCAR scientist Mausumi Dikpati, the leader of the forecast team at NCAR’s High Altitude Observatory that also includes Peter Gilman and Giuliana de Toma.
Understanding the cycles
The Sun goes through approximately 11-year cycles, from peak storm activity to quiet and back again. Solar scientists have tracked them for some time without being able to predict their relative intensity or timing.
NCAR scientists Mausumi Dikpati (left), Peter Gilman, and Giuliana de Toma examine results from a new computer model of solar dynamics. (Photo by Carlye Calvin, UCAR) |
Forecasting the cycle may help society anticipate solar storms, which can disrupt communications and power systems and affect the orbits of satellites. The storms are linked to twisted magnetic fields in the Sun that suddenly snap and release tremendous amounts of energy. They tend to occur near dark regions of concentrated magnetic fields, known as sunspots.
The NCAR team’s computer model, known as the Predictive Flux-transport Dynamo Model, draws on research by NCAR scientists indicating that the evolution of sunspots is caused by a current of plasma, or electrified gas, that circulates between the Sun’s equator and its poles over a period of 17 to 22 years. This current acts like a conveyor belt of sunspots.
The sunspot process begins with tightly concentrated magnetic field lines in the solar convection zone (the outermost layer of the Sun’s interior). The field lines rise to the surface at low latitudes and form bipolar sunspots, which are regions of concentrated magnetic fields. When these sunspots decay, they imprint the moving plasma with a type of magnetic signature. As the plasma nears the poles, it sinks about 200,000 kilometers (124,000 miles) back into the convection zone and starts returning toward the equator at a speed of about one meter (three feet) per second or slower. The increasingly concentrated fields become stretched and twisted by the internal rotation of the Sun as they near the equator, gradually becoming less stable than the surrounding plasma. This eventually causes coiled-up magnetic field lines to rise up, tear through the Sun’s surface, and create new sunspots.
The subsurface plasma flow used in the model has been verified with the relatively new technique of helioseismology, based on observations from both NSF– and NASA–supported instruments. This technique tracks sound waves reverberating inside the Sun to reveal details about the interior, much as a doctor might use an ultrasound to see inside a patient.
NCAR scientists have succeeded in simulating the intensity of the sunspot cycle by developing a new computer model of solar processes. This figure compares observations of the past 12 cycles (above) with model results that closely match the sunspot peaks (below). The intensity level is based on the amount of the Sun’s visible hemisphere with sunspot activity. The NCAR team predicts the next cycle will be 30-50% more intense than the current cycle. (Figure by Mausumi Dikpati, Peter Gilman, and Giuliana de Toma, NCAR.) |
Predicting Cycles 24 and 25
The Predictive Flux-transport Dynamo Model is enabling NCAR scientists to predict that the next solar cycle, known as Cycle 24, will produce sunspots across an area slightly larger than 2.5% of the visible surface of the Sun. The scientists expect the cycle to begin in late 2007 or early 2008, which is about 6 to 12 months later than a cycle would normally start. Cycle 24 is likely to reach its peak about 2012.
By analyzing recent solar cycles, the scientists also hope to forecast sunspot activity two solar cycles, or 22 years, into the future. The NCAR team is planning in the next year to issue a forecast of Cycle 25, which will peak in the early 2020s.
“This is a significant breakthrough with important applications, especially for satellite-dependent sectors of society,” explains NCAR scientist Peter Gilman.
The NCAR team received funding from the National Science Foundation and NASA’s Living with a Star program.
IMPORTANT NOTE:
The date of this NCAR News Release is March 6, 2006
Source: http://www.ucar.edu/news/releases/2006/sunspot.shtml
(hat tip to WUWT reader Paul Bleicher)
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Atone, ye sinners, and ye shall be forgiven!
But then they are obliged to go and sin no more, which takes all the fun out of it.
I give high marks for at least being bold and precise in their predictions, but I’m sure one doesn’t have to give them a call to advise them to be a little more humble in choosing a confidence level in the future.
The most telling thing here about all models – particularly the climate models that AGWers also attach 95%+ probabilities (am I wrong in thinking that the probabilities of interdependent events 1, 2, 3,…,n is P1*P2*P3*….Pn). Can one have such high probabilities for each factor that when multiplied out they would arrive at 95 or 95% or even 65% probability? Indeed, in the field of possible climate “causing” factors, solar cycles are the most predictive of all – wouldn’t a climate scientist just love to be able to predict future climate so accurately as one can predict solar cycles – say be a year or two off. And yet, even with this sinusoidal behaviour we can be so off the mark.
Kath (19:37:42) :
1.2 million die in the world, annually, in traffic accidents
and so on…
Old proverb:
Life is sexually transmitted and 100% fatal.
Leif Svalgaard (20:29:17) :
BTW, I was a reviewer of their prediction paper. My review is here: http://www.leif.org/research/Dikpati%20Referee%20Report.pdf
Great review. How much attention did they actually give it?
The date of this NCAR News Release is March 6, 2006
Unfortunately, it appears that failed predictions are rarely reported in the MSM.
I think it is daft to give the discredited Dikpati paper prominence without at the same time publishing the papers that discredit it.
See the devasting critiques by see Choudhuri, Chatterjee and Jiang.
In this regard see Choudhuri, Chatterjee and Jiang (2007). Using solar dynamo modelling, these authors predict a very low amplitude for Sunspot Cycle 24 similar to the prediction of Svalgaard et al 2005. Kapyle (2007) compared the solar dynamo models of Choudhuris, Chatterjee and Jiang (2007) and Dikpati et al (2006), concluding the Choudhuri et al model the superior of the two. Amongst other things, the model used by Choudhuri et al provides that the poloidal field generation is intrinsically random whereas the model used by Dikpati et al uses sunspot area data as a deterministic source for the poloidal field.
The Choudhuri et al model is considered the more realistic of the two. Secondly, the Choudhuri et al model was published in 2004 and subject to scrutiny by scientists. The Dikpati et al model has not been published.
See further: http://en.scientificcommons.org/piyali_chatterjee
AND
Choudhuri, A. R., Chatterjee, P., and Jiang, J. 2007. “Predicting the solar cycle 24 with a solar dynamo model” ArXiv Astrophysics e-prints, arXiv:astro-ph/0701527 18 January 2007.
Kapyla, P., 2007. “Solar cycle – modelling and prediction” on website: http://agenda.albanova.se/conferenceDisplay.py?confId=140 March 2007.
Svalgaard, L. and Cliver, E. W. 2007. “A floor in the solar wind magnetic field” The Astrophysical Journal Letters. Can be found on Dr Svalgaard’s website.
Ok since the one arm bandit is out.. its time for my new planetary predictor. The tarot reading of the climate. Center card is Earth, Crossing card is Solar system.. then we have a N, S, E, W spread for compass points of earth. The four cards down the left from top to bottom would be for ocean currents, volcanic activity, water vapor and sun activity. 😀 Ya think if I run my predictors 400 times they would give me 10k for funding? hahahahaha..!!! Its a lot of work, but I bet I could come up with a better prediction then most.
Mike Bryant (20:18:09) :
“The CAGW disinformation machine often employs boring, rhetorically-challenged advocates who deliver their messages of fear and confusion in inaccurately measured and untested absurdities.” M. Bryant
I can see we are in the presence of our betters. But sorry Mike, we considered your frightfully incisive little dithyramb and rejected it for the quote of the week.
Gilbert (21:51:24) :
Great review. How much attention did they actually give it?
They did follow all my requests, otherwise it would not have been accepted as I get to see it again and again, until I’m happy with it. The reviewer most of the time wields enormous power in that regard.
At solarcycle24.com, they are talking about a sunspot number of around 70 at the next solar max.
http://solarcycle24com.proboards.com/index.cgi?board=general&action=display&thread=629&page=18
I don’t mind scientists positing ideas and hypotheses. It is what is done and encouraged……
I only start minding when those yet unproven ideas and hypotheses are used to change the World’s economy and energy use, whilst declaring a minor, but important atmospheric trace gas, a “pollutant”.
Also I’m not terribly happy with scientists using everyone else’s money to pursue what is basically a glorified hobby…. Most of ’em need a haircut and a proper job….. They can still do science on the weekends 😉
Long ago, before cheese was invented, I was a teacher. My task was to purvey various principles of English law to the willing but not necessarily able. One thing I learned very early on was that my students would cross-check everything I said against the content of a variety of textbooks and academic papers. If it wasn’t in writing it was treated with utmost skepticism.
That’s fair enough, people far more experienced than me and with far better paper qualifications wrote the books and articles. Or so one might think. In fact there were instances of my explanations being questioned on the basis of articles and books written by people whose experience and qualifications were indistinguishable from my own. It was all done very politely, but it was clear that most students presumed what they read to be more reliable than what they heard.
Over time my name appeared at the bottom of articles in journals and on the title pages of books (not many and not very good ones) and the result was that I then had authority in their eyes. What I said in lectures and tutorial classes might have remained the same but they were now words of confirmation rather than of dissent. The written word was very much King.
I wonder whether we are seeing the same thing with the spewings of computer models. Once something has been spewed it seems to be presumed that it is correct. That is not an entirely illogical approach, after all the models are set-up and operated by people with strings of letters after their names. It is logical to accept the word of people far better qualified than you are, what is not logical is to accept the word of a computer. Yet we seem to find that the authority afforded to computerised results is greater than the authority given to the word of those who fed the computer in the first place.
It’s a recipe for overstatement and for the weakening of critical analysis. Not good.
Richard Mackey (21:53:38) :
Amongst other things, the model used by Choudhuri et al provides that the poloidal field generation is intrinsically random whereas the model used by Dikpati et al uses sunspot area data as a deterministic source for the poloidal field.
The randomness is an important element in the model and is what makes prediction more than one cycle ahead impossible [except in a statistical sense].
The Choudhuri et al model is considered the more realistic of the two. Secondly, the Choudhuri et al model was published in 2004 and subject to scrutiny by scientists. The Dikpati et al model has not been published.
Richard means the actual source code. I have studied the Choudhuri code in detail and it is well documented and understandable. During our panel meetings I urged Dikpati to show us her code so we could form an opinion about it, but she refused with the excuse that the code was the result of many years of work and was patch upon patch and so ‘messy’ that it was not ready for public consumption for which it must be cleaned up and documented [Choudhuri actually remarks that he spent a considerable amount of time doing just that]. I asked her how she could have faith in the correctness of the programming if the code was such a mess, but never got a good answer. Another argument was something about ‘intellectual property’ [of taxpayer funded work???].
Hello Lief 20:29:17
I read your review. Did the final version make the changes you suggested?
I could not find a link to the final version, sorry
Also I note this comment… “Our model has demonstrated the necessary skill to be used as a forecasting tool”…
I would think that it would be necessary for the model to have actually correctly forecast something to make this statement, what do you think?
Regards
Michael
So evidently we are two years into cycle 24 eh?
Heh. Had me at the end there.
How dreadfully aweful that forecast panned out…goodness.
I think it would be wise for someone to grade these fools on the performance of their models and see how useful they really are.
Accountability lacks and accuracy is wishful thinking in these fields it seems.
But people wholeheartedly believe them to translate to reality. That’s not only arrogant, it’s just stupid!
Yeah that’s right! I said it…cuz it had to be said! Stupids!
Michael (22:28:01) :
I read your review. Did the final version make the changes you suggested?
Yes
I could not find a link to the final version, sorry
http://www.leif.org/EOS/2005GL025221.pdf
Also I note this comment… “Our model has demonstrated the necessary skill to be used as a forecasting tool”…
I would think that it would be necessary for the model to have actually correctly forecast something to make this statement, what do you think?
Perhaps they were a bit too optimistic here. But the coming cycle will be a good test case. Dikpati is sticking to her guns and expect the huge cycle to be just around the corner. And in truth, we don’t KNOW which way it is going to go. The coming cycle is ALSO a test of my method, so we shall see. In either case we will learn something.
Talking about the past: 1998 article from BBC news
Scientists blame sun for global warming
Climate changes such as global warming may be due to changes in the sun rather than to the release of greenhouse gases on Earth.
http://news.bbc.co.uk/2/hi/science/nature/56456.stm
My stats professor more than 20 years ago made the point that when a mathematical a model can be made to fit historical data, it does not guarantee the predicitive ability of the model.
Things haven’t changed.
Excellent investment opportunity: Get someone to pick up the tab for your computer game development, then hide the source code.
I would expect something funded by NSF to be open source, where the idea is that if you get it wrong, someone else can come along and try to improve it, especially if they have an understanding of the underlying processes.
No advancement possible there.
Wonder what thier justification was for the funding?
Even when you get an HST award, you can normally only keep the data proprietary for 1 year, after which the data becomes public record.
How did they get 98% when it got SC14 wrong, and butchered SC12??
Hmmm…. maybe I am in the wrong business. If I dust my C off, I could write a program to generate loops and fill them with color so that the image matches all the Solar Cycles, and sell it to NSF for a couple million.
Copy+paste from Space Daily:
“New Solar Cycle Predictions
by Tony Phillips
Boulder CO (SPX) May 28, 2009
An international panel of experts has released a new prediction for the next solar cycle, stating that Solar Cycle 24 will peak in May 2013 with a below-average number of sunspots. Led by the National Oceanic and Atmospheric Administration (NOAA) and sponsored by NASA, the panel includes a dozen members from nine different government and academic institutions.
Their forecast sets the stage for at least another year of mostly quiet conditions before solar activity resumes in earnest.
“If our prediction is correct, Solar Cycle 24 will have a peak sunspot number of 90, the lowest of any cycle since 1928 when Solar Cycle 16 peaked at 78,” says panel chairman Doug Biesecker of the NOAA Space Weather Prediction Center, Boulder, Colo.”
Everything here:
http://www.spacedaily.com/reports/New_Solar_Cycle_Predictions_999.html
NCAR – in my mind, a four-letter word, and I don’t mean that kindly.
Aren’t they also running a program to enlighten TV meteorologists of the reality of AGW? I believe I’ve seen a model on their site that shows how, if it wasn’t for all the CO2 in the atmosphere, the climate would have been cooling for the past 20-30 years or so. Here’s a rhetorical question – do they do any real science?
It is Archimedes who is thought to have said, “Give me a fulcrum, and I shall move the world!” Some of today’s ‘scientists’ have left facts behind and seem to believe, “Give me a computer, and I will create the reality that suits my purposes.”
The abusive misuse of all that computational power is really sad.
The thing that bothers me the most is the claim that if a model prediction turns out to be close that we will have learned something, that the model is somehow validated because of a single prediction being close, when it could be nothing more than coincidence. Several fairly accurate predictions of *future* cycles would be a different matter, but that encompasses several decades of waiting.
rbateman (23:01:47) :
How did they get 98% when it got SC14 wrong, and butchered SC12??
They use the first three cycles [12-14] to seed the model, so they are predicted poorly. Only when loaded with three cycles is their model expected [by them] to perform well.
Glenn (23:17:22) :
Several fairly accurate predictions of *future* cycles would be a different matter, but that encompasses several decades of waiting.
The polar field precursor method has now performed reasonably well for three cycles and may be on track for number four, which in any case will be yet another test.
It would be good to know how many independent parameters are in the Dikpati model. If there are more than four, it is a foregone conclusion that they could match curves to extant cycle data.
Luckily, we will not have to wait long to see whether the cycle 24 prediction is falsified.
According to my breakthrough statistical reanalysis of sunspot activity over the past two years, the NCAR prediction was actually correct. Sunspot cycle #24 is a already a raging bull! I won’t release my data-base to any of you counter-revolutionary cads because, after all, the debate is over. But, the New York Times will trust my work and so should you. Believe me; RAGING BULL! I recommend pointy, tin-foil hats for all as a precaution. I also predict a thumping EMF pulse that will tear the fanny off every Prius Smugmobile on planet earth.