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Supercomputer Models Sun's Corona Dynamics
gihan_ripper writes "Researchers from San Diego are using supercomputers to accurately predict the shape of the Sun's corona, based on magnetic field data from the photosphere. It is hoped that this model will enable us to predict Coronal Mass Ejections. When CMEs reach the Earth, they produce geomagnetic storms and can wreak havoc with communcations, GPS, and power networks. In the decade or so, the researchers hope to be able to predict CME collisions with the Earth and determine their impact."
I just hope the next advancement is getting the Earth to dodge the CME. :)
Hopefully that means in the future we'll get CME days off from work, since havok-wreaking on communcations, GPS, and power networks would severly limit my productivity.
CME's produce some incredible video when they hit our sun-pointed satellites. If you haven't seen them I highly recommend checking out NASA's "Best Of SOHO Movies" for a better idea of what these things are capable of.
m ovies2.html
http://sohowww.nascom.nasa.gov/bestofsoho/Movies/
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Ok, fine, fine, it'll enable them to predict things coming out of Sun, but will it tell us if Java will ever be open source?
The satellites which would be severely affected by CMEs are most probably located at geo-synchronous orbit. To bring one closer to Earth, you will have to (1) move it closer to the Earth, and then (2) you also have to slow it down because, as it gets closer to Earth with its angular momentum still conserved (imagine the ice-skater's spinning with and without the arms stretched), the satellite would undergo a faster revolution around the Earth. If you don't slow it down, it'll sling back out to a higher orbit.
Many GPS satellites are orbiting in low-Earth orbits. Those are protected by Earth's magnetic field (most of the time) and will be fine against a regular CME.
> it seems unlikely that we will ever accurately predict these events. Chaos has already doomed weather forcasters
:rolleyes
Let me guess, you heard a butterfly can cause a hurricaine due to chaos theory right?
It depends what you mean by "accurately" I guess. If you mean predictions with high probability several days in advance, yes that's doable. As you may recall we're already predicting hurricaine formation and movement days to a week or more in advance now, with a decent level of accuracy, and getting better all the time.
Global forcasting is already able to predict micro-climate changes months and even years in advance on a resolution of only several miles due to shifting weather patterns on a global/continential scale.
If weather was truly chaotic, i.e. if the total of all buterflys and other tiny variables made for completly unpredictable weather, then such predictions wouldn't be possible. Obviously the weather is not as chaotic as many HS professors have cliamed in that famous example. For that matter we wouldn't likely see big stable spots on Venus or have predictble trade winds here on earth, or all sorts of other fairly predictable features.
From monitoring the globe via satellite for things like ocean temps, and with many sensors for wind speed, forecasters construct fluid dynamic simulations which make it possible to predict smaller and smaller weather patterns further into the future, with increasing accuracy, butterflys or no.
Good point about trade winds and such. But while some weather features are long term predictable to some degree, I think for the most part weather really is quite chaotic. I doubt forcasts more than a couple days will ever be very precise. If you can't appreciate the large influence of a small butterfly on a partially chaotic system, then consider the forest fire. It will probably always be impossible to predict where someone will throw down their cigarette and start a forest fire. After a day or two a forest fire will have effects that will significantly alter the weather around the world, thus making precise prediction impossible because you never know what the inputs to the system are going to be.
Sorry, but you're over estimating the chaotic qualities of weather based on some outdated thinking. Yes it's true weather is too chaotic to ever be completly deterministic and there is a limited horizon on forcasting. We're not ever likly to predict individual rainshowers months or years in advance for example.
However, it will be possible to predict large weather patterns long in advance, years and even decades. For averages over longer periods of time they're already making predictions by running simulations on a global resolution of only several miles.
Medium scale weather events like hurricaines can be predicted days in advance now becasue it's not that chaotic, it relies on large events like global weather fronts, ocean temps, etc which allow prediction to a high degree of accuracy now. And yes, better methods and increased comuatational power are making those predictions more accurate, earlier.
You should actually read papers on what's being done on climate modeling by going to some of the relevant sites. Operating on classroom theory of chaos generalized to weather isn't exactly useful.
Are we talking about the corona or Corona ? Because ejections of the second one are disgusting.
The benefit in knowing collision dates is that we'll be able to partially protect our assets from the storm. For example, power companies can issue a planned outage, taking their transformers off-line for a brief period during the storm in order to prevent a longer outage caused by damage.
This is like our desire to know how the (terrestrial) weather is going to behave, even though we can't influence it. Advance warning helps us to prepare for adverse weather.
Phoenix, Boston, Little Rock, see a pattern?
Forcasts that go years ahead are subject to an even more huge array of uncertainties. A species of algae may evolve a one percent more efficient metabolism thus changing the influence of the ocean. A human inventor may develop a more popular diesel car engine. We may find out that Saudi Arabia has been grossly exaggerating their oil reserves. A volcanic eruption can throw things out of whack for quite a while. Forecasts that go years in advance can barely be considered "predictions" at all. Rough estimate would be a generous description.
I won't get into any examples, as I'm not qualified to make such predictions (though I'm sure some here are). That being said, researching for the sake of research produces useful results. Strictly researching "science with a purpose" could have prevented a good portion of our current discoveries. We don't know what our results will bring us, and that's the best part. We can apply this information where ever it fits, and use it to further understand our problems, which might lead to more "Science with a purpose" as you put it. All science is valuable, purposeful or not.
just an analog boy living in a digital age.