Distributed Computing World Climate Simulation 287
Burnt Offerings writes: "The BBC reports that scientists at climateprediction.com are nearing the completion and public release in late summer of a distributed computing project that simulates the world's climate from 1950-2050 AD. It seems that each user's simulation will have different initial conditions built into their runtime simulation and a single completed simulation from 1950-2050 AD takes on average eight-months (Doh!), assuming average household computing power. The results will be sent back to the project's team, where they will select the models that resulted in the 'real' climate patterns that have occured since 1950-2000. I presume they will then use these validated models to help extrapolate the world's climate from 2000-2050. Pretty cool (or should I say warm? or hot?)."
correct me if i'm wrong but... (Score:1)
Except (Score:1)
For me, a single completed simulation from 1950-2050 AD should take a little over 100 years. Can't wait to get started.
With luck, however, I should get the right answer.
Re:Except (Score:4, Funny)
end result (Score:4, Funny)
"On 1st January, 2050, it will start rather cloudy with outbreaks of rain, mainly in the north. These will clear up by late afternoon, leaving it warm with mild breezes in most of the country."
graspee
Re:end result (Score:2, Funny)
now the bad news... (Score:2, Funny)
Re:end result (Score:3, Insightful)
Oh boy.... (Score:2, Funny)
On this day in 1950, it was raining. The rain was as pure as Evian.
On this day in 1980, it was raining. The rain was as pure as the innards of a Duracell battery.
Weather is a chaotic system (Score:2, Interesting)
Websurfing done right! StumbleUpon [stumbleupon.com]
Weather != Climate (Score:5, Informative)
Predicting climate 50 years in the future is a computationally difficult task, but it isn't impossible the way that predicting weather would be.
(Weather + Weather )/ 2 = Climate (Score:3)
I must take issue with the parent post, though. I agree that weather is a choatic system, very much so. But, all aspects of weather can be parameterized, even the most chaotic ones. The key here is a matter of scale. The mesoscale type systems are extremely hard to model, but you take a global system (long wave patterns), and you will have a much better time of modeling them. How? You throw out the small scale stuff like your butterfly and such. On a global scale, something like that would quickly disappear into the larger scale. That is why global models (like the MRF, NOGAPS, and such) work better out farther (those models run out to 384 hours as opposed to smaller scale models that run out 84). Verification rates are acceptable for those models out that far (numbers I cannot quote off the top of my head). They could do better, but they would require more time to process and would not be useful to the operational meteorologist.
This distributed system will be over eight months and on such a large scale, the results will be useful.
Re:(Weather + Weather )/ 2 = Climate (Score:2)
Re:(Weather + Weather )/ 2 = Climate (Score:2)
I suspect that the distributions of answers will be more informative than the answers themselves.
The nonlinearities should make a very real difference between the average of the simulations and the simulation of the averages, probably different enough that scientifically bad fudge factors are required to bring things to match reality.
Correlations can do some nasty things to you. Correlate which way the steering wheel is pointed with whether you are too far left or right in your lane. All it takes is a feedback system with something aproximating intelligence and your very good model can get things backwards.
Weather ~= Climate (Score:2)
Sorry to fall back to dictionary definitions, but this sure sounds like weather to me. Maybe averaged on a longer time scale, but it's still quite obviously a chaotic system. We've found loose correlations with sunspots, deforestation, etc.. but even very large trends like the "little ice age" of 1500AD are unexplained and most likely chaotic. If we can't explain hundreds of years of pronounced trends, I don't see how we can do anything with the relatively uneventful last 50 years.
Websurfing: The Next Generation - StumbleUpon [stumbleupon.com]
Re:Weather != Climate (Score:3, Interesting)
Perhaps it's not impossible, but no-one has been able to do it yet. That's why they're resorting to this...
Can anybody read between the lines here? They're essentially saying, "Every climate model we have (that predicts global warming) wasn't able to accurately predict the global warming 1900-2000. We're fresh out of ideas so let's run a couple of million models with varying random values. When one of them (inevitably) comes pretty close we can cling to that as "proving" it to be a working model and use its results as convincing evidence that we must cut CO2 production or we will all die."
I'm not giving these jokers a minute of my CPU time. They are guessing. They don't have a workable model so instead of trying to keep thinking they're in a rush to get a "verified" (by passed events) model within a year so they can try to use the results to push their political agenda. The fact that a few of the millions of models they run correctly guesses the last 50 years of climate change is no indication it will predict future climate change unless there is a reasonable belief that the model was based on some logic. These models are based on random guesses at chaotic values.
Trust me, the results are already known. It will show global warming for 2000-2050. Can you imagine the coup if the random model that happened to guess 1950-2000 also showed global cooling of 5 degrees in the next 5 decades? How much you wanna bet that that result would NEVER see the light of day...
Spend your CPU cycles on SETI...
Re:Weather != Climate (Score:2)
Oh, come on. Give me some science I can believe in and I will. What these people are doing (by running millions of climate models) isn't science.
These people are essentially running a climate model with the same "starting variables" (1950) millions of times using different random values for the values they don't know (effect of greenhouse gases, effect of the sun, effect of plants, reflectance of the atmosphere, etc.). Then they can look through those results that are accurate to 2000 and then say, "Here is a model that works."
If the numbers plugged in for these variables are based on some logical scientific observation that suggests a value then that is ok and that is science. A scientist says, "The observed reflectivity of the Earth is 0.67. We plug it into our model and the model doesn't work; the model must be wrong."
These people, however, are running a million models and seeing which variables make the model right. They then (presumably) will go back and say, "Oh, this works if the reflectivity of the Eath is 0.34. Well, the observed reflectivity of the Earth is 0.67, but 0.34 is what makes the model work. There must be something wrong with the observed reflectivity. It must be more reflective now than it was; probably because there are more greenhouse gases. See, we need to reduce CO2 emissions!"
The point is: Climate models are currently inaccurate and they know it. Their models haven't been able to correctly predict the actual climate observed 1900-2000. What they want to do here is run their model millions of time until they find some combination of variables that produces the right climate data for the year 2000. Their conclusion, then, is their model worked.
That's not science. They are trying to find values for their model that should be obtained by scientific observation--those values should be used and the model refined until it produces the correct answer based on the known variables.
Rather, they want to find the values that make their current model work. But that supposes that the model itself is right. But if the model was right they wouldn't have to do this in the first place.
But mark my words. When this process is done (if anyone participates) you'll see a story on CNN (and a few weeks later on Slashdot) about how they now have a climate model that successfully predicted 1950-2000 climate and which further predicts additional warming for 2000-2050. "It must be right because it guessed 1950-2000." Well, yeah, but a million monkeys will eventually guess it right, too--but I wouldn't trust those same monkeys to guess 2000-2050 correctly.
Re:Weather != Climate (Score:2)
It's the only thing that they can do. If they know the values then they don't need to run the model a million different times. Unless each run is using a different model, but I highly doubt that they have a million different models they want to test. They want to plug what should be known values into their probably-flawed models to see what works.
If we knew the reflectivity of Earth is 0.67, then we wouldn't use it as a parameter in the model. As you said yourself, they're choosing parameters that we don't already know.
You're probably right that that's what I said. What I meant, however, is they almost certainly will test values for variables we know and also those that we don't. When they run their models with known values, they don't work. They're looking for values that do.
If they manage to correctly predict the climate, and if all of the models that do so give the same future predictions, then they can quite legitimately be said to have calculated a prediction of the model. It doesn't prove the model, but getting predictions from a model is the first step. The prediction won't be borne out as valid until we can get independent confirmation for the parameters.
I agree, if they had multiple runs using different values that got the right answer for 2000 and they all predicted the same effect in the future then perhaps they'd be on to something.
But perhaps not. Like I've already said, if you have some fancy equation that takes numbers in and produces new numbers based on the input if you feed it enough random numbers you will eventually get the right answer for 2000. Different sets of random numbers might both get the right answer for 2000. Different sets of random numbers might even get the same answer for 2000 and predict the same effect for 2050. None of that is particularly convincing if the source of the numbers is random. It just proves the old theory that enough monkeys typing randomly for enough time will reproduce the works of Shakespear.
Incorrect. It's possible that the model could be right
It's possible it's right. So they should validate that by inserting the observed variables, entering the data for start year 1950 and see if it gets 2000 right. That's how they can test the model. Not by plugging in random numbers into a million runs of the model.
The real test will be to try it for two consecutive periods, both for which we have data. The first is used to determine the model parameters, and the other will be the control against which "future predictions" of the model are tested. That way, the model's predictions can be tested against real data. It will only test the model out to half as far as they want it, but it would be a solid test.
I'd agree with that.
What they ought to do is come up with a model that takes 1950 data and predicts 1975 and 2000 climate. See if it got it right. If it doesn't, keep working on the model--don't look for random values for variables that MAKE it work.
The thing that concerns me is that if they run these models and come up with some model that shows global warming for 2050 it'll certainly make news. After all, it "predicted" 2000 climate correctly so it will be spun such that everyone thinks the whole thing has been proven.
If, however, the model shows global cooling or no change I am reasonably sure that the model will be conveniently forgotten and there will be no news media reports.
The sad thing is that I'm NOT a cynical person, but I believe the above is true.
Re:Weather != Climate (Score:2)
Yes, based on the evidence (or lack thereof) to-date, I'm quite convinced that global warming is not happening.
Since we're getting into the "nobody knows" mindset here, tell me, how do YOU know?
Well, I know there has been no global warming since 1979 when the satellite record was started. That's a fact.
In the light of the fact that there's been no global warming in the last 23 years, I need to be shown evidence that it IS happening to disregard the satellite record. And that evidence has to be VERY compelling.
The only way for you to *know*, would be if *you* had an accurate prediction model, which you just claimed noone has.
As I said, I only know that there hasn't been any in the last 23 years. That's the satellite record, and that's the fact. It's not based on assumptions, predictions, or personal beliefs. It is based on hard concrete data collected by satellites.
Whether there will be any global warming in the future I can't say any more than the envrionmentalists. But in the absence of compelling evidence that would somehow be more important than actual, concrete worldwide observations I have no reason to believe that it will occur.
Yet if that was the result they eventually chose, it sounds to me like you would be *satisfied* with that result - simply because it would fall in line with *your* opinion (and believe me, it *is* just an opinion).
You assume too much. No, I would not be satisfied. The whole excercise is a waste of time and even if they did publish results that contradicted global warming, the model itself would not be any more significant. It might give me hope in that the media would actually report something that contradicts the trendy global warming craze, but the model itself would remain as irrelevant as always.
That makes you about the same as them.
Actually it makes you just about the same as them since both you and they assume too much about unknown values.
Re:Weather != Climate (Score:2)
Bzz, wrong, try again. Better yet, check the following links for your own personal intellectual growth:
Corrected Satellite Record still doesn't shown global warming [nasa.gov]
Ice caps have been melting since last ice age [globalwarming.org]
Satellite record shows no warming in NA, Europe, neither does surface record [greeningearthsociety.org]
I highly recommend the last article. It shows that, among other things:
- Of the 0.9 degrees that the temperature has risen since 1890, 2/3rd of the increase occured before 1940.
- The majority of the the remaining 1/3rd of heating actually occured in 1998, and is attributed to an El Nino effect that year.
- The satellite record and the surface record tend to coincide quite nicely (and show no significant warming, except for above mentioned El Nino) in N. America, Western Europe, and Australia where the surface record is more reliable. Most of the "global warming" is occuring in areas of the world where the surface record is not as reliable, such as S. America, Africa, Asia. That is, the surface temperature record only shows a deviation from the no-warming satellite trend in those areas with unreliable stations.
- Since 1979, there has been no warming except for an El Nino event in 1998. In fact, were it not for the El Nino event there would have been global cooling since 1979.
- There was also global cooling of -0.2C from 1940 to 1975.
So, no, there is not any undebatable evidence that the earth is warming up. I would say you've only looked at the global warming claims without truly investigating the facts. I invite you to start your investigation with the above links.The question is not whether or not the earth is warming up, we *know* it is.
Again, wrong. We don't know that. In fact, the evidence disproves your assertion. Please review the above sites, including NASA, which contradict your belief.
The only debate left is what is *causing* it, whether or not it is "natural", and whether or not it is cause for alarm (which is not necessarily the same as whether or not it is natural - even if it turns out to be an entirely naturally-caused warming, if it might harm millions (or billions) of people, we should damn well do something about it anyway).
Again, I stress that the evidence cited above (and available elsewhere if you spend some time in google) shows that global warming is far from proven.
Even if there is global warming, again you make the assumption that it is bad. The earth has warmed and cooled many times in the last 4 billion years. The mini-ice age some 500 years ago cooled things off and, since then, earth has been rebounding to its pre-ice age temperature.
Are we really so arrogant as to believe that we can know whether global warming is bad? Especially if it's naturally occuring, who are we to alter that course just because we are used to things the way they are? Every species has to adapt... We are no exception. If the seas rise, we will move. If the seas fall, we'll extend our beaches. If there is more severe weather we'll build stronger homes.
I think the most important thing here, though, is that you review the above links. You seem to believe that global warming is an undebated fact. While many people have chosen to believe it due to rather one-sided reporting in the media, it is far from proven. Even if you consider some of the sources biased, at least they will balance the other bias you've been reading so far. PLEASE READ THE LINKS.
Re:Weather != Climate (Score:2)
What makes you think the sea level will rise? Because "warmer temperature, ice melts, sea level rises?" Ok, maybe it's that simple. Or maybe not.
Sea level has fallen 30cm in last 150 years in NZ [vision.net.au]
Global warming will not cause sea level rise [globalwarming.org]
Sea levels falling in Tuvalu [globalwarming.org]
In short, evidence shows that the sea level has fallen over the last 150 years despite the modest rise in temperatures in the early 1900's. That combined with the above links that show that many believe that global warming does not necessarily mean rising sea levels mean that even if there were global warming, it is far frrom certain that sea levels would rise.
Check the links out. The first one is especially convincing and interesting reading.
All in all I see you falling prey to lots of propaganda that has been repeated in the media but that a precious few have really taken the time to investigate. You automatically assume that there is global warming. You automatically assume that that means there would be a rise in sea level. You automatically assume that that would be bad for humans.
Unfortunately there isn't much middle ground. Whatever you read is either for it or against it--almost always with the disclaimer "...but we really don't know yet." I can give you evidence after evidence and you can discard it one after the other claiming it is biased. But from my point of view your sources are biased.
That said, I think I'm done.
Re:Weather != Climate (Score:2)
I did go read your links quite extensively, and it sounded like a lot of propaganda to me.
As does IPCC and most pro-global warming sites seem to me to be propaganda. I explicitly told you that you would probably see the sites as biased, but hopefully be able to read the "other" side, consider what you already know, and come up with a balanced view. I guess, even with my disclaimer, you were unable to do that.
if the US flatly refuses to make any effort to curb emissions, WHY THE HELL should any other country?
They shouldn't and we shouldn't ask them to.
But if they are expecting the U.S. to make cuts they shouldn't expect exemptions just because they are developing countries. All that will do is export pollution (and jobs) to developing countries without actually solving the problem.
Sounds like the only thing achieved is a wealth transfer from rich countries to poor countries. That economic system crashed and burned last century.
The US should be leading the way on this, providing the example for other countries to follow, and they can best afford to.
So we should say, "We can afford it. A few billion dollars. A few million jobs. Let's provide an example of what happens to an economy when jobs are exported overseas."
I'm fully in favor of free-trade and all that means. That means that we should ZERO import/export tarrifs and let the chips fall where they may. If Malaysia is more efficient at producing product X than we are, they should produce it and we should import it. And if we're more efficient at something else, we should export it.
But I am not going to accept that the U.S. unilaterally give up a competitive position. That's just stupid business. If we're going to solve the environment it has to be done TOGETHER. No exemptions for anyone. Anything less will NOT solve the environment but will cause a transfer of jobs and wealth to other countries--again, an economic system that died in the last millenium.
Further, since the "solutions" many environmentalists propose clearly will not do anything to help the environment but will cause a wealth transfer to developing nations, I must conclude that THAT is their real goal. And I am opposed to that.
And this has NOTHING to do with global warming - it should be done because its the right thing to do.
It's the right thing to do? It has nothing to do with global warming?
If it has nothing to do with global warming, then why is it the right thing to do? Why is it "right" to throw millions of Americans out of work and transfer those plants, jobs, and money to developing countries and pollute THEIR neighborhood? Why is that the right thing to do?
Come on, if you're now saying "It's not a matter of global warming" then you've given up the only possible justification for such a radical worldwide change. The developed worls is not going to accept a massive wealth transfer if it's just to make those countries richer at our expense. We struggled to be as productive as we are and they too will achieve what we've achieved... in time. It is not our job to make them rich today. It's their job to work for a better tomorrow.
You don't seem to be able to see it, but those sites are plainly propaganda mouthpieces.
I don't want to resort to name-calling, but IDIOT: RE-READ MY MESSAGE. I EXPLICITLY TOLD YOU THAT YOU'D SEE THEM AS BEING BIASED. Likewise I see most environmental sites and news as being biased propaganda. What the heck is the difference? What you see as propaganda I see as facts, and what you see as facts I see as propaganda...
Whenever equipment measurements are not in their favour, they blame the equipment (even making sweeping statements in some cases like "3rd world equipment, badly maintained"). Basically any *evidence* that contradicts their own agendas they make up some BS why that is not valid.
Check the article again. Where they have said the measurements are wrong they have even supplied PICTURES where you can see the problems yourself.
If you can't see that these sites are *biased*, you are blind.
Hello, McFly! Re-read my previous post. I TOLD YOU THEY WERE BIASED. If you can't read my post then YOU are blind... This is what I get for getting into a discussion with an Anonymous Coward, i Know...
That said, I provided them to BALANCE the BIASED sites that YOU have been reading that promote the falacy of global warming.
Please provide me with some links to sites that you consider to not be biased? I'd be interested in seeing that...
I'm not saying that sites on the other side are not biased, on the contrary. Nor am I saying that this proves that global warming is happening, I'm not saying that at all. I'm just saying that these sites are definitely biased.
And I knew that, as I mentioned in my previous post.
That said, I'd like to see some links to sites that you consider worthy of me checking out. You know, some good unbiased sites that present the facts of global warming...
Note, *I* am not the one who is falling prey to propaganda here. YOU are the one who *refuses* to look at the issue from outside your already-decided position.
You know, I'm not rich. I'm currently an independent consultant that is currently without work. I don't have any investments that will be hurt whether global warming is true or false.
I have made my decision based on reading both sides of the story. My standpoint is, "No, I don't believe global warming is happening and in the absence of proof that it is I believe any solutions that disrupt the economy are not justified." There you have it.
Please, re-read this msg and previous msgs before replying. You either didn't read my previous posts or chose to ignore them when you replied and it'll save us both time if you'll not attack me on points that I've already conceded (that the sites I provided are biased)--with the exception of the site regarding mean sea level measured by Cap. Cook in New Zealand--that article seems to be completely unbiased, not supported by any corporate interest whatsoever. Check it out if you haven't already.
And, again, I'll be waiting for your list of reliable, unbiased sites with information regarding global warming so I can see what a truly independent and unbiased site on the topic looks like.
Re:Weather is a chaotic system (Score:2, Informative)
(a) there may not be enough models that have been run, so we may pick something that "seems close"
(b) running a 50 year simulation (rather 100 year) in 8 months on small computers means that the model is not going to be very sophisticated
(c) there are random parameters, such as volcanic eruptions, man made emissions, deforestation/aforestation, etc., that won't get into the model properly
A prof of mine told this in the class: In the good old days, many mechanical engineers came up with formulae for heat transfer in pipes under various conditions. The formulae matched experimental data almost perfectly. They started extrapolating the results. Eventually, they found out that *ALL* those extrapolations violated the second law of thermodynamics -- and they went back to just interpolating.
S
Infeasible (Score:4, Insightful)
Spend your extra CPU cycles computing the cure for cancer or finding ET. I doubt this will prove useful.
Re:Infeasible (Score:4, Insightful)
That being said, 8 months is way too long to get something useful. I know a couple friends who reinstall their OS (and apps) in shorter terms than that, and don't really bother with bringing all data along, just some backup on CDR "in case I really want it again". I think they could at least chop it in periods of a few years, so that if you finish a "unit", somebody else can then pick up where you left. I'd like to see the completion efficiency of whole units in a few months.
Wow (Score:1)
Morality of distributed computing (Score:1)
Something about my computer time being put to work so that a bunch of scientists can invent a new drug and make lots of money; or put out a new study and get some fame. It just doesn't seem right.
Re:Morality of distributed computing (Score:2, Interesting)
1. Must Be Non-Profit. If it is for Profit I Must get a cut.
A. example: Seti@Home is run by the University of Berkley.
B. United Devices is for profit (think about it, Drug companies will make money). However, Easynews.com gives me 2 free Gigs of access a month for running it. Hey all I want is a piece, and I am getting it.
2. A DC project must be bug free. This may seem like a bloody obvious sort of thing. But considering the state of software releases nowadays one might think I am asking for a miracle! Seriously I understand the point of Version 2 releases and stuff like that. As long as it is handled competently and professionally I probably will forgive them. But I will have zero patience for a DC project that crashes my machine or keeps me from running ANY app. And that leads me to rule 3...
3. A DC must take a back seat to.. everything. It must also be maintence free.
Does this require any explanation?
4. Finally, it must be controversy free.
I have yet to come across a
What about small things that change weather? (Score:2)
I'm not going to reprint the page [rl.ac.uk] ,HadSM3,HadCM3,HadCM3L)
unless it get's slashdotted, but none of the models (HadAM3
in the simulation take into account the biological factor.
It has been said, that both termites, cars, factories, cows, and Taco
Bell produce huge amounts of greenhouse gas which do attribute to global
warming. How can this lead to an accurate prediction model if these factors
aren't accounted for?
Re:What about small things that change weather? (Score:2)
El nino (Score:1)
Re:El nino (Score:1)
(It appears from Mayan records that they had a few years off unseasonable weather that brought them to the edge---and redoubling the human sacrifice rate not only didn't work but ran into resource constraints).
Sounds Like Bad Science (Score:2)
Those models wouldn't be "validated" as the poster claims, or would they? It seems to me that without identifying the reasons the computed models differed from the measured results, the selection is damn near arbitrary -- the difference may be something the scientists never considered.
I've been wrong before.... once.
This is called "Boostrapping" and it is practical (Score:5, Interesting)
My background - you develop a program to predict something biological. Let us say, to pick a problem on the same order of difficulty as predicting the weather, that you're trying to predict the three dimensional confirmation that proteins assume, based on their sequence.
Now, okay, you have a bunch of known sequences, which other people (personally, I do both the data mining and some crystalography) have attached to known structures. So, what do you do?
Well, you could fiddle with your program until it predicts really well on those sequences, and announce that it was good. This is "Bad Science", as the parent-poster points out, since the criterion are arbitrary - you have a tendency to "discover" random noise in the data, and you have no way of validating your results.
So, second option. Instead, you split the data in half at random (actually into more than 2 pieces, but conceptually in half.) You take one half, and you make the model predict as well as you can on that data. Then, you VALIDATE ON THE OTHER HALF OF THE DATA. You *never* change the model on the basis of the second half of the data - that is arbitrary/bad/cheating. This is called "bootstrapping". It has nothing to do with compiler installation.
So, as far as most scientists (as opposed to mathematicians) are concerned, the important question is - does this work? In the biological sciences, I can say categorically, yes, this bootstrapping technique has a proven track record. It does work. Obviously, you can screw up (using non-representative data is a good start) but the technique, when properly applied, is sound.
So, I assume it would work for predicting the weather, as well. By work I mean - you would know how well your software predicted the weather. Bootstrapping is not a means of predicting the weather in and of itself, merely of honestly evaluating the effectiveness of a weather prediction mechanism you already have.
Re:This is called "Boostrapping" and it is practic (Score:2)
I'm currently working on an application that monitors seemingly random data -- the stock market. I never stopped to consider that there may be statistical techniques above and beyond the standard technincal indicators.
Food for thought!
Re:This is called "Boostrapping" and it is practic (Score:2)
They will probably get some form of result. It wont be valid, but it will nonetheless be a result which matches the earlier period.
Of course, this will start breaking down as soon as natural climate variation changes cycle. Likely it would be invalidated even faster if they try to apply the model to known data from the last 20k years (altho if they could get the model to account for the earlier climate variations that far back, I'd tend to accept it as more valid).
I remember an example of this "bootstrapping". (Score:2)
Some branch of the US military was trying to train a neural network to look at a photograph and recognize whether or not there was a tank there.
The people designing the system had pictures of scenes without tanks, and pictures of scenes with tanks. Half of the pictures were sealed away in a safe for later testing. Then, a neural net was trained on the first half of the pictures until it could, with 100% accuracy, correctly identify if there was a tank, or not, in the picture. Finally, the second half of the pictures were presented to the algorithm, and it also correctly identified those pictures as tank/not-tank.
However, when it was tried on another series of pictures, the neural net could only accurately identify about 50% - no better than chance. The engineers who trained the net were dumbfounded, so they went back and started studying exactly what the neural net was trying to use to recognize a tank.
Finally, they found the answer - all the pictures with tanks were taken on an overcast day, and all the pictures without tanks were taken on a sunny day. The million dollar neural net had been trained to differentiate between blue and grey skies! Back to the drawing board...
Re:Sounds Like Bad Science (Score:2)
What do they mean by 'PC' (Score:1)
No doubt the odd geek has a room full of Alphas to add to the cause.
Re:What do they mean by 'PC' (Score:2, Informative)
On their FAQ [rl.ac.uk] (dated 5 Oct 2000!), they state they will support Linux initially and are looking for sponsorship to port the client to Windows. Considering the "What's New" page was last updated on 17 Aug 2001, the actual status of ports for different clients is unclear.
Seti@Home versus Climateprediction.com (Score:2)
It seems like there is a bit of professional dueling going on between this project and Seti@home looking at their FAQ [rl.ac.uk] and the quote by Dr Meyers Allen saying about their project "It's not a stripped down 'toy' version, so the runs take time"
My favorite quote from their FAQ was in response to the possible affect the computers running the client might have on the environment:
checkpoints (Score:2, Insightful)
If this thing takes eight months to complete, I sure hope they plan on storing periodic checkpoints of progress for each test in a central location. What happens if my machine gets hosed at four months? Is all that data lost?
How about weather for TOMORROW? (Score:1)
Just a thought.
Re:How about weather for TOMORROW? (Score:2, Interesting)
Speaking as someone who builds clusters to run mesoscale atmospheric models, the amount of data that's required to be passed back and forth between the compute nodes of a cluster requires gigabit bandwidth to keep decent processors happy. I don't see how a WAN-based distributed computing project without massive bandwidth and nearly isochronous data transmissions are going to be of any use in producing a working forecast. Most atmospheric models I've seen require frequent communication between the nodes to keep the processors busy. In an average run for an area the size of a couple of average states for a 36 hour forecast, the traffic on the network in a five node cluster approaches a terabyte.
Uh...good luck (Score:3, Insightful)
Therefore, how do they expect this to work -- additionally absent any outside changes in the environment?
What I mean is, how do they know if they did a good job? Perhaps if the results are all very close to the current day climate, I'd buy that they got it right, but if they have a reasonable distribution of results, how do you decide? I mean, we've been clear-cutting the hell out of forests left and right for years: do they somehow takes this into account? Heck, how do they present the geographic information about the Earth: this bit has forest, this bit is desert. I would think that this would make quite a bit of difference in results (changes in albedo, for instance).
I certainly wish them luck, but they're not getting my PC for that long without something more detailed , informationwise.
Re:Uh...good luck (Score:3, Insightful)
Notice that the dates being simulated are 1950-2050. We have historical data for 1950 to the present. One of the big accepted checks for a climate model is to run a period for which you have historic data from the same initial conditions and check to see if you end up with similar answers to reality. Pretty simple, in theory. The real problem is that the cell size is just enormous. Do you have any idea what sorts of ocean current and landscape variables are contained in a 3.75x2.25 degree square? To get better results, you need small cell size and very detailed modeling of feedbacks. However, the shear range of permutations that can be attempted with a seti@home size user base is useful in and of itself.
Re:The more I look at it... the more it sux. (Score:3, Insightful)
On the contrary, scientists first formulate a hypothesis (in other words, a preconceived notion; human activity has led to global warming, for instance) and then perform an experiment to test it. And like it or not, global warming is occurring. The average temperature of the planet is rising, which is all that is meant by global warming. Whether or not this is the result of human action is still being contested. <OPINION>But personally, I would be very shocked if human activity has had NO effect whatsoever on the climate of the planet.</OPINION>
Next in news (Score:3, Funny)
Re:Next in news (Score:1)
Re:Next in news (Score:2, Interesting)
From the FAQ:
Won't all these computers being left on for 24 hours a day have a detrimental impact on the Climate System?
Assume a computer running 24hrs/day requires, on average, 50W of power. If 100,000 computers join the Casino-21 project, the project will require 5,000kW of power. There are 24 hours in a day, so each day the project will consume 120,000kW-hrs, or 432,000,000kJ of energy.
That's a big number, so let's try and put it in perspective by calculating how much energy is necessary to boil water for a cup of tea. Assuming a specific heat of water of 4.19 kJ/(kg-K), 0.237kg/cup of water, a necessary temperature rise from 20 degrees Celsius to 100 degrees Celsius, and that only one cup of water is boiled for each cup of tea, then about 80kJ/cup of energy are necessary (assuming our kettle is 100% efficient). This means that running the Casino-21 project for one day is equivalent to boiling water for 5,400,000 cups of tea.
Is 5,400,000 cups of tea a lot? According to the Tea Council, some 37 million people in the United Kingdom drink, on average, 3.4 cups of tea per day. That's nearly 126 million cups of tea per day in the UK alone!
Each day, about 23 times more energy will be spent boiling water for tea in the United Kingdom than would be used by the computers involved in the Casino-21 project. More seriously, a rough calculation suggests that 100,000 computers running 24hrs/day for one year at a power consumption of 50W will contribute approximately 0.0001% of the total amount of CO2 generated in one year. This is not an insignificant amount, but seems (to us) a worthwhile investment to better understand the climate system.
Re:Next in news (Score:2)
According to it's datasheet, it's typical power consumption is 59.2W. Add to this the rest of the cards in the system, RAM, chipset, HDD, CD, etc. Lets say the total is 80W, which is conservative. You don't need a fan on your NB or your GPU for nothing, although when you're not doing 3D the latter shouldn't be hot. Then you have the power supply, the efficiency of which is usually 70% at full load, and less than that if it's not fully loaded. Since the vast majority of PSU shipped nowadays is 300W, and 80W is way lower (but you still need 300W for peaks, like when you boot or game, or if you have quite some cards or HDD), the efficiency is probably around 50%. The rest of the calculation seems correct, so the total for 100 000 computers is about 17.4 million cup of teas.
Total is, it's still lower than the power needed to boil the number of cup of tea drank in UK in a day (I would have taken coffee rather than tea for the example, as it's more common internationally), but the starting figure of 50W per computer seems low. In my room, my 2 computers quickly heat the room more than if I have a 100W light bulb on (although part of it is light, so doesn't heat the room as much).
Just to do this calculation is intersting: it shows the relative weight of some human activities. I'd also really like to have an accurate view of the electrical consumption of my computers.
And since I prefer cold juice to tea or coffee, I don't take part as much as you to the global warming. My drink gives back more heat than it absorbs
Re:Next in news (Score:2)
Idle: 107 watts
Unreal Tournament: 132 watts
Re:Next in news (Score:2)
Ouch. You have an expensive computer. My 1GHz Toshiba laptop draws about 30watts finding prime numbers. I bet your air conditioner gets a workout.
Re:Next in news (Score:2)
I bet what you save on electricity bills, he saved at the time of purchase.
Re:Next in news (Score:2)
My laptop draws only 20 watts. I don't play unreal tournament on it though.
Laptops aren't optimized for speed. I'm sure you're getting less than 1.0/1.8 of the performance as my system. Throw in consideration for the power wasted by my honking graphics card, and you're probably not getting more instructions per joule than I am.
BTW, I only run that beast of a machine when I'm using it.
Re:Next in news (Score:2)
That was the point.
When you pay x joules to a fridge for him to keep your juice cold, he extracts some more heat from that juice before relinquishing (x + some) joules in the surroundings. The x joules are what is used to cool it, the balance is only displaced from inside the fridge to outside, and doesn't really participate in global warming since if I take the juice out of the fridge, that same heat can bring it back to the temperature it was at before I put it in the fridge. Still following?
Secondly, the heat needed to be removed from the juice is less than that needed to boil a cup of water or of coffee (the temperature difference is way smaller).
Therefore, it uses less energy to cool it (so less participation in global warming), and since when I finish it it's a bit warmer than when I started to drink it, but still colder than before I put it in the fridge, it gives back more energy (when in the fridge) than it absorbs (when I drink it).
So it's better to drink juice or a pop than coffee.
Other Uses, Such As Proving Obscure WX Theory (Score:2)
Perfect example would be an article out of the latest AMS Bulletin of the American Meteorological Society Earth Interactions [allenpress.com] that discusses plane contrails. It seems that the lack of air traffic after 9/11 allowed the meteorlogist to work on a long held theory that plane contrails affect weather. Only problem was that the dataset was only over three days, which was just a small time sample.
Using a system such as this, those weather conditions could be recreated over a longer period of time and the results could be realized. Too cool.
obligatory smartass response (Score:2)
You should wait until the results come in.
Say "cool", global warming leads to ice age (Score:1)
Say "cool", global warming could lead to an ice age. One theory predicts that warming can lead to too much fresh water being introduced into the north atlantic and decrease salinity levels beyond a key threshold. This in turn "shuts off" a descending (vertical) current, which in turn disrupts the gulf stream (horizontal) that currently sends warm water north, which ultimately results in cooling in north america and europe.
FWIW, there is evidence that the above occurs fairly regularly on a geological time scale. Man's efforts may or may not have much of an impact, it may or may not be egotistical to think we can change weather patterns with our SUVs. Perhaps if we have an impact the system was teetering on the edge in the first place. Not that this justifies a push over the edge.
What about the "funding" factor? (Score:3, Funny)
In simulation B we set the Funding Amount variable to 200,000$ and the Donating Corporation to Exxon Mobile. Their result was no global warming at all in 2050.
In simulation C we set the Funding Amount variable to 300,000$ and the Donating Corporation to Amazon Lumber Harvesters. Their result was an actual decrease in green house gases by the year 2050 due to deforestation.
In simulation D...
Suggestion (Score:1)
Wait eight months and tell us!
Patterns... (Score:2)
Wow, that same method is used to pick stocks (Score:2)
Reminds me of a friend of mine. He tried to use neural nets to predict trends on commodities by training different models with tons of data, and then using the best fitted time series to predict future trends. It seems pretty obvious to some people, but it just doesn't work. The models may be simplifying the data, but they are not basing it on true relationships. For systems that have well-defined dynamics and precise measurements, you do have a fighting chance with this approach, but I doubt that the weather falls into either of these categories.
What he didn't realize (Score:2, Funny)
Interesting (Score:2)
Won't all these computers being left on for 24 hours a day have a detrimental impact on the Climate System?
Thanks to Craig Greenock for this one, and several others since. Assume a computer running 24hrs/day requires, on average, 50W of power. If 100,000 computers join the Casino-21 project, the project will require 5,000kW of power. There are 24 hours in a day, so each day the project will consume 120,000kW-hrs, or 432,000,000kJ of energy.
That's a big number, so let's try and put it in perspective by calculating how much energy is necessary to boil water for a cup of tea. Assuming a specific heat of water of 4.19 kJ/(kg-K), 0.237kg/cup of water, a necessary temperature rise from 20 degrees Celsius to 100 degrees Celsius, and that only one cup of water is boiled for each cup of tea, then about 80kJ/cup of energy are necessary (assuming our kettle is 100% efficient). This means that running the Casino-21 project for one day is equivalent to boiling water for 5,400,000 cups of tea.
Is 5,400,000 cups of tea a lot? According to the Tea Council, some 37 million people in the United Kingdom drink, on average, 3.4 cups of tea per day. That's nearly 126 million cups of tea per day in the UK alone!
Each day, about 23 times more energy will be spent boiling water for tea in the United Kingdom than would be used by the computers involved in the Casino-21 project. More seriously, a rough calculation suggests that 100,000 computers running 24hrs/day for one year at a power consumption of 50W will contribute approximately 0.0001% of the total amount of CO2 generated in one year. This is not an insignificant amount, but seems (to us) a worthwhile investment to better understand the climate system.
Assuming you are convinced this experiment needs to be done, there are basically two options: to buy a hangar-full of PCs and run it ourselves (not even an option right now, since the climate research community doesn't have the resources); or to recycle spare CPU out in the community, as we propose to do under the Casino-21 experiment. Since the main environmental impact of a PC is in manufacture and disposal, not the power consumed in running it (never mind the air-conditioning costs and visual impact of that hangar on some innocent rural community), environmentalists will, we hope, approve of our strategy.
----/SNIP FROM FAQ----
I found this interesting. I've always worried about leaving my computer on 24/7/365 because I feel so wasteful of electricity. Not that I won't, but that puts it in perspective. Especially when I look around my school and see all those CPUs idling (or even just running a word processor).
What's so amazing about this? (Score:2)
And the poll is asking about CPU speed, eh? (Score:2)
Seriously, this sort of modeling will take less time as processors scale bigger and Internet connectivity proliferates. I would like to participate, but it would be nice if I didn't have to run an MS OS to do so. I can, do and probably will, but if they would just release the source
Something isn't right. (Score:4, Insightful)
Shouldn't they use the last 50 years of weather as initial conditions and vary parameters of the model instead?
What they're doing is like flipping an imaginary coin 500 times hoping to match the first 250 flips of a real coin to predict the the last 250 flips (albeit in a system with non-independent trials). But then they're taking those 500 flips and matching the first 250 to weather reports (might as well be coin flips) and then imagining the next 250 flips will approximate the future weather reports. What they need to do is fix the initial conditions and modify the model (coin flips vs. rolls of the die vs. LCRNG, etc.) to find a model that approximates the dynamics of the system.
Am I making sense here? How are these bozos not just going to apply their effective innumeracy to waste a few trillion CPU hours that could otherwise have been used to do protein folding or cancer-killing molecule matching?
--Blair
Re:Something isn't right. (Score:5, Informative)
No. The term `starting conditions' appears in the BBC article, but if you go to the website [rl.ac.uk] it says:
In large-scale simulations such as these, there are often bits of physics/chemistry/weather that have to be put in by hand because, usually, the relevant bits of science would be too expensive to calculate, or couldn't be seen on the resolution of the simulation. While it's usually pretty doable to come up with reasonable models for the unresolved effects, there are often parameters in the models that could take a range of values.
This ensemble of models allows for the callibration of the model parameters against 50 years of data; this gives some confidence in the predictive power of the models for the next 50 years.
This sort of parameter estimation based on calibration is very common for models of complex systems, and not just for computer models. Ideally, one wants to get to the point where such things aren't necessary and you can directly calculate all the science a priori of course, but these model calibrations are often useful steps along the way.
Never extrapolate a polynomial (Score:2)
It will be interesting to see how divergent the predictions for the next 50 years are from the best fits to the past 50 years.
It will also be interesting to see how badly the best fits for the next 50 years fit the past 50 years. (There's gotta be a better way to phrase that)
There's also the long term effects that we have no good means to capture, like what turns off and on the various ocean currents.
Re:Something isn't right. (Score:3, Interesting)
But what the researchers should be doing first is back-testing by using the first 25 years as calibration and the second 25 as a check on the extrapolation. Then doing it the other way around. Or maybe the distributed software does that, and all the permutations in-between.
At any rate, where it should fall on its ass is in the prediction of weather that actually makes a difference: hurricanes and tornadoes, which have crucial features that won't be well modeled, if at all, by the large differential boxes they selected. It will also run afoul of interference from random volcanic eruptions on a Pinatubo-Mount St. Helens ashfall scale, which happen on a decade or so time scale, the timing and location of which would be critical to the rest of the test run.
So I'm going to stick with my attitude that this is a tragic waste of CPU cycles that might actually go towards developing a drug that might actually save a life.
--Blair
P.S. SETI is likewise a waste; if we do hear a beep in the darkness, our only logical reaction will be to band together 6 billion of us as one to build the biggest, nastiest zero-time-of-flight weapon we can create, then hunker down in the sweaty dark to wait to fire it. Anyone coming that far is going to be wanting to make a buck off of it, taking chunks of the planet or slaves, and they're going to be ready for casual resistance.
Re:Something isn't right. (Score:3, Insightful)
PS: IMHO, volcanic ash effects are overrated.
Re:Its a Complex System (Score:2)
The world as you know it changes every three months.
It's a reflection of the fact that each human's understanding of the universe depends on back-testing his current understanding with his understanding of the history, and that it will be invalidated by events that could not have been predicted that add up to a gross revision of the model fairly regularly.
And human brains are uniquely designed to recognize and compare these patterns in gross.
Human societies are as malleable as they are varied. (Because that's how they got to be so varied, see?)
You might think you're creating a predictive model, but it only works to predict within those facets of society for which reality has not yet invalidated the model.
A similar problem exists in using back-testing to tune models to predict the stock markets. It's succinctly summed up by the old brokerage saw:
Past results are no guarantee of future performance.
Which is to say, all "technical trading" is as good as voodoo.
The climate may be more tractable, as it hasn't as yet involved control by something as truly random as a human. But the Global Warming argument indicates that the more paranoid among us at least are finding evidence that weakly correlates human activity with climatic change.
But I still don't think the people doing this particular modelling are using a fine-grained enough model, and are likely rushing to steal cycles from projects that are producing viable results.
--Blair
Quick Poll (Score:2)
Search For A Cure Instead (Score:2)
TKOE perhaps? (Score:2, Insightful)
Have you ever thought of how much garbage the world population puts out, trees we cut down, pollutants we flush, and general mayhem we induce?
Maybe we should be using our excess computing time into working on projects that actually might affect our environment in a positive way, rather than saying we should see what it is going to be like down the road...we all know what is going on here, and I'm not talking about global warming.
Its not the effect of global warming that is our problem right now, but the effect of our blatant misuse of resources and obvious disregard for the earth. Do we not live on this planet with the environment we are destroying...I don't think you need to be a very good scientist to realize that when the environment is decimated, we will be hard pressed to survive...
I guess everyone has some idea that God is going to come and fix everything for us, so we don't have to worry about cleaning up...hey, why don't we all call our mommys and see if they will do our work for us...why don't we own up and say, "Holy shit, I don't want to take the chance that my children are not going to grow up because I ruined their world for them." What is our general purpose in life besides taking up space, making money, and destroying the environment?
The world is a big place, but eventually our actions are going to reach around to spank us, just like our mom's did when we were bad...except it won't be a spanking we live through:/
I invite everyone to spend their 8 months attempting to exact reform in our environmental policies and personal resource use, rather than hoping your computer will somehow figure it out for you.
Splitting it up (Score:2)
"How's the global climate simulation going?"
"We're still waiting on the data from Australia. We sent it out to 5 people but we haven't gotten anything back yet."
In the meantime, the Earth's atmosphere bursts into flames and makes the whole point moot.
Extrapolation not pratical with chaotic systems (Score:4, Insightful)
Chaos is gravely misunderstood though so let me real quick through in my explaination for why this experiment will just generate FUD.
Chaotic equations are chaotic not because of the number of variables involved but because of the interdependency on themselves (each iteration requires the former iteration). This leads to extreme sensitive dependency on initial conditions (a.k.a. the Butterfly Effect). I should have probably emphasized the word extreme because even the slightly deviation will produce dramatically different results.
Even the best climate prediction algorithm would be crap if the initial condition was off by 10^(-20). The fact that we cannot measure temperatures exactly means that we could never feed a perfect initial condition.
Chaotic equations do have a given period before divergence gets extreme when initial conditions are altered. The original equations that Lorenz used (the pioneer of weather forecasting and the father of Chaos theory) showed divergence after about three days (which is why five-day forecasts still suck to this day).
I find it very hard to believe that these folks have developed an equation that doesn't show divergence for 100 years. Not to mention the fact that the number of initial conditions are much larger than the project makes them out to be.
Summary: Some PhD is looking for research money and figures that mixing "scientific" proof for global warming, chaos, and SETI-style distributed computer has to be good for a couple million at least.
Climate and weather (Score:2)
Re:Climate and weather (Score:2)
But does any chaotic system exhibit such behavoir??` The mere fact that climate is study of average weather is irrelevant to the system at hand. It is equivalent to studying the trends of a graph between [0, 10] and [0, 10000]. A chaotic system will by definition exhibit divergence either way with a slight change in initial conditions.
Re:Climate and weather (Score:3, Insightful)
Yes. In fact, any system which displays locally nonlinear disturbances in a globally linear function will do so.
The mere fact that climate is study of average weather is irrelevant to the system at hand.
No it isn't. It should immediately alert you to the possibility that climate might be more predictable than weather. Averages always have lower variance than the underlying data.
A chaotic system will by definition exhibit divergence either way with a slight change in initial conditions
This isn't a rigourous definition you're talking about here, and your definition doesn't prove your point. A chaotic system might exhibit divergent behaviour, but that doesn't necessarily require that the divergence be either permanent of large in relation to an underlying linear trend. For example, if I take the output of a nonlinear oscillator and add it to the signal for Radio Luxembourg, I can make a system which is "chaotic" in the sense that its local behaviour is divergent in a nonlinear way dependent on small variations in initial conditions. But I can still extract a useful signal from my system by applying the right filter.
Re:Climate and weather (Score:2)
But that is because part of the system isn't chaotic. This argument relies on the assumption that part of the climate system is not chaotic. The article points out things like El Nino as an example of such parts of the system that may exhibit predictability but even El Nino is not predictable in any way other than making an educated guess. It also is still dependent on localized prediction.
This experiment is trying to make a prediction 100 ahead in a system. Extrapolating the data from 50 years doesn't seem to make any sense because of the fact that the system is nonlinear to begin with and therefore doesn't lend itself to extrapolation.
Re:Climate and weather (Score:2)
Your example has no dynamics at all, so it hardly qualifies as a useful example of a non-linear dynamical system.
Furthermore, if your example is to be applied to weather/climate, you seem to be suggesting that weather is a small effect compared to long-term climate variation, but the daily fluctuations in temperature, not to mention the annual differences between summer and winter are *larger* or comparable to the long-term climate variations. The longer-term secular trends are much smaller (a few degrees per century, say) compared to the chaotic portion (tens of degrees daily departure from "average")!
Re:Climate and weather (Score:2)
You are quite wrong if you think it's impossible to filter out nonlinear distrubances.
Your example has no dynamics at all, so it hardly qualifies as a useful example of a non-linear dynamical system.
I think you're out of your depth here. I've described a system with non-linear distubances to a linear system. My whole point was that you can't argue from the local non-stability of the data to the conclusion that the whole system has nonlinear dynamics.
Furthermore, if your example is to be applied to weather/climate, you seem to be suggesting that weather is a small effect compared to long-term climate variation, but the daily fluctuations in temperature, not to mention the annual differences between summer and winter are *larger* or comparable to the long-term climate variations.
You completely misunderstand my point. I simply suggested that the effect of weather on the *average* climate might be small and non-persistent. For example, the daily and monthly fluctuations in the stock market are large compared to the long term return, but it's well known that stock returns are more predictable over long holding periods than short ones.
The longer-term secular trends are much smaller (a few degrees per century, say) compared to the chaotic portion (tens of degrees daily departure from "average")!
Yes, but, you fool, if you're concerned with melting icecaps, a change of a few degrees in the 100-year average temperature is much more important than ten degrees for a day.
Re:Climate and weather (Score:2)
Your comment about the melting icecaps makes my point for me. That the longer term climate can shift between qualitiatively different regimes (ice age vs. tropical) with small quantitative changes indicates that the longer term trends are indeed chaotic. The climate signal you are looking for in the presence of large short-term effects is both small and likely chaotic---exactly opposed to the examples you present.
To further explain the "dynamics" comment I made; the presence of the large radio signal does not feedback in any way to affect the nonlinear oscillator, and the nonlinear oscillator does not affect Radio Luxembourg [Neglecting the unfortunate fact that RTL is now off the air.] To use the linear combination of the two as an analogy to the weather only works if the melting of ice doesn't depend on the daily temperature.
Re:Extrapolation not pratical with chaotic systems (Score:3, Insightful)
Here's the difference. To predict the weather would mean to give the exact distribution of temperature, rainfall, wind etc at a certain date. This is what the weather report after the news is all about. This cannot be done reliably more than about 3 days into the future, because the system is so chaotic.
The climate is a different matter. It's basically an average of the weather. What they want to predict is things like the average temperature for period 2000-2010 in North America, for example. Over long periods (centuries or more), climate seems to be chaotic, too. It is certainly at least partially chaotic on smaller timescales, but there should be trends that are more or less predictable on medium timescales (decades?).
For example, if there are more greenhouse gases in the atmosphere, then this has an effect on the average weather, so one might expect average temperatures to rise. But even this is not yet completely understood. For example, increased levels of CO2 might increase cloud formation, which might increase albedo, and hence decrease the temperature. This is not yet completely understood, not because the subject matter is inherintly chaotic and thus impossible to understand, but rather because the science of climatology is not yet sufficiently advanced. This is precisely the point behind this project - to advance our understanding in climatology, so that we can better understand the effects of greenhouse gases, for example. By no means does this justify the American energy policy of sitting back and happily burning fossil fuels with gusto, until the scientists are 99.8% sure that it was a bad thing and now it's too late. That's a bit like Russian roulette: "The scientists can't yet prove that this chamber is loaded, so we might as well pull the trigger".
To sum up what is known so far: increased levels of CO2 (and other "greenhouse" gases) has a very real effect on the climate. Exactly what this effect is, is not yet 100% sure, but it seems most likely to raise the temperature. On the other hand, the world average temperature has increased dramatically over the last few decades, correlating strongly with rising CO2 levels. Of course, there are natural climate fluctuations, so this could still be a coincidence. We haven't proved with 100% certainty that our increased emissions are responsible for global warming, but it seems very likely. That is why we should try to do something about it.
In summary: Global warming is a very real threat, and not just to some unheard-of third world countries. It affects you, Americans, too. Yes, you! Hence this project is very important and potentially very useful. I hope they get a lot of support.
Re:Extrapolation not pratical with chaotic systems (Score:2)
Which is still chaotic. See my response to the first reply in this thread.
It is certainly at least partially chaotic on smaller timescales, but there should be trends that are more or less predictable on medium timescales (decades?).
No, not in a chaotic system. The most that could be accomplished is that a small sampling from today's climate could be used to understand what possible climatical period we are in but this is not what the experiment is attempting to do.
What that would entail is collecting data in order to generate an attractor for the system. This would involve calculating phase-space coordinates. This project is attempting to extrapolate a system that can't be extrapolated.
I won't get into a global warming debate here as that wasn't my intention behind my original post but please note that bad science hurts everyone on either side of the issue.
Re:Extrapolation not pratical with chaotic systems (Score:2)
No, you're mistaken. You seem to be making the elementary mistake of confusing climate modelling with weather forecasting. Curiously enough, you've fallen victim to the very thing you accuse the experimenters of: you made a (relatively) small blunder before you started writing, which has rendered the rest of your comment utterly irrelevant.
Further research is left as an exercise for the original poster. If you can't be bothered to read the article, or the detailed write up on the project's site, I can't be bothered to point out all the places you're wrong.
Re:Extrapolation not pratical with chaotic systems (Score:2)
Don't get me wrong, either... I'm not trying to dog on this particular guy, since there are a bunch of other crap posts in reply to this story.
So, before we start, I am a mathematician, and I pretty much do applied dynamical systems (applied chaos theory, in lay-terms). (Always wanted to drop that N... Woo)
If we buy the argument above (essentially: weather is chaotic, therefore cannot be modeled, so let's quit), then there would be almost no science done on nonlinear systems. But people are studying chaotic systems all of the time, and doing good science.
Yes, it is true that the weather exhibits sensitive dependence on IC, but so does just about every physical system, even linear ones. (Think of standing a pencil on its end. Let it go. Which way will it fall? Repeat 100 times.) Just because something exhibits SDIC does not mean it cannot be modelled and does not mean no prediction is good. For example, consider a mixing fluid (say milk in your coffee). There's no question that there is chaos in the coffee if you look at it, but, no matter what you do, you expect to see a homogeneous light-brown mixture eventually. To say that I cannot predict the eventual state of my coffee is wrong.
I want to make three points:
I also don't want to get into the debate about global warming which inevitably comes up, but some of the above fallacies always crop up in the arguments against it. It is certainly true that we don't understand the climate completely, not by a long shot. But the amount of evidence that the earth is warming, and that we are playing a role in this warming, is becoming very large. It is certainly not sure one way or the other, but, anyone who says that they are sure it is not happening (as I have seen other posters in this thread do) is simply completely full of shit.
Well, ok, that's enough rambling for one night... just wanted to get that off my chest
INFORM yourself with the FACTS (Score:4, Informative)
... or at least the best science has come up with so far, are downloadable from the Intergovernmental Panel on Climate Change (IPCC) [www.ipcc.ch].
I'd start with the Summaries for Policy Makers, as a way of becoming very well infomrmed in just ~20pp.
AFAIK: It's a UN organization that is the center of research. Their reports are a consensus of almost all the leading scientists from every country on the globe, and their policy statements are approved line-by-line by governments. Even with all that, there are pretty strong statements.Here's better background [ucsusa.org].
Re:INFORM yourself with the FACTS (Score:3, Insightful)
Close... the IPCC was designed to collate all well-reviewed, reliable, statistically sound studies done around the world, and describe the consensus of opinion amongst researchers in the field.
RANT MODE = "ON"
The idea was to prevent scum-sucking American corporations from buying the US Government (by convincing the typical Merkin in the street) and preventing the measures required to help allleviate the threat, from being introduced. Of course we (rational human that is) reckoned without the extraordinary phenomena of Gee Dubya. The US is now storing up
Better luck in 2004.
Re:INFORM yourself with the FACTS (Score:2)
The first two things you mention don't dispute the increase in temperature; they say, like the IPCC, that it is uncertain whether the pollutants caused the increase. (I'm basing that on the linked website and reviews I've read of Lomborg's now famous book; I haven't read the book itself. I don't know anything about the "Environmental Overkill" book).
Again, I encourage you to read the IPCC documents. They are politically very neutral, and state the evidence *very* carefully. After 30 min., you'll be better informed than your friends, the media, most slashdotters, and almost all the politicians.
The most important point is, however, that we must make decisions before we know for sure what is going on in the climate. Like all real life, we must decide with incomplete information. That is nothing new in politics -- in fact, it's the case 100% of the time. But it's not science, which strives to produce timeless certainties. So in the end, the decisions are political, hopefully well informed by the answers science has produced so far.
Shortsighted? (Score:2)
Let's estimate the average income of everyone in the US over time by looking at people in Rhode Island for the last three days. Same sampling scale, or close.
Useless experiment to hype up the global warming debate again. Gee, I wonder if they'll pick any of the initial conditions that say "things aren't so bad after all". Nope, the only starting conditions that will ever see the light of day are the ones that back up their theory.
Not that the science on the other side is any better. I'm getting tired of the entire debate because, guess what kids, this is supposed to be SCIENCE. Not prognositcation. There is a difference. Come up with a theory, build a series of experiments to prove it, and see if it sticks to the fridge or not. All I'm seeing here is "come up with a theory, pick the data points that will support it, and then publish it in the NY Times".
Waste of Time (Score:2)
8 months is a long time... (Score:2)
I don't know how much amount of immediate data that needs to be stored, but there definitely should still be a mechanism for periodically sending up progress-dumps so that somebody else can take over from wherever you were. This could at least shorten the time for having all the data run since you would notice participant drop-outs earlier and could hand over the rest of the calculations to another participant.
It could also be used to sort out really bad seeds at an earlier stage where the system, for example already after 10 or 20 years discover that you are way off and could hand you another seed instead.
call me the enternal naysayer (Score:2)
And with this specific project - isn't the earth's climate largely dependent on the amount of solar output, and isn't that amount relatively variable? How are they gonna know the slight variations in solar output over the next 50 years?
Initial conditions don't matter... (Score:2)
Now this is a climate model and not a weather model, but I fail to see how the hell that's anything more than a labeling difference.
OK (Score:2)
I'll give you that, but in weather it still doesn't matter. Given the uncertainty priciple it's impossible to know the inital condtion for a system such as the weather. So even if they have the right mathematically model (which I doubt) this is still all futile.
Re:Energy cost of experiment (Score:2, Interesting)
"Many people have complained about the screensaver aspect of the Casino-21 client, and rightfully so. Screensavers only run when a computer has been idle for a period of time, are resource-hungry and place a limit on the platforms that can be supported. A background client will run whenever there is spare processing power, can be made more efficient than a screensaver and will support many more platforms. Following all of your suggestions, the Casino-21 client will be designed to run in the background. An additional client will be provided to view the progress of your climate simulation, and will be able to be run in screensaver mode when applicable."
So...Running the screen saver is not necessary.
Re:Rediculus (Score:2)
Maybe they're not interested in data that far back simply because it would be harder to really match it to a model that includes the effects of things like CO2 emissions.
Using the last 50 years makes it easy to get a model that points to human interference. Using or verifying against several centuries or millenias worth of data could indeed make it more accurate, but it would rather point to natural variation from causes like solar radiation output, vegetation changes, etc.
Re:Brute force solution. (Score:2)
Climate prediction is not about dynamics,it is about statistics. In other words, it is about identifying the shape of the butterfly, not where the dot happens to be on the butterfly.
So you have just made a much more sophisticated version of the same error that everyone who wants to believe that climate principles are somehow unknowable (ooh, "chaos", so let me keep my SUV) are making.
Tuning the model to generate appropriate statistics is very different than tuning the model to generate very specific dynamics. In the latter case you are limited by chaotic nonlinear dynamics to a few weeks. In the former, you are trying to identify processes that are interacting in complex ways but are fundamentally dissipative and hence predictable in principle.