Distributed Computing World Climate Simulation

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?)."

Comments

Infeasible

[Enonu]

Blame the climate changes from 1950 to 2000 on the expanded use of the automobile and unregular industrial waste. Do you think any scientist in 1950 could have known about our current situation? How can we in 2000 know about the new problems that'll creep up between now and 2050?

Spend your extra CPU cycles computing the cure for cancer or finding ET. I doubt this will prove useful.

Re:Infeasible

[Papineau]

I think what they want to do is, given the state in 1950 and what we know about the inputs (use of automobile, etc.), which models predicts correctly what we see in 2000, so that those models can then be used, along with some new inputs, to forecast what 2050 will be. Either prospective inputs, to get a glimpse of our possible futures, or actual inputs, to further validate the model or get a sharper view of the future climate.

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.

Something isn't right.

[blair1q]

They're starting with different initial conditions and hoping that some subset results in 50 years of weather?

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

Extrapolation not pratical with chaotic systems

[lkaos]

As one poster has pointed out, weather is a chaotic system (and climate is also chaotic by definition).

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.