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Supercomputers Race to Predict Storms
pillageplunder writes "CNN has an interesting article on how different supercomputers from around the world are working to predict large storms tracks. The 3 days it takes now has been cut in half. Cool read."
Oh wait, that's the job of the Diebold supercomputer.
If you think
I'll be impressed when I see supercomputers chasing tornadoes around Kansas in rusty pickup trucks. Not before.
lysergically yours
Actually if you read the article you will realize that it only takes about an hour of number crunching, but that the three day storm path accuracy errors have been cut in half... and that 5-day forcast is getting much more accurate.
I guess we should read articles before submitting them...
D.O.U.O.S.V.A.V.V.M.
I like how the article says: Just as a 5-megapixel digital camera more accurately depicts reality than a 1-megapixel device, higher resolution grids can capture a better picture of the atmosphere and help produce accurate forecasts.
:)
Way to pitch to the high-tech crowd CNN
But....... imagine a beowulf cluster of these weather predicting supercomputers.
Chris
Yeah, the Earth Simulator http://www.es.jamstec.go.jp/ does try to do this, however it does a vast number of other things as well. The other systems focus on more specific incident (such as Ivan), thus more computing power is aim'd at a short-term problem.
Earth Simulator does - Atmosphere & Ocean Simulation, Solid Earth Simulation, Multiscale Simulation, and Advanced Precipitation Simulations. (And other cooperative projects).
I am
http://www.sgi.com/company_info/newsroom/press_rel eases/2004/june/fleet_numerical.html
Nope, the Earth Simulator is to predict overall climatic change, not specific weather conditions.
...but still not as fast as "nowcasting" (and yes, it's an actual meteorological term.) I've always wondered why the local news just has to tell us, "And in downtown it is currently raining at the moment." The people who go outside already know, and the rest of us don't care.
According to New Scientist 28/08/2004, it's a little more to do with long-term climate change, rather than predicting if you need your umbrella tomorrow in Bristol... Earthquakes and the Earth's magnetic field are also modelled too apparently...
A snip at $430 million...
No Norm, those are your safety glasses; I'll wear my own thanks...
The models -- actually complicated software written in a computer language called Fortran -- attempt to account for everything happening in the atmosphere on a global basis.
... actually I used to work for the National Weather Service ... C++, Tcl/Tk, and even Fortran ...
Well no wonder weather prediction is so off!
I kid, I kid
The storms will hit the Caribbean and Florida in September.
I currently work for NOAA at a facility called GFDL. We house some of the super computers here. I currently operate and control the computers and its deffinitly a treat to be able to work with these fast machines. We have some of the worlds fastest computers here and they compete very well with the earth simulator. We also have some of the top hurricane guys working for us as well. It is good to see that the techonology that we use is getting publicity. It will inform everyone how things are done and where they get the information from.
You don't know too many scientists-turned-programmers do you? Fortran is still alive and well in scientific circles. Companies like IBM and SGI still write and optimize Fortran compilers for their newest CPUs. Even Intel recently released a major update to their P4 and Itanium2 Fortran compilers.
i) because most numerical weather codes are already written in Fortran. This means that people with the right scientific knowledge tend to be Fortran programmers, and makes porting a whole lot easier.
ii) Fortran compilers are the ones where the most work has gone into optimising the hardcore mathematical routines. Thus, the compiled code has traditionally been faster. This may no longer be true.
Athletic Scholarships to universities make as much sense as academic scholarships to sports teams.
They are written in Fortran because that is what they have always been written in. Keep in mind that we are talking of at least tens of thousands of lines and in some cases a few hundred thousand lines of complicated math. This isn't one of those things you port to C or C++ in an afternoon. Also note that most of these models are written by scientists (physicists/chemists) not computer scientists. Most groups now have programmers on staff to help with problems but scientific programming isn't always about having elegant code; more often then not, we care about the output and Fortran does just fine. Yes, we do mix in C where appropriate.
You can see the current predictions by each model at any given time here:n g/at200406_model.html
http://www.weatherunderground.com/tropical/tracki
The NHC discussion of the model guidance for each storm is here, under 'discussion' for each storm:
http://www.nhc.noaa.gov/
They explain why they're agreeing with or discounting each model in their overall forecasts.
Generally, it's difficult to find much prediction of hurricane tracks that doesn't come somehow from the NHC. This isn't because there aren't independent analysists, but because they try not to send mixed signals, which might lead to people not evacuating when they should. The raw information from the computer models is the closest you get to dissenting opinions, afiak.
xkcd.com - a webcomic of mathematics, love, and language.
To a casual observer of the weather, like me, it seems that the paths of the hurricanes are little more than extrapolations of the current path with a slight bend to the east. For the hurricanes this year, it seems that time and again the models proved wrong for last minutes changes to the storm. I know from family who lives on the west coast of Florida that many people were caught off guard by Charlie. I really think that it is probably impossible to accurrately predict the path of a storm. I mean I could take a look at the motion of the storm and guess about as accurately as the models guess. My same family that was caught off guard by Charlie headed to Orlando when Ivan was about a week away, but the storm didn't land near their house. If you think about it, 3 days notice is not enough to have every person in a metropolis patch up their houses and move to higher ground. Some might say that everyone with the possibilty of getting hit by the storm should prepare, but imagine having to board your windows every 3 weeks or so only to be missed by the storm. It would be even worse if you evactuated on the same schedule. This would make it very difficult to live a normal life. Honestly, the prediction of storms like hurricanes needs to get much better, but I doubt that it ever will.
SIGFAULT
Fortran is still the dominant language for programming high performance code. I'd still rather use C, but it's not really that different. When you're trying to optimize a piece of software for a machine architecture you need to use a language that is pretty low-level. The closer to assembly you are, the greater chance you have to best exploit the functionality of the hardware. C++/Java are right out.
As a resident of Florida (who's so far been pretty lucky with respect to the hurricanes), I've taken a keen interest in these models. The best place I've found to see them is at Weather Underground. Each listed storm has a "Computer Models" link at the end. See
Ivan
Jeanne.
Since the pages auto-refresh, I've just been leaving them up in a tab in Mozilla and checking them every once and a while. Though the models aren't always accurate and tend to change a lot, they kind of give you a feel for where the storm is probably going to go.
"Save the whales, feed the hungry, free the mallocs" -- author unknown
Fortran compilers are guaranteed that the programs do not try to do strange things behind their backs (such as pointer aliasing). Therefore they can make optimizations that would be almost impossible to prove valid in, say, C. Also, Fortran numerical libraries are of very high quality.
Finally! A year of moderation! Ready for 2019?
Weather simulation is not a tast you can cut up into a bunch of smaller tasks and farm out. If you cut the atmosphere up into lots of little chunks to model, after each step every chunk needs to know what the results from all the chunks around it where.
If you're waiting for those results at Internet (Latency: 100ms) speeds instead of intra-system speeds (latencyL 1 us) it takes you 100,000 times as long to get your data.
With SETI, all you do is get the data once, compute, and send back the answer.
paintball
Landfall dynamics are a VERY active point of research in hurricanes right now. Land changes a lot of variables which we can normally take for granted in a hurricane over the water... the surface has different properties, elevation changes make the air behave differently, land doesn't evaporate near as much water vapor as the ocean, etc.
u idance/at lantic/store/early_AAL06_04090300.png
So, with land, you leave the realm of an initial value problem with relatively well-understood boundary conditions that you have with a storm over the ocean to a realm that has much-less-well-understood boundary conditions. The problem becomes much harder to close, much less solve. And with a system like the hurricane which REQUIRES good knowledge of the boundary (after all, the hurricane is fueled by latent heat release by condensation of water vapor which comes from the ocean), not knowing the boundary as well as you can makes prediction much much harder.
Charley's swerve was forecast by a good number of models, but NHC played the worse case scenario card a little too long by persisting on a landfall near Tampa Bay.
Frances' stop was due to a very irregular pattern, much like a saddle point. If you are pushed any direction, you get very different behavior. You can see that on the following model ensemble plot... there's a small cluster of 48 hour predictions that are slower than the others.
http://euler.atmos.colostate.edu/~vigh/g
Ivan's bounce off Jamaica is a seriously cool research topic, since Jamaica is a mountainous island. That big elevation change could make it more "visible" to the core of the storm (unlike the plains of Florida). This will be a serious research topic for decades to come. Many of the models did not handle it well (which isn't too surprising since Jamaica is a relatively small island and the models that are used frequently are global or near-global models). And some previous storms (Gilbert, 1988) didn't even notice Jamaica as they passed over, so experience is a split decision.
So, hopefully that sheds a little insight on this issue. Land is a BIG problem for track forecasting, and we're just starting to work out the kinks.
-Jellisky