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Supercomputing Upgrade Produces High-Resolution Storm Forecasts
dcblogs writes A supercomputer upgrade is paying off for the U.S. National Weather Service, with new high-resolution models that will offer better insight into severe weather. This improvement in modeling detail is a result of a supercomputer upgrade. The National Oceanic and Atmospheric Administration, which runs the weather service, put into production two new IBM supercomputers, each 213 teraflops, running Linux on Intel processors. These systems replaced 74-teraflop, four-year old systems. More computing power means systems can run more mathematics, and increase the resolution or detail on the maps from 8 miles to 2 miles.
a) we don't care if the models match
1) the most impotant thing, the one true thing, is that the model remain stable
2) if the model remains stable, then it's judged against reality, not other models. However,
3) Don't break the stability of the model
b) this is a global differential equation. We don't know the initial conditions, and the model can only approximate them. However, the finer the mesh, the closer we can get to the initial conditions, so the further out in time the model will remain useful.
TFL in TFA goes over it.
www.computerworld.com/article/2484337/computer-hardware/noaa-goes--live--with-new-weather-supercomputers.html
It's been a complicated process to get to this point. The NWS has had to ensure that the software running on the new system is producing scientifically correct results. It had been running the old and new systems in parallel for months, and comparing the output.
This comparative testing involved examining output data to determine whether it is numerically reproducible out to five decimal places. There is also a statistical analysis of weather predictions on the new system against the actual weather conditions.
The process wasn't just an examination of numerical data. NWS scientists also studied the weather products and examined them for subtle differences. "There is a lot of human, highly experienced, subjective evaluation," said Kyger.
There are computational differences involved in switching to new chips and a new operating system. They are subtle, and appear in decimal places six through 12.
As you go further out in a forecast, the differences compound. The changes may appear in the fifth day of an extended, five-day forecast as a difference of one degree.
I'm a computer engineer, not a meteorologist, but I've worked with them off and on for about eight years now. One of the most common models for research use is "Weather Research and Forecasting Model" (WRF, pronounced like the dude from ST:TNG). There are several versions in use, so caveats are in order, but in general WRF can produce really good results at a 1.6KM grid for 48 hours in the future. I was given the impression that coarser grids are the route to happiness for longer period forecasts.
WRF will accept about as much or as little of an initializer as you want to give it. Between NEXRAD radar observations, ground met stations all over the place, two hundred or so balloon launches per day, satellite water vapor estimates, and a cooperative agreement with airlines to download in-flight met conditions (after landing, natch), there's gobs of data available.
The National Weather Service wants to run new models side-by-side with older models and then back check the daylights out of them, so we can expect the regular forecast products to improve dramatically over the next (very) few years.
These simulations are forecasts. They check every forecast against observations, and have very good metrics on how good their forecasts are, and how much skill changes.
See for example how the European ECMWF does its forecasts:
http://www.ecmwf.int/en/foreca...
Every change to the operational model(s) can be and is checked out first against " will it improve the forecast". Similarly improvements in computing power: we simply run yesterdays forecast at higher resolution for example; we can then say "this new model is n% better, but takes 10x as long to calculate", and use that to decide whether its worth buying a faster computer.
On the climate timescale we have a challenge verifying the simulations, but on the weather timescale its straightforward, and done.
Anyone who believes exponential growth can go on forever in a finite world is either a madman or an economist