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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.
Now they can be wrong in hi-def!
How can I believe you when you tell me what I don't want to hear?
I was at a supercomputing conference back in the 90's. There were wonderful reports on doubling the resolution of the grid and so on. Advances in the scale are all good.
The questions are
a) with the increase in detail of the simulations have we converged on a solution. That is do solutions at scale N and 10N match. If they do then the resolution and model are aligned for accuracy in the solution.
b) do the simulations agree with reality.
If a) and not b) then there is something wrong with the model that is not related to compute power or problem resolution, and no amount of compute power will fix it.
Better resolution is good, but with each improvement in the system, the input data also needs to be improved and remeasured.
Ultimately the ground features need to be modelled in greater detail to match the increased resolution of the grid.
Which comes own to knowing where each tree/building and similar sized static feature is and how this affects the model.
However, as the grid increases it should not need to know where the butterflies are .
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.
The July 2013 article discusses an old model that used a 27 kilometer resolution new model that used a 13 kilometer resolution. The new article discusses moving from that to a 2 mile (3.21 kilometer) resolution.
Of course, you can get estimates for water vapour from IR satellite measurements. I saw this done also in the 1980s. At the time I didn't understand all the math used to do this, but remember that it involved taking IR emissions over several wavelength bands, and somehow combining these to infer the water vapour content at various heights in the atmosphere, under each pixel. These satellites certainly have 2-mile spatial resolution, but the problem I see there is that the polar-orbiting satellites that provide this information pass over any spot on earth about 4 times per day, so the temporal resolution is as low as the balloons'.
Finally, data from airlines is going to be largely restricted to heights at cruising altitude, so you're missing a large cross section of the atmosphere there.
And don't get me started on weather observations over the ocean, where there are very few ground stations or balloons.
The issue is that the Navier- Stokes equations being solved in weather forecasting are very sensitive to initial conditions, so it's really crucial to get the data right to set up the calculations. Sitting in my armchair, I remain a bit skeptical that we will ever be able to get the true initial conditions.
Despite all this I'm always impressed that the NWS manages to get pretty decent one-week forecasts out, despite the impossible task they face. There must be some deep voodoo in those numerical models!
This was an interesting article. However as UW's Cliff Mass has previously pointed out (And, today, he privately confirmed is still the case), NOAA is sitting on already-approved funds to purchase a weather modeling computer that's seen as a potential "game changer" for US climate modeling.
Over a year ago Congress approved the purchase of a computer that's roughly an order of magnitude more powerful than the pair mentioned in this article - but, because NOAA has a contract with IBM and IBM recently sold their server business to Lenovo, NOAA has been sitting on their hands regarding approval of the purchase of such a computer from a Chinese company.
So while the improvements mentioned in the article are better than nothing... in truth we should be a significant step beyond that by now.
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