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Supercomputers Help Researchers Improve Severe Hail Storm Forecasts (nsf.gov)
aarondubrow writes: Researchers working on the Severe Hail Analysis, Representation and Prediction (SHARP) project at the University of Oklahoma used the Stampede supercomputer to gain a better understanding of the conditions that cause severe hail to form, and to produce hail forecasts with far greater accuracy than those currently used operationally. The model the team used is six times more resolved that the National Weather Service's highest-resolution forecasts and applies machine learning algorithms to improve its predictions. The researchers will publish their results in an upcoming issue of the American Meteorological Society journal Weather and Forecasting.
'bout time.
A hurricane named Ike hit Galveston in 2009. With plenty of forewarning, 37 total deaths are generally accredited to the storms wrath. The usual number of folks decided not to leave despite advice to the contrary.
Another storm hit Galveston in 1900 with no warning. People were sitting on the beach when a wall of water hit that was taller than their houses.
Happiness in intelligent people is the rarest thing I know.
Ernest Hemingway
Deliver to their Senator Inhofe so he can throw it on the Senate floor.
Good story to read while I'm waiting on my current job on 9600 procs on my local supercomputer :-)
Currently working on scalability of a new algorithm that will ultimately get applied to nuclear reactor simulation.
As for the this story... being a graduate of University of Texas I do have to snicker a bit that Oklahoma has to use our supercomputer ;-)
global warming. Those Republicans are responsible for all of the damage.
And trying to drown us with increased rainfall!
They just don't give a damn about us.
And the floods those people cause
The article is fairly light on the details of what they're doing. It's also deceiving.
Warn-on-forecasting is highly unlikely to result in severe thunderstorm warnings issued hours in advance. Right now, warnings are generally issued when any two of these three things occur: 1) the atmosphere is favorable for severe or tornadic storms; 2) radar indicates that severe weather is probably occurring; 3) storm spotter reports indicate that severe weather is occurring. If spotter reports are credible enough, warnings may be issued on the basis of those even if the other two conditions are marginal. Warnings are issued based on observations of something that's happening now. Warn-on-forecasting will involve issuing warnings because numerical models of a storm indicate there is a high probability a thunderstorm will become severe or tornadic in the future. These warnings will still be based on actual storms that have already formed and are likely to be for lead times of an hour or two.
We already have predictions for when storms are likely to be severe hours or days in advance. The Storm Prediction Center issues convective outlooks as much as eight days in advance. They also issue severe thunderstorm and tornado watches, which are hours in advance. They indicate areas where there's a high probability of severe weather, but they're not forecasts for individual storms. They're more general in nature.
What's really going on is that researchers have data mined the characteristics of a very large number of thunderstorms to determine what characteristics are the best indicators of hail size. They've developed another algorithm for identifying and tracking individual thunderstorms, so they can track those characteristics over time. It seems like the algorithm may be an improvement over prior storm identification and tracking algorithms, though a huge number of these algorithms exist. They're using the algorithm to track storms in both observations and forecasts that come out of numerical models. They've also improved the grid spacing of the models, going from 3 km horizontal (the resolution of the HRRR model) to 500 m horizontal. Presumably they've added more vertical levels. When you increase the resolution, you also need shorter time steps in the model, otherwise you'll get what are called CFL errors and the model won't run (or won't run properly). I believe dt for the HRRR is around 18 seconds, so you'd probably have to lower dt to 3 seconds (maybe lower) for a 500 m model. Also, instead of running the model once, they're running an ensemble, meaning that they have 50 or 100 different model simulations with slightly different initial conditions so they can determine the probabilities.
What's missing from this are three things, though those researchers may be working on them anyway. One is that forecasts are only as good as the observations going into the model and its initial conditions. Getting good initial conditions is a challenge for thunderstorms because you need good observations of the storm structure (radar can help with this, but more observations are needed) and good data of the storm environment. We have lots of surface observations, but few observations above the surface. The first 1,500 meters or so above ground level are very important in how strong or tornadic storms are. We don't have a lot of observations above the surface in this area, but they're important. We also need better data assimilation techniques so those observations translate to better initial conditions for our models. Finally, we can improve models in ways other than data assimilation and improved resolution. We don't directly simulate hail in models; there simply isn't the computing power to simulate individual hydrometeors (e.g., hail stones, raindrops, ice crystals, and cloud droplets). We parameterize those using microphysics schemes in models. We've improved the microphysics schemes a lot over time, adding more classes of hydrometers and adding the ability to predict their size distribution and other data about them. Ge
You're a moron. Overall, there hasn't been an abnormal amount of hail this winter. There have been some severe storms, but that's not uncommon in the Southeast during the winter. While global warming may well increase the overall amount of severe weather, including hail, you can't blame the weather in a particular storm, thunderstorm outbreak, or even a particular season on global warming. Global warming will make certain types of weather more likely, but let's not conflate weather and climate. As for the weather this winter such as the floods and other unusual weather that you reference when replying to yourself, I don't think you can implicate say that climate change caused it to any significant degree. It's weather, not climate, and extreme events will occur. The strong El Nino is far more to blame for this unusual weather than global warming. It's very possible that global warming will result in an upward trend in hail over the coming decades, but on a seasonal basis, El Nino was far more impactful. Sorry to burst your trollish bubble with actual science.
...not all Republicans are dolts. Some of them actually believe that the rest of mankind exists to serve their needs. It is authoritarianism versus libertarianism that is the big battle here.
Lets see something forecast hail in Alberta
Thanks to Chinooks weather goes all over the place (today was sunny/rainy/sloushy/haily/snowy)
https://en.wikipedia.org/wiki/...
...some sunny spells in the region to break up the severe hail storm, with rays of sunshine poking through the clouds later on in the day"
Not bad for a supercomputer, eh? I wonder if they fancy improving the forecast for us in old Blighty?